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Laurent B, Lanrezac A, Santuz H, Ferey N, Delalande O, Baaden M. BioSpring: An elastic network framework for interactive exploration of macromolecular mechanics. Protein Sci 2025; 34:e70130. [PMID: 40249023 PMCID: PMC12006919 DOI: 10.1002/pro.70130] [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: 10/31/2024] [Revised: 03/07/2025] [Accepted: 04/06/2025] [Indexed: 04/19/2025]
Abstract
BioSpring is an innovative tool for interactive molecular modeling and simulation, designed to explore the dynamics of biological structures in real time. Using an augmented elastic network model, the BioSpring framework enables researchers to intuitively examine complex biomolecules, and it combines real-time feedback with the user's experience. This capability makes it ideal for initial analysis of molecular systems, protein-protein and protein-DNA docking, protein mechanics, and protein-membrane interactions. The multi-resolution modeling approach combines accuracy and efficiency, supporting user-driven analysis of molecular interactions, conformational flexibility, and structural mechanics. This framework improves upon traditional methods in terms of robustness, accessibility, and ease of use, while requiring only modest computational resources and enabling a fast turnaround time to obtain initial results. It provides insights into molecular function and dynamics that advance the field of structural biology. Source code, executables, and examples for the BioSpring simulation engine are available at https://biospring.mol3d.tech.
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Affiliation(s)
- Benoist Laurent
- Laboratoire de Biochimie ThéoriqueUniversité Paris Cité, CNRSParisFrance
| | - André Lanrezac
- Laboratoire de Biochimie ThéoriqueUniversité Paris Cité, CNRSParisFrance
| | - Hubert Santuz
- Laboratoire de Biochimie ThéoriqueUniversité Paris Cité, CNRSParisFrance
| | - Nicolas Ferey
- Laboratoire Interdisciplinaire des Sciences du NumériqueCNRS, Université Paris‐SaclayOrsayFrance
| | - Olivier Delalande
- Institut de Génétique et Développement de Rennes (IGDR)CNRS, Université RennesRennesFrance
| | - Marc Baaden
- Laboratoire de Biochimie ThéoriqueUniversité Paris Cité, CNRSParisFrance
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2
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Iram F, Aiman A, Vijh D, Shahid M, Choudhir G, Khan T, Alam D, Hassan MI, Islam A. Unraveling the catalase dynamics: Biophysical and computational insights into co-solutes driven stabilization under extreme pH conditions. Int J Biol Macromol 2025; 301:140467. [PMID: 39884626 DOI: 10.1016/j.ijbiomac.2025.140467] [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: 11/12/2024] [Revised: 01/24/2025] [Accepted: 01/27/2025] [Indexed: 02/01/2025]
Abstract
Catalase plays a vital role in eliminating toxic peroxides from the human body and the environment. The versatile applications of this enzyme extend across biotechnological industries and innovative bioremediation approaches. Nonetheless, ensuring enzyme stability is a challenging task. This study investigated the efficacy of co-solutes (glucose and dextran 70) as stabilizing agents for catalase under denaturing pH conditions by employing a combination of spectroscopic techniques (UV-visible, circular dichroism, and Trp fluorescence), calorimetric measurements (DSC and ITC), enzymatic assay, and in silico studies. The results of spectroscopic and thermal stability studies indicated that the co-solutes tend to stabilize catalase, even under extreme pH conditions. Molecular docking and ITC findings showed that glucose has a higher binding tendency to catalase than dextran 70. MD simulations further underscore reduced structural deviations (RMSF and RMSD), compact structure (Rg and SASA), and formation of H-bonds between catalase and co-solutes, complementing the in vitro observations. This study contributes to the understanding of enzyme stability under suboptimal pH conditions and paves the way for the development of more robust enzyme formulations suitable for a range of applications.
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Affiliation(s)
- Faiza Iram
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, Jamia Nagar, New Delhi 110025, India
| | - Ayesha Aiman
- Department of Biosciences, Jamia Millia Islamia, Jamia Nagar, New Delhi 110025, India
| | - Deepanshi Vijh
- University School of Biotechnology, Guru Gobind Singh Indraprastha University, Dwarka, Delhi 110078, India
| | - Mohammad Shahid
- Department of Basic Medical Sciences, College of Medicine, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
| | - Gourav Choudhir
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, Jamia Nagar, New Delhi 110025, India
| | - Tanzeel Khan
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, Jamia Nagar, New Delhi 110025, India
| | - Danish Alam
- Department of Biosciences, Jamia Millia Islamia, Jamia Nagar, New Delhi 110025, India
| | - Md Imtaiyaz Hassan
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, Jamia Nagar, New Delhi 110025, India
| | - Asimul Islam
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, Jamia Nagar, New Delhi 110025, India.
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3
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Tran MH, Martina CE, Moretti R, Nagel M, Schey KL, Meiler J. RosettaHDX: Predicting antibody-antigen interaction from hydrogen-deuterium exchange mass spectrometry data. J Struct Biol 2025; 217:108166. [PMID: 39765317 PMCID: PMC12010952 DOI: 10.1016/j.jsb.2025.108166] [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: 10/01/2024] [Revised: 12/06/2024] [Accepted: 01/04/2025] [Indexed: 01/20/2025]
Abstract
High-throughput characterization of antibody-antigen complexes at the atomic level is critical for understanding antibody function and enabling therapeutic development. Hydrogen-deuterium exchange mass spectrometry (HDX-MS) enables rapid epitope mapping, but its data are too sparse for independent structure determination. In this study, we introduce RosettaHDX, a hybrid method that combines computational docking with differential HDX-MS data to enhance the accuracy of antibody-antigen complex models beyond what either method can achieve individually. By incorporating HDX data as both distance restraints and a scoring term in the RosettaDock algorithm, RosettaHDX successfully generated near-native models (interface root-mean square deviation ≤ 4 Å) for all 9 benchmark complexes examined, averaging 3.6 times more near-native models than Rosetta alone. Near-native models among the top 10 scoring were identified in 3/9 cases, compared to 1/9 with Rosetta alone. Additionally, we developed a predictive metric based on docking results with HDX restraints to identify allosteric peptides in HDX datasets.
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Affiliation(s)
- Minh H Tran
- Chemical and Physical Biology Program, Vanderbilt University, Nashville, TN, USA; Center of Structural Biology, Vanderbilt University, Nashville, TN, USA.
| | - Cristina E Martina
- Center of Structural Biology, Vanderbilt University, Nashville, TN, USA; Department of Chemistry, Vanderbilt University, Nashville, TN, USA
| | - Rocco Moretti
- Center of Structural Biology, Vanderbilt University, Nashville, TN, USA; Department of Chemistry, Vanderbilt University, Nashville, TN, USA
| | - Marcus Nagel
- Mass Spectrometry Research Center, Department of Biochemistry, Vanderbilt University, Nashville, TN, USA
| | - Kevin L Schey
- Mass Spectrometry Research Center, Department of Biochemistry, Vanderbilt University, Nashville, TN, USA.
| | - Jens Meiler
- Center of Structural Biology, Vanderbilt University, Nashville, TN, USA; Department of Chemistry, Vanderbilt University, Nashville, TN, USA; Institute for Drug Discovery, Institute for Computer Science, Wilhelm Ostwald Institute for Physical and Theoretical Chemistry, University Leipzig, Leipzig, Germany; Center for Scalable Data Analytics and Artificial Intelligence ScaDS.AI and School of Embedded Composite Artificial Intelligence SECAI, Dresden/Leipzig, Germany; Department of Pharmacology, Institute of Chemical Biology, Center for Applied Artificial Intelligence in Protein Dynamics, Vanderbilt University, Nashville, TN, USA.
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4
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Rosignoli S, Pacelli M, Manganiello F, Paiardini A. An outlook on structural biology after AlphaFold: tools, limits and perspectives. FEBS Open Bio 2025; 15:202-222. [PMID: 39313455 PMCID: PMC11788754 DOI: 10.1002/2211-5463.13902] [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: 03/13/2024] [Revised: 08/19/2024] [Accepted: 09/13/2024] [Indexed: 09/25/2024] Open
Abstract
AlphaFold and similar groundbreaking, AI-based tools, have revolutionized the field of structural bioinformatics, with their remarkable accuracy in ab-initio protein structure prediction. This success has catalyzed the development of new software and pipelines aimed at incorporating AlphaFold's predictions, often focusing on addressing the algorithm's remaining challenges. Here, we present the current landscape of structural bioinformatics shaped by AlphaFold, and discuss how the field is dynamically responding to this revolution, with new software, methods, and pipelines. While the excitement around AI-based tools led to their widespread application, it is essential to acknowledge that their practical success hinges on their integration into established protocols within structural bioinformatics, often neglected in the context of AI-driven advancements. Indeed, user-driven intervention is still as pivotal in the structure prediction process as in complementing state-of-the-art algorithms with functional and biological knowledge.
