1
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Dommer AC, Rogers MM, Carter-Fenk KA, Wauer NA, Rubio P, Davasam A, Allen HC, Amaro RE. Interfacial Enrichment of Lauric Acid Assisted by Long-Chain Fatty Acids, Acidity and Salinity at Sea Spray Aerosol Surfaces. J Phys Chem A 2024; 128:7195-7207. [PMID: 39106367 PMCID: PMC11372753 DOI: 10.1021/acs.jpca.4c03335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/09/2024]
Abstract
Surfactant monolayers at sea spray aerosol (SSA) surfaces regulate various atmospheric processes including gas transfer, cloud interactions, and radiative properties. Most experimental studies of SSA employ a simplified surfactant mixture of long-chain fatty acids (LCFAs) as a proxy for the sea surface microlayer or SSA surface. However, medium-chain fatty acids (MCFAs) make up nearly 30% of the FA fraction in nascent SSA. Given that LCFA monolayers are easily disrupted upon the introduction of chemical heterogeneity (such as mixed chain lengths), simple FA proxies are unlikely to represent realistic SSA interfaces. Integrating experimental and computational techniques, we characterize the impact that partially soluble MCFAs have on the properties of atmospherically relevant LCFA mixtures. We explore the extent to which the MCFA lauric acid (LA) is surface stabilized by varying acidity, salinity, and monolayer composition. We also discuss the impacts of pH on LCFA-assisted LA retention, where the presence of LCFAs may shift the surface-adsorption equilibria of laurate─the conjugate base─toward higher surface activities. Molecular dynamic simulations suggest a mechanism for the enhanced surface retention of laurate. We conclude that increased FA heterogeneity at SSA surfaces promotes surface activity of soluble FA species, altering monolayer phase behavior and impacting climate-relevant atmospheric processes.
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Affiliation(s)
- Abigail C Dommer
- Department of Molecular Biology, University of California, San Diego, La Jolla, California 92093, United States
| | - Mickey M Rogers
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Kimberly A Carter-Fenk
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
| | - Nicholas A Wauer
- Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, California 92093, United States
| | - Patiemma Rubio
- Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, California 92093, United States
| | - Aakash Davasam
- Department of Molecular Biology, University of California, San Diego, La Jolla, California 92093, United States
- Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, California 92093, United States
| | - Heather C Allen
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
| | - Rommie E Amaro
- Department of Molecular Biology, University of California, San Diego, La Jolla, California 92093, United States
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2
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Gadiyaram V, Prabantu VM, Manjaly AA, Muthiah A, Vishveshwara S. GraSp-PSN: A web server for graph spectra based analysis of protein structure networks. Curr Res Struct Biol 2024; 7:100147. [PMID: 38766653 PMCID: PMC11098725 DOI: 10.1016/j.crstbi.2024.100147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 04/18/2024] [Accepted: 04/23/2024] [Indexed: 05/22/2024] Open
Abstract
The function of a protein is most of the time achieved due to minute conformational changes in its structure due to ligand binding or environmental changes or other interactions. Hence the analysis of structure of proteins should go beyond the analysis of mere atom contacts and should include the emergent global structure as a whole. This can be achieved by graph spectra based analysis of protein structure networks. GraSp-PSN is a web server that can assist in (1) acquiring weighted protein structure network (PSN) and network parameters ranging from atomic level to global connectivity from the three dimensional coordinates of a protein, (2) generating scores for comparison of a pair of protein structures with detailed information of local to global connectivity, and (3) assigning perturbation scores to the residues and their interactions, that can prioritise them in terms of residue clusters. The methods implemented in the server are generic in nature and can be used for comparing networks in any discipline by uploading adjacency matrices in the server. The webserver can be accessed using the following link: https://pople.mbu.iisc.ac.in/.
