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Jung J, Yagi K, Tan C, Oshima H, Mori T, Yu I, Matsunaga Y, Kobayashi C, Ito S, Ugarte La Torre D, Sugita Y. GENESIS 2.1: High-Performance Molecular Dynamics Software for Enhanced Sampling and Free-Energy Calculations for Atomistic, Coarse-Grained, and Quantum Mechanics/Molecular Mechanics Models. J Phys Chem B 2024. [PMID: 38876465 DOI: 10.1021/acs.jpcb.4c02096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2024]
Abstract
GENeralized-Ensemble SImulation System (GENESIS) is a molecular dynamics (MD) software developed to simulate the conformational dynamics of a single biomolecule, as well as molecular interactions in large biomolecular assemblies and between multiple biomolecules in cellular environments. To achieve the latter purpose, the earlier versions of GENESIS emphasized high performance in atomistic MD simulations on massively parallel supercomputers, with or without graphics processing units (GPUs). Here, we implemented multiscale MD simulations that include atomistic, coarse-grained, and hybrid quantum mechanics/molecular mechanics (QM/MM) calculations. They demonstrate high performance and are integrated with enhanced conformational sampling algorithms and free-energy calculations without using external programs except for the QM programs. In this article, we review new functions, molecular models, and other essential features in GENESIS version 2.1 and discuss ongoing developments for future releases.
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Affiliation(s)
- Jaewoon Jung
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198, Japan
| | - Kiyoshi Yagi
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198, Japan
| | - Cheng Tan
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
| | - Hiraku Oshima
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047, Japan
- Graduate School of Life Science, University of Hyogo, Harima Science Park City, Hyogo 678-1297, Japan
| | - Takaharu Mori
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198, Japan
- Department of Chemistry, Tokyo University of Science, Shinjuku-ku, Tokyo 162-8601, Japan
| | - Isseki Yu
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198, Japan
- Department of Bioinformatics, Maebashi Institute of Technology, Maebashi, Gunma 371-0816, Japan
| | - Yasuhiro Matsunaga
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
- Graduate School of Science and Engineering, Saitama University, Saitama 338-8570, Japan
| | - Chigusa Kobayashi
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
| | - Shingo Ito
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198, Japan
| | - Diego Ugarte La Torre
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
| | - Yuji Sugita
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198, Japan
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047, Japan
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2
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Qiao G, Wang P, Hou D. Quasi-Reaction Coarse-Grained Simulation: Unveiling the Mesoscale Interfacial Response of CSH/PVA Fiber. ACS APPLIED MATERIALS & INTERFACES 2024. [PMID: 38864608 DOI: 10.1021/acsami.4c03994] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2024]
Abstract
The lack of a comprehensive force field and understanding at the mesoscale for hydrated calcium silicate (CSH)/polyvinyl alcohol (PVA) fiber has hindered the upscaling and bridging of nanoscale to macroscale phenomena. In this study, we propose a coarse-grained (CG) force field that incorporates bond-breaking operations to endow fiber reactivity, abrasion, and fracture properties. By employing a cubic lattice modeling, we effectively address the challenges associated with semicrystalline relaxation of fibers. For the first time, quasi-reaction CG simulation successfully replicates slip-hardening behaviors and surface abrasion. We demonstrate that abrasion improves interface load transfer and triggers slip-hardening by redistributing stress. Additionally, the influences of single and coupled factors, such as nonbonding interactions and surface roughness, are investigated. Mesoscale understanding provides insights for enabling precise control of load transfer paths and fabrication of interface damage-predictable materials.
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Affiliation(s)
- Gang Qiao
- Department of Civil Engineering, Qingdao University of Technology, Qingdao 266033, China
| | - Pan Wang
- Department of Civil Engineering, Qingdao University of Technology, Qingdao 266033, China
| | - Dongshuai Hou
- Department of Civil Engineering, Qingdao University of Technology, Qingdao 266033, China
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3
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Rigobello L, Lugli F, Caporali L, Bartocci A, Fadanni J, Zerbetto F, Iommarini L, Carelli V, Ghelli AM, Musiani F. A computational study to assess the pathogenicity of single or combinations of missense variants on respiratory complex I. Int J Biol Macromol 2024; 273:133086. [PMID: 38871105 DOI: 10.1016/j.ijbiomac.2024.133086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 06/07/2024] [Accepted: 06/09/2024] [Indexed: 06/15/2024]
Abstract
Variants found in the respiratory complex I (CI) subunit genes encoded by mitochondrial DNA can cause severe genetic diseases. However, it is difficult to establish a priori whether a single or a combination of CI variants may impact oxidative phosphorylation. Here we propose a computational approach based on coarse-grained molecular dynamics simulations aimed at investigating new CI variants. One of the primary CI variants associated with the Leber hereditary optic neuropathy (m.14484T>C/MT-ND6) was used as a test case and was investigated alone or in combination with two additional rare CI variants whose role remains uncertain. We found that the primary variant positioned in the E-channel region, which is fundamental for CI function, stiffens the enzyme dynamics. Moreover, a new mechanism for the transition between π- and α-conformation in the helix carrying the primary variant is proposed. This may have implications for the E-channel opening/closing mechanism. Finally, our findings show that one of the rare variants, located next to the primary one, further worsens the stiffening, while the other rare variant does not affect CI function. This approach may be extended to other variants candidate to exert a pathogenic impact on CI dynamics, or to investigate the interaction of multiple variants.
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Affiliation(s)
- Laura Rigobello
- Department of Pharmacy and Biotechnology, University of Bologna, Bologna I-40127, Italy
| | - Francesca Lugli
- Department of Chemistry "Giacomo Ciamician", University of Bologna, Bologna I-40126, Italy.
| | - Leonardo Caporali
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Programma di Neurogenetica, Bologna I-40124, Italy
| | - Alessio Bartocci
- Department of Physics, University of Trento, Trento I-38123, Italy; INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento I-38123, Italy
| | - Jacopo Fadanni
- Department of Chemistry "Giacomo Ciamician", University of Bologna, Bologna I-40126, Italy
| | - Francesco Zerbetto
- Department of Chemistry "Giacomo Ciamician", University of Bologna, Bologna I-40126, Italy
| | - Luisa Iommarini
- Department of Pharmacy and Biotechnology, University of Bologna, Bologna I-40127, Italy
| | - Valerio Carelli
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Programma di Neurogenetica, Bologna I-40124, Italy; Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna I-40123, Italy
| | - Anna Maria Ghelli
- Department of Pharmacy and Biotechnology, University of Bologna, Bologna I-40127, Italy; IRCCS Istituto delle Scienze Neurologiche di Bologna, Programma di Neurogenetica, Bologna I-40124, Italy
| | - Francesco Musiani
- Department of Pharmacy and Biotechnology, University of Bologna, Bologna I-40127, Italy.
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Tang K, Cui X. A Review on Investigating the Interactions between Nanoparticles and the Pulmonary Surfactant Monolayer with Coarse-Grained Molecular Dynamics Method. LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2024; 40:11829-11842. [PMID: 38809819 DOI: 10.1021/acs.langmuir.4c00909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2024]
Abstract
Pulmonary drug delivery has garnered significant attention due to its targeted local lung action, minimal toxic side effects, and high drug utilization. However, the physicochemical properties of inhaled nanoparticles (NPs) used as drug carriers can influence their interactions with the pulmonary surfactant (PS) monolayer, potentially altering the fate of the NPs and impairing the biophysical function of the PS monolayer. Thus, the objective of this review is to summarize how the physicochemical properties of NPs affect their interactions with the PS monolayer. Initially, the definition and properties of NPs, as well as the composition and characteristics of the PS monolayer, are introduced. Subsequently, the coarse-grained molecular dynamics (CGMD) simulation method for studying the interactions between NPs and the PS monolayer is presented. Finally, the implications of the hydrophobicity, size, shape, surface charge, surface modification, and aggregation of NPs on their interactions with the PS monolayer and on the composition of biomolecular corona are discussed. In conclusion, gaining a deeper understanding of the effects of the physicochemical properties of NPs on their interactions with the PS monolayer will contribute to the development of safer and more effective nanomedicines for pulmonary drug delivery.
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Affiliation(s)
- Kailiang Tang
- School of Aerospace Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Xinguang Cui
- School of Aerospace Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
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Giulini M, Fiorentini R, Tubiana L, Potestio R, Menichetti R. EXCOGITO, an Extensible Coarse-Graining Toolbox for the Investigation of Biomolecules by Means of Low-Resolution Representations. J Chem Inf Model 2024. [PMID: 38860513 DOI: 10.1021/acs.jcim.4c00490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2024]
Abstract
Bottom-up coarse-grained (CG) models proved to be essential to complement and sometimes even replace all-atom representations of soft matter systems and biological macromolecules. The development of low-resolution models takes the moves from the reduction of the degrees of freedom employed, that is, the definition of a mapping between a system's high-resolution description and its simplified counterpart. Even in the absence of an explicit parametrization and simulation of a CG model, the observation of the atomistic system in simpler terms can be informative: this idea is leveraged by the mapping entropy, a measure of the information loss inherent to the process of coarsening. Mapping entropy lies at the heart of the extensible coarse-graining toolbox, EXCOGITO, developed to perform a number of operations and analyses on molecular systems pivoting around the properties of mappings. EXCOGITO can process an all-atom trajectory to compute the mapping entropy, identify the mapping that minimizes it, and establish quantitative relations between a low-resolution representation and the geometrical, structural, and energetic features of the system. Here, the software, which is available free of charge under an open-source license, is presented and showcased to introduce potential users to its capabilities and usage.
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Affiliation(s)
- Marco Giulini
- Physics Department, University of Trento, Via Sommarive, 14, Trento I-38123, Italy
- INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento I-38123, Italy
| | - Raffaele Fiorentini
- Physics Department, University of Trento, Via Sommarive, 14, Trento I-38123, Italy
- INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento I-38123, Italy
| | - Luca Tubiana
- Physics Department, University of Trento, Via Sommarive, 14, Trento I-38123, Italy
- INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento I-38123, Italy
| | - Raffaello Potestio
- Physics Department, University of Trento, Via Sommarive, 14, Trento I-38123, Italy
- INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento I-38123, Italy
| | - Roberto Menichetti
- Physics Department, University of Trento, Via Sommarive, 14, Trento I-38123, Italy
- INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento I-38123, Italy
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Ghosh D, Biswas A, Radhakrishna M. Advanced computational approaches to understand protein aggregation. BIOPHYSICS REVIEWS 2024; 5:021302. [PMID: 38681860 PMCID: PMC11045254 DOI: 10.1063/5.0180691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 03/18/2024] [Indexed: 05/01/2024]
Abstract
Protein aggregation is a widespread phenomenon implicated in debilitating diseases like Alzheimer's, Parkinson's, and cataracts, presenting complex hurdles for the field of molecular biology. In this review, we explore the evolving realm of computational methods and bioinformatics tools that have revolutionized our comprehension of protein aggregation. Beginning with a discussion of the multifaceted challenges associated with understanding this process and emphasizing the critical need for precise predictive tools, we highlight how computational techniques have become indispensable for understanding protein aggregation. We focus on molecular simulations, notably molecular dynamics (MD) simulations, spanning from atomistic to coarse-grained levels, which have emerged as pivotal tools in unraveling the complex dynamics governing protein aggregation in diseases such as cataracts, Alzheimer's, and Parkinson's. MD simulations provide microscopic insights into protein interactions and the subtleties of aggregation pathways, with advanced techniques like replica exchange molecular dynamics, Metadynamics (MetaD), and umbrella sampling enhancing our understanding by probing intricate energy landscapes and transition states. We delve into specific applications of MD simulations, elucidating the chaperone mechanism underlying cataract formation using Markov state modeling and the intricate pathways and interactions driving the toxic aggregate formation in Alzheimer's and Parkinson's disease. Transitioning we highlight how computational techniques, including bioinformatics, sequence analysis, structural data, machine learning algorithms, and artificial intelligence have become indispensable for predicting protein aggregation propensity and locating aggregation-prone regions within protein sequences. Throughout our exploration, we underscore the symbiotic relationship between computational approaches and empirical data, which has paved the way for potential therapeutic strategies against protein aggregation-related diseases. In conclusion, this review offers a comprehensive overview of advanced computational methodologies and bioinformatics tools that have catalyzed breakthroughs in unraveling the molecular basis of protein aggregation, with significant implications for clinical interventions, standing at the intersection of computational biology and experimental research.