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Affiliation(s)
- Serena Rosignoli
- Department of Biochemical sciences “A. Rossi Fanelli”Sapienza Università di RomaItaly
| | - Maddalena Pacelli
- Department of Biochemical sciences “A. Rossi Fanelli”Sapienza Università di RomaItaly
| | - Francesca Manganiello
- Department of Biochemical sciences “A. Rossi Fanelli”Sapienza Università di RomaItaly
| | - Alessandro Paiardini
- Department of Biochemical sciences “A. Rossi Fanelli”Sapienza Università di RomaItaly
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Cui Z, Liu X, E T, Lin H, Wang D, Liu Y, Ruan X, Wang P, Liu L, Xue Y. Effect of SNORD113-3/ADAR2 on glycolipid metabolism in glioblastoma via A-to-I editing of PHKA2. Cell Mol Biol Lett 2025; 30:5. [PMID: 39794701 PMCID: PMC11724473 DOI: 10.1186/s11658-024-00680-9] [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: 05/15/2024] [Accepted: 12/17/2024] [Indexed: 01/13/2025] Open
Abstract
BACKGROUND Glioblastoma multiforme (GBM) is a highly aggressive brain tumor, characterized by its poor prognosis. Glycolipid metabolism is strongly associated with GBM development and malignant behavior. However, the precise functions of snoRNAs and ADARs in glycolipid metabolism within GBM cells remain elusive. The objective of the present study is to delve into the underlying mechanisms through which snoRNAs and ADARs exert regulatory effects on glycolipid metabolism in GBM cells. METHODS RNA immunoprecipitation and RNA pull-down experiments were conducted to verify the homodimerization of ADAR2 by SNORD113-3, and Sanger sequencing and Western blot experiments were used to detect the A-to-I RNA editing of PHKA2 mRNA by ADAR2. Furthermore, the phosphorylation of EBF1 was measured by in vitro kinase assay. Finally, in vivo studies using nude mice confirmed that SNORD113-3 and ADAR2 overexpression, along with PHKA2 knockdown, could suppress the formation of subcutaneous xenograft tumors and improve the outcome of tumor-bearing nude mice. RESULTS We found that PHKA2 in GBM significantly promoted glycolipid metabolism, while SNORD113-3, ADAR2, and EBF1 significantly inhibited glycolipid metabolism. SNORD113-3 promotes ADAR2 protein expression by promoting ADAR2 homodimer formation. ADAR2 mediates the A-to-I RNA editing of PHKA2 mRNA. Mass spectrometry analysis and in vitro kinase testing revealed that PHKA2 phosphorylates EBF1 on Y256, reducing the stability and expression of EBF1. Furthermore, direct binding of EBF1 to PKM2 and ACLY promoters was observed, suggesting the inhibition of their expression by EBF1. These findings suggest the existence of a SNORD113-3/ADAR2/PHKA2/EBF1 pathway that collectively regulates the metabolism of glycolipid and the growth of GBM cells. Finally, in vivo studies using nude mice confirmed that knockdown of PHKA2, along with overexpression of SNORD113-3 and ADAR2, could obviously suppress GBM subcutaneous xenograft tumor formation and improve the outcome of those tumor-bearing nude mice. CONCLUSIONS Herein, we clarified the underlying mechanism involving the SNORD113-3/ADAR2/PHKA2/EBF1 pathway in the regulation of GBM cell growth and glycolipid metabolism. Our results provide a framework for the development of innovative therapeutic interventions to improve the prognosis of patients with GBM.
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Affiliation(s)
- Zheng Cui
- Department of Neurology, The First Affiliated Hospital, China Medical University, Shenyang, 110001, Liaoning, China
- Key Laboratory of Neurological Disease Big Data of Liaoning Province, Shenyang, China
- Shenyang Clinical Medical Research Center for Difficult and Serious Diseases of the Nervous System, Shenyang, China
| | - Xiaobai Liu
- Department of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang, 110004, China
- Key Laboratory of Neuro-Oncology in Liaoning Province, Shenyang, 110004, China
- Liaoning Medical Surgery and Rehabilitation Robot Technology Engineering Research Center, Shenyang, 110004, China
| | - Tiange E
- Department of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang, 110004, China
- Key Laboratory of Neuro-Oncology in Liaoning Province, Shenyang, 110004, China
- Liaoning Medical Surgery and Rehabilitation Robot Technology Engineering Research Center, Shenyang, 110004, China
| | - Hongda Lin
- Department of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang, 110004, China
- Key Laboratory of Neuro-Oncology in Liaoning Province, Shenyang, 110004, China
- Liaoning Medical Surgery and Rehabilitation Robot Technology Engineering Research Center, Shenyang, 110004, China
| | - Di Wang
- Department of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang, 110004, China
- Key Laboratory of Neuro-Oncology in Liaoning Province, Shenyang, 110004, China
- Liaoning Medical Surgery and Rehabilitation Robot Technology Engineering Research Center, Shenyang, 110004, China
| | - Yunhui Liu
- Department of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang, 110004, China
- Key Laboratory of Neuro-Oncology in Liaoning Province, Shenyang, 110004, China
- Liaoning Medical Surgery and Rehabilitation Robot Technology Engineering Research Center, Shenyang, 110004, China
| | - Xuelei Ruan
- Key Laboratory of Neuro-Oncology in Liaoning Province, Shenyang, 110004, China
- Department of Neurobiology, School of Life Sciences, China Medical University, Shenyang, 110122, China
| | - Ping Wang
- Key Laboratory of Neuro-Oncology in Liaoning Province, Shenyang, 110004, China
- Department of Neurobiology, School of Life Sciences, China Medical University, Shenyang, 110122, China
| | - Libo Liu
- Key Laboratory of Neuro-Oncology in Liaoning Province, Shenyang, 110004, China
- Department of Neurobiology, School of Life Sciences, China Medical University, Shenyang, 110122, China
| | - Yixue Xue
- Key Laboratory of Neuro-Oncology in Liaoning Province, Shenyang, 110004, China.
- Department of Neurobiology, School of Life Sciences, China Medical University, Shenyang, 110122, China.
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6
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le Maire A, Bourguet W. What Structural Biology Tells Us About the Mode of Action and Detection of Toxicants. Annu Rev Pharmacol Toxicol 2025; 65:529-546. [PMID: 39107041 DOI: 10.1146/annurev-pharmtox-061724-080642] [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] [Indexed: 08/09/2024]
Abstract
The study of the adverse effects of chemical substances on living organisms is an old and intense field of research. However, toxicological and environmental health sciences have long been dominated by descriptive approaches that enable associations or correlations but relatively few robust causal links and molecular mechanisms. Recent achievements have shown that structural biology approaches can bring this added value to the field. By providing atomic-level information, structural biology is a powerful tool to decipher the mechanisms by which toxicants bind to and alter the normal function of essential cell components, causing adverse effects. Here, using endocrine-disrupting chemicals as illustrative examples, we describe recent advances in the structure-based understanding of their modes of action and how this knowledge can be exploited to develop computational tools aimed at predicting properties of large collections of compounds.
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Affiliation(s)
- Albane le Maire
- Centre de Biologie Structurale (CBS), Univ Montpellier, CNRS, Inserm, Montpellier, France; ,
| | - William Bourguet
- Centre de Biologie Structurale (CBS), Univ Montpellier, CNRS, Inserm, Montpellier, France; ,
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7
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Xue Z, Sun C, Zheng W, Lv J, Liu X. TargetSA: adaptive simulated annealing for target-specific drug design. Bioinformatics 2024; 41:btae730. [PMID: 39656791 PMCID: PMC12013812 DOI: 10.1093/bioinformatics/btae730] [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: 09/05/2024] [Revised: 10/28/2024] [Accepted: 12/02/2024] [Indexed: 12/17/2024] Open
Abstract
MOTIVATION The burgeoning field of target-specific drug design has attracted considerable attention, focusing on identifying compounds with high binding affinity toward specific target pockets. Nevertheless, existing target-specific deep generative models encounter notable challenges. Some models heavily rely on elaborate datasets and complicated training methodologies, while others neglect the multi-constraint optimization problem inherent in drug design, resulting in generated molecules with irrational structures or chemical properties. RESULTS To address these issues, we propose a novel framework (TargetSA) that leverages adaptive simulated annealing (SA) for target-specific molecular generation and multi-constraint optimization. The SA process explores the discrete structural space of molecules, progressively converging toward the optimal solution that fulfills the predefined objective. To propose novel compounds, we first predict promising editing positions based on historical experience, and then iteratively edit molecular graphs through four operations (insertion, replacement, deletion, and cyclization). Together, these operations collectively constitute a complete operation set, facilitating a thorough exploration of the drug-like space. Furthermore, we introduce a reversible sampling strategy to re-accept currently suboptimal solutions, greatly enhancing the generation quality. Empirical evaluations demonstrate that TargetSA achieves state-of-the-art performance in generating high-affinity molecules (average vina dock -9.09) while maintaining desirable chemical properties. AVAILABILITY AND IMPLEMENTATION https://github.com/XueZhe-Zachary/TargetSA.
