1
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Rosignoli S, di Paola L, Paiardini A. PyPCN: protein contact networks in PyMOL. Bioinformatics 2023; 39:btad675. [PMID: 37941462 PMCID: PMC10641099 DOI: 10.1093/bioinformatics/btad675] [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: 04/27/2023] [Revised: 09/25/2023] [Accepted: 11/03/2023] [Indexed: 11/10/2023] Open
Abstract
MOTIVATION Protein contact networks (PCNs) represent the 3D structure of a protein using network formalism. Inter-residue contacts are described as binary adjacency matrices, which are derived from the graph representation of residues (as α-carbons, β-carbons or centroids) and Euclidean distances according to defined thresholds. Functional characterization algorithms are computed on binary adjacency matrices to unveil allosteric, dynamic, and interaction mechanisms in proteins. Such strategies are usually applied in a combinatorial manner, although rarely in seamless and user-friendly implementations. RESULTS PyPCN is a plugin for PyMOL wrapping more than twenty PCN algorithms and metrics in an easy-to-use graphical user interface, to support PCN analysis. The plugin accepts 3D structures from the Protein Data Bank, user-provided PDBs, or precomputed adjacency matrices. The results are directly mapped to 3D protein structures and organized into interactive diagrams for their visualization. A dedicated graphical user interface combined with PyMOL visual support makes analysis more intuitive and easier, extending the applicability of PCNs. AVAILABILITY AND IMPLEMENTATION https://github.com/pcnproject/PyPCN.
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Affiliation(s)
- Serena Rosignoli
- Department of Biochemical Sciences “A. Rossi Fanelli”, Sapienza University of Rome, 00185 Rome, Italy
| | - Luisa di Paola
- Unit of Chemical-Physics Fundamentals in Chemical Engineering, Department of Engineering, Università Campus Bio-Medico di Roma, 00128 Rome, Italy
| | - Alessandro Paiardini
- Department of Biochemical Sciences “A. Rossi Fanelli”, Sapienza University of Rome, 00185 Rome, Italy
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2
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Dehury B, Mishra S, Pati S. Structural insights into SARS-CoV-2 main protease conformational plasticity. J Cell Biochem 2023. [PMID: 37099673 DOI: 10.1002/jcb.30409] [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: 02/17/2023] [Revised: 03/30/2023] [Accepted: 04/11/2023] [Indexed: 04/28/2023]
Abstract
The spread of different severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants underscores the need for insights into the structural properties of its structural and non-structural proteins. The highly conserved homo-dimeric chymotrypsin-like protease (3CL MPRO ), belonging to the class of cysteine hydrolases, plays an indispensable role in processing viral polyproteins that are involved in viral replication and transcription. Studies have successfully demonstrated the role of MPRO as an attractive drug target for designing antiviral treatments because of its importance in the viral life cycle. Herein, we report the structural dynamics of six experimentally solved structures of MPRO (i.e., 6LU7, 6M03, 6WQF, 6Y2E, 6Y84, and 7BUY including both ligand-free and ligand-bound states) at different resolutions. We have employed a structure-based balanced forcefield, CHARMM36m through state-of-the-art all-atoms molecular dynamics simulations at µ-seconds scale at room temperature (303K) and pH 7.0 to explore their structure-function relationship. The helical domain-III responsible for dimerization mostly contributes to the altered conformational states and destabilization of MPRO . A keen observation of the high degree of flexibility in the P5 binding pocket adjoining domain II-III highlights the reason for observation of conformational heterogeneity among the structural ensembles of MPRO . We also observe a differential dynamics of the catalytic pocket residues His41, Cys145, and Asp187, which may lead to catalytic impairment of the monomeric proteases. Among the highly populated conformational states of the six systems, 6LU7 and 7M03 forms the most stable and compact MPRO conformation with intact catalytic site and structural integrity. Altogether, our findings from this extensive study provides a benchmark to identify physiologically relevant structures of such promising drug targets for structure-based drug design and discovery of potent drug-like compounds having clinical potential.
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Affiliation(s)
- Budheswar Dehury
- Division of Bioinformatics, ICMR-Regional Medical Research Centre, Bhubaneswar, Odisha, India
| | - Sarbani Mishra
- Division of Bioinformatics, ICMR-Regional Medical Research Centre, Bhubaneswar, Odisha, India
| | - Sanghamitra Pati
- Division of Bioinformatics, ICMR-Regional Medical Research Centre, Bhubaneswar, Odisha, India
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3
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Rey Apostol Romal J, Kee Ong S. Extending the Library of 4‐Hydroxycoumarin Derivatives with Potential Pharmacological Activity by a Catalyst‐Free and Purification‐Free Method. ChemistrySelect 2023. [DOI: 10.1002/slct.202300519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/09/2023]
Affiliation(s)
- John Rey Apostol Romal
- Department of Chemistry Grand View University 1200 Grandview Ave Des Moines IA 50316 USA
- Department of Civil, Construction, and Environmental Engineering Iowa State University 813 Bissell Rd. Ames IA 50011 USA
| | - Say Kee Ong
- Department of Civil, Construction, and Environmental Engineering Iowa State University 813 Bissell Rd. Ames IA 50011 USA
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4
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Guzzi PH, di Paola L, Puccio B, Lomoio U, Giuliani A, Veltri P. Computational analysis of the sequence-structure relation in SARS-CoV-2 spike protein using protein contact networks. Sci Rep 2023; 13:2837. [PMID: 36808182 PMCID: PMC9936485 DOI: 10.1038/s41598-023-30052-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 02/15/2023] [Indexed: 02/19/2023] Open
Abstract
The structure of proteins impacts directly on the function they perform. Mutations in the primary sequence can provoke structural changes with consequent modification of functional properties. SARS-CoV-2 proteins have been extensively studied during the pandemic. This wide dataset, related to sequence and structure, has enabled joint sequence-structure analysis. In this work, we focus on the SARS-CoV-2 S (Spike) protein and the relations between sequence mutations and structure variations, in order to shed light on the structural changes stemming from the position of mutated amino acid residues in three different SARS-CoV-2 strains. We propose the use of protein contact network (PCN) formalism to: (i) obtain a global metric space and compare various molecular entities, (ii) give a structural explanation of the observed phenotype, and (iii) provide context dependent descriptors of single mutations. PCNs have been used to compare sequence and structure of the Alpha, Delta, and Omicron SARS-CoV-2 variants, and we found that omicron has a unique mutational pattern leading to different structural consequences from mutations of other strains. The non-random distribution of changes in network centrality along the chain has allowed to shed light on the structural (and functional) consequences of mutations.
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Affiliation(s)
- Pietro Hiram Guzzi
- Department of Surgical and Medical Sciences, Magna Graecia University of Catanzaro, Catanzaro, Italy.