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Affiliation(s)
- Deepshikha Ghosh
- Department of Biological Sciences and Engineering, Indian Institute of Technology (IIT) Gandhinagar, Palaj, Gujarat 382355, India
| | - Anushka Biswas
- Department of Chemical Engineering, Indian Institute of Technology (IIT) Gandhinagar, Palaj, Gujarat 382355, India
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Levintov L, Gorai B, Vashisth H. Spontaneous Dimerization and Distinct Packing Modes of Transmembrane Domains in Receptor Tyrosine Kinases. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.09.593448. [PMID: 38798363 PMCID: PMC11118388 DOI: 10.1101/2024.05.09.593448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
The insulin receptor (IR) and the insulin-like growth factor-1 receptor (IGF1R) are homodimeric transmembrane glycoproteins that transduce signals across the membrane on binding of extracellular peptide ligands. The structures of IR/IGF1R fragments in apo and liganded states have revealed that the extracellular subunits of these receptors adopt Λ-shaped configurations to which are connected the intracellular tyrosine kinase (TK) domains. The binding of peptide ligands induces structural transitions in the extracellular subunits leading to potential dimerization of transmembrane domains (TMDs) and autophosphorylation in TKs. However, the activation mechanisms of IR/IGF1R, especially the role of TMDs in coordinating signal-inducing structural transitions, remain poorly understood, in part due to the lack of structures of full-length receptors in apo or liganded states. While atomistic simulations of IR/IGF1R TMDs showed that these domains can dimerize in single component membranes, spontaneous unbiased dimerization in a plasma membrane having physiologically representative lipid composition has not been observed. We address this limitation by employing coarse-grained (CG) molecular dynamics simulations to probe the dimerization propensity of IR/IGF1R TMDs. We observed that TMDs in both receptors spontaneously dimerized independent of their initial orientations in their dissociated states, signifying their natural propensity for dimerization. In the dimeric state, IR TMDs predominantly adopted X-shaped configurations with asymmetric helical packing and significant tilt relative to the membrane normal, while IGF1R TMDs adopted symmetric V-shaped or parallel configurations with either no tilt or a small tilt relative to the membrane normal. Our results suggest that IR/IGF1R TMDs spontaneously dimerize and adopt distinct dimerized configurations.
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Affiliation(s)
- Lev Levintov
- Department of Chemical Engineering and Bioengineering, University of New Hampshire, Durham 03824, New Hampshire, USA
| | - Biswajit Gorai
- Institute of Chemistry, Technical University of Berlin, Berlin 10623, Germany
| | - Harish Vashisth
- Department of Chemical Engineering and Bioengineering, University of New Hampshire, Durham 03824, New Hampshire, USA
- Department of Chemistry, University of New Hampshire, Durham 03824, New Hampshire, USA
- Integrated Applied Mathematics Program, University of New Hampshire, Durham 03824, New Hampshire, USA
- Molecular and Cellular Biotechnology Program, University of New Hampshire, Durham 03824, New Hampshire, USA
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8
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Masella M, Léonforté F. The multi-scale polarizable pseudo-particle solvent coarse-grained approach: From NaCl salt solutions to polyelectrolyte hydration. J Chem Phys 2024; 160:204902. [PMID: 38780384 DOI: 10.1063/5.0194968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Accepted: 04/22/2024] [Indexed: 05/25/2024] Open
Abstract
We discuss key parameters that affect the reliability of hybrid simulations in the aqueous phase based on an efficient multi-scale coarse-grained polarizable pseudo-particle approach, denoted as pppl, to model the solvent water, whereas solutes are modeled using an all atom polarizable force field. Among those parameters, the extension of the solvent domain (SD) at the solute vicinity (domain in which each solvent particle corresponds to a single water molecule) and the magnitude of solute/solvent short range polarization damping effects are shown to be pivotal to model NaCl salty aqueous solutions and the hydration of charged systems, such as the hydrophobic polyelectrolyte polymer that we have recently investigated [Masella et al., J. Chem. Phys. 155, 114903 (2021)]. Strong short range damping is pivotal to simulate aqueous salt NaCl solutions at moderate concentration (up to 1.0M). The SD extension (as well as short range damping) has a weak effect on the polymer conformation; however, it plays a pivotal role in computing accurate polymer/solvent interaction energies. As the pppl approach is up to two orders of magnitude computationally more efficient than all atom polarizable force field methods, our results show it to be an efficient alternative route to investigate the equilibrium properties of complex charged molecular systems in extended chemical environments.
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Affiliation(s)
- Michel Masella
- Laboratoire de Biologie Structurale et Radiobiologie, Service de Bioénergétique, Biologie Structurale et Mécanismes, Institut de Biologie et de Technologies de Saclay, CEA Saclay, F-91191 Gif sur Yvette Cedex, France
| | - Fabien Léonforté
- L'Oréal Group, Research and Innovation, Aulnay-Sous-Bois, France
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9
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Shimono Y, Hakamada M, Mabuchi M. NPEX: Never give up protein exploration with deep reinforcement learning. J Mol Graph Model 2024; 131:108802. [PMID: 38838617 DOI: 10.1016/j.jmgm.2024.108802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 05/05/2024] [Accepted: 05/24/2024] [Indexed: 06/07/2024]
Abstract
Elucidating unknown structures of proteins, such as metastable states, is critical in designing therapeutic agents. Protein structure exploration has been performed using advanced computational methods, especially molecular dynamics and Markov chain Monte Carlo simulations, which require untenably long calculation times and prior structural knowledge. Here, we developed an innovative method for protein structure determination called never give up protein exploration (NPEX) with deep reinforcement learning. The NPEX method leverages the soft actor-critic algorithm and the intrinsic reward system, effectively adding a bias potential without the need for prior knowledge. To demonstrate the method's effectiveness, we applied it to four models: a double well, a triple well, the alanine dipeptide, and the tryptophan cage. Compared with Markov chain Monte Carlo simulations, NPEX had markedly greater sampling efficiency. The significantly enhanced computational efficiency and lack of prior domain knowledge requirements of the NPEX method will revolutionize protein structure exploration.
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Affiliation(s)
- Yuta Shimono
- Graduate School of Energy Science, Kyoto University, Yoshidahonmachi, Sakyo-ku, Kyoto, 606-8501, Japan
| | - Masataka Hakamada
- Graduate School of Energy Science, Kyoto University, Yoshidahonmachi, Sakyo-ku, Kyoto, 606-8501, Japan.
| | - Mamoru Mabuchi
- Graduate School of Energy Science, Kyoto University, Yoshidahonmachi, Sakyo-ku, Kyoto, 606-8501, Japan
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Varenyk Y, Theodorakis PE, Pham DQH, Li MS, Krupa P. Exploring Structural Insights of Aβ42 and α-Synuclein Monomers and Heterodimer: A Comparative Study Using Implicit and Explicit Solvent Simulations. J Phys Chem B 2024; 128:4655-4669. [PMID: 38700150 PMCID: PMC11103699 DOI: 10.1021/acs.jpcb.4c00503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 04/10/2024] [Accepted: 04/16/2024] [Indexed: 05/05/2024]
Abstract
Protein misfolding, aggregation, and fibril formation play a central role in the development of severe neurological disorders, including Alzheimer's and Parkinson's diseases. The structural stability of mature fibrils in these diseases is of great importance, as organisms struggle to effectively eliminate amyloid plaques. To address this issue, it is crucial to investigate the early stages of fibril formation when monomers aggregate into small, toxic, and soluble oligomers. However, these structures are inherently disordered, making them challenging to study through experimental approaches. Recently, it has been shown experimentally that amyloid-β 42 (Aβ42) and α-synuclein (α-Syn) can coassemble. This has motivated us to investigate the interaction between their monomers as a first step toward exploring the possibility of forming heterodimeric complexes. In particular, our study involves the utilization of various Amber and CHARMM force-fields, employing both implicit and explicit solvent models in replica exchange and conventional simulation modes. This comprehensive approach allowed us to assess the strengths and weaknesses of these solvent models and force fields in comparison to experimental and theoretical findings, ensuring the highest level of robustness. Our investigations revealed that Aβ42 and α-Syn monomers can indeed form stable heterodimers, and the resulting heterodimeric model exhibits stronger interactions compared to the Aβ42 dimer. The binding of α-Syn to Aβ42 reduces the propensity of Aβ42 to adopt fibril-prone conformations and induces significant changes in its conformational properties. Notably, in AMBER-FB15 and CHARMM36m force fields with the use of explicit solvent, the presence of Aβ42 significantly increases the β-content of α-Syn, consistent with the experiments showing that Aβ42 triggers α-Syn aggregation. Our analysis clearly shows that although the use of implicit solvent resulted in too large compactness of monomeric α-Syn, structural properties of monomeric Aβ42 and the heterodimer were preserved in explicit-solvent simulations. We anticipate that our study sheds light on the interaction between α-Syn and Aβ42 proteins, thus providing the atom-level model required to assess the initial stage of aggregation mechanisms related to Alzheimer's and Parkinson's diseases.
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Affiliation(s)
- Yuliia Varenyk
- Institute
of Physics Polish Academy of Sciences, Al. Lotnikow 32/46, 02-668 Warsaw, Poland
- Department
of Theoretical Chemistry, University of
Vienna, Vienna 1090, Austria
| | | | - Dinh Q. H. Pham
- Institute
of Physics Polish Academy of Sciences, Al. Lotnikow 32/46, 02-668 Warsaw, Poland
| | - Mai Suan Li
- Institute
of Physics Polish Academy of Sciences, Al. Lotnikow 32/46, 02-668 Warsaw, Poland
| | - Paweł Krupa
- Institute
of Physics Polish Academy of Sciences, Al. Lotnikow 32/46, 02-668 Warsaw, Poland
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11
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Siebenmorgen T, Menezes F, Benassou S, Merdivan E, Didi K, Mourão ASD, Kitel R, Liò P, Kesselheim S, Piraud M, Theis FJ, Sattler M, Popowicz GM. MISATO: machine learning dataset of protein-ligand complexes for structure-based drug discovery. NATURE COMPUTATIONAL SCIENCE 2024; 4:367-378. [PMID: 38730184 PMCID: PMC11136668 DOI: 10.1038/s43588-024-00627-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 04/11/2024] [Indexed: 05/12/2024]
Abstract
Large language models have greatly enhanced our ability to understand biology and chemistry, yet robust methods for structure-based drug discovery, quantum chemistry and structural biology are still sparse. Precise biomolecule-ligand interaction datasets are urgently needed for large language models. To address this, we present MISATO, a dataset that combines quantum mechanical properties of small molecules and associated molecular dynamics simulations of ~20,000 experimental protein-ligand complexes with extensive validation of experimental data. Starting from the existing experimental structures, semi-empirical quantum mechanics was used to systematically refine these structures. A large collection of molecular dynamics traces of protein-ligand complexes in explicit water is included, accumulating over 170 μs. We give examples of machine learning (ML) baseline models proving an improvement of accuracy by employing our data. An easy entry point for ML experts is provided to enable the next generation of drug discovery artificial intelligence models.
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Affiliation(s)
- Till Siebenmorgen
- Molecular Targets and Therapeutics Center, Institute of Structural Biology, Helmholtz Munich, Neuherberg, Germany
- TUM School of Natural Sciences, Department of Bioscience, Bayerisches NMR Zentrum, Technical University of Munich, Garching, Germany
| | - Filipe Menezes
- Molecular Targets and Therapeutics Center, Institute of Structural Biology, Helmholtz Munich, Neuherberg, Germany
- TUM School of Natural Sciences, Department of Bioscience, Bayerisches NMR Zentrum, Technical University of Munich, Garching, Germany
| | - Sabrina Benassou
- Jülich Supercomputing Centre, Forschungszentrum Jülich, Jülich, Germany
| | | | - Kieran Didi
- Computer Laboratory, Cambridge University, Cambridge, UK
| | - André Santos Dias Mourão
- Molecular Targets and Therapeutics Center, Institute of Structural Biology, Helmholtz Munich, Neuherberg, Germany
- TUM School of Natural Sciences, Department of Bioscience, Bayerisches NMR Zentrum, Technical University of Munich, Garching, Germany
| | - Radosław Kitel
- Faculty of Chemistry, Jagiellonian University, Krakow, Poland
| | - Pietro Liò
- Computer Laboratory, Cambridge University, Cambridge, UK
| | - Stefan Kesselheim
- Jülich Supercomputing Centre, Forschungszentrum Jülich, Jülich, Germany
| | - Marie Piraud
- Helmholtz AI, Helmholtz Munich, Neuherberg, Germany
| | - Fabian J Theis
- Helmholtz AI, Helmholtz Munich, Neuherberg, Germany
- Computational Health Center, Institute of Computational Biology, Helmholtz Munich, Neuherberg, Germany
- TUM School of Computation, Information and Technology, Technical University of Munich, Garching, Germany
| | - Michael Sattler
- Molecular Targets and Therapeutics Center, Institute of Structural Biology, Helmholtz Munich, Neuherberg, Germany
- TUM School of Natural Sciences, Department of Bioscience, Bayerisches NMR Zentrum, Technical University of Munich, Garching, Germany
| | - Grzegorz M Popowicz
- Molecular Targets and Therapeutics Center, Institute of Structural Biology, Helmholtz Munich, Neuherberg, Germany.
- TUM School of Natural Sciences, Department of Bioscience, Bayerisches NMR Zentrum, Technical University of Munich, Garching, Germany.