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Affiliation(s)
- Zhe Xue
- College of Computer Science, Sichuan University, Chengdu, Sichuan 610065, China
| | - Chenwei Sun
- College of Computer Science, Sichuan University, Chengdu, Sichuan 610065, China
| | - Wenhao Zheng
- College of Computer Science, Sichuan University, Chengdu, Sichuan 610065, China
| | - Jiancheng Lv
- College of Computer Science, Sichuan University, Chengdu, Sichuan 610065, China
| | - Xianggen Liu
- College of Computer Science, Sichuan University, Chengdu, Sichuan 610065, China
- Laboratory of Anesthesia and Critical Care Medicine, Department of Anesthesiology, Translational Neuroscience Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
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8
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Zhao Y, Singh K, Chowdary Karuturi R, Hefny AA, Shakeri A, Beazely MA, Rao PPN. Benzofuran and Benzo[b]thiophene-2-Carboxamide Derivatives as Modulators of Amyloid Beta (Aβ42) Aggregation. ChemMedChem 2024; 19:e202400198. [PMID: 39083696 PMCID: PMC11581421 DOI: 10.1002/cmdc.202400198] [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: 03/15/2024] [Revised: 07/25/2024] [Accepted: 07/31/2024] [Indexed: 08/02/2024]
Abstract
A group of N-phenylbenzofuran-2-carboxamide and N-phenylbenzo[b]thiophene-2-carboxamide derivatives were designed and synthesized as a novel class of Aβ42 aggregation modulators. In the thioflavin-T based fluorescence aggregation kinetics study, compounds 4 a, 4 b, 5 a and 5 b possessing a methoxyphenol pharmacophore were able to demonstrate concentration dependent inhibition of Aβ42 aggregation with maximum inhibition of 54 % observed for compound 4 b. In contrast, incorporation of a 4-methoxyphenyl ring in compounds 4 d and 5 d led to a significant increase in Aβ42 fibrillogenesis demonstrating their ability to accelerate Aβ42 aggregation. Compound 4 d exhibited 2.7-fold increase in Aβ42 fibrillogenesis when tested at the maximum concentration of 25 μM. These results were further confirmed by electron microscopy studies which demonstrates the ability of compounds 4 a, 4 b, 4 d, 5 a, 5 b and 5 d to modulate Aβ42 fibrillogenesis. Compounds 5 a and 5 b provided significant neuroprotection to mouse hippocampal neuronal HT22 cells against Aβ42-induced cytotoxicity. Molecular docking studies suggest that the orientation of the bicyclic aromatic rings (either benzofuran or benzo[b]thiophene) plays a major role in moderating their ability to either inhibit or accelerate Aβ42 aggregation. Our findings support the application of these novel derivatives as pharmacological tools to study the mechanisms of Aβ42 aggregation.
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Affiliation(s)
- Yusheng Zhao
- School of PharmacyHealth Sciences CampusUniversity of Waterloo200 University Avenue West, WaterlooN2L 3G1OntarioCanada
| | - Kartar Singh
- School of PharmacyHealth Sciences CampusUniversity of Waterloo200 University Avenue West, WaterlooN2L 3G1OntarioCanada
| | - Rahul Chowdary Karuturi
- School of PharmacyHealth Sciences CampusUniversity of Waterloo200 University Avenue West, WaterlooN2L 3G1OntarioCanada
| | - Ahmed A. Hefny
- School of PharmacyHealth Sciences CampusUniversity of Waterloo200 University Avenue West, WaterlooN2L 3G1OntarioCanada
| | - Arash Shakeri
- School of PharmacyHealth Sciences CampusUniversity of Waterloo200 University Avenue West, WaterlooN2L 3G1OntarioCanada
| | - Mike A. Beazely
- School of PharmacyHealth Sciences CampusUniversity of Waterloo200 University Avenue West, WaterlooN2L 3G1OntarioCanada
| | - Praveen P. N. Rao
- School of PharmacyHealth Sciences CampusUniversity of Waterloo200 University Avenue West, WaterlooN2L 3G1OntarioCanada
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9
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Pellequer JL. Perspectives Toward an Integrative Structural Biology Pipeline With Atomic Force Microscopy Topographic Images. J Mol Recognit 2024; 37:e3102. [PMID: 39329418 DOI: 10.1002/jmr.3102] [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: 07/15/2024] [Revised: 08/21/2024] [Accepted: 09/03/2024] [Indexed: 09/28/2024]
Abstract
After the recent double revolutions in structural biology, which include the use of direct detectors for cryo-electron microscopy resulting in a significant improvement in the expected resolution of large macromolecule structures, and the advent of AlphaFold which allows for near-accurate prediction of any protein structures, the field of structural biology is now pursuing more ambitious targets, including several MDa assemblies. But complex target systems cannot be tackled using a single biophysical technique. The field of integrative structural biology has emerged as a global solution. The aim is to integrate data from multiple complementary techniques to produce a final three-dimensional model that cannot be obtained from any single technique. The absence of atomic force microscopy data from integrative structural biology platforms is not necessarily due to its nm resolution, as opposed to Å resolution for x-ray crystallography, nuclear magnetic resonance, or electron microscopy. Rather a significant issue was that the AFM topographic data lacked interpretability. Fortunately, with the introduction of the AFM-Assembly pipeline and other similar tools, it is now possible to integrate AFM topographic data into integrative modeling platforms. The advantages of single molecule techniques, such as AFM, include the ability to confirm experimentally any assembled molecular models or to produce alternative conformations that mimic the inherent flexibility of large proteins or complexes. The review begins with a brief overview of the historical developments of AFM data in structural biology, followed by an examination of the strengths and limitations of AFM imaging, which have hindered its integration into modern modeling platforms. This review discusses the correction and improvement of AFM topographic images, as well as the principles behind the AFM-Assembly pipeline. It also presents and discusses a series of challenges that need to be addressed in order to improve the incorporation of AFM data into integrative modeling platform.
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Affiliation(s)
- Jean-Luc Pellequer
- Univ. Grenoble Alpes, CEA, CNRS, Institut de Biologie Structurale (IBS), Grenoble, France
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10
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Wang CR, McFarlane LO, Pukala TL. Exploring snake venoms beyond the primary sequence: From proteoforms to protein-protein interactions. Toxicon 2024; 247:107841. [PMID: 38950738 DOI: 10.1016/j.toxicon.2024.107841] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Revised: 06/26/2024] [Accepted: 06/28/2024] [Indexed: 07/03/2024]
Abstract
Snakebite envenomation has been a long-standing global issue that is difficult to treat, largely owing to the flawed nature of current immunoglobulin-based antivenom therapy and the complexity of snake venoms as sophisticated mixtures of bioactive proteins and peptides. Comprehensive characterisation of venom compositions is essential to better understanding snake venom toxicity and inform effective and rationally designed antivenoms. Additionally, a greater understanding of snake venom composition will likely unearth novel biologically active proteins and peptides that have promising therapeutic or biotechnological applications. While a bottom-up proteomic workflow has been the main approach for cataloguing snake venom compositions at the toxin family level, it is unable to capture snake venom heterogeneity in the form of protein isoforms and higher-order protein interactions that are important in driving venom toxicity but remain underexplored. This review aims to highlight the importance of understanding snake venom heterogeneity beyond the primary sequence, in the form of post-translational modifications that give rise to different proteoforms and the myriad of higher-order protein complexes in snake venoms. We focus on current top-down proteomic workflows to identify snake venom proteoforms and further discuss alternative or novel separation, instrumentation, and data processing strategies that may improve proteoform identification. The current higher-order structural characterisation techniques implemented for snake venom proteins are also discussed; we emphasise the need for complementary and higher resolution structural bioanalytical techniques such as mass spectrometry-based approaches, X-ray crystallography and cryogenic electron microscopy, to elucidate poorly characterised tertiary and quaternary protein structures. We envisage that the expansion of the snake venom characterisation "toolbox" with top-down proteomics and high-resolution protein structure determination techniques will be pivotal in advancing structural understanding of snake venoms towards the development of improved therapeutic and biotechnology applications.
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Affiliation(s)
- C Ruth Wang
- Discipline of Chemistry, School of Physics, Chemistry and Earth Sciences, The University of Adelaide, Adelaide, 5005, Australia
| | - Lewis O McFarlane
- Discipline of Chemistry, School of Physics, Chemistry and Earth Sciences, The University of Adelaide, Adelaide, 5005, Australia
| | - Tara L Pukala
- Discipline of Chemistry, School of Physics, Chemistry and Earth Sciences, The University of Adelaide, Adelaide, 5005, Australia.
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11
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Turkoglu B, Mansuroglu B. Investigating the Effects of Chelidonic Acid on Oxidative Stress-Induced Premature Cellular Senescence in Human Skin Fibroblast Cells. Life (Basel) 2024; 14:1070. [PMID: 39337855 PMCID: PMC11433492 DOI: 10.3390/life14091070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2024] [Revised: 08/18/2024] [Accepted: 08/20/2024] [Indexed: 09/30/2024] Open
Abstract
This study investigated the effects of chelidonic acid (CA) on hydrogen peroxide (H2O2) induced cellular senescence in human skin fibroblast cells (BJ). Cellular senescence is a critical mechanism that is linked to age-related diseases and chronic conditions. CA, a γ-pyrone compound known for its broad pharmacological activity, was assessed for its potential to mitigate oxidative stress and alter senescence markers. A stress-induced premature senescence (SIPS) model was designed in BJ fibroblast cells using the oxidative stress agent H2O2. After this treatment, cells were treated with CA, and the potential effect of CA on senescence was evaluated using senescence-related β-galactosidase, 4',6-diamino-2-phenylindole (DAPI), acridine-orange staining (AO), comet assay, molecular docking assays, gene expression, and protein analysis. These results demonstrate that CA effectively reduces senescence markers, including senescence-associated β-galactosidase activity, DNA damage, lysosomal activity, and oxidative stress indicators such as malondialdehyde. Molecular docking revealed CA's potential interactions with critical proteins involved in senescence signalling pathways, suggesting mechanisms by which CA may exert its effects. Gene expression and protein analyses corroborated the observed anti-senescent effects, with CA modulating p16, p21, and pRB1 expressions and reducing oxidative stress markers. In conclusion, CA appeared to have senolytic and senomorphic potential in vitro, which could mitigate and reverse SIPS markers in BJ fibroblasts.