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Affiliation(s)
| | | | | | - Ananth Muthiah
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India
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3
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Godbole SS, Dokholyan NV. Allosteric regulation of kinase activity in living cells. eLife 2023; 12:RP90574. [PMID: 37943025 PMCID: PMC10635643 DOI: 10.7554/elife.90574] [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] [Indexed: 11/10/2023] Open
Abstract
The dysregulation of protein kinases is associated with multiple diseases due to the kinases' involvement in a variety of cell signaling pathways. Manipulating protein kinase function, by controlling the active site, is a promising therapeutic and investigative strategy to mitigate and study diseases. Kinase active sites share structural similarities, making it difficult to specifically target one kinase, and allosteric control allows specific regulation and study of kinase function without directly targeting the active site. Allosteric sites are distal to the active site but coupled via a dynamic network of inter-atomic interactions between residues in the protein. Establishing an allosteric control over a kinase requires understanding the allosteric wiring of the protein. Computational techniques offer effective and inexpensive mapping of the allosteric sites on a protein. Here, we discuss the methods to map and regulate allosteric communications in proteins, and strategies to establish control over kinase functions in live cells and organisms. Protein molecules, or 'sensors,' are engineered to function as tools to control allosteric activity of the protein as these sensors have high spatiotemporal resolution and help in understanding cell phenotypes after immediate activation or inactivation of a kinase. Traditional methods used to study protein functions, such as knockout, knockdown, or mutation, cannot offer a sufficiently high spatiotemporal resolution. We discuss the modern repertoire of tools to regulate protein kinases as we enter a new era in deciphering cellular signaling and developing novel approaches to treat diseases associated with signal dysregulation.
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Affiliation(s)
| | - Nikolay V Dokholyan
- Department of Pharmacology, Penn State College of MedicineHersheyUnited States
- Department of Biomedical Engineering, Penn State University, University ParkHersheyUnited States
- Department of Engineering Science and Mechanics, Penn State University, University ParkHersheyUnited States
- Department of Biochemistry & Molecular Biology, Penn State College of MedicineHersheyUnited States
- Department of Chemistry, Penn State University, University ParkHersheyUnited States
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4
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Prabantu VM, Tandon H, Sandhya S, Sowdhamini R, Srinivasan N. The alteration of structural network upon transient association between proteins studied using graph theory. Proteins 2023. [PMID: 37902388 DOI: 10.1002/prot.26606] [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: 05/30/2023] [Revised: 08/31/2023] [Accepted: 09/14/2023] [Indexed: 10/31/2023]
Abstract
Proteins such as enzymes perform their function by predominant non-covalent bond interactions between transiently interacting units. There is an impact on the overall structural topology of the protein, albeit transient nature of such interactions, that enable proteins to deactivate or activate. This aspect of the alteration of the structural topology is studied by employing protein structural networks, which are node-edge representative models of protein structure, reported as a robust tool for capturing interactions between residues. Several methods have been optimized to collect meaningful, functionally relevant information by studying alteration of structural networks. In this article, different methods of comparing protein structural networks are employed, along with spectral decomposition of graphs to study the subtle impact of protein-protein interactions. A detailed analysis of the structural network of interacting partners is performed across a dataset of around 900 pairs of bound complexes and corresponding unbound protein structures. The variation in network parameters at, around, and far away from the interface are analyzed. Finally, we present interesting case studies, where an allosteric mechanism of structural impact is understood from communication-path detection methods. The results of this analysis are beneficial in understanding protein stability, for future engineering, and docking studies.
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Affiliation(s)
| | - Himani Tandon
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India
- Structural Studies Division, MRC Laboratory of Molecular Biology, Cambridge, UK
| | - Sankaran Sandhya
- Faculty of Life and Health Sciences, Department of Biotechnology, Ramaiah University of Applied Sciences, Bangalore, India
| | - Ramanathan Sowdhamini
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India
- National Centre for Biological Sciences (TIFR), Bangalore, India
- Institute of Bioinformatics and Applied Biotechnology, Bangalore, India
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5
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Noshay J, Walker T, Alexander W, Klingeman D, Romero J, Walker A, Prates E, Eckert C, Irle S, Kainer D, Jacobson D. Quantum biological insights into CRISPR-Cas9 sgRNA efficiency from explainable-AI driven feature engineering. Nucleic Acids Res 2023; 51:10147-10161. [PMID: 37738140 PMCID: PMC10602897 DOI: 10.1093/nar/gkad736] [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: 07/08/2022] [Revised: 08/07/2023] [Accepted: 08/29/2023] [Indexed: 09/24/2023] Open
Abstract
CRISPR-Cas9 tools have transformed genetic manipulation capabilities in the laboratory. Empirical rules-of-thumb have been developed for only a narrow range of model organisms, and mechanistic underpinnings for sgRNA efficiency remain poorly understood. This work establishes a novel feature set and new public resource, produced with quantum chemical tensors, for interpreting and predicting sgRNA efficiency. Feature engineering for sgRNA efficiency is performed using an explainable-artificial intelligence model: iterative Random Forest (iRF). By encoding quantitative attributes of position-specific sequences for Escherichia coli sgRNAs, we identify important traits for sgRNA design in bacterial species. Additionally, we show that expanding positional encoding to quantum descriptors of base-pair, dimer, trimer, and tetramer sequences captures intricate interactions in local and neighboring nucleotides of the target DNA. These features highlight variation in CRISPR-Cas9 sgRNA dynamics between E. coli and H. sapiens genomes. These novel encodings of sgRNAs enhance our understanding of the elaborate quantum biological processes involved in CRISPR-Cas9 machinery.