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12
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Dash R, Jabbari E. A Structure Independent Molecular Fragment Interfuse Model for Mesoscale Dissipative Particle Dynamics Simulation of Peptides. ACS OMEGA 2024; 9:18001-18022. [PMID: 38680324 PMCID: PMC11044228 DOI: 10.1021/acsomega.3c09534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 03/07/2024] [Accepted: 04/02/2024] [Indexed: 05/01/2024]
Abstract
There is a need to develop robust computational models for mesoscale simulation of the structure of peptides over large length scales toward the discovery of novel peptides for medical applications to address the issues of peptide aggregation, enzymatic degradation, and short half-life. The primary objective was to predict the structure and conformation of peptides whose native structures are not known. This work presents a new model for computation of interaction parameters between the beads in coarse-grained dissipative particle dynamics (DPD) simulation that is properly calibrated for amino acids, supports compressibility requirement of water molecules, and accounts for subtle differences in the structure of amino acids and the charge in the side chain of charged amino acids. This new model is referred to as Structure Independent Molecular Fragment Interfuse Model, abbreviated as SIMFIM, because it accounts for specific interactions between different beads, which represent molecular fragments of the amino acids, in calculating nonbonded interaction parameters in the absence of knowing the actual peptide structure. The electrostatic interactions are incorporated in this model by using a normal distribution of charges around the center of the beads to prevent the collapse of oppositely charged soft beads. The uniquely parameterized DPD force field in the SIMFIM model is optimized for a given peptide with respect to the degree of coarse-grained graining for simulating the peptide over long times and length scales. The SIMFIM model was tested in this work using four peptides, namely, TrpZip2, Rubrivinodin, Lihuanodin, and IC3-CB1/Gai peptides, whose structures were sourced from the Protein Data Bank. The SIMFIM model predicted radius of gyration (Rg) values for the peptides closer to the actual structures as compared to the conventional model, and there was less deviation between the predicted and actual structures of the peptides.
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Affiliation(s)
- Ricky
Anshuman Dash
- Biomimetic Materials and
Tissue Engineering Laboratory, Chemical Engineering Department, University of South Carolina, 301 Main Street, Columbia, South Carolina 29208, United States
| | - Esmaiel Jabbari
- Biomimetic Materials and
Tissue Engineering Laboratory, Chemical Engineering Department, University of South Carolina, 301 Main Street, Columbia, South Carolina 29208, United States
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13
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Walter LJ, Quoika PK, Zacharias M. Structure-Based Protein Assembly Simulations Including Various Binding Sites and Conformations. J Chem Inf Model 2024; 64:3465-3476. [PMID: 38602938 DOI: 10.1021/acs.jcim.4c00212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/13/2024]
Abstract
Many biological functions are mediated by large complexes formed by multiple proteins and other cellular macromolecules. Recent progress in experimental structure determination, as well as in integrative modeling and protein structure prediction using deep learning approaches, has resulted in a rapid increase in the number of solved multiprotein assemblies. However, the assembly process of large complexes from their components is much less well-studied. We introduce a rapid computational structure-based (SB) model, GoCa, that allows to follow the assembly process of large multiprotein complexes based on a known native structure. Beyond existing SB Go̅-type models, it distinguishes between intra- and intersubunit interactions, allowing us to include coupled folding and binding. It accounts automatically for the permutation of identical subunits in a complex and allows the definition of multiple minima (native) structures in the case of proteins that undergo global transitions during assembly. The model is successfully tested on several multiprotein complexes. The source code of the GoCa program including a tutorial is publicly available on Github: https://github.com/ZachariasLab/GoCa. We also provide a web source that allows users to quickly generate the necessary input files for a GoCa simulation: https://goca.t38webservices.nat.tum.de.
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Affiliation(s)
- Luis J Walter
- Center for Functional Protein Assemblies, Technical University of Munich, Ernst-Otto-Fischer-Str. 8, Garching 85748, Germany
| | - Patrick K Quoika
- Center for Functional Protein Assemblies, Technical University of Munich, Ernst-Otto-Fischer-Str. 8, Garching 85748, Germany
| | - Martin Zacharias
- Center for Functional Protein Assemblies, Technical University of Munich, Ernst-Otto-Fischer-Str. 8, Garching 85748, Germany
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14
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Maizels RJ. A dynamical perspective: moving towards mechanism in single-cell transcriptomics. Philos Trans R Soc Lond B Biol Sci 2024; 379:20230049. [PMID: 38432314 PMCID: PMC10909508 DOI: 10.1098/rstb.2023.0049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 10/31/2023] [Indexed: 03/05/2024] Open
Abstract
As the field of single-cell transcriptomics matures, research is shifting focus from phenomenological descriptions of cellular phenotypes to a mechanistic understanding of the gene regulation underneath. This perspective considers the value of capturing dynamical information at single-cell resolution for gaining mechanistic insight; reviews the available technologies for recording and inferring temporal information in single cells; and explores whether better dynamical resolution is sufficient to adequately capture the causal relationships driving complex biological systems. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.
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Affiliation(s)
- Rory J. Maizels
- The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK
- University College London, London WC1E 6BT, UK
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15
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Borówko M, Staszewski T. Molecular Dynamics Simulations of Different Nanoparticles at Substrates. Int J Mol Sci 2024; 25:4550. [PMID: 38674134 PMCID: PMC11050098 DOI: 10.3390/ijms25084550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Revised: 04/17/2024] [Accepted: 04/19/2024] [Indexed: 04/28/2024] Open
Abstract
We report the results of large-scale molecular dynamics simulations of adsorption nanoparticles on solid surfaces. The particles were modeled as stiff aggregates of spherical segments. Three types of particles were studied: rods, rectangles, and triangles built of the same number of segments. We show how the particle shape affects the adsorption, the structure of the surface layer, and the degree of the removal of particles from the solvent. The systems with different segment-segment and segment-surface interactions and different concentrations of particles were investigated. The ordered structures formed in adsorption monolayers were also analyzed. The results are consistent with experimental observations.
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Affiliation(s)
- Małgorzata Borówko
- Department of Theoretical Chemistry, Institute of Chemical Sciences, Faculty of Chemistry, Maria Curie-Skłodowska University in Lublin, 20-031 Lublin, Poland;
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16
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Jung J, Tan C, Sugita Y. GENESIS CGDYN: large-scale coarse-grained MD simulation with dynamic load balancing for heterogeneous biomolecular systems. Nat Commun 2024; 15:3370. [PMID: 38643169 PMCID: PMC11032353 DOI: 10.1038/s41467-024-47654-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 04/08/2024] [Indexed: 04/22/2024] Open
Abstract
Residue-level coarse-grained (CG) molecular dynamics (MD) simulation is widely used to investigate slow biological processes that involve multiple proteins, nucleic acids, and their complexes. Biomolecules in a large simulation system are distributed non-uniformly, limiting computational efficiency with conventional methods. Here, we develop a hierarchical domain decomposition scheme with dynamic load balancing for heterogeneous biomolecular systems to keep computational efficiency even after drastic changes in particle distribution. These schemes are applied to the dynamics of intrinsically disordered protein (IDP) droplets. During the fusion of two droplets, we find that the changes in droplet shape correlate with the mixing of IDP chains. Additionally, we simulate large systems with multiple IDP droplets, achieving simulation sizes comparable to those observed in microscopy. In our MD simulations, we directly observe Ostwald ripening, a phenomenon where small droplets dissolve and their molecules redeposit into larger droplets. These methods have been implemented in CGDYN of the GENESIS software, offering a tool for investigating mesoscopic biological processes using the residue-level CG models.
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Affiliation(s)
- Jaewoon Jung
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo, 650-0047, Japan
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama, 351-0198, Japan
| | - Cheng Tan
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo, 650-0047, Japan
| | - Yuji Sugita
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo, 650-0047, Japan.
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama, 351-0198, Japan.
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo, 650-0047, Japan.
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17
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Sharma P, Vaiwala R, Gopinath AK, Chockalingam R, Ayappa KG. Structure of the Bacterial Cell Envelope and Interactions with Antimicrobials: Insights from Molecular Dynamics Simulations. LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2024; 40:7791-7811. [PMID: 38451026 DOI: 10.1021/acs.langmuir.3c03474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
Bacteria have evolved over 3 billion years, shaping our intrinsic and symbiotic coexistence with these single-celled organisms. With rising populations of drug-resistant strains, the search for novel antimicrobials is an ongoing area of research. Advances in high-performance computing platforms have led to a variety of molecular dynamics simulation strategies to study the interactions of antimicrobial molecules with different compartments of the bacterial cell envelope of both Gram-positive and Gram-negative species. In this review, we begin with a detailed description of the structural aspects of the bacterial cell envelope. Simulations concerned with the transport and associated free energy of small molecules and ions through the outer membrane, peptidoglycan, inner membrane and outer membrane porins are discussed. Since surfactants are widely used as antimicrobials, a section is devoted to the interactions of surfactants with the cell wall and inner membranes. The review ends with a discussion on antimicrobial peptides and the insights gained from the molecular simulations on the free energy of translocation. Challenges involved in developing accurate molecular models and coarse-grained strategies that provide a trade-off between atomic details with a gain in sampling time are highlighted. The need for efficient sampling strategies to obtain accurate free energies of translocation is also discussed. Molecular dynamics simulations have evolved as a powerful tool that can potentially be used to design and develop novel antimicrobials and strategies to effectively treat bacterial infections.
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Affiliation(s)
- Pradyumn Sharma
- Department of Chemical Engineering, Indian Institute of Science, Bangalore, Karnataka, India, 560012
| | - Rakesh Vaiwala
- Department of Chemical Engineering, Indian Institute of Science, Bangalore, Karnataka, India, 560012
| | - Amar Krishna Gopinath
- Department of Chemical Engineering, Indian Institute of Science, Bangalore, Karnataka, India, 560012
| | - Rajalakshmi Chockalingam
- Department of Chemical Engineering, Indian Institute of Science, Bangalore, Karnataka, India, 560012
| | - K Ganapathy Ayappa
- Department of Chemical Engineering, Indian Institute of Science, Bangalore, Karnataka, India, 560012
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18
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DeLuca M, Duke D, Ye T, Poirier M, Ke Y, Castro C, Arya G. Mechanism of DNA origami folding elucidated by mesoscopic simulations. Nat Commun 2024; 15:3015. [PMID: 38589344 PMCID: PMC11001925 DOI: 10.1038/s41467-024-46998-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 03/18/2024] [Indexed: 04/10/2024] Open
Abstract
Many experimental and computational efforts have sought to understand DNA origami folding, but the time and length scales of this process pose significant challenges. Here, we present a mesoscopic model that uses a switchable force field to capture the behavior of single- and double-stranded DNA motifs and transitions between them, allowing us to simulate the folding of DNA origami up to several kilobases in size. Brownian dynamics simulations of small structures reveal a hierarchical folding process involving zipping into a partially folded precursor followed by crystallization into the final structure. We elucidate the effects of various design choices on folding order and kinetics. Larger structures are found to exhibit heterogeneous staple incorporation kinetics and frequent trapping in metastable states, as opposed to more accessible structures which exhibit first-order kinetics and virtually defect-free folding. This model opens an avenue to better understand and design DNA nanostructures for improved yield and folding performance.
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Affiliation(s)
- Marcello DeLuca
- Thomas Lord Department of Mechanical Engineering and Materials Science, Duke University, Durham, NC, 27705, USA
| | - Daniel Duke
- Thomas Lord Department of Mechanical Engineering and Materials Science, Duke University, Durham, NC, 27705, USA
| | - Tao Ye
- Department of Chemistry & Biochemistry, University of California, Merced, CA, 95343, USA
- Department of Materials and Biomaterials Science & Engineering, University of California, Merced, CA, 95343, USA
| | - Michael Poirier
- Department of Physics, The Ohio State University, Columbus, OH, 43210, USA
| | - Yonggang Ke
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, 30322, USA
| | - Carlos Castro
- Department of Mechanical and Aerospace Engineering, The Ohio State University, Columbus, OH, 43210, USA
| | - Gaurav Arya
- Thomas Lord Department of Mechanical Engineering and Materials Science, Duke University, Durham, NC, 27705, USA.
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19
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Ratajczyk EJ, Šulc P, Turberfield AJ, Doye JPK, Louis AA. Coarse-grained modeling of DNA-RNA hybrids. J Chem Phys 2024; 160:115101. [PMID: 38497475 DOI: 10.1063/5.0199558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 01/26/2024] [Indexed: 03/19/2024] Open
Abstract
We introduce oxNA, a new model for the simulation of DNA-RNA hybrids that is based on two previously developed coarse-grained models-oxDNA and oxRNA. The model naturally reproduces the physical properties of hybrid duplexes, including their structure, persistence length, and force-extension characteristics. By parameterizing the DNA-RNA hydrogen bonding interaction, we fit the model's thermodynamic properties to experimental data using both average-sequence and sequence-dependent parameters. To demonstrate the model's applicability, we provide three examples of its use-calculating the free energy profiles of hybrid strand displacement reactions, studying the resolution of a short R-loop, and simulating RNA-scaffolded wireframe origami.