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Affiliation(s)
| | - Banu Mansuroglu
- Department of Molecular Biology and Genetics, Faculty of Arts and Science, Yildiz Technical University, Istanbul 34220, Turkey;
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12
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Chihomvu P, Ganesan A, Gibbons S, Woollard K, Hayes MA. Phytochemicals in Drug Discovery-A Confluence of Tradition and Innovation. Int J Mol Sci 2024; 25:8792. [PMID: 39201478 PMCID: PMC11354359 DOI: 10.3390/ijms25168792] [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: 06/12/2024] [Revised: 07/22/2024] [Accepted: 07/25/2024] [Indexed: 09/02/2024] Open
Abstract
Phytochemicals have a long and successful history in drug discovery. With recent advancements in analytical techniques and methodologies, discovering bioactive leads from natural compounds has become easier. Computational techniques like molecular docking, QSAR modelling and machine learning, and network pharmacology are among the most promising new tools that allow researchers to make predictions concerning natural products' potential targets, thereby guiding experimental validation efforts. Additionally, approaches like LC-MS or LC-NMR speed up compound identification by streamlining analytical processes. Integrating structural and computational biology aids in lead identification, thus providing invaluable information to understand how phytochemicals interact with potential targets in the body. An emerging computational approach is machine learning involving QSAR modelling and deep neural networks that interrelate phytochemical properties with diverse physiological activities such as antimicrobial or anticancer effects.
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Affiliation(s)
- Patience Chihomvu
- Compound Synthesis and Management, Discovery Sciences, Biopharmaceuticals R&D, AstraZeneca, 431 83 Mölndal, Sweden
| | - A. Ganesan
- School of Chemistry, Pharmacy & Pharmacology, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK;
| | - Simon Gibbons
- Natural and Medical Sciences Research Center, University of Nizwa, Birkat Al Mawz 616, Oman;
| | - Kevin Woollard
- Bioscience Renal, Research and Early Development, Cardiovascular, Renal and Metabolic, BioPharmaceuticals R&D, AstraZeneca, Cambridge CB21 6GH, UK;
| | - Martin A. Hayes
- Compound Synthesis and Management, Discovery Sciences, Biopharmaceuticals R&D, AstraZeneca, 431 83 Mölndal, Sweden
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13
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Durbin KR, Robey MT, Voong LN, Fellers RT, Lutomski CA, El-Baba TJ, Robinson CV, Kelleher NL. ProSight Native: Defining Protein Complex Composition from Native Top-Down Mass Spectrometry Data. J Proteome Res 2023; 22:2660-2668. [PMID: 37436406 PMCID: PMC10407923 DOI: 10.1021/acs.jproteome.3c00171] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Indexed: 07/13/2023]
Abstract
Native mass spectrometry has recently moved alongside traditional structural biology techniques in its ability to provide clear insights into the composition of protein complexes. However, to date, limited software tools are available for the comprehensive analysis of native mass spectrometry data on protein complexes, particularly for experiments aimed at elucidating the composition of an intact protein complex. Here, we introduce ProSight Native as a start-to-finish informatics platform for analyzing native protein and protein complex data. Combining mass determination via spectral deconvolution with a top-down database search and stoichiometry calculations, ProSight Native can determine the complete composition of protein complexes. To demonstrate its features, we used ProSight Native to successfully determine the composition of the homotetrameric membrane complex Aquaporin Z. We also revisited previously published spectra and were able to decipher the composition of a heterodimer complex bound with two noncovalently associated ligands. In addition to determining complex composition, we developed new tools in the software for validating native mass spectrometry fragment ions and mapping top-down fragmentation data onto three-dimensional protein structures. Taken together, ProSight Native will reduce the informatics burden on the growing field of native mass spectrometry, enabling the technology to further its reach.
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Affiliation(s)
| | | | - Lilien N. Voong
- Proteinaceous,
Inc., Evanston, Illinois 60201, United States
| | - Ryan T. Fellers
- Proteinaceous,
Inc., Evanston, Illinois 60201, United States
- Northwestern
University, Evanston, Illinois 60208, United States
| | - Corinne A. Lutomski
- Department
of Chemistry, University of Oxford, 12 Mansfield Rd. Oxford OX1 3TA, U.K.
- Kavli
Institute for NanoScience Discovery, Dorothy
Crowfoot Hodgkin Building University of Oxford, Oxford OX1 3QU, U.K.
| | - Tarick J. El-Baba
- Department
of Chemistry, University of Oxford, 12 Mansfield Rd. Oxford OX1 3TA, U.K.
- Kavli
Institute for NanoScience Discovery, Dorothy
Crowfoot Hodgkin Building University of Oxford, Oxford OX1 3QU, U.K.
| | - Carol V. Robinson
- Department
of Chemistry, University of Oxford, 12 Mansfield Rd. Oxford OX1 3TA, U.K.
- Kavli
Institute for NanoScience Discovery, Dorothy
Crowfoot Hodgkin Building University of Oxford, Oxford OX1 3QU, U.K.
| | - Neil L. Kelleher
- Proteinaceous,
Inc., Evanston, Illinois 60201, United States
- Northwestern
University, Evanston, Illinois 60208, United States
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14
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Mondal A, Lenz S, MacCallum JL, Perez A. Hybrid computational methods combining experimental information with molecular dynamics. Curr Opin Struct Biol 2023; 81:102609. [PMID: 37224642 DOI: 10.1016/j.sbi.2023.102609] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Revised: 04/12/2023] [Accepted: 04/23/2023] [Indexed: 05/26/2023]
Abstract
A goal of structural biology is to understand how macromolecules carry out their biological roles by identifying their metastable states, mechanisms of action, pathways leading to conformational changes, and the thermodynamic and kinetic relationships between those states. Integrative modeling brings structural insights into systems where traditional structure determination approaches cannot help. We focus on the synergies and challenges of integrative modeling combining experimental data with molecular dynamics simulations.
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Affiliation(s)
- Arup Mondal
- Quantum Theory Project, Department of Chemistry, University of Florida, Leigh, UK. https://twitter.com/@amondal_chem
| | - Stefan Lenz
- Department of Chemistry, University of Calgary, 2500 University Drive, Canada
| | - Justin L MacCallum
- Department of Chemistry, University of Calgary, 2500 University Drive, Canada. https://twitter.com/@jlmaccal
| | - Alberto Perez
- Quantum Theory Project, Department of Chemistry, University of Florida, Leigh, UK.
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15
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Hvorecny KL, Kollman JM. Greater than the sum of parts: Mechanisms of metabolic regulation by enzyme filaments. Curr Opin Struct Biol 2023; 79:102530. [PMID: 36709625 PMCID: PMC10023394 DOI: 10.1016/j.sbi.2023.102530] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 11/28/2022] [Accepted: 12/19/2022] [Indexed: 01/28/2023]
Abstract
Recent work in structural biology is shedding light on how many of the enzymes of intermediary metabolism are self- and co-assembling into large, filamentous polymers or agglomerates to organize and regulate the complex and essential biochemical pathways in cells. Filament assembly provides an additional layer of regulation by modulating the intrinsic allostery of the enzyme protomers which tunes activity in response to a variety of environmental cues. Enzyme filaments dynamically assemble and disassemble in response to changes in metabolite levels and environmental cues, shifting metabolic flux on a more rapid timescale than transcriptional or translational reprogramming. Here we present recent examples of high-resolution structures of filaments from proteins in intermediary metabolism and we discuss how filament assembly modulates the activities of these and other proteins.
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Affiliation(s)
- Kelli L Hvorecny
- Department of Biochemistry, University of Washington, Seattle, WA, USA
| | - Justin M Kollman
- Department of Biochemistry, University of Washington, Seattle, WA, USA.
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16
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Santorelli L, Caterino M, Costanzo M. Dynamic Interactomics by Cross-Linking Mass Spectrometry: Mapping the Daily Cell Life in Postgenomic Era. OMICS : A JOURNAL OF INTEGRATIVE BIOLOGY 2022; 26:633-649. [PMID: 36445175 DOI: 10.1089/omi.2022.0137] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
The majority of processes that occur in daily cell life are modulated by hundreds to thousands of dynamic protein-protein interactions (PPI). The resulting protein complexes constitute a tangled network that, with its continuous remodeling, builds up highly organized functional units. Thus, defining the dynamic interactome of one or more proteins allows determining the full range of biological activities these proteins are capable of. This conceptual approach is poised to gain further traction and significance in the current postgenomic era wherein the treatment of severe diseases needs to be tackled at both genomic and PPI levels. This also holds true for COVID-19, a multisystemic disease affecting biological networks across the biological hierarchy from genome to proteome to metabolome. In this overarching context and the current historical moment of the COVID-19 pandemic where systems biology increasingly comes to the fore, cross-linking mass spectrometry (XL-MS) has become highly relevant, emerging as a powerful tool for PPI discovery and characterization. This expert review highlights the advanced XL-MS approaches that provide in vivo insights into the three-dimensional protein complexes, overcoming the static nature of common interactomics data and embracing the dynamics of the cell proteome landscape. Many XL-MS applications based on the use of diverse cross-linkers, MS detection methods, and predictive bioinformatic tools for single proteins or proteome-wide interactions were shown. We conclude with a future outlook on XL-MS applications in the field of structural proteomics and ways to sustain the remarkable flexibility of XL-MS for dynamic interactomics and structural studies in systems biology and planetary health.