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Affiliation(s)
- Jaclyn M Noshay
- Computational and Predictive Biology, Biosciences, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Tyler Walker
- Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee-Knoxville, Knoxville, TN, USA
| | - William G Alexander
- Synthetic Biology, Biosciences,Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Dawn M Klingeman
- Synthetic Biology, Biosciences,Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Jonathon Romero
- Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee-Knoxville, Knoxville, TN, USA
| | - Angelica M Walker
- Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee-Knoxville, Knoxville, TN, USA
| | - Erica Prates
- Computational and Predictive Biology, Biosciences, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Carrie Eckert
- Synthetic Biology, Biosciences,Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Stephan Irle
- Computational Sciences and Engineering, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - David Kainer
- Computational and Predictive Biology, Biosciences, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Daniel A Jacobson
- Computational and Predictive Biology, Biosciences, Oak Ridge National Laboratory, Oak Ridge, TN, USA
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6
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Godbole S, Dokholyan NV. Allosteric regulation of kinase activity in living cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.19.549709. [PMID: 37503033 PMCID: PMC10370130 DOI: 10.1101/2023.07.19.549709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
The dysregulation of protein kinases is associated with multiple diseases due to the kinases' involvement in a variety of cell signaling pathways. Manipulating protein kinase function, by controlling the active site, is a promising therapeutic and investigative strategy to mitigate and study diseases. Kinase active sites share structural similarities making it difficult to specifically target one kinase, allosteric control allows specific regulation and study of kinase function without directly targeting the active site. Allosteric sites are distal to the active site but coupled via a dynamic network of inter-atomic interactions between residues in the protein. Establishing an allosteric control over a kinase requires understanding the allosteric wiring of the protein. Computational techniques offer effective and inexpensive mapping of the allosteric sites on a protein. Here, we discuss methods to map and regulate allosteric communications in proteins, and strategies to establish control over kinase functions in live cells and organisms. Protein molecules, or "sensors" are engineered to function as tools to control allosteric activity of the protein as these sensors have high spatiotemporal resolution and help in understanding cell phenotypes after immediate activation or inactivation of a kinase. Traditional methods used to study protein functions, such as knockout, knockdown, or mutation, cannot offer a sufficiently high spatiotemporal resolution. We discuss the modern repertoire of tools to regulate protein kinases as we enter a new era in deciphering cellular signaling and developing novel approaches to treat diseases associated with signal dysregulation.
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Affiliation(s)
- Shivani Godbole
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA 17033-0850, USA
| | - Nikolay V. Dokholyan
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA 17033-0850, USA
- Department of Biomedical Engineering, Penn State University, University Park, PA 16802, USA
- Department of Engineering Science and Mechanics, Penn State University, University Park, PA 16802, USA
- Department of Biochemistry & Molecular Biology, Penn State College of Medicine, Hershey, PA 17033-0850, USA
- Department of Chemistry, Penn State University, University Park, PA 16802, USA
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7
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Franke L, Peter C. Visualizing the Residue Interaction Landscape of Proteins by Temporal Network Embedding. J Chem Theory Comput 2023; 19:2985-2995. [PMID: 37122117 DOI: 10.1021/acs.jctc.2c01228] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
Characterizing the structural dynamics of proteins with heterogeneous conformational landscapes is crucial to understanding complex biomolecular processes. To this end, dimensionality reduction algorithms are used to produce low-dimensional embeddings of the high-dimensional conformational phase space. However, identifying a compact and informative set of input features for the embedding remains an ongoing challenge. Here, we propose to harness the power of Residue Interaction Networks (RINs) and their centrality measures, established tools to provide a graph theoretical view on molecular structure. Specifically, we combine the closeness centrality, which captures global features of the protein conformation at residue-wise resolution, with EncoderMap, a hybrid neural-network autoencoder/multidimensional-scaling like dimensionality reduction algorithm. We find that the resulting low-dimensional embedding is a meaningful visualization of the residue interaction landscape that resolves structural details of the protein behavior while retaining global interpretability. This feature-based graph embedding of temporal protein graphs makes it possible to apply the general descriptive power of RIN formalisms to the analysis of protein simulations of complex processes such as protein folding and multidomain interactions requiring no protein-specific input. We demonstrate this on simulations of the fast folding protein Trp-Cage and the multidomain signaling protein FAT10. Due to its generality and modularity, the presented approach can easily be transferred to other protein systems.