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Affiliation(s)
- Eryk J Ratajczyk
- Clarendon Laboratory, Department of Physics, University of Oxford, Parks Road, Oxford OX1 3PU, United Kingdom
- Kavli Institute for Nanoscience Discovery, University of Oxford, Dorothy Crowfoot Hodgkin Building, South Parks Road, Oxford OX1 3QU, United Kingdom
| | - Petr Šulc
- School of Molecular Sciences and Center for Molecular Design and Biomimetics, The Biodesign Institute, Arizona State University, 1001 South McAllister Avenue, Tempe, Arizona 85281, USA
- School of Natural Sciences, Department of Bioscience, Technical University Munich, 85748 Garching, Germany
| | - Andrew J Turberfield
- Clarendon Laboratory, Department of Physics, University of Oxford, Parks Road, Oxford OX1 3PU, United Kingdom
- Kavli Institute for Nanoscience Discovery, University of Oxford, Dorothy Crowfoot Hodgkin Building, South Parks Road, Oxford OX1 3QU, United Kingdom
| | - Jonathan P K Doye
- Physical and Theoretical Chemistry Laboratory, Department of Chemistry, University of Oxford, South Parks Road, Oxford OX1 3QZ, United Kingdom
| | - Ard A Louis
- Rudolf Peierls Centre for Theoretical Physics, University of Oxford, 1 Keble Road, Oxford OX1 3NP, United Kingdom
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20
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Nabi F, Ahmad O, Khan A, Hassan MN, Hisamuddin M, Malik S, Chaari A, Khan RH. Natural compound plumbagin based inhibition of hIAPP revealed by Markov state models based on MD data along with experimental validations. Proteins 2024. [PMID: 38497314 DOI: 10.1002/prot.26682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 02/26/2024] [Accepted: 02/28/2024] [Indexed: 03/19/2024]
Abstract
Human islet amyloid polypeptide (amylin or hIAPP) is a 37 residue hormone co-secreted with insulin from β cells of the pancreas. In patients suffering from type-2 diabetes, amylin self-assembles into amyloid fibrils, ultimately leading to the death of the pancreatic cells. However, a research gap exists in preventing and treating such amyloidosis. Plumbagin, a natural compound, has previously been demonstrated to have inhibitory potential against insulin amyloidosis. Our investigation unveils collapsible regions within hIAPP that, upon collapse, facilitates hydrophobic and pi-pi interactions, ultimately leading to aggregation. Intriguingly plumbagin exhibits the ability to bind these specific collapsible regions, thereby impeding the aforementioned interactions that would otherwise drive hIAPP aggregation. We have used atomistic molecular dynamics approach to determine secondary structural changes. MSM shows metastable states forming native like hIAPP structure in presence of PGN. Our in silico results concur with in vitro results. The ThT assay revealed a striking 50% decrease in fluorescence intensity at a 1:1 ratio of hIAPP to Plumbagin. This finding suggests a significant inhibition of amyloid fibril formation by plumbagin, as ThT fluorescence directly correlates with the presence of these fibrils. Further TEM images revealed disappearance of hIAPP fibrils in plumbagin pre-treated hIAPP samples. Also, we have shown that plumbagin disrupts the intermolecular hydrogen bonding in hIAPP fibrils leading to an increase in the average beta strand spacing, thereby causing disaggregation of pre-formed fibrils demonstrating overall disruption of the aggregation machinery of hIAPP. Our work is the first to report a detailed atomistic simulation of 22 μs for hIAPP. Overall, our studies put plumbagin as a potential candidate for both preventive and therapeutic candidate for hIAPP amyloidosis.
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Affiliation(s)
- Faisal Nabi
- Interdisciplinary Biotechnology Unit, Aligarh Muslim University, Aligarh, India
| | - Owais Ahmad
- Interdisciplinary Biotechnology Unit, Aligarh Muslim University, Aligarh, India
| | - Adeeba Khan
- Zakir Hussain College of Engineering and Technology, Aligarh Muslim University, Aligarh, India
| | - Md Nadir Hassan
- Interdisciplinary Biotechnology Unit, Aligarh Muslim University, Aligarh, India
| | - Malik Hisamuddin
- Interdisciplinary Biotechnology Unit, Aligarh Muslim University, Aligarh, India
| | - Sadia Malik
- Interdisciplinary Biotechnology Unit, Aligarh Muslim University, Aligarh, India
| | - Ali Chaari
- Premedical Division, Weill Cornell Medicine Qatar, Qatar Foundation, Doha, Qatar
| | - Rizwan Hasan Khan
- Interdisciplinary Biotechnology Unit, Aligarh Muslim University, Aligarh, India
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21
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Schnee P, Pleiss J, Jeltsch A. Approaching the catalytic mechanism of protein lysine methyltransferases by biochemical and simulation techniques. Crit Rev Biochem Mol Biol 2024:1-49. [PMID: 38449437 DOI: 10.1080/10409238.2024.2318547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 02/10/2024] [Indexed: 03/08/2024]
Abstract
Protein lysine methyltransferases (PKMTs) transfer up to three methyl groups to the side chains of lysine residues in proteins and fulfill important regulatory functions by controlling protein stability, localization and protein/protein interactions. The methylation reactions are highly regulated, and aberrant methylation of proteins is associated with several types of diseases including neurologic disorders, cardiovascular diseases, and various types of cancer. This review describes novel insights into the catalytic machinery of various PKMTs achieved by the combined application of biochemical experiments and simulation approaches during the last years, focusing on clinically relevant and well-studied enzymes of this group like DOT1L, SMYD1-3, SET7/9, G9a/GLP, SETD2, SUV420H2, NSD1/2, different MLLs and EZH2. Biochemical experiments have unraveled many mechanistic features of PKMTs concerning their substrate and product specificity, processivity and the effects of somatic mutations observed in PKMTs in cancer cells. Structural data additionally provided information about the substrate recognition, enzyme-substrate complex formation, and allowed for simulations of the substrate peptide interaction and mechanism of PKMTs with atomistic resolution by molecular dynamics and hybrid quantum mechanics/molecular mechanics methods. These simulation technologies uncovered important mechanistic details of the PKMT reaction mechanism including the processes responsible for the deprotonation of the target lysine residue, essential conformational changes of the PKMT upon substrate binding, but also rationalized regulatory principles like PKMT autoinhibition. Further developments are discussed that could bring us closer to a mechanistic understanding of catalysis of this important class of enzymes in the near future. The results described here illustrate the power of the investigation of enzyme mechanisms by the combined application of biochemical experiments and simulation technologies.
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Affiliation(s)
- Philipp Schnee
- Institute of Biochemistry and Technical Biochemistry, University of Stuttgart, Stuttgart, Germany
| | - Jürgen Pleiss
- Institute of Biochemistry and Technical Biochemistry, University of Stuttgart, Stuttgart, Germany
| | - Albert Jeltsch
- Institute of Biochemistry and Technical Biochemistry, University of Stuttgart, Stuttgart, Germany
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22
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Grazioli G, Tao A, Bhatia I, Regan P. Genetic Algorithm for Automated Parameterization of Network Hamiltonian Models of Amyloid Fibril Formation. J Phys Chem B 2024; 128:1854-1865. [PMID: 38359362 PMCID: PMC10910512 DOI: 10.1021/acs.jpcb.3c07322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Revised: 01/07/2024] [Accepted: 02/05/2024] [Indexed: 02/17/2024]
Abstract
The time scales of long-time atomistic molecular dynamics simulations are typically reported in microseconds, while the time scales for experiments studying the kinetics of amyloid fibril formation are typically reported in minutes or hours. This time scale deficit of roughly 9 orders of magnitude presents a major challenge in the design of computer simulation methods for studying protein aggregation events. Coarse-grained molecular simulations offer a computationally tractable path forward for exploring the molecular mechanism driving the formation of these structures, which are implicated in diseases such as Alzheimer's, Parkinson's, and type-II diabetes. Network Hamiltonian models of aggregation are centered around a Hamiltonian function that returns the total energy of a system of aggregating proteins, given the graph structure of the system as an input. In the graph, or network, representation of the system, each protein molecule is represented as a node, and noncovalent bonds between proteins are represented as edges. The parameter, i.e., a set of coefficients that determine the degree to which each topological degree of freedom is favored or disfavored, must be determined for each network Hamiltonian model, and is a well-known technical challenge. The methodology is first demonstrated by beginning with an initial set of randomly parametrized models of low fibril fraction (<5% fibrillar), and evolving to subsequent generations of models, ultimately leading to high fibril fraction models (>70% fibrillar). The methodology is also demonstrated by applying it to optimizing previously published network Hamiltonian models for the 5 key amyloid fibril topologies that have been reported in the Protein Data Bank (PDB). The models generated by the AI produced fibril fractions that surpass previously published fibril fractions in 3 of 5 cases, including the most naturally abundant amyloid fibril topology, the 1,2 2-ribbon, which features a steric zipper. The authors also aim to encourage more widespread use of the network Hamiltonian methodology for fitting a wide variety of self-assembling systems by releasing a free open-source implementation of the genetic algorithm introduced here.
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Affiliation(s)
- Gianmarc Grazioli
- Department of Chemistry, San
José State University, San Jose, California 95192, United States
| | - Andy Tao
- Department of Chemistry, San
José State University, San Jose, California 95192, United States
| | - Inika Bhatia
- Department of Chemistry, San
José State University, San Jose, California 95192, United States
| | - Patrick Regan
- Department of Chemistry, San
José State University, San Jose, California 95192, United States
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23
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Christians LF, Halingstad EV, Kram E, Okolovitch EM, Pak AJ. Formalizing Coarse-Grained Representations of Anisotropic Interactions at Multimeric Protein Interfaces Using Virtual Sites. J Phys Chem B 2024; 128:1394-1406. [PMID: 38316012 DOI: 10.1021/acs.jpcb.3c07023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Abstract
Molecular simulations of biomacromolecules that assemble into multimeric complexes remain a challenge due to computationally inaccessible length and time scales. Low-resolution and implicit-solvent coarse-grained modeling approaches using traditional nonbonded interactions (both pairwise and spherically isotropic) have been able to partially address this gap. However, these models may fail to capture the complex anisotropic interactions present at macromolecular interfaces unless higher-order interaction potentials are incorporated at the expense of the computational cost. In this work, we introduce an alternate and systematic approach to represent directional interactions at protein-protein interfaces by using virtual sites restricted to pairwise interactions. We show that virtual site interaction parameters can be optimized within a relative entropy minimization framework by using only information from known statistics between coarse-grained sites. We compare our virtual site models to traditional coarse-grained models using two case studies of multimeric protein assemblies and find that the virtual site models predict pairwise correlations with higher fidelity and, more importantly, assembly behavior that is morphologically consistent with experiments. Our study underscores the importance of anisotropic interaction representations and paves the way for more accurate yet computationally efficient coarse-grained simulations of macromolecular assembly in future research.
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Affiliation(s)
- Luc F Christians
- Department of Chemical and Biological Engineering, Colorado School of Mines, Golden, Colorado 80401, United States
| | - Ethan V Halingstad
- Department of Chemical and Biological Engineering, Colorado School of Mines, Golden, Colorado 80401, United States
| | - Emiel Kram
- Department of Chemical and Biological Engineering, Colorado School of Mines, Golden, Colorado 80401, United States
| | - Evan M Okolovitch
- Department of Chemical and Biological Engineering, Colorado School of Mines, Golden, Colorado 80401, United States
| | - Alexander J Pak
- Department of Chemical and Biological Engineering, Colorado School of Mines, Golden, Colorado 80401, United States
- Quantitative Biosciences and Engineering Program, Colorado School of Mines, Golden, Colorado 80401, United States
- Materials Science Program, Colorado School of Mines, Golden, Colorado 80401, United States
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24
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Ni B, Kaplan DL, Buehler MJ. ForceGen: End-to-end de novo protein generation based on nonlinear mechanical unfolding responses using a language diffusion model. SCIENCE ADVANCES 2024; 10:eadl4000. [PMID: 38324676 PMCID: PMC10849601 DOI: 10.1126/sciadv.adl4000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 01/08/2024] [Indexed: 02/09/2024]
Abstract
Through evolution, nature has presented a set of remarkable protein materials, including elastins, silks, keratins and collagens with superior mechanical performances that play crucial roles in mechanobiology. However, going beyond natural designs to discover proteins that meet specified mechanical properties remains challenging. Here, we report a generative model that predicts protein designs to meet complex nonlinear mechanical property-design objectives. Our model leverages deep knowledge on protein sequences from a pretrained protein language model and maps mechanical unfolding responses to create proteins. Via full-atom molecular simulations for direct validation, we demonstrate that the designed proteins are de novo, and fulfill the targeted mechanical properties, including unfolding energy and mechanical strength, as well as the detailed unfolding force-separation curves. Our model offers rapid pathways to explore the enormous mechanobiological protein sequence space unconstrained by biological synthesis, using mechanical features as the target to enable the discovery of protein materials with superior mechanical properties.
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Affiliation(s)
- Bo Ni
- Laboratory for Atomistic and Molecular Mechanics (LAMM), Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA 02139, USA
| | - David L. Kaplan
- Department of Biomedical Engineering, Tufts University, Medford, MA 02155, USA
| | - Markus J. Buehler
- Laboratory for Atomistic and Molecular Mechanics (LAMM), Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA 02139, USA
- Center for Computational Science and Engineering, Schwarzman College of Computing, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA 02139, USA
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25
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Kidder KM, Shell MS, Noid WG. Surveying the energy landscape of coarse-grained mappings. J Chem Phys 2024; 160:054105. [PMID: 38310476 DOI: 10.1063/5.0182524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 12/28/2023] [Indexed: 02/05/2024] Open
Abstract
Simulations of soft materials often adopt low-resolution coarse-grained (CG) models. However, the CG representation is not unique and its impact upon simulated properties is poorly understood. In this work, we investigate the space of CG representations for ubiquitin, which is a typical globular protein with 72 amino acids. We employ Monte Carlo methods to ergodically sample this space and to characterize its landscape. By adopting the Gaussian network model as an analytically tractable atomistic model for equilibrium fluctuations, we exactly assess the intrinsic quality of each CG representation without introducing any approximations in sampling configurations or in modeling interactions. We focus on two metrics, the spectral quality and the information content, that quantify the extent to which the CG representation preserves low-frequency, large-amplitude motions and configurational information, respectively. The spectral quality and information content are weakly correlated among high-resolution representations but become strongly anticorrelated among low-resolution representations. Representations with maximal spectral quality appear consistent with physical intuition, while low-resolution representations with maximal information content do not. Interestingly, quenching studies indicate that the energy landscape of mapping space is very smooth and highly connected. Moreover, our study suggests a critical resolution below which a "phase transition" qualitatively distinguishes good and bad representations.