| | - Luisa di Paola
- grid.9657.d0000 0004 1757 5329Unit of Chemical-Physics Fundamentals in Chemical Engineering, Department of Engineering, Universita Campus Bio-Medico di Roma, via Alvaro del Portillo 21, 00128 Rome, Italy
| | - Barbara Puccio
- grid.411489.10000 0001 2168 2547Department of Surgical and Medical Sciences, Magna Graecia University of Catanzaro, Catanzaro, Italy
| | - Ugo Lomoio
- grid.411489.10000 0001 2168 2547Department of Surgical and Medical Sciences, Magna Graecia University of Catanzaro, Catanzaro, Italy
| | - Alessandro Giuliani
- grid.416651.10000 0000 9120 6856Environment and Health Department, Istituto Superiore di Sanita, Rome, Italy
| | - Pierangelo Veltri
- grid.411489.10000 0001 2168 2547Department of Surgical and Medical Sciences, Magna Graecia University of Catanzaro, Catanzaro, Italy ,grid.7778.f0000 0004 1937 0319Department of Computer, Modeling, Electronics and System Engineering, University of Calabria, Rende, Italy
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5
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Banerjee A, Gosavi S. Potential Self-Peptide Inhibitors of the SARS-CoV-2 Main Protease. J Phys Chem B 2023; 127:855-865. [PMID: 36689738 PMCID: PMC9883841 DOI: 10.1021/acs.jpcb.2c05917] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 11/23/2022] [Indexed: 01/24/2023]
Abstract
The SARS-CoV-2 main protease (Mpro) plays an essential role in viral replication, cleaving viral polyproteins into functional proteins. This makes Mpro an important drug target. Mpro consists of an N-terminal catalytic domain and a C-terminal α-helical domain (MproC). Previous studies have shown that peptides derived from a given protein sequence (self-peptides) can affect the folding and, in turn, the function of that protein. Since the SARS-CoV-1 MproC is known to stabilize its Mpro and regulate its function, we hypothesized that SARS-CoV-2 MproC-derived self-peptides may modulate the folding and the function of SARS-CoV-2 Mpro. To test this, we studied the folding of MproC in the presence of various self-peptides using coarse-grained structure-based models and molecular dynamics simulations. In these simulations of MproC and one self-peptide, we found that two self-peptides, the α1-helix and the loop between α4 and α5 (loop4), could replace the equivalent native sequences in the MproC structure. Replacement of either sequence in full-length Mpro should, in principle, be able to perturb Mpro function albeit through different mechanisms. Some general principles for the rational design of self-peptide inhibitors emerge: The simulations show that prefolded self-peptides are more likely to replace native sequences than those which do not possess structure. Additionally, the α1-helix self-peptide is kinetically stable and once inserted rarely exchanges with the native α1-helix, while the loop4 self-peptide is easily replaced by the native loop4, making it less useful for modulating function. In summary, a prefolded α1-derived peptide should be able to inhibit SARS-CoV-2 Mpro function.
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Affiliation(s)
- Arkadeep Banerjee
- Simons Centre for the Study
of Living Machines, National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bengaluru 560065, India
| | - Shachi Gosavi
- Simons Centre for the Study
of Living Machines, National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bengaluru 560065, India
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6
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SARS-CoV-2 proteases Mpro and PLpro: Design of inhibitors with predicted high potency and low mammalian toxicity using artificial neural networks, ligand-protein docking, molecular dynamics simulations, and ADMET calculations. Comput Biol Med 2023; 153:106449. [PMID: 36586228 PMCID: PMC9788855 DOI: 10.1016/j.compbiomed.2022.106449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2022] [Revised: 11/28/2022] [Accepted: 12/19/2022] [Indexed: 12/25/2022]
Abstract
The main (Mpro) and papain-like (PLpro) proteases are highly conserved viral proteins essential for replication of the COVID-19 virus, SARS-COV-2. Therefore, a logical plan for producing new drugs against this pathogen is to discover inhibitors of these enzymes. Accordingly, the goal of the present work was to devise a computational approach to design, characterize, and select compounds predicted to be potent dual inhibitors - effective against both Mpro and PLpro. The first step employed LigDream, an artificial neural network, to create a virtual ligand library. Ligands with computed ADMET profiles indicating drug-like properties and low mammalian toxicity were selected for further study. Initial docking of these ligands into the active sites of Mpro and PLpro was done with GOLD, and the highest-scoring ligands were redocked with AutoDock Vina to determine binding free energies (ΔG). Compounds 89-00, 89-07, 89-32, and 89-38 exhibited favorable ΔG values for Mpro (-7.6 to -8.7 kcal/mol) and PLpro (-9.1 to -9.7 kcal/mol). Global docking of selected compounds with the Mpro dimer identified prospective allosteric inhibitors 89-00, 89-27, and 89-40 (ΔG -8.2 to -8.9 kcal/mol). Molecular dynamics simulations performed on Mpro and PLpro active site complexes with the four top-scoring ligands from Vina demonstrated that the most stable complexes were formed with compounds 89-32 and 89-38. Overall, the present computational strategy generated new compounds with predicted drug-like characteristics, low mammalian toxicity, and high inhibitory potencies against both target proteases to form stable complexes. Further preclinical studies will be required to validate the in silico findings before the lead compounds could be considered for clinical trials.
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7
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Bram Y, Duan X, Nilsson-Payant BE, Chandar V, Wu H, Shore D, Fajardo A, Sinha S, Hassan N, Weinstein H, TenOever BR, Chen S, Schwartz RE. Dual-Reporter System for Real-Time Monitoring of SARS-CoV-2 Main Protease Activity in Live Cells Enables Identification of an Allosteric Inhibition Path. ACS BIO & MED CHEM AU 2022; 2:627-641. [PMID: 36570071 PMCID: PMC9603010 DOI: 10.1021/acsbiomedchemau.2c00034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/29/2022] [Revised: 09/21/2022] [Accepted: 09/21/2022] [Indexed: 11/17/2022]
Abstract
The SARS-CoV-2 pandemic is an ongoing threat to global health, and the continuing emergence of contagious variants highlights the urgent need for additional antiviral therapy to attenuate COVID-19 disease. The SARS-CoV-2 main protease (3CLpro) presents an attractive target for such therapy due to its high sequence conservation and key role in the viral life cycle. In this study, we designed a fluorescent-luminescent cell-based reporter for the detection and quantification of 3CLpro intracellular activity. Employing this platform, we examined the efficiency of known protease inhibitors against 3CLpro and further identified potent inhibitors through high-throughput chemical screening. Computational analysis confirmed a direct interaction of the lead compounds with the protease catalytic site and identified a prototype for efficient allosteric inhibition. These developments address a pressing need for a convenient sensor and specific targets for both virus detection and rapid discovery of potential inhibitors.
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Affiliation(s)
- Yaron Bram
- Division
of Gastroenterology and Hepatology, Department of Medicine, Weill Cornell Medicine, 1300 York Avenue, New York, New York 10065, United States
| | - Xiaohua Duan
- Department
of Surgery, Weill Cornell Medicine, 1300 York Avenue, New York, New York 10065, United States
| | - Benjamin E. Nilsson-Payant
- Department
of Microbiology, Icahn School of Medicine
at Mount Sinai, One Gustav L Levy Place, New York, New York 10029, United
States
| | - Vasuretha Chandar
- Division
of Gastroenterology and Hepatology, Department of Medicine, Weill Cornell Medicine, 1300 York Avenue, New York, New York 10065, United States
| | - Hao Wu
- Department
of Physiology, Biophysics, Weill Cornell
Medicine, 1300 York Avenue, New York, New York 10065, United States
| | - Derek Shore
- Department
of Physiology, Biophysics, Weill Cornell
Medicine, 1300 York Avenue, New York, New York 10065, United States
| | - Alvaro Fajardo
- Division
of Gastroenterology and Hepatology, Department of Medicine, Weill Cornell Medicine, 1300 York Avenue, New York, New York 10065, United States
| | - Saloni Sinha
- Division
of Gastroenterology and Hepatology, Department of Medicine, Weill Cornell Medicine, 1300 York Avenue, New York, New York 10065, United States
| | - Nora Hassan
- Division
of Gastroenterology and Hepatology, Department of Medicine, Weill Cornell Medicine, 1300 York Avenue, New York, New York 10065, United States
| | - Harel Weinstein
- Department
of Physiology, Biophysics, Weill Cornell
Medicine, 1300 York Avenue, New York, New York 10065, United States,
| | - Benjamin R. TenOever
- Department
of Microbiology, Icahn School of Medicine
at Mount Sinai, One Gustav L Levy Place, New York, New York 10029, United
States,
| | - Shuibing Chen
- Department
of Surgery, Weill Cornell Medicine, 1300 York Avenue, New York, New York 10065, United States,
| | - Robert E. Schwartz
- Division
of Gastroenterology and Hepatology, Department of Medicine, Weill Cornell Medicine, 1300 York Avenue, New York, New York 10065, United States,Department
of Physiology, Biophysics, Weill Cornell
Medicine, 1300 York Avenue, New York, New York 10065, United States,
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8
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Wu Y, Zhang M, Yuan C, Ma Z, Li W, Zhang Y, Su L, Xu J, Liu W. Progress of cGAS-STING signaling in response to SARS-CoV-2 infection. Front Immunol 2022; 13:1010911. [PMID: 36569852 PMCID: PMC9767964 DOI: 10.3389/fimmu.2022.1010911] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 11/22/2022] [Indexed: 12/12/2022] Open
Abstract
Coronavirus disease 2019 (COVID-19) is an epidemic respiratory disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that can cause infections in millions of individuals, who can develop lung injury, organ failure, and subsequent death. As the first line of host defense, the innate immune system is involved in initiating the immune response to SARS-CoV-2 infection and the hyperinflammatory phenotype of COVID-19. However, the interplay between SARS-CoV-2 and host innate immunity is not yet well understood. It had become known that the cGAS-STING pathway is involved in the detection of cytosolic DNA, which elicits an innate immune response involving a robust type I interferon response against viral and bacterial infections. Nevertheless, several lines of evidence indicate that SARS-CoV-2, a single-stranded positive-sense RNA virus, triggered the cGAS-STING signaling pathway. Therefore, understanding the molecular and cellular details of cGAS-STING signaling upon SARS-CoV-2 infection is of considerable biomedical importance. In this review, we discuss the role of cGAS-STING signaling in SARS-CoV-2 infection and summarize the potential therapeutics of STING agonists as virus vaccine adjuvants.