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Affiliation(s)
- Lucia Santorelli
- Department of Oncology and Hematology-Oncology, University of Milano, Milan, Italy.,IFOM ETS, The AIRC Institute of Molecular Oncology, Milan, Italy
| | - Marianna Caterino
- Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, Naples, Italy.,CEINGE-Biotecnologie Avanzate s.c.ar.l., Naples, Italy
| | - Michele Costanzo
- Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, Naples, Italy.,CEINGE-Biotecnologie Avanzate s.c.ar.l., Naples, Italy
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17
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Huang W, Sun YM, Pan Q, Fang K, Chen XT, Zeng ZC, Chen TQ, Zhu SX, Huang LB, Luo XQ, Wang WT, Chen YQ. The snoRNA-like lncRNA LNC-SNO49AB drives leukemia by activating the RNA-editing enzyme ADAR1. Cell Discov 2022; 8:117. [PMID: 36316318 PMCID: PMC9622897 DOI: 10.1038/s41421-022-00460-9] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Accepted: 08/18/2022] [Indexed: 01/24/2023] Open
Abstract
Long noncoding RNAs (lncRNAs) are usually 5' capped and 3' polyadenylated, similar to most typical mRNAs. However, recent studies revealed a type of snoRNA-related lncRNA with unique structures, leading to questions on how they are processed and how they work. Here, we identify a novel snoRNA-related lncRNA named LNC-SNO49AB containing two C/D box snoRNA sequences, SNORD49A and SNORD49B; and show that LNC-SNO49AB represents an unreported type of lncRNA with a 5'-end m7G and a 3'-end snoRNA structure. LNC-SNO49AB was found highly expressed in leukemia patient samples, and silencing LNC-SNO49AB dramatically suppressed leukemia progression in vitro and in vivo. Subcellular location indicated that the LNC-SNO49AB is mainly located in nucleolus and interacted with the nucleolar protein fibrillarin. However, we found that LNC-SNO49AB does not play a role in 2'-O-methylation regulation, a classical function of snoRNA; instead, its snoRNA structure affected the lncRNA stability. We further demonstrated that LNC-SNO49AB could directly bind to the adenosine deaminase acting on RNA 1(ADAR1) and promoted its homodimerization followed by a high RNA A-to-I editing activity. Transcriptome profiling shows that LNC-SNO49AB and ADAR1 knockdown respectively share very similar patterns of RNA modification change in downstream signaling pathways, especially in cell cycle pathways. These findings suggest a previously unknown class of snoRNA-related lncRNAs, which function via a manner in nucleolus independently on snoRNA-guide rRNA modification. This is the first report that a lncRNA regulates genome-wide RNA A-to-I editing by enhancing ADAR1 dimerization to facilitate hematopoietic malignancy, suggesting that LNC-SNO49AB may be a novel target in therapy directed to leukemia.
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Affiliation(s)
- Wei Huang
- grid.12981.330000 0001 2360 039XGuangdong Province Key Laboratory of Pharmaceutical Functional Genes, MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory for Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong China
| | - Yu-Meng Sun
- grid.12981.330000 0001 2360 039XGuangdong Province Key Laboratory of Pharmaceutical Functional Genes, MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory for Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong China
| | - Qi Pan
- grid.12981.330000 0001 2360 039XGuangdong Province Key Laboratory of Pharmaceutical Functional Genes, MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory for Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong China
| | - Ke Fang
- grid.12981.330000 0001 2360 039XGuangdong Province Key Laboratory of Pharmaceutical Functional Genes, MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory for Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong China
| | - Xiao-Tong Chen
- grid.12981.330000 0001 2360 039XGuangdong Province Key Laboratory of Pharmaceutical Functional Genes, MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory for Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong China
| | - Zhan-Cheng Zeng
- grid.12981.330000 0001 2360 039XGuangdong Province Key Laboratory of Pharmaceutical Functional Genes, MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory for Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong China
| | - Tian-Qi Chen
- grid.12981.330000 0001 2360 039XGuangdong Province Key Laboratory of Pharmaceutical Functional Genes, MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory for Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong China
| | - Shun-Xin Zhu
- grid.12981.330000 0001 2360 039XGuangdong Province Key Laboratory of Pharmaceutical Functional Genes, MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory for Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong China
| | - Li-Bin Huang
- grid.412615.50000 0004 1803 6239The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong China
| | - Xue-Qun Luo
- grid.412615.50000 0004 1803 6239The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong China
| | - Wen-Tao Wang
- grid.12981.330000 0001 2360 039XGuangdong Province Key Laboratory of Pharmaceutical Functional Genes, MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory for Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong China
| | - Yue-Qin Chen
- grid.12981.330000 0001 2360 039XGuangdong Province Key Laboratory of Pharmaceutical Functional Genes, MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory for Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong China
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18
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Vakser IA, Grudinin S, Jenkins NW, Kundrotas PJ, Deeds EJ. Docking-based long timescale simulation of cell-size protein systems at atomic resolution. Proc Natl Acad Sci U S A 2022; 119:e2210249119. [PMID: 36191203 PMCID: PMC9565162 DOI: 10.1073/pnas.2210249119] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 09/02/2022] [Indexed: 01/03/2023] Open
Abstract
Computational methodologies are increasingly addressing modeling of the whole cell at the molecular level. Proteins and their interactions are the key component of cellular processes. Techniques for modeling protein interactions, thus far, have included protein docking and molecular simulation. The latter approaches account for the dynamics of the interactions but are relatively slow, if carried out at all-atom resolution, or are significantly coarse grained. Protein docking algorithms are far more efficient in sampling spatial coordinates. However, they do not account for the kinetics of the association (i.e., they do not involve the time coordinate). Our proof-of-concept study bridges the two modeling approaches, developing an approach that can reach unprecedented simulation timescales at all-atom resolution. The global intermolecular energy landscape of a large system of proteins was mapped by the pairwise fast Fourier transform docking and sampled in space and time by Monte Carlo simulations. The simulation protocol was parametrized on existing data and validated on a number of observations from experiments and molecular dynamics simulations. The simulation protocol performed consistently across very different systems of proteins at different protein concentrations. It recapitulated data on the previously observed protein diffusion rates and aggregation. The speed of calculation allows reaching second-long trajectories of protein systems that approach the size of the cells, at atomic resolution.
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Affiliation(s)
- Ilya A. Vakser
- Computational Biology Program, The University of Kansas, Lawrence, KS
- Department of Molecular Biosciences, The University of Kansas, Lawrence, KS
| | - Sergei Grudinin
- University of Grenoble Alpes, CNRS, Grenoble INP, LJK, Grenoble, France
| | - Nathan W. Jenkins
- Computational Biology Program, The University of Kansas, Lawrence, KS
| | | | - Eric J. Deeds
- Department of Integrative Biology and Physiology, Institute for Quantitative and Computational Biosciences, University of California, Los Angeles, CA
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19
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Hofmann L, Ruthstein S. EPR Spectroscopy Provides New Insights into Complex Biological Reaction Mechanisms. J Phys Chem B 2022; 126:7486-7494. [PMID: 36137278 PMCID: PMC9549461 DOI: 10.1021/acs.jpcb.2c05235] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
![]()
In the last 20 years, the use of electron paramagnetic
resonance
(EPR) has made a pronounced and lasting impact in the field of structural
biology. The advantage of EPR spectroscopy over other structural techniques
is its ability to target even minor conformational changes in any
biomolecule or macromolecular complex, independent of its size or
complexity, or whether it is in solution or in the cell during a biological
or chemical reaction. Here, we focus on the use of EPR spectroscopy
to study transmembrane transport and transcription mechanisms. We
discuss experimental and analytical concerns when referring to studies
of two biological reaction mechanisms, namely, transfer of copper
ions by the human copper transporter hCtr1 and the mechanism of action
of the Escherichia coli copper-dependent
transcription factor CueR. Last, we elaborate on future avenues in
the field of EPR structural biology.
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Affiliation(s)
- Lukas Hofmann
- Department of Chemistry and the Institute of Nanotechnology & Advanced Materials, Faculty of Exact Sciences, Bar-Ilan University, Ramat-Gan 5290002, Israel
| | - Sharon Ruthstein
- Department of Chemistry and the Institute of Nanotechnology & Advanced Materials, Faculty of Exact Sciences, Bar-Ilan University, Ramat-Gan 5290002, Israel
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20
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Blackburn MR, Minkoff BB, Sussman MR. Mass spectrometry-based technologies for probing the 3D world of plant proteins. PLANT PHYSIOLOGY 2022; 189:12-22. [PMID: 35139210 PMCID: PMC9070838 DOI: 10.1093/plphys/kiac039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 12/30/2021] [Indexed: 05/03/2023]
Abstract
Over the past two decades, mass spectrometric (MS)-based proteomics technologies have facilitated the study of signaling pathways throughout biology. Nowhere is this needed more than in plants, where an evolutionary history of genome duplications has resulted in large gene families involved in posttranslational modifications and regulatory pathways. For example, at least 5% of the Arabidopsis thaliana genome (ca. 1,200 genes) encodes protein kinases and protein phosphatases that regulate nearly all aspects of plant growth and development. MS-based technologies that quantify covalent changes in the side-chain of amino acids are critically important, but they only address one piece of the puzzle. A more crucially important mechanistic question is how noncovalent interactions-which are more difficult to study-dynamically regulate the proteome's 3D structure. The advent of improvements in protein 3D technologies such as cryo-electron microscopy, nuclear magnetic resonance, and X-ray crystallography has allowed considerable progress to be made at this level, but these methods are typically limited to analyzing proteins, which can be expressed and purified in milligram quantities. Newly emerging MS-based technologies have recently been developed for studying the 3D structure of proteins. Importantly, these methods do not require protein samples to be purified and require smaller amounts of sample, opening the wider proteome for structural analysis in complex mixtures, crude lysates, and even in intact cells. These MS-based methods include covalent labeling, crosslinking, thermal proteome profiling, and limited proteolysis, all of which can be leveraged by established MS workflows, as well as newly emerging methods capable of analyzing intact macromolecules and the complexes they form. In this review, we discuss these recent innovations in MS-based "structural" proteomics to provide readers with an understanding of the opportunities they offer and the remaining challenges for understanding the molecular underpinnings of plant structure and function.