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Affiliation(s)
- Katherine M Kidder
- Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - M Scott Shell
- Department of Chemical Engineering, University of California, Santa Barbara, California 93106, USA
| | - W G Noid
- Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
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26
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Doni D, Cavallari E, Noguera ME, Gentili HG, Cavion F, Parisi G, Fornasari MS, Sartori G, Santos J, Bellanda M, Carbonera D, Costantini P, Bortolus M. Searching for Frataxin Function: Exploring the Analogy with Nqo15, the Frataxin-like Protein of Respiratory Complex I from Thermus thermophilus. Int J Mol Sci 2024; 25:1912. [PMID: 38339189 PMCID: PMC10855754 DOI: 10.3390/ijms25031912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Revised: 01/26/2024] [Accepted: 02/02/2024] [Indexed: 02/12/2024] Open
Abstract
Nqo15 is a subunit of respiratory complex I of the bacterium Thermus thermophilus, with strong structural similarity to human frataxin (FXN), a protein involved in the mitochondrial disease Friedreich's ataxia (FRDA). Recently, we showed that the expression of recombinant Nqo15 can ameliorate the respiratory phenotype of FRDA patients' cells, and this prompted us to further characterize both the Nqo15 solution's behavior and its potential functional overlap with FXN, using a combination of in silico and in vitro techniques. We studied the analogy of Nqo15 and FXN by performing extensive database searches based on sequence and structure. Nqo15's folding and flexibility were investigated by combining nuclear magnetic resonance (NMR), circular dichroism, and coarse-grained molecular dynamics simulations. Nqo15's iron-binding properties were studied using NMR, fluorescence, and specific assays and its desulfurase activation by biochemical assays. We found that the recombinant Nqo15 isolated from complex I is monomeric, stable, folded in solution, and highly dynamic. Nqo15 does not share the iron-binding properties of FXN or its desulfurase activation function.
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Affiliation(s)
- Davide Doni
- Department of Biology, University of Padova, 35121 Padova, Italy; (D.D.); (F.C.)
| | - Eva Cavallari
- Department of Biology, University of Padova, 35121 Padova, Italy; (D.D.); (F.C.)
- Grenoble Alpes University, CNRS, CEA, INRAE, IRIG-LPCV, 38000 Grenoble, France
| | - Martin Ezequiel Noguera
- Department of Physiology and Molecular and Cellular Biology, Institute of Biosciences, Biotechnology and Translational Biology (iB3), Faculty of Exact and Natural Sciences, University of Buenos Aires, Intendente Güiraldes 2160, Buenos Aires C1428EG, Argentina; (M.E.N.); (H.G.G.); (J.S.)
- Institute of Biological Chemistry and Physical Chemistry, Dr Alejandro Paladini (UBA-CONICET), University of Buenos Aires, Junín 956, Buenos Aires 1113AAD, Argentina
- Department of Science and Technology, National University of Quilmes, Roque Saenz Peña 352, Bernal B1876BXD, Argentina; (G.P.); (M.S.F.)
| | - Hernan Gustavo Gentili
- Department of Physiology and Molecular and Cellular Biology, Institute of Biosciences, Biotechnology and Translational Biology (iB3), Faculty of Exact and Natural Sciences, University of Buenos Aires, Intendente Güiraldes 2160, Buenos Aires C1428EG, Argentina; (M.E.N.); (H.G.G.); (J.S.)
| | - Federica Cavion
- Department of Biology, University of Padova, 35121 Padova, Italy; (D.D.); (F.C.)
| | - Gustavo Parisi
- Department of Science and Technology, National University of Quilmes, Roque Saenz Peña 352, Bernal B1876BXD, Argentina; (G.P.); (M.S.F.)
| | - Maria Silvina Fornasari
- Department of Science and Technology, National University of Quilmes, Roque Saenz Peña 352, Bernal B1876BXD, Argentina; (G.P.); (M.S.F.)
| | - Geppo Sartori
- Department of Biomedical Sciences, University of Padova, 35121 Padova, Italy;
| | - Javier Santos
- Department of Physiology and Molecular and Cellular Biology, Institute of Biosciences, Biotechnology and Translational Biology (iB3), Faculty of Exact and Natural Sciences, University of Buenos Aires, Intendente Güiraldes 2160, Buenos Aires C1428EG, Argentina; (M.E.N.); (H.G.G.); (J.S.)
| | - Massimo Bellanda
- Department of Chemical Sciences, University of Padova, 35131 Padova, Italy; (M.B.); (D.C.)
- Consiglio Nazionale delle Ricerche Institute of Biomolecular Chemistry, 35131 Padova, Italy
| | - Donatella Carbonera
- Department of Chemical Sciences, University of Padova, 35131 Padova, Italy; (M.B.); (D.C.)
| | - Paola Costantini
- Department of Biology, University of Padova, 35121 Padova, Italy; (D.D.); (F.C.)
| | - Marco Bortolus
- Department of Chemical Sciences, University of Padova, 35131 Padova, Italy; (M.B.); (D.C.)
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27
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Ertik O, Yanardag R. The evaluations of the inhibition of orlistat on Clostridium perfringens sialidase (NanI) activity by in vitro and in silico approaches. Chem Biodivers 2024; 21:e202301634. [PMID: 38156512 DOI: 10.1002/cbdv.202301634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 12/21/2023] [Accepted: 12/29/2023] [Indexed: 12/30/2023]
Abstract
Clostridium perfringens (C. perfringens) is a bacterium that causes serious problems in humans and animals such as food poisoning, gas gangrene and infections. C. perfringens has three sialidases (NanH, NanI, NanJ) and inhibition of NanI constitutes an approach in the treatment of C. perfringens since NanI provides the carbohydrate source necessary for the growth of bacteria. In our study, the inhibition effect of some drugs belonging to different drug groups on NanI activity was investigated. Among these drugs, orlistat (0.21±0.05 μM) was determined to have a lower IC50 value than the positive control quercetin (15.58±1.59 μM). It was determined in vitro by spectrofluorometric method. Additionally, NanI molecular docking studies with orlistatand quercetin were performed using iGemdock, DockThor and SwissDock. Orlistat (-93.93, -8.649 and -10.03 kcal/mol, respectively) was found to have a higher binding affinity than quercetin (-92.68, -7.491 and -8.70 kcal/mol, respectively), and the results were in line with in vitro studies. The results may suggest that orlistat is a molecule with drug potential for C. perfringens because it inhibits the drug target NanI, and that the inhibition efficiency can be increased by studies with orlistat derivatives.
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Affiliation(s)
- Onur Ertik
- Department of Chemistry, Faculty of Engineering, Istanbul University-Cerrahpaşa, Avcilar, Istanbul, Turkey
| | - Refiye Yanardag
- Department of Chemistry, Faculty of Engineering, Istanbul University-Cerrahpaşa, Avcilar, Istanbul, Turkey
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28
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Hosseini AN, van der Spoel D. Martini on the Rocks: Can a Coarse-Grained Force Field Model Crystals? J Phys Chem Lett 2024; 15:1079-1088. [PMID: 38261634 PMCID: PMC10839907 DOI: 10.1021/acs.jpclett.4c00012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 01/18/2024] [Accepted: 01/19/2024] [Indexed: 01/25/2024]
Abstract
Computational chemistry is an important tool in numerous scientific disciplines, including drug discovery and structural biology. Coarse-grained models offer simple representations of molecular systems that enable simulations of large-scale systems. Because there has been an increase in the adoption of such models for simulations of biomolecular systems, critical evaluation is warranted. Here, the stability of the amyloid peptide and organic crystals is evaluated using the Martini 3 coarse-grained force field. The crystals change shape drastically during the simulations. Radial distribution functions show that the distance between backbone beads in β-sheets increases by ∼1 Å, breaking the crystals. The melting points of organic compounds are much too low in the Martini force field. This suggests that Martini 3 lacks the specific interactions needed to accurately simulate peptides or organic crystals without imposing artificial restraints. The problems may be exacerbated by the use of the 12-6 potential, suggesting that a softer potential could improve this model for crystal simulations.
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Affiliation(s)
- A. Najla Hosseini
- Department of Cell and Molecular
Biology, Uppsala University, Box 596, SE-75124 Uppsala, Sweden
| | - David van der Spoel
- Department of Cell and Molecular
Biology, Uppsala University, Box 596, SE-75124 Uppsala, Sweden
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29
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Wu X, Hone AJ, Huang YH, Clark RJ, McIntosh JM, Kaas Q, Craik DJ. Computational Design of α-Conotoxins to Target Specific Nicotinic Acetylcholine Receptor Subtypes. Chemistry 2024; 30:e202302909. [PMID: 37910861 PMCID: PMC10872529 DOI: 10.1002/chem.202302909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 10/25/2023] [Accepted: 10/26/2023] [Indexed: 11/03/2023]
Abstract
Nicotinic acetylcholine receptors (nAChRs) are drug targets for neurological diseases and disorders, but selective targeting of the large number of nAChR subtypes is challenging. Marine cone snail α-conotoxins are potent blockers of nAChRs and some have been engineered to achieve subtype selectivity. This engineering effort would benefit from rapid computational methods able to predict mutational energies, but current approaches typically require high-resolution experimental structures, which are not widely available for α-conotoxin complexes. Herein, five mutational energy prediction methods were benchmarked using crystallographic and mutational data on two acetylcholine binding protein/α-conotoxin systems. Molecular models were developed for six nAChR subtypes in complex with five α-conotoxins that were studied through 150 substitutions. The best method was a combination of FoldX and molecular dynamics simulations, resulting in a predictive Matthews Correlation Coefficient (MCC) of 0.68 (85 % accuracy). Novel α-conotoxin mutants designed using this method were successfully validated by experimental assay with improved pharmaceutical properties. This work paves the way for the rapid design of subtype-specific nAChR ligands and potentially accelerated drug development.
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Affiliation(s)
- Xiaosa Wu
- Institute for Molecular Bioscience, Australian Research Council Centre of Excellence for Innovations in Peptide and Protein Science, The University of Queensland, Brisbane, Queensland, 4072, Australia
- School of Biomedical Sciences, The University of Queensland, Brisbane, Queensland, 4072, Australia
| | - Arik J Hone
- School of Biological Science, University of Utah, Salt Lake City, Utah, 84112, USA
- MIRECC, George E. Whalen Veterans Affairs Medical Center, Salt Lake City, Utah, 84112, USA
| | - Yen-Hua Huang
- Institute for Molecular Bioscience, Australian Research Council Centre of Excellence for Innovations in Peptide and Protein Science, The University of Queensland, Brisbane, Queensland, 4072, Australia
| | - Richard J Clark
- School of Biomedical Sciences, The University of Queensland, Brisbane, Queensland, 4072, Australia
| | - J Michael McIntosh
- School of Biological Science, University of Utah, Salt Lake City, Utah, 84112, USA
- Department of Psychiatry, University of Utah, Salt Lake City, Utah, 84112, USA
- George E. Whalen Veterans Affairs Medical Center, Salt Lake City, Utah, 84112, USA
| | - Quentin Kaas
- Institute for Molecular Bioscience, Australian Research Council Centre of Excellence for Innovations in Peptide and Protein Science, The University of Queensland, Brisbane, Queensland, 4072, Australia
| | - David J Craik
- Institute for Molecular Bioscience, Australian Research Council Centre of Excellence for Innovations in Peptide and Protein Science, The University of Queensland, Brisbane, Queensland, 4072, Australia
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30
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Badaczewska-Dawid A, Wróblewski K, Kurcinski M, Kmiecik S. Structure prediction of linear and cyclic peptides using CABS-flex. Brief Bioinform 2024; 25:bbae003. [PMID: 38305457 PMCID: PMC10836054 DOI: 10.1093/bib/bbae003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 12/08/2023] [Accepted: 12/28/2023] [Indexed: 02/03/2024] Open
Abstract
The structural modeling of peptides can be a useful aid in the discovery of new drugs and a deeper understanding of the molecular mechanisms of life. Here we present a novel multiscale protocol for the structure prediction of linear and cyclic peptides. The protocol combines two main stages: coarse-grained simulations using the CABS-flex standalone package and an all-atom reconstruction-optimization process using the Modeller program. We evaluated the protocol on a set of linear peptides and two sets of cyclic peptides, with cyclization through the backbone and disulfide bonds. A comparison with other state-of-the-art tools (APPTEST, PEP-FOLD, ESMFold and AlphaFold implementation in ColabFold) shows that for most cases, AlphaFold offers the highest resolution. However, CABS-flex is competitive, particularly when it comes to short linear peptides. As demonstrated, the protocol performance can be further improved by combination with the residue-residue contact prediction method or more efficient scoring. The protocol is included in the CABS-flex standalone package along with online documentation to aid users in predicting the structure of peptides and mini-proteins.