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Affiliation(s)
- Leon Franke
- Department of Chemistry, University of Konstanz, Universitätsstraße 10, Konstanz 78457, Germany
- Konstanz Research School Chemical Biology, University of Konstanz, Universitätsstraße 10, Konstanz 78457, Germany
| | - Christine Peter
- Department of Chemistry, University of Konstanz, Universitätsstraße 10, Konstanz 78457, Germany
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8
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Baek SS, Yun D, Pyo J, Kang D, Cho KH, Jeon J. Analysis of micropollutants in a marine outfall using network analysis and decision tree. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 806:150938. [PMID: 34655621 DOI: 10.1016/j.scitotenv.2021.150938] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 10/08/2021] [Accepted: 10/08/2021] [Indexed: 06/13/2023]
Abstract
The presence of micropollutants (MPs), including pharmaceutical, industrial, and pesticidal compounds, threatens both human health and the aquatic ecosystem. The development and extensive use of new chemicals have also inevitably led to the accumulation of MPs in aquatic environments. Recreational beaches are especially vulnerable to contamination, affecting humans and aquatic animals via the absorption of MPs in water during marine activities (e.g., swimming, sailing, and windsurfing). Additionally, marine outfalls in an urbanized coastal city can cause serious chemical and microbial pollution on recreational beaches, leading to an increase in adverse effects on public health and the ecological system. Therefore, the aim of this study was to, with the use of network and decision tree analyses, identify the features and factors that influence the change in MP concentrations in a marine outfall. These analyses were conducted to inspect the relationship between each MP and its hierarchical structure as well as hydrometeorological variables. Additionally, a risk analysis was conducted in this study in which the MPs were prioritized based on their optimized risk quotient values. During our monitoring of MP concentrations over time at the marine outfall, high concentrations of pharmaceutical and industrial compounds were detected when the tide level was low after rainfall. Furthermore, results of the risk analysis and the prioritization revealed that a total of 18 substances identified in our study posed a risk to the ecosystem; these include major ecotoxicologically hazardous substances such as telmisartan, mevinphos, and methiocarb. Results of the network analysis demonstrated distinct trends for pharmaceutical and industrial substances, whilst those for pesticide compounds were irregular. Additionally, the hierarchical structures for most MPs consisted of rainfall, tide level, and antecedent dry hours; this implies that these factors influence MP dynamics. These findings will be helpful for establishing chemical contamination management plans for recreational beaches in the future.
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Affiliation(s)
- Sang-Soo Baek
- School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea
| | - Daeun Yun
- School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea
| | - JongCheol Pyo
- Center for Environmental Data Strategy, Korea Environment Institute, Sejong 30147, Republic of Korea
| | - Daeho Kang
- Department of Environmental Engineering, Changwon National University, Changwondaehak-ro 20, Uichang-gu, Changwon-si, Gyeongsangnam-do 51140, Republic of Korea
| | - Kyung Hwa Cho
- School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea
| | - Junho Jeon
- Department of Environmental Engineering, Changwon National University, Changwondaehak-ro 20, Uichang-gu, Changwon-si, Gyeongsangnam-do 51140, Republic of Korea; School of Civil, Environmental and Chemical Engineering, Changwon National University, Changwon, Gyeongsangnamdo 51140, Republic of Korea.