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Affiliation(s)
- Yaru Wu
- College of Life Sciences, Henan Agricultural University, Zhengzhou, China
| | - Min Zhang
- College of Pharmacy, Henan University of Chinese Medicine, Zhengzhou, China
| | - Cui Yuan
- College of Life Sciences, Henan Agricultural University, Zhengzhou, China
| | - Zhenling Ma
- College of Life Sciences, Henan Agricultural University, Zhengzhou, China
| | - Wenqing Li
- College of Life Sciences, Henan Agricultural University, Zhengzhou, China
| | - Yanyan Zhang
- College of Life Sciences, Henan Agricultural University, Zhengzhou, China
| | - Lijuan Su
- College of Life Sciences, Henan Agricultural University, Zhengzhou, China
| | - Jun Xu
- College of Life Sciences, Henan Agricultural University, Zhengzhou, China
| | - Wei Liu
- College of Life Sciences, Henan Agricultural University, Zhengzhou, China,*Correspondence: Wei Liu,
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9
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Promising SARS-CoV-2 main protease inhibitor ligand-binding modes evaluated using LB-PaCS-MD/FMO. Sci Rep 2022; 12:17984. [PMID: 36289271 PMCID: PMC9606277 DOI: 10.1038/s41598-022-22703-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 10/18/2022] [Indexed: 01/24/2023] Open
Abstract
Parallel cascade selection molecular dynamics-based ligand binding-path sampling (LB-PaCS-MD) was combined with fragment molecular orbital (FMO) calculations to reveal the ligand path from an aqueous solution to the SARS-CoV-2 main protease (Mpro) active site and to customise a ligand-binding pocket suitable for delivering a potent inhibitor. Rubraxanthone exhibited mixed-inhibition antiviral activity against SARS-CoV-2 Mpro, relatively low cytotoxicity, and high cellular inhibition. However, the atomic inhibition mechanism remains ambiguous. LB-PaCS-MD/FMO is a hybrid ligand-binding evaluation method elucidating how rubraxanthone interacts with SARS-CoV-2 Mpro. In the first step, LB-PaCS-MD, which is regarded as a flexible docking, efficiently samples a set of ligand-binding pathways. After that, a reasonable docking pose of LB-PaCS-MD is evaluated by the FMO calculation to elucidate a set of protein-ligand interactions, enabling one to know the binding affinity of a specified ligand with respect to a target protein. A possible conformation was proposed for rubraxanthone binding to the SARS-CoV-2 Mpro active site, and allosteric inhibition was elucidated by combining blind docking with k-means clustering. The interaction profile, key binding residues, and considerable interaction were elucidated for rubraxanthone binding to both Mpro sites. Integrated LB-PaCS-MD/FMO provided a more reasonable complex structure for ligand binding at the SARS-CoV-2 Mpro active site, which is vital for discovering and designing antiviral drugs.
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10
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Strömich L, Wu N, Barahona M, Yaliraki SN. Allosteric Hotspots in the Main Protease of SARS-CoV-2. J Mol Biol 2022; 434:167748. [PMID: 35843284 PMCID: PMC9288249 DOI: 10.1016/j.jmb.2022.167748] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Revised: 06/30/2022] [Accepted: 07/11/2022] [Indexed: 02/06/2023]
Abstract
Inhibiting the main protease of SARS-CoV-2 is of great interest in tackling the COVID-19 pandemic caused by the virus. Most efforts have been centred on inhibiting the binding site of the enzyme. However, considering allosteric sites, distant from the active or orthosteric site, broadens the search space for drug candidates and confers the advantages of allosteric drug targeting. Here, we report the allosteric communication pathways in the main protease dimer by using two novel fully atomistic graph-theoretical methods: Bond-to-bond propensity, which has been previously successful in identifying allosteric sites in extensive benchmark data sets without a priori knowledge, and Markov transient analysis, which has previously aided in finding novel drug targets in catalytic protein families. Using statistical bootstrapping, we score the highest ranking sites against random sites at similar distances, and we identify four statistically significant putative allosteric sites as good candidates for alternative drug targeting.
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Affiliation(s)
- Léonie Strömich
- Department of Chemistry Imperial College London, United Kingdom
| | - Nan Wu
- Department of Chemistry Imperial College London, United Kingdom
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11
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Guzzi PH, Di Paola L, Giuliani A, Veltri P. PCN-Miner: an open-source extensible tool for the analysis of Protein Contact Networks. Bioinformatics 2022; 38:4235-4237. [PMID: 35799364 DOI: 10.1093/bioinformatics/btac450] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 06/14/2022] [Accepted: 07/04/2022] [Indexed: 12/24/2022] Open
Abstract
MOTIVATION Protein Contact Network (PCN) is a powerful method for analysing the structure and function of proteins, with a specific focus on disclosing the molecular features of allosteric regulation through the discovery of modular substructures. The importance of PCN analysis has been shown in many contexts, such as the analysis of SARS-CoV-2 Spike protein and its complexes with the Angiotensin Converting Enzyme 2 (ACE2) human receptors. Even if there exist many software tools implementing such methods, there is a growing need for the introduction of tools integrating existing approaches. RESULTS We present PCN-Miner, a software tool implemented in the Python programming language, able to (i) import protein structures from the Protein Data Bank; (ii) generate the corresponding PCN; (iii) model, analyse and visualize PCNs and related protein structures by using a set of known algorithms and metrics. The PCN-Miner can cover a large set of applications: from clustering to embedding and subsequent analysis. AVAILABILITY AND IMPLEMENTATION The PCN-Miner tool is freely available at the following GitHub repository: https://github.com/hguzzi/ProteinContactNetworks. It is also available in the Python Package Index (PyPI) repository.