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Affiliation(s)
| | - Karol Wróblewski
- Biological and Chemical Research Center, Faculty of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
| | - Mateusz Kurcinski
- Biological and Chemical Research Center, Faculty of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
| | - Sebastian Kmiecik
- Biological and Chemical Research Center, Faculty of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
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31
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Zhang Y, Li S, Gong X, Chen J. Toward Accurate Simulation of Coupling between Protein Secondary Structure and Phase Separation. J Am Chem Soc 2024; 146:342-357. [PMID: 38112495 PMCID: PMC10842759 DOI: 10.1021/jacs.3c09195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
Intrinsically disordered proteins (IDPs) frequently mediate phase separation that underlies the formation of a biomolecular condensate. Together with theory and experiment, efficient coarse-grained (CG) simulations have been instrumental in understanding the sequence-specific phase separation of IDPs. However, the widely used Cα-only models are limited in capturing the peptide nature of IDPs, particularly backbone-mediated interactions and effects of secondary structures, in phase separation. Here, we describe a hybrid resolution (HyRes) protein model toward a more accurate description of the backbone and transient secondary structures in phase separation. With an atomistic backbone and coarse-grained side chains, HyRes can semiquantitatively capture the residue helical propensity and overall chain dimension of monomeric IDPs. Using GY-23 as a model system, we show that HyRes is efficient enough for the direct simulation of spontaneous phase separation and, at the same time, appears accurate enough to resolve the effects of single His to Lys mutations. HyRes simulations also successfully predict increased β-structure formation in the condensate, consistent with available experimental CD data. We further utilize HyRes to study the phase separation of TPD-43, where several disease-related mutants in the conserved region (CR) have been shown to affect residual helicities and modulate the phase separation propensity as measured by the saturation concentration. The simulations successfully recapitulate the effect of these mutants on the helicity and phase separation propensity of TDP-43 CR. Analyses reveal that the balance between backbone and side chain-mediated interactions, but not helicity itself, actually determines phase separation propensity. These results support that HyRes represents an effective protein model for molecular simulation of IDP phase separation and will help to elucidate the coupling between transient secondary structures and phase separation.
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Affiliation(s)
| | | | - Xiping Gong
- Department of Chemistry, University of Massachusetts, Amherst, MA 01003, USA
| | - Jianhan Chen
- Department of Chemistry, University of Massachusetts, Amherst, MA 01003, USA
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32
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Kehrein J, Sotriffer C. Molecular Dynamics Simulations for Rationalizing Polymer Bioconjugation Strategies: Challenges, Recent Developments, and Future Opportunities. ACS Biomater Sci Eng 2024; 10:51-74. [PMID: 37466304 DOI: 10.1021/acsbiomaterials.3c00636] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2023]
Abstract
The covalent modification of proteins with polymers is a well-established method for improving the pharmacokinetic properties of therapeutically valuable biologics. The conjugated polymer chains of the resulting hybrid represent highly flexible macromolecular structures. As the dynamics of such systems remain rather elusive for established experimental techniques from the field of protein structure elucidation, molecular dynamics simulations have proven as a valuable tool for studying such conjugates at an atomistic level, thereby complementing experimental studies. With a focus on new developments, this review aims to provide researchers from the polymer bioconjugation field with a concise and up to date overview of such approaches. After introducing basic principles of molecular dynamics simulations, as well as methods for and potential pitfalls in modeling bioconjugates, the review illustrates how these computational techniques have contributed to the understanding of bioconjugates and bioconjugation strategies in the recent past and how they may lead to a more rational design of novel bioconjugates in the future.
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Affiliation(s)
- Josef Kehrein
- Institute of Pharmacy and Food Chemistry, University of Würzburg, Würzburg 97074, Germany
| | - Christoph Sotriffer
- Institute of Pharmacy and Food Chemistry, University of Würzburg, Würzburg 97074, Germany
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33
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Heo L, Feig M. One bead per residue can describe all-atom protein structures. Structure 2024; 32:97-111.e6. [PMID: 38000367 PMCID: PMC10872525 DOI: 10.1016/j.str.2023.10.013] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 09/16/2023] [Accepted: 10/30/2023] [Indexed: 11/26/2023]
Abstract
Atomistic resolution is the standard for high-resolution biomolecular structures, but experimental structural data are often at lower resolution. Coarse-grained models are also used extensively in computational studies to reach biologically relevant spatial and temporal scales. This study explores the use of advanced machine learning networks for reconstructing atomistic models from reduced representations. The main finding is that a single bead per amino acid residue allows construction of accurate and stereochemically realistic all-atom structures with minimal loss of information. This suggests that lower resolution representations of proteins may be sufficient for many applications when combined with a machine learning framework that encodes knowledge from known structures. Practical applications include the rapid addition of atomistic detail to low-resolution structures from experiment or computational coarse-grained models. The application of rapid, deterministic all-atom reconstruction within multi-scale frameworks is further demonstrated with a rapid protocol for the generation of accurate models from cryo-EM densities close to experimental structures.
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Affiliation(s)
- Lim Heo
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA
| | - Michael Feig
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA.
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34
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Basu S, Veeraraghavan B, Anbarasu A. Impact of PmrB mutations on clinical Klebsiella pneumoniae with variable colistin-susceptibilities: Structural insights and potent therapeutic solutions. Chem Biol Drug Des 2024; 103:e14381. [PMID: 37875387 DOI: 10.1111/cbdd.14381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 08/09/2023] [Accepted: 10/10/2023] [Indexed: 10/26/2023]
Abstract
Carbapenem-resistant Klebsiella pneumoniae (CRKP) infections continue to impose high morbidity threats to hospitalized patients worldwide, limiting therapeutic options to last-resort antibiotics like colistin. However, the dynamic genomic landscape of colistin-resistant K. pneumoniae (COLR-Kp) invoked ardent exploration of underlying molecular signatures for therapeutic propositions/designs. We unveiled the structural impact of the widespread and emerging PmrB mutations involved in colistin resistance (COLR) in K. pneumoniae. In the present study, clinical isolates of K. pneumoniae expressed variable susceptibilities to colistin (>0.5 μg/mL for resistant and ≤0.25 μg/mL for susceptible) despite mutations such as T157P, G207D and T246A. The protein sequences extracted from in-house sequenced genomes were used to model mutant PmrB proteins and analyze the underlying structural alterations. The mutations were contrasted based on molecular dynamics simulation trajectories, free-energy landscapes and structural flexibility profiles. The altered backbone flexibilities can be an essential factor for mutant selection by COLR K. pneumoniae and can provide clues to deal with emerging mutants. Furthermore, PmrB having high druggability confidence (>0.99), was explored as a potential target for 1396 virtually screened FDA-approved drug candidates. Among the top-10 compounds (scores >70), amphotericin B was found to be potential candidate with high affinity (Binding energy <-8 kcal/mol) and stable interactions (RMSF <0.7 Å) against PmrB druggable pockets, despite the mutations, which encourages future adjunct therapeutic research against COLR-Kp.
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Affiliation(s)
- Soumya Basu
- Medical and Biological Computing Laboratory, School of Biosciences and Technology (SBST), Vellore Institute of Technology (VIT), Vellore, India
| | - Balaji Veeraraghavan
- Department of Clinical Microbiology, Christian Medical College (CMC), Vellore, India
| | - Anand Anbarasu
- Medical and Biological Computing Laboratory, School of Biosciences and Technology (SBST), Vellore Institute of Technology (VIT), Vellore, India
- Department of Biotechnology, SBST, VIT, Vellore, India
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35
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Levintov L, Vashisth H. Structural and computational studies of HIV-1 RNA. RNA Biol 2024; 21:1-32. [PMID: 38100535 PMCID: PMC10730233 DOI: 10.1080/15476286.2023.2289709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/21/2023] [Indexed: 12/17/2023] Open
Abstract
Viruses remain a global threat to animals, plants, and humans. The type 1 human immunodeficiency virus (HIV-1) is a member of the retrovirus family and carries an RNA genome, which is reverse transcribed into viral DNA and further integrated into the host-cell DNA for viral replication and proliferation. The RNA structures from the HIV-1 genome provide valuable insights into the mechanisms underlying the viral replication cycle. Moreover, these structures serve as models for designing novel therapeutic approaches. Here, we review structural data on RNA from the HIV-1 genome as well as computational studies based on these structural data. The review is organized according to the type of structured RNA element which contributes to different steps in the viral replication cycle. This is followed by an overview of the HIV-1 transactivation response element (TAR) RNA as a model system for understanding dynamics and interactions in the viral RNA systems. The review concludes with a description of computational studies, highlighting the impact of biomolecular simulations in elucidating the mechanistic details of various steps in the HIV-1's replication cycle.
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Affiliation(s)
- Lev Levintov
- Department of Chemical Engineering & Bioengineering, University of New Hampshire, Durham, USA
| | - Harish Vashisth
- Department of Chemical Engineering & Bioengineering, University of New Hampshire, Durham, USA
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36
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Ali S, Chourasia P, Patterson M. When Protein Structure Embedding Meets Large Language Models. Genes (Basel) 2023; 15:25. [PMID: 38254915 PMCID: PMC10815811 DOI: 10.3390/genes15010025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 12/16/2023] [Accepted: 12/21/2023] [Indexed: 01/24/2024] Open
Abstract
Protein structure analysis is essential in various bioinformatics domains such as drug discovery, disease diagnosis, and evolutionary studies. Within structural biology, the classification of protein structures is pivotal, employing machine learning algorithms to categorize structures based on data from databases like the Protein Data Bank (PDB). To predict protein functions, embeddings based on protein sequences have been employed. Creating numerical embeddings that preserve vital information while considering protein structure and sequence presents several challenges. The existing literature lacks a comprehensive and effective approach that combines structural and sequence-based features to achieve efficient protein classification. While large language models (LLMs) have exhibited promising outcomes for protein function prediction, their focus primarily lies on protein sequences, disregarding the 3D structures of proteins. The quality of embeddings heavily relies on how well the geometry of the embedding space aligns with the underlying data structure, posing a critical research question. Traditionally, Euclidean space has served as a widely utilized framework for embeddings. In this study, we propose a novel method for designing numerical embeddings in Euclidean space for proteins by leveraging 3D structure information, specifically employing the concept of contact maps. These embeddings are synergistically combined with features extracted from LLMs and traditional feature engineering techniques to enhance the performance of embeddings in supervised protein analysis. Experimental results on benchmark datasets, including PDB Bind and STCRDAB, demonstrate the superior performance of the proposed method for protein function prediction.
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Affiliation(s)
| | | | - Murray Patterson
- Department of Computer Science, Georgia State University, Atlanta, GA 30303, USA; (S.A.); (P.C.)
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37
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Fang R, Lu Y. Simulating the conformational dynamics of the ATPase complex on proteasome using its free-energy landscape. STAR Protoc 2023; 4:102182. [PMID: 37768828 PMCID: PMC10542641 DOI: 10.1016/j.xpro.2023.102182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 01/16/2023] [Accepted: 02/23/2023] [Indexed: 09/30/2023] Open
Abstract
The AAA+ ATPase complex on proteasome powers its functions through a series of intricate conformational transitions. Here, we describe a procedure to simulate the conformational dynamics of the proteasomal ATPase complex. We first empirically determined the free-energy landscape (FEL) of proteasome and then simulated proteasome's conformational changes as stochastic transitions on its FEL. We compared the FEL-predicted proteasomal behaviors with experimental measurements and analyzed the map of the ATPase's global dynamics to gain mechanistic insights into proteasomal degradation. For complete details on the use and execution of this protocol, please refer to Fang et al. (2022).1.
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Affiliation(s)
- Rui Fang
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA; Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA.
| | - Ying Lu
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA.
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38
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Kim S. Backmapping with Mapping and Isomeric Information. J Phys Chem B 2023. [PMID: 38049145 DOI: 10.1021/acs.jpcb.3c05593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/06/2023]
Abstract
I present a powerful and flexible backmapping tool named Multiscale Simulation Tool (mstool) that converts a coarse-grained (CG) system into all-atom (AA) resolution and only requires AA to CG mapping and isomeric information (cis/trans/dihedral/chiral). The backmapping procedure includes two simple steps: (a) AA atoms are randomly placed near the corresponding CG beads according to the provided mapping scheme. (b) Energy minimization is performed with two modifications in the AA force field (FF). First, nonbonded interactions are replaced with cosine functions to ensure the numerical stability. Second, additional torsions are imposed to maintain the molecules' isomeric properties. To test the simplicity and robustness of the tool, I backmapped multiple membrane and protein CG structures into AA resolution, including a four-bead CG lipid model (resolution increased by a factor of 34) without using intermediate resolution. The tool is freely available at github.com/ksy141/mstool.