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9
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Halder A, Anto A, Subramanyan V, Bhattacharyya M, Vishveshwara S, Vishveshwara S. Surveying the Side-Chain Network Approach to Protein Structure and Dynamics: The SARS-CoV-2 Spike Protein as an Illustrative Case. Front Mol Biosci 2020; 7:596945. [PMID: 33392257 PMCID: PMC7775578 DOI: 10.3389/fmolb.2020.596945] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Accepted: 11/04/2020] [Indexed: 02/04/2023] Open
Abstract
Network theory-based approaches provide valuable insights into the variations in global structural connectivity between different dynamical states of proteins. Our objective is to review network-based analyses to elucidate such variations, especially in the context of subtle conformational changes. We present technical details of the construction and analyses of protein structure networks, encompassing both the non-covalent connectivity and dynamics. We examine the selection of optimal criteria for connectivity based on the physical concept of percolation. We highlight the advantages of using side-chain-based network metrics in contrast to backbone measurements. As an illustrative example, we apply the described network approach to investigate the global conformational changes between the closed and partially open states of the SARS-CoV-2 spike protein. These conformational changes in the spike protein is crucial for coronavirus entry and fusion into human cells. Our analysis reveals global structural reorientations between the two states of the spike protein despite small changes between the two states at the backbone level. We also observe some differences at strategic locations in the structures, correlating with their functions, asserting the advantages of the side-chain network analysis. Finally, we present a view of allostery as a subtle synergistic-global change between the ligand and the receptor, the incorporation of which would enhance drug design strategies.
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Affiliation(s)
- Anushka Halder
- Department of Pharmacology, Yale University, New Haven, CT, United States
| | - Arinnia Anto
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India
| | - Varsha Subramanyan
- Department of Physics, University of Illinois at Urbana-Champaign, Champaign, IL, United States
| | | | - Smitha Vishveshwara
- Department of Physics, University of Illinois at Urbana-Champaign, Champaign, IL, United States
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10
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Kumar V, Hoag H, Sader S, Scorese N, Liu H, Wu C. GDP Release from the Open Conformation of Gα Requires Allosteric Signaling from the Agonist-Bound Human β 2 Adrenergic Receptor. J Chem Inf Model 2020; 60:4064-4075. [PMID: 32786510 DOI: 10.1021/acs.jcim.0c00432] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
G-protein-coupled receptors (GPCRs) transmit signals into the cell in response to ligand binding at its extracellular domain, which is characterized by the coupling of agonist-induced receptor conformational change to guanine nucleotide (GDP) exchange with guanosine triphosphate on a heterotrimeric (αβγ) guanine nucleotide-binding protein (G-protein), leading to the activation of the G-protein. The signal transduction mechanisms have been widely researched in vivo and in silico. However, coordinated communication from stimulating ligands to the bound GDP still remains elusive. In the present study, we used microsecond (μS) molecular dynamic (MD) simulations to directly probe the communication from the β2 adrenergic receptor (β2AR) with an agonist or an antagonist or no ligand to GDP bound to the open conformation of the Gα protein. Molecular mechanism-general Born surface area calculation results indicated either the agonist or the antagonist destabilized the binding between the receptor and the G-protein but the agonist caused a higher level of destabilization than the antagonist. This is consistent with the role of agonist in the activation of the G-protein. Interestingly, while GDP remained bound with the Gα-protein for the two inactive systems (antagonist-bound and apo form), GDP dissociated from the open conformation of the Gα protein for the agonist activated system. Data obtained from MD simulations indicated that the receptor and the Gα subunit play a big role in coordinated communication and nucleotide exchange. Based on residue interaction network analysis, we observed that engagement of agonist-bound β2AR with an α5 helix of Gα is essential for the GDP release and the residues in the phosphate-binding loop, α1 helix, and α5 helix play very important roles in the GDP release. The insights on GPCR-G-protein communication will facilitate the rational design of agonists and antagonists that target both active and inactive GPCR binding pockets, leading to more precise drugs.