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Affiliation(s)
- Pietro Hiram Guzzi
- Department of Surgical and Medical Sciences, Magna Graecia University of Catanzaro, 88100 Catanzaro, Italy
| | - Luisa Di Paola
- Unit of Chemical-Physics Fundamentals in Chemical Engineering, Department of Engineering, Università Campus Bio-Medico di Roma, 00128 Rome, Italy
| | - Alessandro Giuliani
- Environment and Health Department, Istituto Superiore di Sanità, 00161Rome, Italy
| | - Pierangelo Veltri
- Department of Surgical and Medical Sciences, Magna Graecia University of Catanzaro, 88100 Catanzaro, Italy
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12
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Alzyoud L, Ghattas MA, Atatreh N. Allosteric Binding Sites of the SARS-CoV-2 Main Protease: Potential Targets for Broad-Spectrum Anti-Coronavirus Agents. Drug Des Devel Ther 2022; 16:2463-2478. [PMID: 35941927 PMCID: PMC9356625 DOI: 10.2147/dddt.s370574] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 07/23/2022] [Indexed: 12/23/2022] Open
Abstract
The current pandemic caused by the COVID-19 disease has reached everywhere in the world and has affected every aspect of our lives. As of the current data, the World Health Organization (WHO) has reported more than 300 million confirmed COVID-19 cases worldwide and more than 5 million deaths. Mpro is an enzyme that plays a key role in the life cycle of the SARS-CoV-2 virus, and it is vital for the disease progression. The Mpro enzyme seems to have several allosteric sites that can hinder the enzyme catalytic activity. Furthermore, some of these allosteric sites are located at or nearby the dimerization interface which is essential for the overall Mpro activity. In this review paper, we investigate the potential of the Mpro allosteric site to act as a drug target, especially since they interestingly appear to be resistant to mutation. The work is illustrated through three subsequent sections: First, the two main categories of Mpro allosteric sites have been explained and discussed. Second, a total of six pockets have been studied and evaluated for their druggability and cavity characteristics. Third, the experimental and computational attempts for the discovery of new allosteric inhibitors have been illustrated and discussed. To sum up, this review paper gives a detailed insight into the feasibility of developing new Mpro inhibitors to act as a potential treatment for the COVID-19 disease.
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Affiliation(s)
- Lara Alzyoud
- College of Pharmacy, Al Ain University, Abu Dhabi, United Arab Emirates
| | - Mohammad A Ghattas
- College of Pharmacy, Al Ain University, Abu Dhabi, United Arab Emirates
- AAU Health and Biomedical Research Center, Al Ain University, Abu Dhabi, United Arab Emirates
- Correspondence: Mohammad A Ghattas; Noor Atatreh, Email ;
| | - Noor Atatreh
- College of Pharmacy, Al Ain University, Abu Dhabi, United Arab Emirates
- AAU Health and Biomedical Research Center, Al Ain University, Abu Dhabi, United Arab Emirates
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13
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Gao K, Wang R, Chen J, Cheng L, Frishcosy J, Huzumi Y, Qiu Y, Schluckbier T, Wei X, Wei GW. Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2. Chem Rev 2022; 122:11287-11368. [PMID: 35594413 PMCID: PMC9159519 DOI: 10.1021/acs.chemrev.1c00965] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.
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Affiliation(s)
- Kaifu Gao
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Rui Wang
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Jiahui Chen
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Limei Cheng
- Clinical
Pharmacology and Pharmacometrics, Bristol
Myers Squibb, Princeton, New Jersey 08536, United States
| | - Jaclyn Frishcosy
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Yuta Huzumi
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Yuchi Qiu
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Tom Schluckbier
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Xiaoqi Wei
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Guo-Wei Wei
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
- Department
of Electrical and Computer Engineering, Michigan State University, East Lansing, Michigan 48824, United States
- Department
of Biochemistry and Molecular Biology, Michigan
State University, East Lansing, Michigan 48824, United States
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14
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Dubanevics I, McLeish TCB. Optimising Elastic Network Models for Protein Dynamics and Allostery: Spatial and Modal Cut-offs and Backbone Stiffness. J Mol Biol 2022; 434:167696. [PMID: 35810792 DOI: 10.1016/j.jmb.2022.167696] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 06/16/2022] [Accepted: 06/19/2022] [Indexed: 01/15/2023]
Abstract
The family of coarse-grained models for protein dynamics known as Elastic Network Models (ENMs) require careful choice of parameters to represent well experimental measurements or fully-atomistic simulations. The most basic ENM that represents each protein residue by a node at the position of its C-alpha atom, all connected by springs of equal stiffness, up to a cut-off in distance. Even at this level a choice is required of the optimum cut-off distance and the upper limit of elastic normal modes taken in any sum for physical properties, such as dynamic correlation or allosteric effects on binding. Additionally, backbone-enhanced ENM (BENM) may improve the model by allocating a higher stiffness to springs that connect along the protein backbone. This work reports on the effect of varying these three parameters (distance and mode cutoffs, backbone stiffness) on the dynamical structure of three proteins, Catabolite Activator Protein (CAP), Glutathione S-transferase (GST), and the SARS-CoV-2 Main Protease (M pro ). Our main results are: (1) balancing B-factor and dispersion-relation predictions, a near-universal optimal value of 8.5 Å is advisable for ENMs; (2) inhomogeneity in elasticity brings the first mode containing spatial structure not well-resolved by the ENM typically within the first 20; (3) the BENM only affects modes in the upper third of the distribution, and, additionally to the ENM, is only able to model the dispersion curve better in this vicinity; (4) BENM does not typically affect fluctuation-allostery, which also requires careful treatment of the effector binding to the host protein to capture.
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15
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Allosteric Modulation of the Main Protease (MPro) of SARS-CoV-2 by Casticin—Insights from Molecular Dynamics Simulations. CHEMISTRY AFRICA 2022. [PMCID: PMC9261893 DOI: 10.1007/s42250-022-00411-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Inhibition of the main protease (Mpro) of SARS-CoV-2 has been suggested to be vital in shutting down viral replication in a host. Most efforts aimed at inhibiting MPro activity have been channeled into competitive inhibition at the active site, but this strategy will require a high inhibitor concentration and impressive inhibitor-MPro binding affinity. Allosteric inhibition can potentially serve as an effective strategy for alleviating these limitations. In this study, the ability of antiviral natural products to inhibit MPro in an allosteric fashion was explored with in silico techniques. Molecular docking revealed a strong interaction between casticin, an antiviral flavonoid, and Mpro at a site distant from the active site. This site, characterized as a distal site, has been shown to have an interdependent dynamic effect with the active site region. Mpro only, Mpro-peptide (binary) and Mpro-peptide-casticin (ternary) complexes were subjected to molecular dynamics simulations for 50 ns to investigate the modulatory activity of casticin binding on Mpro. Molecular dynamic simulations revealed that binding of casticin at the distal site interferes with the proper orientation of the peptide substrate in the oxyanion hole of the active site, and this could lead to a halt or decrease in catalytic activity. This study therefore highlights casticin as a potential allosteric modulator of the SARS-CoV-2 main protease, which could be optimized and developed into a potential lead compound for anti-SARS-CoV-2 chemotherapy.
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16
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Fagnani L, Nazzicone L, Bellio P, Franceschini N, Tondi D, Verri A, Petricca S, Iorio R, Amicosante G, Perilli M, Celenza G. Protocetraric and Salazinic Acids as Potential Inhibitors of SARS-CoV-2 3CL Protease: Biochemical, Cytotoxic, and Computational Characterization of Depsidones as Slow-Binding Inactivators. Pharmaceuticals (Basel) 2022; 15:ph15060714. [PMID: 35745633 PMCID: PMC9227325 DOI: 10.3390/ph15060714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 06/01/2022] [Accepted: 06/02/2022] [Indexed: 11/25/2022] Open
Abstract
The study investigated the inhibitory activity of protocetraric and salazinic acids against SARS-CoV-2 3CLpro. The kinetic parameters were determined by microtiter plate-reading fluorimeter using a fluorogenic substrate. The cytotoxic activity was tested on murine Sertoli TM4 cells. In silico analysis was performed to ascertain the nature of the binding with the 3CLpro. The compounds are slow-binding inactivators of 3CLpro with a Ki of 3.95 μM and 3.77 μM for protocetraric and salazinic acid, respectively, and inhibitory efficiency kinact/Ki at about 3 × 10−5 s−1µM−1. The mechanism of inhibition shows that both compounds act as competitive inhibitors with the formation of a stable covalent adduct. The viability assay on epithelial cells revealed that none of them shows cytotoxicity up to 80 μM, which is well below the Ki values. By molecular modelling, we predicted that the catalytic Cys145 makes a nucleophilic attack on the carbonyl carbon of the cyclic ester common to both inhibitors, forming a stably acyl-enzyme complex. The computational and kinetic analyses confirm the formation of a stable acyl-enzyme complex with 3CLpro. The results obtained enrich the knowledge of the already numerous biological activities exhibited by lichen secondary metabolites, paving the way for developing promising scaffolds for the design of cysteine enzyme inhibitors.