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Affiliation(s)
- Siyoung Kim
- Pritzker School of Molecular Engineering, University of Chicago, Chicago, Illinois 60637 United States
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39
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Zhou H, Shiel E, Bell T, Lin S, Lenhert S. Kinetic Mechanism of Surfactant-Based Molecular Recognition: Selective Permeability across an Oil-Water Interface Regulated by Supramolecular Aggregates. J Phys Chem B 2023; 127:10201-10214. [PMID: 37972386 DOI: 10.1021/acs.jpcb.3c05017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2023]
Abstract
Lipids are known to play a vital role in the molecular organization of all cellular life. Molecular recognition is another fundamental biological process that is generally attributed to biological polymers, such as proteins and nucleic acids. However, there is evidence that aggregates of lipids and lipid-like molecules are also capable of selectively binding to or regulating the partitioning of other molecules. We previously demonstrated that a model two-phase octanol/water system can selectively partition Red 40 and Blue 1 dyes added to an aqueous phase, with the selectivity depending on the surfactant (e.g., cetyltrimethylammonium bromide) dissolved in the organic phase. Here, we elucidate the mechanism of molecular recognition in this system by using quantitative partitioning experiments and molecular dynamics (MD) simulations. Our results indicate that the selectivity for the red dye is thermodynamically favored at all surfactant concentrations, while selectivity for the blue dye is kinetically favored at high surfactant concentrations. The kinetic selectivity for the blue dye correlates with the presence of molecular aggregation at the oil-water interface. Coarse-grained MD simulations elucidate nanoscale supramolecular structures that can preferentially bind one small molecule rather than another at an interface, providing a selectively permeable barrier in the absence of proteins. The results suggest a new supramolecular mechanism for molecular recognition with potential applications in drug delivery, drug discovery, and biosensing.
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Affiliation(s)
- Huanhuan Zhou
- Department of Biological Science and Integrative Nanoscience Institute, Florida State University, Tallahassee, Florida 32306, United States
| | - Emily Shiel
- Department of Chemistry and Biochemistry, Florida State University, Tallahassee, Florida 32306, United States
| | - Tracey Bell
- Department of Biological Science and Integrative Nanoscience Institute, Florida State University, Tallahassee, Florida 32306, United States
| | - Shangchao Lin
- Institute of Engineering Thermophysics, School of Mechanical and Power Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Steven Lenhert
- Department of Biological Science and Integrative Nanoscience Institute, Florida State University, Tallahassee, Florida 32306, United States
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40
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Vlachy V, Kalyuzhnyi YV, Hribar-Lee B, Dill KA. Protein Association in Solution: Statistical Mechanical Modeling. Biomolecules 2023; 13:1703. [PMID: 38136574 PMCID: PMC10742237 DOI: 10.3390/biom13121703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 11/16/2023] [Accepted: 11/20/2023] [Indexed: 12/24/2023] Open
Abstract
Protein molecules associate in solution, often in clusters beyond pairwise, leading to liquid phase separations and high viscosities. It is often impractical to study these multi-protein systems by atomistic computer simulations, particularly in multi-component solvents. Instead, their forces and states can be studied by liquid state statistical mechanics. However, past such approaches, such as the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory, were limited to modeling proteins as spheres, and contained no microscopic structure-property relations. Recently, this limitation has been partly overcome by bringing the powerful Wertheim theory of associating molecules to bear on protein association equilibria. Here, we review these developments.
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Affiliation(s)
- Vojko Vlachy
- Faculty of Chemistry and Chemical Technology, University of Ljubljana, 1000 Ljubljana, Slovenia;
| | | | - Barbara Hribar-Lee
- Faculty of Chemistry and Chemical Technology, University of Ljubljana, 1000 Ljubljana, Slovenia;
| | - Ken A. Dill
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, New York, NY 11794, USA;
- Department of Chemistry, Physics and Astronomy, Stony Brook University, New York, NY 11790, USA
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41
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Aierken D, Bachmann M. Secondary-structure phase formation for semiflexible polymers by bifurcation in hyperphase space. Phys Chem Chem Phys 2023; 25:30246-30258. [PMID: 37921656 DOI: 10.1039/d3cp02815a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2023]
Abstract
Canonical analysis has long been the primary analysis method for studies of phase transitions. However, this approach is not sensitive enough if transition signals are too close in temperature space. The recently introduced generalized microcanonical inflection-point analysis method not only enables the systematic identification and classification of transitions in systems of any size, but it can also distinguish transitions that standard canonical analysis cannot resolve. By applying this method to a generic coarse-grained model for semiflexible polymers, we identify a mixed structural phase dominated by secondary structures such as hairpins and loops that originates from a bifurcation in the hyperspace spanned by inverse temperature and bending stiffness. This intermediate phase, which is embraced by the well-known random-coil and toroidal phases, is testimony to the necessity of balancing entropic variability and energetic stability in functional macromolecules under physiological conditions.
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Affiliation(s)
- Dilimulati Aierken
- Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ 08544, USA
- Omenn-Darling Bioengineering Institute, Princeton University, Princeton, NJ 08540, USA.
- Soft Matter Systems Research Group, Center for Simulational Physics, Department of Physics and Astronomy, The University of Georgia, Athens, GA 30602, USA.
| | - Michael Bachmann
- Soft Matter Systems Research Group, Center for Simulational Physics, Department of Physics and Astronomy, The University of Georgia, Athens, GA 30602, USA.
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42
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Jones MS, Shmilovich K, Ferguson AL. DiAMoNDBack: Diffusion-Denoising Autoregressive Model for Non-Deterministic Backmapping of Cα Protein Traces. J Chem Theory Comput 2023; 19:7908-7923. [PMID: 37906711 DOI: 10.1021/acs.jctc.3c00840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Coarse-grained molecular models of proteins permit access to length and time scales unattainable by all-atom models and the simulation of processes that occur on long time scales, such as aggregation and folding. The reduced resolution realizes computational accelerations, but an atomistic representation can be vital for a complete understanding of mechanistic details. Backmapping is the process of restoring all-atom resolution to coarse-grained molecular models. In this work, we report DiAMoNDBack (Diffusion-denoising Autoregressive Model for Non-Deterministic Backmapping) as an autoregressive denoising diffusion probability model to restore all-atom details to coarse-grained protein representations retaining only Cα coordinates. The autoregressive generation process proceeds from the protein N-terminus to C-terminus in a residue-by-residue fashion conditioned on the Cα trace and previously backmapped backbone and side-chain atoms within the local neighborhood. The local and autoregressive nature of our model makes it transferable between proteins. The stochastic nature of the denoising diffusion process means that the model generates a realistic ensemble of backbone and side-chain all-atom configurations consistent with the coarse-grained Cα trace. We train DiAMoNDBack over 65k+ structures from the Protein Data Bank (PDB) and validate it in applications to a hold-out PDB test set, intrinsically disordered protein structures from the Protein Ensemble Database (PED), molecular dynamics simulations of fast-folding mini-proteins from DE Shaw Research, and coarse-grained simulation data. We achieve state-of-the-art reconstruction performance in terms of correct bond formation, avoidance of side-chain clashes, and the diversity of the generated side-chain configurational states. We make the DiAMoNDBack model publicly available as a free and open-source Python package.
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Affiliation(s)
- Michael S Jones
- Pritzker School of Molecular Engineering, University of Chicago, Chicago, Illinois 60637, United States
| | - Kirill Shmilovich
- Pritzker School of Molecular Engineering, University of Chicago, Chicago, Illinois 60637, United States
| | - Andrew L Ferguson
- Pritzker School of Molecular Engineering, University of Chicago, Chicago, Illinois 60637, United States
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43
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Laurent H, Hughes MDG, Walko M, Brockwell DJ, Mahmoudi N, Youngs TGA, Headen TF, Dougan L. Visualization of Self-Assembly and Hydration of a β-Hairpin through Integrated Small and Wide-Angle Neutron Scattering. Biomacromolecules 2023; 24:4869-4879. [PMID: 37874935 PMCID: PMC10646990 DOI: 10.1021/acs.biomac.3c00583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 10/03/2023] [Indexed: 10/26/2023]
Abstract
Fundamental understanding of the structure and assembly of nanoscale building blocks is crucial for the development of novel biomaterials with defined architectures and function. However, accessing self-consistent structural information across multiple length scales is challenging. This limits opportunities to exploit atomic scale interactions to achieve emergent macroscale properties. In this work we present an integrative small- and wide-angle neutron scattering approach coupled with computational modeling to reveal the multiscale structure of hierarchically self-assembled β hairpins in aqueous solution across 4 orders of magnitude in length scale from 0.1 Å to 300 nm. Our results demonstrate the power of this self-consistent cross-length scale approach and allows us to model both the large-scale self-assembly and small-scale hairpin hydration of the model β hairpin CLN025. Using this combination of techniques, we map the hydrophobic/hydrophilic character of this model self-assembled biomolecular surface with atomic resolution. These results have important implications for the multiscale investigation of aqueous peptides and proteins, for the prediction of ligand binding and molecular associations for drug design, and for understanding the self-assembly of peptides and proteins for functional biomaterials.
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Affiliation(s)
- Harrison Laurent
- School
of Physics and Astronomy, University of
Leeds, Leeds, United Kingdom, LS2
9JT
| | - Matt D. G. Hughes
- School
of Physics and Astronomy, University of
Leeds, Leeds, United Kingdom, LS2
9JT
- Astbury
Centre for Structural Molecular Biology, University of Leeds, Leeds, United Kingdom LS2
9JT
| | - Martin Walko
- School
of Chemistry, University of Leeds, Leeds, United
Kingdom, LS2 9JT
| | - David J. Brockwell
- Astbury
Centre for Structural Molecular Biology, University of Leeds, Leeds, United Kingdom LS2
9JT
| | - Najet Mahmoudi
- ISIS
Neutron and Muon Source, Rutherford Appleton
Laboratory, Harwell Oxford, Didcot, United Kingdom, OX11 0QX
| | - Tristan G. A. Youngs
- ISIS
Neutron and Muon Source, Rutherford Appleton
Laboratory, Harwell Oxford, Didcot, United Kingdom, OX11 0QX
| | - Thomas F. Headen
- ISIS
Neutron and Muon Source, Rutherford Appleton
Laboratory, Harwell Oxford, Didcot, United Kingdom, OX11 0QX
| | - Lorna Dougan
- School
of Physics and Astronomy, University of
Leeds, Leeds, United Kingdom, LS2
9JT
- Astbury
Centre for Structural Molecular Biology, University of Leeds, Leeds, United Kingdom LS2
9JT
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44
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Lipska A, Sieradzan AK, Atmaca S, Czaplewski C, Liwo A. Toward Consistent Physics-Based Modeling of Local Backbone Structures and Chirality Change of Proteins in Coarse-Grained Approaches. J Phys Chem Lett 2023; 14:9824-9833. [PMID: 37889895 PMCID: PMC10641867 DOI: 10.1021/acs.jpclett.3c01988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 10/23/2023] [Accepted: 10/24/2023] [Indexed: 10/29/2023]
Abstract
A reliable representation of local interactions is critical for the accuracy of modeling protein structure and dynamics at both the all-atom and coarse-grained levels. The development of local (mainly torsional) potentials was focused on careful parametrization of the predetermined (usually Fourier) formulas rather than on their physics-based derivation. In this Perspective we discuss the state-of-the-art methods for modeling local interactions, including the scale-consistent theory developed in our laboratory, which implies that the coarse-grained torsional potentials inseparably depend on the virtual-bond angles adjacent to a given dihedral and that multitorsional terms should be considered. We extend the treatment to split the residue-based torsional potentials into the site-based regular and improper torsional potentials. These considerations are illustrated with the revised torsional potentials and improper-torsional potentials involving the l-alanine residue and the improper-torsional potential corresponding to serine-residue enantiomerization. Applications of the new approach in coarse-grained modeling and revising all-atom force fields are discussed.
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Affiliation(s)
- Agnieszka
G. Lipska
- Centre
of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit
Union of Universities in Gdańsk, ul. G. Narutowicza 11/12, 80-233 Gdańsk, Poland
| | - Adam K. Sieradzan
- Centre
of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit
Union of Universities in Gdańsk, ul. G. Narutowicza 11/12, 80-233 Gdańsk, Poland
- Faculty
of Chemistry, University of Gdańsk,
Fahrenheit Union of Universities, ul. Wita Stwosza 63, 80-308 Gdańsk, Poland
| | - Sümeyye Atmaca
- Kocaeli
University, Institute of Science,
Umuttepe Yerleşkesi, 41001 İzmit/Kocaeli̇, Türkiye
| | - Cezary Czaplewski
- Centre
of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit
Union of Universities in Gdańsk, ul. G. Narutowicza 11/12, 80-233 Gdańsk, Poland
- Faculty
of Chemistry, University of Gdańsk,
Fahrenheit Union of Universities, ul. Wita Stwosza 63, 80-308 Gdańsk, Poland
| | - Adam Liwo
- Centre
of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit
Union of Universities in Gdańsk, ul. G. Narutowicza 11/12, 80-233 Gdańsk, Poland
- Faculty
of Chemistry, University of Gdańsk,
Fahrenheit Union of Universities, ul. Wita Stwosza 63, 80-308 Gdańsk, Poland
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45
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Kryś JD, Gront D. Coarse-grained potential for hydrogen bond interactions. J Mol Graph Model 2023; 124:108507. [PMID: 37295157 DOI: 10.1016/j.jmgm.2023.108507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 04/12/2023] [Accepted: 04/18/2023] [Indexed: 06/12/2023]
Abstract
Understanding protein structure and dynamics is crucial for investigating numerous biological processes. This however requires proper description of molecular interactions, most notably hydrogen bonds, which are the driving force behind the folding of protein sequences into working molecules. Due to the multi-body character of this interaction, proper mathematical formulation has been a matter of long debate in the literature. This description becomes even more complex in reduced protein models. In this contribution, we propose a novel hydrogen bond energy function definition that is based only on Cα positions and used for coarse-grained simulations. We show that this new method has the capability to recognize hydrogen bonds with over 80% accuracy and can successfully identify β-sheet in β-amyloid peptide simulations.