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Affiliation(s)
- Vikash Kumar
- Complex Systems Division, Beijing Computational Science Research Center, Haidian district, Beijing 100193, China
| | - Hannah Hoag
- College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028, United States
| | - Safaa Sader
- College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028, United States
| | - Nicolas Scorese
- College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028, United States
| | - Haiguang Liu
- Complex Systems Division, Beijing Computational Science Research Center, Haidian district, Beijing 100193, China
| | - Chun Wu
- College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028, United States
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11
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Small Conformational Changes Underlie Evolution of Resistance to NNRTI in HIV Reverse Transcriptase. Biophys J 2020; 118:2489-2501. [PMID: 32348721 DOI: 10.1016/j.bpj.2020.04.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Revised: 02/12/2020] [Accepted: 04/06/2020] [Indexed: 11/23/2022] Open
Abstract
Despite achieving considerable success in reducing the number of fatalities due to acquired immunodeficiency syndrome, emergence of resistance against the reverse transcriptase (RT) inhibitor drugs remains one of the biggest challenges of the human immunodeficiency virus antiretroviral therapy (ART). Non-nucleoside reverse transcriptase inhibitors (NNRTIs) form a large class of drugs and a crucial component of ART. In NNRTIs, even a single resistance mutation is known to make the drugs completely ineffective. Additionally, several inhibitor-bound RTs with single resistance mutations do not exhibit any significant variations in their three-dimensional structures compared with the inhibitor-bound RT but completely nullify their inhibitory functions. This makes understanding the structural mechanism of these resistance mutations crucial for drug development. Here, we study several single resistance mutations in the allosteric inhibitor (nevirapine)-bound RT to analyze the mechanism of small structural changes leading to these large functional effects. In this study, we have shown that in absence of significant conformational variations in the inhibitor-bound wild-type RT and RT with single resistance mutations, the protein contact network analysis of their static structures, along with molecular dynamics simulations, can be a useful approach to understand the functional effect of small local conformational variations. The simple network analysis exposes the localized contact changes that lead to global rearrangement in the communication pattern within RT. Furthermore, these conformational changes have implications on the overall dynamics of RT. Using various measures, we show that a single resistance mutation can change the network structure and dynamics of RT to behave more like unbound RT, even in the presence of the inhibitor. This combined coarse-grained contact network and molecular dynamics approach promises to be a useful tool to analyze structure-function studies of proteins that show large functional changes with negligible variations in their overall conformation.
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12
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Sullivan HJ, Tursi A, Moore K, Campbell A, Floyd C, Wu C. Binding Interactions of Ergotamine and Dihydroergotamine to 5-Hydroxytryptamine Receptor 1B (5-HT 1b) Using Molecular Dynamics Simulations and Dynamic Network Analysis. J Chem Inf Model 2020; 60:1749-1765. [PMID: 32078320 DOI: 10.1021/acs.jcim.9b01082] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Ergotamine (ERG) and dihydroergotamine (DHE), common migraine drugs, have small structural differences but lead to clinically important distinctions in their pharmacological profiles. For example, DHE is less potent than ERG by about 10-fold at the 5-hydroxytrptamine receptor 1B (5-HT1B). Although the high-resolution crystal structures of the 5-HT1B receptor with both ligands have been solved, the high similarity between these two complex structures does not sufficiently explain their activity differences and the activation mechanism of the receptor. Hence, an examination of the dynamic motion of both drugs with the receptor is required. In this study, we ran a total of 6.0 μs molecular dynamics simulations on each system. Our simulation data show the subtle variations between the two systems in terms of the ligand-receptor interactions and receptor secondary structures. More importantly, the ligand and protein root-mean-square fluctuations (RMSFs) for the two systems were distinct, with ERG having a trend of lower RMSF values, indicating it to be bound tighter to 5-HT1B with less fluctuations. The molecular mechanism-general born surface area (MM-GBSA) binding energies illustrate this further, proving ERG has an overall stronger MM-GBSA binding energy. Analysis of several different microswitches has shown that the 5-HT1B-ERG complex is in a more active conformation state than 5-HT1B-DHE, which is further supported by the dynamic network model, with reference to mutagenesis data with the critical nodes and the first three low-energy modes from the normal mode analysis. We also identify Trp3276.48 and Phe3316.52 as key residues involved in the active state 5-HT1B for both ligands. Using the detailed dynamic information from our analysis, we made predictions for possible modifications to DHE and ERG that yielded five derivatives that might have more favorable binding energies and reduced structural fluctuations.
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Affiliation(s)
- Holli-Joi Sullivan
- College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028 United States
| | - Amanda Tursi
- College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028 United States
| | - Kelly Moore
- College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028 United States
| | - Alexandra Campbell
- College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028 United States
| | - Cecilia Floyd
- College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028 United States
| | - Chun Wu
- College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028 United States
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13
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Wahab HA, Amaro RE, Cournia Z. A Celebration of Women in Computational Chemistry. J Chem Inf Model 2019; 59:1683-1692. [DOI: 10.1021/acs.jcim.9b00368] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
| | - Rommie E. Amaro
- Department of Chemistry and Biochemistry, University of California, San Diego, 3234 Urey Hall, #0340, 9500 Gilman Drive, La Jolla, California 92093-0340, United States
| | - Zoe Cournia
- Biomedical Research Foundation, Academy of Athens, 11527 Athens, Greece
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