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Affiliation(s)
- Matthew R Blackburn
- Department of Biochemistry and Center for Genomic Science Innovation, University of Wisconsin, Madison, Wisconsin 53706, USA
| | - Benjamin B Minkoff
- Department of Biochemistry and Center for Genomic Science Innovation, University of Wisconsin, Madison, Wisconsin 53706, USA
| | - Michael R Sussman
- Department of Biochemistry and Center for Genomic Science Innovation, University of Wisconsin, Madison, Wisconsin 53706, USA
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21
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Molza AE, Westermaier Y, Moutte M, Ducrot P, Danilowicz C, Godoy-Carter V, Prentiss M, Robert CH, Baaden M, Prévost C. Building Biological Relevance Into Integrative Modelling of Macromolecular Assemblies. Front Mol Biosci 2022; 9:826136. [PMID: 35480882 PMCID: PMC9035671 DOI: 10.3389/fmolb.2022.826136] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 02/21/2022] [Indexed: 01/25/2023] Open
Abstract
Recent advances in structural biophysics and integrative modelling methods now allow us to decipher the structures of large macromolecular assemblies. Understanding the dynamics and mechanisms involved in their biological function requires rigorous integration of all available data. We have developed a complete modelling pipeline that includes analyses to extract biologically significant information by consistently combining automated and interactive human-guided steps. We illustrate this idea with two examples. First, we describe the ryanodine receptor, an ion channel that controls ion flux across the cell membrane through transitions between open and closed states. The conformational changes associated with the transitions are small compared to the considerable system size of the receptor; it is challenging to consistently track these states with the available cryo-EM structures. The second example involves homologous recombination, in which long filaments of a recombinase protein and DNA catalyse the exchange of homologous DNA strands to reliably repair DNA double-strand breaks. The nucleoprotein filament reaction intermediates in this process are short-lived and heterogeneous, making their structures particularly elusive. The pipeline we describe, which incorporates experimental and theoretical knowledge combined with state-of-the-art interactive and immersive modelling tools, can help overcome these challenges. In both examples, we point to new insights into biological processes that arise from such interdisciplinary approaches.
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Affiliation(s)
- Anne-Elisabeth Molza
- CNRS, Université Paris-Cité, UPR 9080, Laboratoire de Biochimie Théorique, Paris, France
- Institut de Biologie Physico-Chimique-Fondation Edmond de Rothschild, PSL Research University, Paris, France
| | - Yvonne Westermaier
- Biophysics and Modelling Department/In Vitro Pharmacology Unit–IDRS (Servier Research Institute), Croissy-sur-Seine, France
| | | | - Pierre Ducrot
- Biophysics and Modelling Department/In Vitro Pharmacology Unit–IDRS (Servier Research Institute), Croissy-sur-Seine, France
| | | | | | - Mara Prentiss
- Department of Physics, Harvard University, Cambridge, MA, United States
| | - Charles H. Robert
- CNRS, Université Paris-Cité, UPR 9080, Laboratoire de Biochimie Théorique, Paris, France
- Institut de Biologie Physico-Chimique-Fondation Edmond de Rothschild, PSL Research University, Paris, France
| | - Marc Baaden
- CNRS, Université Paris-Cité, UPR 9080, Laboratoire de Biochimie Théorique, Paris, France
- Institut de Biologie Physico-Chimique-Fondation Edmond de Rothschild, PSL Research University, Paris, France
| | - Chantal Prévost
- CNRS, Université Paris-Cité, UPR 9080, Laboratoire de Biochimie Théorique, Paris, France
- Institut de Biologie Physico-Chimique-Fondation Edmond de Rothschild, PSL Research University, Paris, France
- *Correspondence: Chantal Prévost ,
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22
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Yunoki Y, Matsumoto A, Morishima K, Martel A, Porcar L, Sato N, Yogo R, Tominaga T, Inoue R, Yagi-Utsumi M, Okuda A, Shimizu M, Urade R, Terauchi K, Kono H, Yagi H, Kato K, Sugiyama M. Overall structure of fully assembled cyanobacterial KaiABC circadian clock complex by an integrated experimental-computational approach. Commun Biol 2022; 5:184. [PMID: 35273347 PMCID: PMC8913699 DOI: 10.1038/s42003-022-03143-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 02/08/2022] [Indexed: 12/24/2022] Open
Abstract
In the cyanobacterial circadian clock system, KaiA, KaiB and KaiC periodically assemble into a large complex. Here we determined the overall structure of their fully assembled complex by integrating experimental and computational approaches. Small-angle X-ray and inverse contrast matching small-angle neutron scatterings coupled with size-exclusion chromatography provided constraints to highlight the spatial arrangements of the N-terminal domains of KaiA, which were not resolved in the previous structural analyses. Computationally built 20 million structural models of the complex were screened out utilizing the constrains and then subjected to molecular dynamics simulations to examine their stabilities. The final model suggests that, despite large fluctuation of the KaiA N-terminal domains, their preferential positionings mask the hydrophobic surface of the KaiA C-terminal domains, hindering additional KaiA-KaiC interactions. Thus, our integrative approach provides a useful tool to resolve large complex structures harboring dynamically fluctuating domains. The revealed full KaiA12B6C6 complex is assembled including the dynamic and asynchronous KaiA N-terminal domains that have been missing in cryo-EM structures.
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Affiliation(s)
- Yasuhiro Yunoki
- Exploratory Research Center on Life and Living Systems (ExCELLS) and Institute for Molecular Science (IMS), National Institutes of Natural Sciences, 5-1 Higashiyama, Myodaiji-cho, Okazaki, 444-8787, Japan.,Graduate School of Pharmaceutical Sciences, Nagoya City University, 3-1 Tanabe-dori, Mizuhoku, Nagoya, 467-8603, Japan.,Institute for Integrated Radiation and Nuclear Science, Kyoto University, 2-1010 Asashironishi, Kumatori, Sennan-gun, Osaka, 590-0494, Japan
| | - Atsushi Matsumoto
- Institute for Quantum Life Science, National Institutes for Quantum Science and Technology (QST), Umemidai, Kizu, Kyoto, 619-0215, Japan
| | - Ken Morishima
- Institute for Integrated Radiation and Nuclear Science, Kyoto University, 2-1010 Asashironishi, Kumatori, Sennan-gun, Osaka, 590-0494, Japan
| | - Anne Martel
- Institut Laue-Langevin, 71, avenue des martyrs, 38042, Grenoble, France
| | - Lionel Porcar
- Institut Laue-Langevin, 71, avenue des martyrs, 38042, Grenoble, France
| | - Nobuhiro Sato
- Institute for Integrated Radiation and Nuclear Science, Kyoto University, 2-1010 Asashironishi, Kumatori, Sennan-gun, Osaka, 590-0494, Japan
| | - Rina Yogo
- Exploratory Research Center on Life and Living Systems (ExCELLS) and Institute for Molecular Science (IMS), National Institutes of Natural Sciences, 5-1 Higashiyama, Myodaiji-cho, Okazaki, 444-8787, Japan.,Graduate School of Pharmaceutical Sciences, Nagoya City University, 3-1 Tanabe-dori, Mizuhoku, Nagoya, 467-8603, Japan.,Biomedical Research Centre, School of Biomedical Engineering, The University of British Columbia, 2222 Health Sciences Mall, Vancouver, BC, V6T 1Z3, Canada
| | - Taiki Tominaga
- Neutron Science and Technology Center, Comprehensive Research Organization for Science and Society (CROSS), Tokai, Ibaraki, 319-1106, Japan
| | - Rintaro Inoue
- Institute for Integrated Radiation and Nuclear Science, Kyoto University, 2-1010 Asashironishi, Kumatori, Sennan-gun, Osaka, 590-0494, Japan
| | - Maho Yagi-Utsumi
- Exploratory Research Center on Life and Living Systems (ExCELLS) and Institute for Molecular Science (IMS), National Institutes of Natural Sciences, 5-1 Higashiyama, Myodaiji-cho, Okazaki, 444-8787, Japan.,Graduate School of Pharmaceutical Sciences, Nagoya City University, 3-1 Tanabe-dori, Mizuhoku, Nagoya, 467-8603, Japan
| | - Aya Okuda
- Institute for Integrated Radiation and Nuclear Science, Kyoto University, 2-1010 Asashironishi, Kumatori, Sennan-gun, Osaka, 590-0494, Japan
| | - Masahiro Shimizu
- Institute for Integrated Radiation and Nuclear Science, Kyoto University, 2-1010 Asashironishi, Kumatori, Sennan-gun, Osaka, 590-0494, Japan
| | - Reiko Urade
- Institute for Integrated Radiation and Nuclear Science, Kyoto University, 2-1010 Asashironishi, Kumatori, Sennan-gun, Osaka, 590-0494, Japan
| | - Kazuki Terauchi
- Graduate School of Life Sciences, Ritsumeikan University, 1-1-1 Noji-higashi, Kusatsu, Shiga, 525-8577, Japan
| | - Hidetoshi Kono
- Institute for Quantum Life Science, National Institutes for Quantum Science and Technology (QST), Umemidai, Kizu, Kyoto, 619-0215, Japan.
| | - Hirokazu Yagi
- Graduate School of Pharmaceutical Sciences, Nagoya City University, 3-1 Tanabe-dori, Mizuhoku, Nagoya, 467-8603, Japan.
| | - Koichi Kato
- Exploratory Research Center on Life and Living Systems (ExCELLS) and Institute for Molecular Science (IMS), National Institutes of Natural Sciences, 5-1 Higashiyama, Myodaiji-cho, Okazaki, 444-8787, Japan. .,Graduate School of Pharmaceutical Sciences, Nagoya City University, 3-1 Tanabe-dori, Mizuhoku, Nagoya, 467-8603, Japan.
| | - Masaaki Sugiyama
- Institute for Integrated Radiation and Nuclear Science, Kyoto University, 2-1010 Asashironishi, Kumatori, Sennan-gun, Osaka, 590-0494, Japan.