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Affiliation(s)
- Justyna D Kryś
- Faculty of Chemistry, Biological and Chemical Research Center, University of Warsaw, Pasteura 1, 02-093, Warsaw, Poland.
| | - Dominik Gront
- Faculty of Chemistry, Biological and Chemical Research Center, University of Warsaw, Pasteura 1, 02-093, Warsaw, Poland
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46
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Kehrein J, Gürsöz E, Davies M, Luxenhofer R, Bunker A. Unravel the Tangle: Atomistic Insight into Ultrahigh Curcumin-Loaded Polymer Micelles. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2023; 19:e2303066. [PMID: 37403298 DOI: 10.1002/smll.202303066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 06/22/2023] [Indexed: 07/06/2023]
Abstract
Amphiphilic ABA-triblock copolymers, comprised of poly(2-oxazoline) and poly(2-oxazine), can solubilize poorly water-soluble molecules in a structure-dependent manner forming micelles with exceptionally high drug loading. All-atom molecular dynamics simulations are conducted on previously experimentally characterized, curcumin-loaded micelles to dissect the structure-property relationships. Polymer-drug interactions for different levels of drug loading and variation in polymer structures of both the inner hydrophobic core and outer hydrophilic shell are investigated. In silico, the system with the highest experimental loading capacity shows the highest number of drug molecules encapsulated by the core. Furthermore, in systems with lower loading capacity outer A blocks show a greater extent of entanglement with the inner B blocks. Hydrogen bond analyses corroborate previous hypotheses: poly(2-butyl-2-oxazoline) B blocks, found experimentally to have reduced loading capacity for curcumin compared to poly(2-propyl-2-oxazine), establish fewer but longer-lasting hydrogen bonds. This possibly results from different sidechain conformations around the hydrophobic cargo, which is investigated by unsupervised machine learning to cluster monomers in smaller model systems mimicking different micelle compartments. Exchanging poly(2-methyl-2-oxazoline) with poly(2-ethyl-2-oxazoline) leads to increased drug interactions and reduced corona hydration; this suggests an impairment of micelle solubility or colloidal stability. These observations can help driving forward a more rational a priori nanoformulation design.
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Affiliation(s)
- Josef Kehrein
- Soft Matter Chemistry, Department of Chemistry, Faculty of Science, University of Helsinki, Helsinki, 00014, Finland
- Division of Pharmaceutical Biosciences, Drug Research Program, Faculty of Pharmacy, University of Helsinki, Helsinki, 00014, Finland
| | - Ekinsu Gürsöz
- Soft Matter Chemistry, Department of Chemistry, Faculty of Science, University of Helsinki, Helsinki, 00014, Finland
- Division of Pharmaceutical Biosciences, Drug Research Program, Faculty of Pharmacy, University of Helsinki, Helsinki, 00014, Finland
| | - Matthew Davies
- Department of Physics and Astronomy, The University of Western Ontario, 1151 Richmond Street, London, Ontario, N6A 5B7, Canada
| | - Robert Luxenhofer
- Soft Matter Chemistry, Department of Chemistry, Faculty of Science, University of Helsinki, Helsinki, 00014, Finland
| | - Alex Bunker
- Division of Pharmaceutical Biosciences, Drug Research Program, Faculty of Pharmacy, University of Helsinki, Helsinki, 00014, Finland
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47
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Borges-Araújo L, Patmanidis I, Singh AP, Santos LHS, Sieradzan AK, Vanni S, Czaplewski C, Pantano S, Shinoda W, Monticelli L, Liwo A, Marrink SJ, Souza PCT. Pragmatic Coarse-Graining of Proteins: Models and Applications. J Chem Theory Comput 2023; 19:7112-7135. [PMID: 37788237 DOI: 10.1021/acs.jctc.3c00733] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
The molecular details involved in the folding, dynamics, organization, and interaction of proteins with other molecules are often difficult to assess by experimental techniques. Consequently, computational models play an ever-increasing role in the field. However, biological processes involving large-scale protein assemblies or long time scale dynamics are still computationally expensive to study in atomistic detail. For these applications, employing coarse-grained (CG) modeling approaches has become a key strategy. In this Review, we provide an overview of what we call pragmatic CG protein models, which are strategies combining, at least in part, a physics-based implementation and a top-down experimental approach to their parametrization. In particular, we focus on CG models in which most protein residues are represented by at least two beads, allowing these models to retain some degree of chemical specificity. A description of the main modern pragmatic protein CG models is provided, including a review of the most recent applications and an outlook on future perspectives in the field.
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Affiliation(s)
- Luís Borges-Araújo
- Molecular Microbiology and Structural Biochemistry (MMSB, UMR 5086), CNRS, University of Lyon, 7 Passage du Vercors, 69007 Lyon, France
| | - Ilias Patmanidis
- Department of Chemistry, Aarhus University, Langelandsgade 140, 8000 Aarhus C, Denmark
- Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials, University of Groningen, Nijenborgh 7, 9747 AG Groningen, The Netherlands
| | - Akhil P Singh
- Department of Biology, University of Fribourg, Chemin du Musée 10, Fribourg CH-1700, Switzerland
| | - Lucianna H S Santos
- Biomolecular Simulations Group, Institut Pasteur de Montevideo, Montevideo 11400, Uruguay
| | - Adam K Sieradzan
- Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308 Gdansk, Poland
| | - Stefano Vanni
- Department of Biology, University of Fribourg, Chemin du Musée 10, Fribourg CH-1700, Switzerland
- Institut de Pharmacologie Moléculaire et Cellulaire, Université Côte d'Azur, Inserm, CNRS, 06560 Valbonne, France
| | - Cezary Czaplewski
- Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308 Gdansk, Poland
| | - Sergio Pantano
- Biomolecular Simulations Group, Institut Pasteur de Montevideo, Montevideo 11400, Uruguay
| | - Wataru Shinoda
- Research Institute for Interdisciplinary Science, Okayama University, 3-1-1 Tsushima-naka, Kita, Okayama 700-8530, Japan
| | - Luca Monticelli
- Molecular Microbiology and Structural Biochemistry (MMSB, UMR 5086), CNRS, University of Lyon, 7 Passage du Vercors, 69007 Lyon, France
| | - Adam Liwo
- Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308 Gdansk, Poland
| | - Siewert J Marrink
- Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials, University of Groningen, Nijenborgh 7, 9747 AG Groningen, The Netherlands
| | - Paulo C T Souza
- Molecular Microbiology and Structural Biochemistry (MMSB, UMR 5086), CNRS, University of Lyon, 7 Passage du Vercors, 69007 Lyon, France
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48
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Sabei A, Prentiss M, Prévost C. Modeling the Homologous Recombination Process: Methods, Successes and Challenges. Int J Mol Sci 2023; 24:14896. [PMID: 37834348 PMCID: PMC10573387 DOI: 10.3390/ijms241914896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 09/24/2023] [Accepted: 09/25/2023] [Indexed: 10/15/2023] Open
Abstract
Homologous recombination (HR) is a fundamental process common to all species. HR aims to faithfully repair DNA double strand breaks. HR involves the formation of nucleoprotein filaments on DNA single strands (ssDNA) resected from the break. The nucleoprotein filaments search for homologous regions in the genome and promote strand exchange with the ssDNA homologous region in an unbroken copy of the genome. HR has been the object of intensive studies for decades. Because multi-scale dynamics is a fundamental aspect of this process, studying HR is highly challenging, both experimentally and using computational approaches. Nevertheless, knowledge has built up over the years and has recently progressed at an accelerated pace, borne by increasingly focused investigations using new techniques such as single molecule approaches. Linking this knowledge to the atomic structure of the nucleoprotein filament systems and the succession of unstable, transient intermediate steps that takes place during the HR process remains a challenge; modeling retains a very strong role in bridging the gap between structures that are stable enough to be observed and in exploring transition paths between these structures. However, working on ever-changing long filament systems submitted to kinetic processes is full of pitfalls. This review presents the modeling tools that are used in such studies, their possibilities and limitations, and reviews the advances in the knowledge of the HR process that have been obtained through modeling. Notably, we will emphasize how cooperative behavior in the HR nucleoprotein filament enables modeling to produce reliable information.
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Affiliation(s)
- Afra Sabei
- CNRS, UPR 9080, Laboratoire de Biochimie Théorique, Université de Paris, 13 Rue Pierre et Marie Curie, F-75005 Paris, France;
- Institut de Biologie Physico-Chimique-Fondation Edmond de Rotschild, PSL Research University, F-75005 Paris, France
| | - Mara Prentiss
- Department of Physics, Harvard University, Cambridge, MA02138, USA;
| | - Chantal Prévost
- CNRS, UPR 9080, Laboratoire de Biochimie Théorique, Université de Paris, 13 Rue Pierre et Marie Curie, F-75005 Paris, France;
- Institut de Biologie Physico-Chimique-Fondation Edmond de Rotschild, PSL Research University, F-75005 Paris, France
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49
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Mioduszewski Ł. Choosing the right density for a concentrated protein system like gluten in a coarse-grained model. EUROPEAN BIOPHYSICS JOURNAL : EBJ 2023; 52:583-591. [PMID: 37378869 PMCID: PMC10618313 DOI: 10.1007/s00249-023-01667-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 05/05/2023] [Accepted: 05/24/2023] [Indexed: 06/29/2023]
Abstract
Large coarse-grained simulations are often conducted with an implicit solvent, which makes it hard to assess the water content of the sample and the effective concentration of the system. Here the number and the size of cavities and entanglements in the system, together with density profiles, are used to asses the homogeneity and interconnectedness of gluten. This is a continuation of an earlier article, "Viscoelastic properties of wheat gluten in a molecular dynamics study" (Mioduszewski and Cieplak 2021b). It turns out there is a wide range of densities (between 1 residue per cubic nanometer and 3 residues/nm[Formula: see text]) where the system is interconnected, but not homogeneous: there are still large empty spaces, surrounded by an entangled protein network. Those findings should be of importance to any coarse-grained simulation of large protein systems.
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Affiliation(s)
- Łukasz Mioduszewski
- Faculty of Mathematics and Natural Sciences, Cardinal Stefan Wyszyński University, Wóycickiego 1/3, 01-938, Warsaw, Poland.
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50
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Arts M, Garcia Satorras V, Huang CW, Zügner D, Federici M, Clementi C, Noé F, Pinsler R, van den Berg R. Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamics. J Chem Theory Comput 2023; 19:6151-6159. [PMID: 37688551 DOI: 10.1021/acs.jctc.3c00702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/11/2023]
Abstract
Coarse-grained (CG) molecular dynamics enables the study of biological processes at temporal and spatial scales that would be intractable at an atomistic resolution. However, accurately learning a CG force field remains a challenge. In this work, we leverage connections between score-based generative models, force fields, and molecular dynamics to learn a CG force field without requiring any force inputs during training. Specifically, we train a diffusion generative model on protein structures from molecular dynamics simulations, and we show that its score function approximates a force field that can directly be used to simulate CG molecular dynamics. While having a vastly simplified training setup compared to previous work, we demonstrate that our approach leads to improved performance across several protein simulations for systems up to 56 amino acids, reproducing the CG equilibrium distribution and preserving the dynamics of all-atom simulations such as protein folding events.
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Affiliation(s)
- Marloes Arts
- Department of Computer Science, University of Copenhagen, Universitetsparken 1, Copenhagen 2100, Denmark
| | - Victor Garcia Satorras
- AI4Science, Microsoft Research, Evert van de Beekstraat 354, Amsterdam 1118 CZ, The Netherlands
| | - Chin-Wei Huang
- AI4Science, Microsoft Research, Evert van de Beekstraat 354, Amsterdam 1118 CZ, The Netherlands
| | - Daniel Zügner
- AI4Science, Microsoft Research, Karl-Liebknecht-Straße 32, Berlin 10178, Germany
| | - Marco Federici
- Informatics Institute, University of Amsterdam, Science Park 904, Amsterdam 1098 XH, The Netherlands
| | - Cecilia Clementi
- AI4Science, Microsoft Research, Karl-Liebknecht-Straße 32, Berlin 10178, Germany
- Department of Physics, Freie Universität Berlin, Arnimalle 12, Berlin 14195, Germany
| | - Frank Noé
- AI4Science, Microsoft Research, Karl-Liebknecht-Straße 32, Berlin 10178, Germany
| | - Robert Pinsler
- AI4Science, Microsoft Research, 21 Station Road, Cambridge CB1 2FB, U.K
| | - Rianne van den Berg
- AI4Science, Microsoft Research, Evert van de Beekstraat 354, Amsterdam 1118 CZ, The Netherlands
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