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Affiliation(s)
- Lorenza Fagnani
- Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, Via Vetoio 1, 67100 L’Aquila, Italy; (L.F.); (L.N.); (N.F.); (S.P.); (R.I.); (G.A.); (M.P.); (G.C.)
| | - Lisaurora Nazzicone
- Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, Via Vetoio 1, 67100 L’Aquila, Italy; (L.F.); (L.N.); (N.F.); (S.P.); (R.I.); (G.A.); (M.P.); (G.C.)
| | - Pierangelo Bellio
- Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, Via Vetoio 1, 67100 L’Aquila, Italy; (L.F.); (L.N.); (N.F.); (S.P.); (R.I.); (G.A.); (M.P.); (G.C.)
- Correspondence: (P.B.); (D.T.)
| | - Nicola Franceschini
- Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, Via Vetoio 1, 67100 L’Aquila, Italy; (L.F.); (L.N.); (N.F.); (S.P.); (R.I.); (G.A.); (M.P.); (G.C.)
| | - Donatella Tondi
- Department of Life Sciences, University of Modena and Reggio Emilia, Via Campi 103, 41125 Modena, Italy;
- Correspondence: (P.B.); (D.T.)
| | - Andrea Verri
- Department of Life Sciences, University of Modena and Reggio Emilia, Via Campi 103, 41125 Modena, Italy;
| | - Sabrina Petricca
- Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, Via Vetoio 1, 67100 L’Aquila, Italy; (L.F.); (L.N.); (N.F.); (S.P.); (R.I.); (G.A.); (M.P.); (G.C.)
| | - Roberto Iorio
- Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, Via Vetoio 1, 67100 L’Aquila, Italy; (L.F.); (L.N.); (N.F.); (S.P.); (R.I.); (G.A.); (M.P.); (G.C.)
| | - Gianfranco Amicosante
- Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, Via Vetoio 1, 67100 L’Aquila, Italy; (L.F.); (L.N.); (N.F.); (S.P.); (R.I.); (G.A.); (M.P.); (G.C.)
| | - Mariagrazia Perilli
- Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, Via Vetoio 1, 67100 L’Aquila, Italy; (L.F.); (L.N.); (N.F.); (S.P.); (R.I.); (G.A.); (M.P.); (G.C.)
| | - Giuseppe Celenza
- Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, Via Vetoio 1, 67100 L’Aquila, Italy; (L.F.); (L.N.); (N.F.); (S.P.); (R.I.); (G.A.); (M.P.); (G.C.)
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17
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Chen X, Leyendecker S, van den Bedem H. Kinematic Vibrational Entropy Assessment and Analysis of SARS CoV-2 Main Protease. J Chem Inf Model 2022; 62:2869-2879. [PMID: 35594568 DOI: 10.1021/acs.jcim.2c00126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The three-dimensional conformations of a protein influence its function and select for the ligands it can interact with. The total free energy change during protein-ligand complex formation includes enthalphic and entropic components, which together report on the binding affinity and conformational states of the complex. However, determining the entropic contribution is computationally burdensome. Here, we apply kinematic flexibility analysis (KFA) to efficiently estimate vibrational frequencies from static protein and protein-ligand structures. The vibrational frequencies, in turn, determine the vibrational entropies of the structures and their complexes. Our estimates of the vibrational entropy change caused by ligand binding compare favorably to values obtained from a dynamic Normal Mode Analysis (NMA). Higher correlation factors can be achieved by increasing the distance cutoff in the potential energy model. Furthermore, we apply our new method to analyze the entropy changes of the SARS CoV-2 main protease when binding with different ligand inhibitors, which is relevant for the design of potential drugs.
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Affiliation(s)
- Xiyu Chen
- Institute of Applied Dynamics, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany
| | - Sigrid Leyendecker
- Institute of Applied Dynamics, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany
| | - Henry van den Bedem
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, 94720 San Francisco, California, United States
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18
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Campitelli P, Lu J, Ozkan SB. Dynamic Allostery Highlights the Evolutionary Differences between the CoV-1 and CoV-2 Main Proteases. Biophys J 2022; 121:1483-1492. [PMID: 35300968 PMCID: PMC8920573 DOI: 10.1016/j.bpj.2022.03.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 12/28/2021] [Accepted: 03/08/2022] [Indexed: 11/02/2022] Open
Abstract
The SARS-CoV-2 coronavirus has become one of the most immediate and widely-studied systems since its identification and subsequent global outbreak from 2019-2021. In an effort to understand the biophysical changes as a result of mutations, the mechanistic details of multiple different proteins within the SARS-CoV-2 virus have been studied and compared with SARS-CoV-1. Focusing on the main protease (mPro), we first explored the long-range dynamics using the Dynamic Coupling Index (DCI) to investigate the dynamic coupling between the catalytic site residues and the rest of the protein, both inter and intra chain, for the CoV-1 and CoV-2 mPro. We found that there is significant cross-chain coupling between these active sites and specific distal residues in the CoV-2 mPro not present in CoV-1. The enhanced long distance interactions, particularly between the two chains, suggest subsequently enhanced cooperativity for CoV-2. A further comparative analysis of the dynamic flexibility using the Dynamic Flexibility Index (DFI) between the CoV-1 and CoV-2 mPros shows that the inhibitor binding near active sites induces change in flexibility to a distal region of the protein, opposite in behavior between the two systems; this region becomes more flexible upon inhibitor binding in CoV-1 while it becomes less flexible in the CoV-2 mPro. Upon inspection, we show that, on average, the dynamic flexibility of the sites substituted from CoV-1 to CoV-2 changes significantly less than the average calculated across all residues within the structure, indicating that the differences in behaviors between the two systems is likely the result of allosteric influence, where the new substitutions in CoV-2 induce flexibility and dynamical changes elsewhere in the structure.
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19
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Erman B. Gaussian network model revisited: Effects of mutation and ligand binding on protein behavior. Phys Biol 2022; 19. [PMID: 35105836 DOI: 10.1088/1478-3975/ac50ba] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Accepted: 02/01/2022] [Indexed: 11/12/2022]
Abstract
The coarse-grained Gaussian Network model, GNM, considers only the alpha carbons of the folded protein. Therefore it is not directly applicable to the study of mutation or ligand binding problems where atomic detail is required. This shortcoming is improved by including all atom pairs within the coordination shell of each other into the Kirchoff Adjacency Matrix. Counting all contacts rather than only alpha carbon contacts diminishes the magnitude of fluctuations in the system. But more importantly, it changes the graph-like connectivity structure, i.e., the Kirchoff Adjacency Matrix of the protein. This change depends on amino acid type which introduces amino acid specific and position specific information into the classical coarse-grained GNM which was originally modelled in analogy with the phantom network model of rubber elasticity. With this modification, it is now possible to explain the consequences of mutation and ligand binding on residue fluctuations, their pair-correlations and mutual information (MI) shared by each pair. We refer to the new model as 'all-atom GNM'. Using examples from published data we show that the all-atom GNM gives B-factors that are in better agreement with experiment, can explain effects of mutation on long range communication in PDZ domains and can predict effects of GDP and GTP binding on the dimerization of KRAS.