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23
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Ni D, Liu Y, Kong R, Yu Z, Lu S, Zhang J. Computational elucidation of allosteric communication in proteins for allosteric drug design. Drug Discov Today 2022; 27:2226-2234. [DOI: 10.1016/j.drudis.2022.03.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 01/22/2022] [Accepted: 03/17/2022] [Indexed: 02/07/2023]
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24
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Wood DM, Dobson RC, Horne CR. Using cryo-EM to uncover mechanisms of bacterial transcriptional regulation. Biochem Soc Trans 2021; 49:2711-2726. [PMID: 34854920 PMCID: PMC8786299 DOI: 10.1042/bst20210674] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 11/10/2021] [Accepted: 11/15/2021] [Indexed: 11/17/2022]
Abstract
Transcription is the principal control point for bacterial gene expression, and it enables a global cellular response to an intracellular or environmental trigger. Transcriptional regulation is orchestrated by transcription factors, which activate or repress transcription of target genes by modulating the activity of RNA polymerase. Dissecting the nature and precise choreography of these interactions is essential for developing a molecular understanding of transcriptional regulation. While the contribution of X-ray crystallography has been invaluable, the 'resolution revolution' of cryo-electron microscopy has transformed our structural investigations, enabling large, dynamic and often transient transcription complexes to be resolved that in many cases had resisted crystallisation. In this review, we highlight the impact cryo-electron microscopy has had in gaining a deeper understanding of transcriptional regulation in bacteria. We also provide readers working within the field with an overview of the recent innovations available for cryo-electron microscopy sample preparation and image reconstruction of transcription complexes.
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Affiliation(s)
- David M. Wood
- Biomolecular Interaction Centre and School of Biological Sciences, University of Canterbury, Christchurch, New Zealand
| | - Renwick C.J. Dobson
- Biomolecular Interaction Centre and School of Biological Sciences, University of Canterbury, Christchurch, New Zealand
- Bio21 Molecular Science and Biotechnology Institute, Department of Biochemistry and Pharmacology, University of Melbourne, Parkville, VIC, Australia
| | - Christopher R. Horne
- Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, VIC 3052, Australia
- Department of Medical Biology, University of Melbourne, Parkville, VIC 3052, Australia
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25
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Piersimoni L, Kastritis PL, Arlt C, Sinz A. Cross-Linking Mass Spectrometry for Investigating Protein Conformations and Protein-Protein Interactions─A Method for All Seasons. Chem Rev 2021; 122:7500-7531. [PMID: 34797068 DOI: 10.1021/acs.chemrev.1c00786] [Citation(s) in RCA: 148] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Mass spectrometry (MS) has become one of the key technologies of structural biology. In this review, the contributions of chemical cross-linking combined with mass spectrometry (XL-MS) for studying three-dimensional structures of proteins and for investigating protein-protein interactions are outlined. We summarize the most important cross-linking reagents, software tools, and XL-MS workflows and highlight prominent examples for characterizing proteins, their assemblies, and interaction networks in vitro and in vivo. Computational modeling plays a crucial role in deriving 3D-structural information from XL-MS data. Integrating XL-MS with other techniques of structural biology, such as cryo-electron microscopy, has been successful in addressing biological questions that to date could not be answered. XL-MS is therefore expected to play an increasingly important role in structural biology in the future.
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Affiliation(s)
- Lolita Piersimoni
- Department of Pharmaceutical Chemistry & Bioanalytics, Institute of Pharmacy, Kurt-Mothes-Strasse 3, D-06120 Halle (Saale), Germany.,Center for Structural Mass Spectrometry, Kurt-Mothes-Strasse 3, D-06120 Halle (Saale), Germany
| | - Panagiotis L Kastritis
- Interdisciplinary Research Center HALOmem, Charles Tanford Protein Center, Kurt-Mothes-Strasse 3a, D-06120 Halle (Saale), Germany.,Institute of Biochemistry and Biotechnology, Martin Luther University Halle-Wittenberg, Kurt-Mothes-Strasse 3, D-06120 Halle (Saale), Germany.,Biozentrum, Weinbergweg 22, D-06120 Halle (Saale), Germany
| | - Christian Arlt
- Department of Pharmaceutical Chemistry & Bioanalytics, Institute of Pharmacy, Kurt-Mothes-Strasse 3, D-06120 Halle (Saale), Germany.,Center for Structural Mass Spectrometry, Kurt-Mothes-Strasse 3, D-06120 Halle (Saale), Germany
| | - Andrea Sinz
- Department of Pharmaceutical Chemistry & Bioanalytics, Institute of Pharmacy, Kurt-Mothes-Strasse 3, D-06120 Halle (Saale), Germany.,Center for Structural Mass Spectrometry, Kurt-Mothes-Strasse 3, D-06120 Halle (Saale), Germany
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26
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Lyonnais S, Sadiq SK, Lorca-Oró C, Dufau L, Nieto-Marquez S, Escribà T, Gabrielli N, Tan X, Ouizougun-Oubari M, Okoronkwo J, Reboud-Ravaux M, Gatell JM, Marquet R, Paillart JC, Meyerhans A, Tisné C, Gorelick RJ, Mirambeau G. The HIV-1 Nucleocapsid Regulates Its Own Condensation by Phase-Separated Activity-Enhancing Sequestration of the Viral Protease during Maturation. Viruses 2021; 13:v13112312. [PMID: 34835118 PMCID: PMC8625067 DOI: 10.3390/v13112312] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 11/09/2021] [Accepted: 11/11/2021] [Indexed: 02/07/2023] Open
Abstract
A growing number of studies indicate that mRNAs and long ncRNAs can affect protein populations by assembling dynamic ribonucleoprotein (RNP) granules. These phase-separated molecular ‘sponges’, stabilized by quinary (transient and weak) interactions, control proteins involved in numerous biological functions. Retroviruses such as HIV-1 form by self-assembly when their genomic RNA (gRNA) traps Gag and GagPol polyprotein precursors. Infectivity requires extracellular budding of the particle followed by maturation, an ordered processing of ∼2400 Gag and ∼120 GagPol by the viral protease (PR). This leads to a condensed gRNA-NCp7 nucleocapsid and a CAp24-self-assembled capsid surrounding the RNP. The choreography by which all of these components dynamically interact during virus maturation is one of the missing milestones to fully depict the HIV life cycle. Here, we describe how HIV-1 has evolved a dynamic RNP granule with successive weak–strong–moderate quinary NC-gRNA networks during the sequential processing of the GagNC domain. We also reveal two palindromic RNA-binding triads on NC, KxxFxxQ and QxxFxxK, that provide quinary NC-gRNA interactions. Consequently, the nucleocapsid complex appears properly aggregated for capsid reassembly and reverse transcription, mandatory processes for viral infectivity. We show that PR is sequestered within this RNP and drives its maturation/condensation within minutes, this process being most effective at the end of budding. We anticipate such findings will stimulate further investigations of quinary interactions and emergent mechanisms in crowded environments throughout the wide and growing array of RNP granules.
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Affiliation(s)
- Sébastien Lyonnais
- Infectious Disease & AIDS Research Unit, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036 Barcelona, Spain; (C.L.-O.); (S.N.-M.); (T.E.); (N.G.); (X.T.); (M.O.-O.); (J.O.); (J.M.G.)
- Centre d’Etudes des Maladies Infectieuses et Pharmacologie Anti-Infectieuse (CEMIPAI), CNRS UAR 3725, Université de Montpellier, 1919 Route de Mende, CEDEX 05, 34293 Montpellier, France
- Correspondence: (S.L.); (S.K.S.); (G.M.)
| | - S. Kashif Sadiq
- Infection Biology Laboratory, Department of Experimental and Health Sciences (DCEXS), Universitat Pompeu Fabra, Carrer Doctor Aiguader 88, 08003 Barcelona, Spain;
- Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies (HITS), Schloss-Wolfsbrunnenweg 35, 69118 Heidelberg, Germany
- Genome Biology Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany
- Correspondence: (S.L.); (S.K.S.); (G.M.)
| | - Cristina Lorca-Oró
- Infectious Disease & AIDS Research Unit, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036 Barcelona, Spain; (C.L.-O.); (S.N.-M.); (T.E.); (N.G.); (X.T.); (M.O.-O.); (J.O.); (J.M.G.)
| | - Laure Dufau
- Biological Adaptation and Ageing (B2A), CNRS UMR 8256 & INSERM ERL U1164, Institut de Biologie Paris-Seine (IBPS), Faculté des Sciences et d’Ingénierie (FSI), Sorbonne Université, 7 Quai St Bernard, CEDEX 05, 75252 Paris, France; (L.D.); (M.R.-R.)
| | - Sara Nieto-Marquez
- Infectious Disease & AIDS Research Unit, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036 Barcelona, Spain; (C.L.-O.); (S.N.-M.); (T.E.); (N.G.); (X.T.); (M.O.-O.); (J.O.); (J.M.G.)
| | - Tuixent Escribà
- Infectious Disease & AIDS Research Unit, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036 Barcelona, Spain; (C.L.-O.); (S.N.-M.); (T.E.); (N.G.); (X.T.); (M.O.-O.); (J.O.); (J.M.G.)
| | - Natalia Gabrielli
- Infectious Disease & AIDS Research Unit, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036 Barcelona, Spain; (C.L.-O.); (S.N.-M.); (T.E.); (N.G.); (X.T.); (M.O.-O.); (J.O.); (J.M.G.)
| | - Xiao Tan
- Infectious Disease & AIDS Research Unit, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036 Barcelona, Spain; (C.L.-O.); (S.N.-M.); (T.E.); (N.G.); (X.T.); (M.O.-O.); (J.O.); (J.M.G.)