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Affiliation(s)
- Burak Erman
- Department of Chemical and Biological Engineering, Koc University, Rumeifeneri Yolu, Istanbul, Istanbul, 34450, TURKEY
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20
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González-Paz L, Hurtado-León ML, Lossada C, Fernández-Materán FV, Vera-Villalobos J, Loroño M, Paz JL, Jeffreys L, Alvarado YJ. Structural deformability induced in proteins of potential interest associated with COVID-19 by binding of homologues present in ivermectin: Comparative study based in elastic networks models. J Mol Liq 2021; 340:117284. [PMID: 34421159 PMCID: PMC8367659 DOI: 10.1016/j.molliq.2021.117284] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 08/10/2021] [Accepted: 08/12/2021] [Indexed: 12/24/2022]
Abstract
The COVID-19 pandemic has accelerated the study of the potential of multi-target drugs (MTDs). The mixture of homologues called ivermectin (avermectin-B1a + avermectin-B1b) has been shown to be a MTD with potential antiviral activity against SARS-CoV-2 in vitro. However, there are few reports on the effect of each homologue on the flexibility and stiffness of proteins associated with COVID-19, described as ivermectin targets. We observed that each homologue was stably bound to the proteins studied and was able to induce detectable changes with Elastic Network Models (ENM). The perturbations induced by each homologue were characteristic of each compound and, in turn, were represented by a disruption of native intramolecular networks (interactions between residues). The homologues were able to slightly modify the conformation and stability of the connection points between the Cα atoms of the residues that make up the structural network of proteins (nodes), compared to free proteins. Each homologue was able to modified differently the distribution of quasi-rigid regions of the proteins, which could theoretically alter their biological activities. These results could provide a biophysical-computational view of the potential MTD mechanism that has been reported for ivermectin.
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Affiliation(s)
- Lenin González-Paz
- Universidad del Zulia (LUZ), Facultad Experimental de Ciencias (FEC), Departamento de Biología. Laboratorio de Genética y Biología Molecular (LGBM), 4001 Maracaibo, Republica Bolivariana de Venezuela.,Instituto Venezolano de Investigaciones Científicas (IVIC), Centro de Estudios Botánicos y Agroforestales (CEBA), Laboratorio de Protección Vegetal (LPV), 4001 Maracaibo, Republica Bolivariana de Venezuela
| | - María Laura Hurtado-León
- Universidad del Zulia (LUZ), Facultad Experimental de Ciencias (FEC), Departamento de Biología. Laboratorio de Genética y Biología Molecular (LGBM), 4001 Maracaibo, Republica Bolivariana de Venezuela
| | - Carla Lossada
- Instituto Venezolano de Investigaciones Científicas (IVIC), Centro de Investigación y Tecnología de Materiales (CITeMA), Laboratorio de Caracterización Molecular y Biomolecular, 4001 Maracaibo, Republica Bolivariana de Venezuela
| | - Francelys V Fernández-Materán
- Instituto Venezolano de Investigaciones Científicas (IVIC), Centro de Investigación y Tecnología de Materiales (CITeMA), Laboratorio de Caracterización Molecular y Biomolecular, 4001 Maracaibo, Republica Bolivariana de Venezuela
| | - Joan Vera-Villalobos
- Facultad de Ciencias Naturales y Matemáticas, Departamento de Química y Ciencias Ambientales, Laboratorio de Análisis Químico Instrumental (LAQUINS), Escuela Superior Politécnica del Litoral, Guayaquil, Ecuador
| | - Marcos Loroño
- Departamento Académico de Química Analítica e Instrumental, Facultad de Química e Ingeniería Química, Universidad Nacional Mayor de San Marcos, Lima, Perú
| | - J L Paz
- Departamento Académico de Química Inorgánica, Facultad de Química e Ingeniería Química, Universidad Nacional Mayor de San Marcos, Lima, Perú
| | - Laura Jeffreys
- Liverpool School of Tropical Medicine, Pembroke Place, Liverpool L3 5QA, UK
| | - Ysaias J Alvarado
- Instituto Venezolano de Investigaciones Científicas (IVIC), Centro de Investigación y Tecnología de Materiales (CITeMA), Laboratorio de Caracterización Molecular y Biomolecular, 4001 Maracaibo, Republica Bolivariana de Venezuela
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21
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Panagiotopoulos AA, Karakasiliotis I, Kotzampasi DM, Dimitriou M, Sourvinos G, Kampa M, Pirintsos S, Castanas E, Daskalakis V. Natural Polyphenols Inhibit the Dimerization of the SARS-CoV-2 Main Protease: The Case of Fortunellin and Its Structural Analogs. Molecules 2021; 26:6068. [PMID: 34641612 PMCID: PMC8512273 DOI: 10.3390/molecules26196068] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 09/30/2021] [Accepted: 10/03/2021] [Indexed: 12/13/2022] Open
Abstract
3CL-Pro is the SARS-CoV-2 main protease (MPro). It acts as a homodimer to cleave the large polyprotein 1ab transcript into proteins that are necessary for viral growth and replication. 3CL-Pro has been one of the most studied SARS-CoV-2 proteins and a main target of therapeutics. A number of drug candidates have been reported, including natural products. Here, we employ elaborate computational methods to explore the dimerization of the 3CL-Pro protein, and we formulate a computational context to identify potential inhibitors of this process. We report that fortunellin (acacetin 7-O-neohesperidoside), a natural flavonoid O-glycoside, and its structural analogs are potent inhibitors of 3CL-Pro dimerization, inhibiting viral plaque formation in vitro. We thus propose a novel basis for the search of pharmaceuticals as well as dietary supplements in the fight against SARS-CoV-2 and COVID-19.
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Affiliation(s)
- Athanasios A. Panagiotopoulos
- Laboratory of Experimental Endocrinology, School of Medicine, University of Crete, 71003 Heraklion, Greece; (A.A.P.); (D.-M.K.); (M.K.)
| | - Ioannis Karakasiliotis
- Laboratory of Biology, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (I.K.); (M.D.)
| | - Danai-Maria Kotzampasi
- Laboratory of Experimental Endocrinology, School of Medicine, University of Crete, 71003 Heraklion, Greece; (A.A.P.); (D.-M.K.); (M.K.)
| | - Marios Dimitriou
- Laboratory of Biology, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (I.K.); (M.D.)
| | - George Sourvinos
- Laboratory of Virology, School of Medicine, University of Crete, 71003 Heraklion, Greece;
- Nature Crete Pharmaceuticals, 71305 Heraklion, Greece;
| | - Marilena Kampa
- Laboratory of Experimental Endocrinology, School of Medicine, University of Crete, 71003 Heraklion, Greece; (A.A.P.); (D.-M.K.); (M.K.)
- Nature Crete Pharmaceuticals, 71305 Heraklion, Greece;
| | - Stergios Pirintsos
- Nature Crete Pharmaceuticals, 71305 Heraklion, Greece;
- Department of Biology, University of Crete, 71409 Heraklion, Greece
- Botanical Garden, University of Crete, 74100 Rethymnon, Greece
| | - Elias Castanas
- Laboratory of Experimental Endocrinology, School of Medicine, University of Crete, 71003 Heraklion, Greece; (A.A.P.); (D.-M.K.); (M.K.)
- Nature Crete Pharmaceuticals, 71305 Heraklion, Greece;
| | - Vangelis Daskalakis
- Department of Chemical Engineering, Cyprus University of Technology, 3603 Limassol, Cyprus
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22
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Rehman MFU, Akhter S, Batool AI, Selamoglu Z, Sevindik M, Eman R, Mustaqeem M, Akram MS, Kanwal F, Lu C, Aslam M. Effectiveness of Natural Antioxidants against SARS-CoV-2? Insights from the In-Silico World. Antibiotics (Basel) 2021; 10:1011. [PMID: 34439061 PMCID: PMC8388999 DOI: 10.3390/antibiotics10081011] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Revised: 08/14/2021] [Accepted: 08/16/2021] [Indexed: 01/08/2023] Open
Abstract
The SARS CoV-2 pandemic has affected millions of people around the globe. Despite many efforts to find some effective medicines against SARS CoV-2, no established therapeutics are available yet. The use of phytochemicals as antiviral agents provides hope against the proliferation of SARS-CoV-2. Several natural compounds were analyzed by virtual screening against six SARS CoV-2 protein targets using molecular docking simulations in the present study. More than a hundred plant-derived secondary metabolites have been docked, including alkaloids, flavonoids, coumarins, and steroids. SARS CoV-2 protein targets include Main protease (MPro), Papain-like protease (PLpro), RNA-dependent RNA polymerase (RdRp), Spike glycoprotein (S), Helicase (Nsp13), and E-Channel protein. Phytochemicals were evaluated by molecular docking, and MD simulations were performed using the YASARA structure using a modified genetic algorithm and AMBER03 force field. Binding energies and dissociation constants allowed the identification of potentially active compounds. Ligand-protein interactions provide an insight into the mechanism and potential of identified compounds. Glycyrrhizin and its metabolite 18-β-glycyrrhetinic acid have shown a strong binding affinity for MPro, helicase, RdRp, spike, and E-channel proteins, while a flavonoid Baicalin also strongly binds against PLpro and RdRp. The use of identified phytochemicals may help to speed up the drug development and provide natural protection against SARS-CoV-2.
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Affiliation(s)
- Muhammad Fayyaz ur Rehman
- Department of Chemistry, Chemical Engineering and Biotechnology, Donghua University, Shanghai 201620, China
- Institute of Chemistry, University of Sargodha, Sargodha 41600, Pakistan; (S.A.); (R.E.)
| | - Shahzaib Akhter
- Institute of Chemistry, University of Sargodha, Sargodha 41600, Pakistan; (S.A.); (R.E.)
| | - Aima Iram Batool
- Department of Zoology, University of Sargodha, Sargodha 41600, Pakistan;
| | - Zeliha Selamoglu
- Department of Medical Biology, Faculty of Medicine, Nigde Omer Halisdemir University, Nigde 51240, Turkey;
| | - Mustafa Sevindik
- Department of Food Processing, Bahçe Vocational School, Osmaniye Korkut Ata University, Osmaniye 80000, Turkey;
| | - Rida Eman
- Institute of Chemistry, University of Sargodha, Sargodha 41600, Pakistan; (S.A.); (R.E.)
| | - Muhammad Mustaqeem
- Department of Chemistry, University of Sargodha, Bhakkar Campus, Bhakkar 30000, Pakistan;
| | - Muhammad Safwan Akram
- School of Health and Life Sciences, Teesside University, Middlesbrough TS1 3BA, UK;
- National Horizons Centre, Teesside University, Darlington DL1 1HG, UK
| | - Fariha Kanwal
- Med-X Research Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 201620, China;
| | - Changrui Lu
- Department of Chemistry, Chemical Engineering and Biotechnology, Donghua University, Shanghai 201620, China
| | - Mehwish Aslam
- School of Biological Sciences, University of the Punjab, Lahore 54600, Pakistan
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23
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Padhi AK, Rath SL, Tripathi T. Accelerating COVID-19 Research Using Molecular Dynamics Simulation. J Phys Chem B 2021; 125:9078-9091. [PMID: 34319118 PMCID: PMC8340580 DOI: 10.1021/acs.jpcb.1c04556] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 07/12/2021] [Indexed: 12/14/2022]
Abstract
The COVID-19 pandemic has emerged as a global medico-socio-economic disaster. Given the lack of effective therapeutics against SARS-CoV-2, scientists are racing to disseminate suggestions for rapidly deployable therapeutic options, including drug repurposing and repositioning strategies. Molecular dynamics (MD) simulations have provided the opportunity to make rational scientific breakthroughs in a time of crisis. Advancements in these technologies in recent years have become an indispensable tool for scientists studying protein structure, function, dynamics, interactions, and drug discovery. Integrating the structural data obtained from high-resolution methods with MD simulations has helped in comprehending the process of infection and pathogenesis, as well as the SARS-CoV-2 maturation in host cells, in a short duration of time. It has also guided us to identify and prioritize drug targets and new chemical entities, and to repurpose drugs. Here, we discuss how MD simulation has been explored by the scientific community to accelerate and guide translational research on SARS-CoV-2 in the past year. We have also considered future research directions for researchers, where MD simulations can help fill the existing gaps in COVID-19 research.
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Affiliation(s)
- Aditya K. Padhi
- Laboratory for Structural Bioinformatics, Center for
Biosystems Dynamics Research, RIKEN, 1-7-22 Suehiro, Tsurumi,
Yokohama, Kanagawa 230-0045, Japan
| | - Soumya Lipsa Rath
- Department of Biotechnology, National
Institute of Technology, Warangal, Telangana 506004,
India
| | - Timir Tripathi
- Molecular and Structural Biophysics Laboratory,
Department of Biochemistry, North-Eastern Hill University,
Shillong 793022, India
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24
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Sztain T, Amaro R, McCammon JA. Elucidation of Cryptic and Allosteric Pockets within the SARS-CoV-2 Main Protease. J Chem Inf Model 2021; 61:3495-3501. [PMID: 33939913 PMCID: PMC8117783 DOI: 10.1021/acs.jcim.1c00140] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Indexed: 01/09/2023]
Abstract
The SARS-CoV-2 pandemic has rapidly spread across the globe, posing an urgent health concern. Many quests to computationally identify treatments against the virus rely on in silico small molecule docking to experimentally determined structures of viral proteins. One limit to these approaches is that protein dynamics are often unaccounted for, leading to overlooking transient, druggable conformational states. Using Gaussian accelerated molecular dynamics to enhance sampling of conformational space, we identified cryptic pockets within the SARS-CoV-2 main protease, including some within regions far from the active site. These simulations sampled comparable dynamics and pocket volumes to conventional brute force simulations carried out on two orders of magnitude greater timescales.
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Affiliation(s)
| | - Rommie Amaro
- Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, California 92093, United States
| | - J. Andrew McCammon
- Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, California 92093, United States
- Department of Pharmacology, University of California, San Diego, La Jolla, California 92093, United States
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25
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Cho E, Rosa M, Anjum R, Mehmood S, Soban M, Mujtaba M, Bux K, Moin ST, Tanweer M, Dantu S, Pandini A, Yin J, Ma H, Ramanathan A, Islam B, Mey ASJ, Bhowmik D, Haider S. Dynamic Profiling of β-Coronavirus 3CL M pro Protease Ligand-Binding Sites. J Chem Inf Model 2021; 61:3058-3073. [PMID: 34124899 PMCID: PMC8230960 DOI: 10.1021/acs.jcim.1c00449] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Indexed: 01/11/2023]
Abstract
β-coronavirus (CoVs) alone has been responsible for three major global outbreaks in the 21st century. The current crisis has led to an urgent requirement to develop therapeutics. Even though a number of vaccines are available, alternative strategies targeting essential viral components are required as a backup against the emergence of lethal viral variants. One such target is the main protease (Mpro) that plays an indispensable role in viral replication. The availability of over 270 Mpro X-ray structures in complex with inhibitors provides unique insights into ligand-protein interactions. Herein, we provide a comprehensive comparison of all nonredundant ligand-binding sites available for SARS-CoV2, SARS-CoV, and MERS-CoV Mpro. Extensive adaptive sampling has been used to investigate structural conservation of ligand-binding sites using Markov state models (MSMs) and compare conformational dynamics employing convolutional variational auto-encoder-based deep learning. Our results indicate that not all ligand-binding sites are dynamically conserved despite high sequence and structural conservation across β-CoV homologs. This highlights the complexity in targeting all three Mpro enzymes with a single pan inhibitor.
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Affiliation(s)
- Eunice Cho
- UCL
School of Pharmacy, London WC1N 1AX, U.K.
| | | | - Ruhi Anjum
- Department
of Biochemistry, Aligarh Muslim University, Aligarh, Uttar Pradesh 202002, India
| | - Saman Mehmood
- Department
of Zoology, Aligarh Muslim University, Aligarh, Uttar Pradesh 202002, India
| | - Mariya Soban
- Department
of Biochemistry, Aligarh Muslim University, Aligarh, Uttar Pradesh 202002, India
| | - Moniza Mujtaba
- Herricks
High School, New Hyde
Park, New York 11040 United States
| | - Khair Bux
- Third
World Center for Science and Technology, H.E.J. Research Institute
of Chemistry, International Centre of Chemical and Biological Sciences, University of Karachi, Karachi 75270 Pakistan
| | - Syed T. Moin
- Third
World Center for Science and Technology, H.E.J. Research Institute
of Chemistry, International Centre of Chemical and Biological Sciences, University of Karachi, Karachi 75270 Pakistan
| | | | - Sarath Dantu
- Department
of Computer Science, Brunel University, Uxbridge UB8 3PH, U.K.
| | - Alessandro Pandini
- Department
of Computer Science, Brunel University, Uxbridge UB8 3PH, U.K.
| | - Junqi Yin
- Center
for Computational Sciences, Oak Ridge National
Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Heng Ma
- Data
Science and Learning Division, Argonne National
Laboratory, Lemont, Illinois 60439, United States
| | - Arvind Ramanathan
- Data
Science and Learning Division, Argonne National
Laboratory, Lemont, Illinois 60439, United States
- Consortium
for Advanced Science and Engineering, University
of Chicago, Chicago, Illinois 60637, United
States
| | - Barira Islam
- Department
of Bioscience, University of Huddersfield, Huddersfield HD1 3DH, U.K.
| | - Antonia S. J.