- Biological Adaptation and Ageing (B2A), CNRS UMR 8256 & INSERM ERL U1164, Institut de Biologie Paris-Seine (IBPS), Faculté des Sciences et d’Ingénierie (FSI), Sorbonne Université, 7 Quai St Bernard, CEDEX 05, 75252 Paris, France; (L.D.); (M.R.-R.)
| | - Mohamed Ouizougun-Oubari
- Infectious Disease & AIDS Research Unit, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036 Barcelona, Spain; (C.L.-O.); (S.N.-M.); (T.E.); (N.G.); (X.T.); (M.O.-O.); (J.O.); (J.M.G.)
| | - Josephine Okoronkwo
- Infectious Disease & AIDS Research Unit, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036 Barcelona, Spain; (C.L.-O.); (S.N.-M.); (T.E.); (N.G.); (X.T.); (M.O.-O.); (J.O.); (J.M.G.)
| | - Michèle Reboud-Ravaux
- Biological Adaptation and Ageing (B2A), CNRS UMR 8256 & INSERM ERL U1164, Institut de Biologie Paris-Seine (IBPS), Faculté des Sciences et d’Ingénierie (FSI), Sorbonne Université, 7 Quai St Bernard, CEDEX 05, 75252 Paris, France; (L.D.); (M.R.-R.)
| | - José Maria Gatell
- Infectious Disease & AIDS Research Unit, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036 Barcelona, Spain; (C.L.-O.); (S.N.-M.); (T.E.); (N.G.); (X.T.); (M.O.-O.); (J.O.); (J.M.G.)
- Facultat de Medicina y Ciencias de la Salud, Universitat de Barcelona, Carrer de Casanova 143, 08036 Barcelona, Spain
| | - Roland Marquet
- Architecture et Réactivité de l’ARN, CNRS UPR 9002, Université de Strasbourg, 2 Allée Conrad Roentgen, 67000 Strasbourg, France; (R.M.); (J.-C.P.)
| | - Jean-Christophe Paillart
- Architecture et Réactivité de l’ARN, CNRS UPR 9002, Université de Strasbourg, 2 Allée Conrad Roentgen, 67000 Strasbourg, France; (R.M.); (J.-C.P.)
| | - Andreas Meyerhans
- Infection Biology Laboratory, Department of Experimental and Health Sciences (DCEXS), Universitat Pompeu Fabra, Carrer Doctor Aiguader 88, 08003 Barcelona, Spain;
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Passeig de Lluís Companys 23, 08010 Barcelona, Spain
| | - Carine Tisné
- Expression Génétique Microbienne, CNRS UMR 8261, Institut de Biologie Physico-Chimique (IBPC), Université de Paris, 13 Rue Pierre et Marie Curie, 75005 Paris, France;
| | - Robert J. Gorelick
- AIDS and Cancer Virus Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD 21701, USA;
| | - Gilles Mirambeau
- Infectious Disease & AIDS Research Unit, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036 Barcelona, Spain; (C.L.-O.); (S.N.-M.); (T.E.); (N.G.); (X.T.); (M.O.-O.); (J.O.); (J.M.G.)
- Biologie Intégrative des Organismes Marins (BIOM), CNRS UMR 7232, Observatoire Océanologique de Banyuls (OOB), Faculté des Sciences et d’Ingénierie (FSI), Sorbonne Université, 1 Avenue Pierre Fabre, 66650 Banyuls-sur-Mer, France
- Correspondence: (S.L.); (S.K.S.); (G.M.)
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27
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Schaeffer RD, Kinch LN, Pei J, Medvedev KE, Grishin NV. Completeness and Consistency in Structural Domain Classifications. ACS OMEGA 2021; 6:15698-15707. [PMID: 34179613 PMCID: PMC8223206 DOI: 10.1021/acsomega.1c00950] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 05/25/2021] [Indexed: 06/13/2023]
Abstract
Domain classifications are a useful resource for computational analysis of the protein structure, but elements of their composition are often opaque to potential users. We perform a comparative analysis of our classification ECOD against the SCOPe, SCOP2, and CATH domain classifications with respect to their constituent domain boundaries and hierarchal organization. The coverage of these domain classifications with respect to ECOD and to the PDB was assessed by structure and by sequence. We also conducted domain pair analysis to determine broad differences in hierarchy between domains shared by ECOD and other classifications. Finally, we present domains from the major facilitator superfamily (MFS) of transporter proteins and provide evidence that supports their split into domains and for multiple conformations within these families. We find that the ECOD and CATH provide the most extensive structural coverage of the PDB. ECOD and SCOPe have the most consistent domain boundary conditions, whereas CATH and SCOP2 both differ significantly.
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Affiliation(s)
- R. Dustin Schaeffer
- Departments
of Biophysics and Biochemistry, University
of Texas Southwestern Medical Center, Dallas, Texas 75390, United States
| | - Lisa N. Kinch
- Howard
Hughes Medical Institute, University of
Texas Southwestern Medical Center, Dallas, Texas 75390, United States
| | - Jimin Pei
- Howard
Hughes Medical Institute, University of
Texas Southwestern Medical Center, Dallas, Texas 75390, United States
| | - Kirill E. Medvedev
- Departments
of Biophysics and Biochemistry, University
of Texas Southwestern Medical Center, Dallas, Texas 75390, United States
| | - Nick V. Grishin
- Departments
of Biophysics and Biochemistry, University
of Texas Southwestern Medical Center, Dallas, Texas 75390, United States
- Howard
Hughes Medical Institute, University of
Texas Southwestern Medical Center, Dallas, Texas 75390, United States
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28
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Gardner A, Autin L, Fuentes D, Maritan M, Barad BA, Medina M, Olson AJ, Grotjahn DA, Goodsell DS. CellPAINT: Turnkey Illustration of Molecular Cell Biology. FRONTIERS IN BIOINFORMATICS 2021; 1:660936. [PMID: 34790910 PMCID: PMC8594902 DOI: 10.3389/fbinf.2021.660936] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 03/08/2021] [Indexed: 01/01/2023] Open
Abstract
CellPAINT is an interactive digital tool that allows non-expert users to create illustrations of the molecular structure of cells and viruses. We present a new release with several key enhancements, including the ability to generate custom ingredients from structure information in the Protein Data Bank, and interaction, grouping, and locking functions that streamline the creation of assemblies and illustration of large, complex scenes. An example of CellPAINT as a tool for hypothesis generation in the interpretation of cryoelectron tomograms is presented. CellPAINT is freely available at http://ccsb.scripps.edu/cellpaint.
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Affiliation(s)
- Adam Gardner
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, United States
| | - Ludovic Autin
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, United States
| | - Daniel Fuentes
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, United States
| | - Martina Maritan
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, United States
| | - Benjamin A. Barad
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, United States
| | - Michaela Medina
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, United States
| | - Arthur J. Olson
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, United States
| | - Danielle A. Grotjahn
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, United States
| | - David S. Goodsell
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, United States
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ, United States
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29
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Sali A. From integrative structural biology to cell biology. J Biol Chem 2021; 296:100743. [PMID: 33957123 PMCID: PMC8203844 DOI: 10.1016/j.jbc.2021.100743] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 04/09/2021] [Accepted: 04/30/2021] [Indexed: 12/16/2022] Open
Abstract
Integrative modeling is an increasingly important tool in structural biology, providing structures by combining data from varied experimental methods and prior information. As a result, molecular architectures of large, heterogeneous, and dynamic systems, such as the ∼52-MDa Nuclear Pore Complex, can be mapped with useful accuracy, precision, and completeness. Key challenges in improving integrative modeling include expanding model representations, increasing the variety of input data and prior information, quantifying a match between input information and a model in a Bayesian fashion, inventing more efficient structural sampling, as well as developing better model validation, analysis, and visualization. In addition, two community-level challenges in integrative modeling are being addressed under the auspices of the Worldwide Protein Data Bank (wwPDB). First, the impact of integrative structures is maximized by PDB-Development, a prototype wwPDB repository for archiving, validating, visualizing, and disseminating integrative structures. Second, the scope of structural biology is expanded by linking the wwPDB resource for integrative structures with archives of data that have not been generally used for structure determination but are increasingly important for computing integrative structures, such as data from various types of mass spectrometry, spectroscopy, optical microscopy, proteomics, and genetics. To address the largest of modeling problems, a type of integrative modeling called metamodeling is being developed; metamodeling combines different types of input models as opposed to different types of data to compute an output model. Collectively, these developments will facilitate the structural biology mindset in cell biology and underpin spatiotemporal mapping of the entire cell.
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Affiliation(s)
- Andrej Sali
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, the Department of Bioengineering and Therapeutic Sciences, the Quantitative Biosciences Institute (QBI), and the Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California, USA.
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