S. Mey
- EaStCHEM
School of Chemistry, University of Edinburgh, David Brewster Road, Edinburgh EH9 3FJ, U.K.
| | - Debsindhu Bhowmik
- Computer
Sciences and Engineering Division, Oak Ridge
National Laboratory, Oak Ridge, Tennessee 37830, United States
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26
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Weng YL, Naik SR, Dingelstad N, Lugo MR, Kalyaanamoorthy S, Ganesan A. Molecular dynamics and in silico mutagenesis on the reversible inhibitor-bound SARS-CoV-2 main protease complexes reveal the role of lateral pocket in enhancing the ligand affinity. Sci Rep 2021; 11:7429. [PMID: 33795718 PMCID: PMC8016996 DOI: 10.1038/s41598-021-86471-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2020] [Accepted: 03/09/2021] [Indexed: 02/08/2023] Open
Abstract
The 2019 novel coronavirus pandemic caused by SARS-CoV-2 remains a serious health threat to humans and there is an urgent need to develop therapeutics against this deadly virus. Recent scientific evidences have suggested that the main protease (Mpro) enzyme in SARS-CoV-2 can be an ideal drug target due to its crucial role in the viral replication and transcription processes. Therefore, there are ongoing research efforts to identify drug candidates against SARS-CoV-2 Mpro that resulted in hundreds of X-ray crystal structures of ligand-bound Mpro complexes in the Protein Data Bank (PDB) describing the interactions of different fragment chemotypes within different sites of the Mpro. In this work, we performed rigorous molecular dynamics (MD) simulation of 62 reversible ligand-Mpro complexes in the PDB to gain mechanistic insights about their interactions at the atomic level. Using a total of over 3 µs long MD trajectories, we characterized different pockets in the apo Mpro structure, and analyzed the dynamic interactions and binding affinity of ligands within those pockets. Our results identified the key residues that stabilize the ligands in the catalytic sites and other pockets of Mpro. Our analyses unraveled the role of a lateral pocket in the catalytic site in Mpro that is critical for enhancing the ligand binding to the enzyme. We also highlighted the important contribution from HIS163 in the lateral pocket towards ligand binding and affinity against Mpro through computational mutation analyses. Further, we revealed the effects of explicit water molecules and Mpro dimerization in the ligand association with the target. Thus, comprehensive molecular-level insights gained from this work can be useful to identify or design potent small molecule inhibitors against SARS-CoV-2 Mpro.
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Affiliation(s)
- Ying Li Weng
- ArGan's Lab, School of Pharmacy, Faculty of Science, University of Waterloo, Waterloo, ON, Canada
| | - Shiv Rakesh Naik
- ArGan's Lab, School of Pharmacy, Faculty of Science, University of Waterloo, Waterloo, ON, Canada
| | - Nadia Dingelstad
- ArGan's Lab, School of Pharmacy, Faculty of Science, University of Waterloo, Waterloo, ON, Canada
| | - Miguel R Lugo
- ArGan's Lab, School of Pharmacy, Faculty of Science, University of Waterloo, Waterloo, ON, Canada
- Department of Chemistry, Faculty of Science, University of Waterloo, Waterloo, ON, Canada
| | - Subha Kalyaanamoorthy
- Department of Chemistry, Faculty of Science, University of Waterloo, Waterloo, ON, Canada
| | - Aravindhan Ganesan
- ArGan's Lab, School of Pharmacy, Faculty of Science, University of Waterloo, Waterloo, ON, Canada.
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27
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Waman VP, Sen N, Varadi M, Daina A, Wodak SJ, Zoete V, Velankar S, Orengo C. The impact of structural bioinformatics tools and resources on SARS-CoV-2 research and therapeutic strategies. Brief Bioinform 2021; 22:742-768. [PMID: 33348379 PMCID: PMC7799268 DOI: 10.1093/bib/bbaa362] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 11/06/2020] [Accepted: 11/09/2020] [Indexed: 01/18/2023] Open
Abstract
SARS-CoV-2 is the causative agent of COVID-19, the ongoing global pandemic. It has posed a worldwide challenge to human health as no effective treatment is currently available to combat the disease. Its severity has led to unprecedented collaborative initiatives for therapeutic solutions against COVID-19. Studies resorting to structure-based drug design for COVID-19 are plethoric and show good promise. Structural biology provides key insights into 3D structures, critical residues/mutations in SARS-CoV-2 proteins, implicated in infectivity, molecular recognition and susceptibility to a broad range of host species. The detailed understanding of viral proteins and their complexes with host receptors and candidate epitope/lead compounds is the key to developing a structure-guided therapeutic design. Since the discovery of SARS-CoV-2, several structures of its proteins have been determined experimentally at an unprecedented speed and deposited in the Protein Data Bank. Further, specialized structural bioinformatics tools and resources have been developed for theoretical models, data on protein dynamics from computer simulations, impact of variants/mutations and molecular therapeutics. Here, we provide an overview of ongoing efforts on developing structural bioinformatics tools and resources for COVID-19 research. We also discuss the impact of these resources and structure-based studies, to understand various aspects of SARS-CoV-2 infection and therapeutic development. These include (i) understanding differences between SARS-CoV-2 and SARS-CoV, leading to increased infectivity of SARS-CoV-2, (ii) deciphering key residues in the SARS-CoV-2 involved in receptor-antibody recognition, (iii) analysis of variants in host proteins that affect host susceptibility to infection and (iv) analyses facilitating structure-based drug and vaccine design against SARS-CoV-2.
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Affiliation(s)
| | | | | | - Antoine Daina
- Molecular Modeling Group at SIB, Swiss Institute of Bioinformatics
| | | | - Vincent Zoete
- Department of Fundamental Oncology at the University of Lausanne and Group leader at SIB
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28
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Tekpinar M, Yildirim A. Impact of dimerization and N3 binding on molecular dynamics of SARS-CoV and SARS-CoV-2 main proteases. J Biomol Struct Dyn 2021; 40:6243-6254. [PMID: 33525993 PMCID: PMC7869440 DOI: 10.1080/07391102.2021.1880481] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
SARS-CoV-2 main protease is one of the major targets in drug development efforts against Covid-19. Even though several structures were reported to date, its dynamics is not understood well. In particular, impact of dimerization and ligand binding on the dynamics is an important issue to investigate. In this study, we performed molecular dynamics simulations of SARS-CoV and SARS-CoV-2 main proteases to investigate influence of dimerization on the dynamics by modeling monomeric and dimeric apo and holo forms. The dimerization causes an organization of the interdomain dynamics as well as some local structural changes. Moreover, we investigated impact of a peptide mimetic (N3) on the dynamics of SARS-CoV and SARS-CoV-2 Mpro. The ligand binding to the dimeric forms causes some key local changes at the dimer interface and it causes an allosteric interaction between the active sites of two protomers. Our results support the idea that only one protomer is active on SARS-CoV-2 due to this allosteric interaction. Additionally, we analyzed the molecular dynamics trajectories from graph theoretical perspective and found that the most influential residues – as measured by eigenvector centrality – are a group of residues in active site and dimeric interface of the protease. This study may form a bridge between what we know about the dynamics of SARS-CoV and SARS-CoV-2 Mpro. We think that enlightening allosteric communication of the active sites and the role of dimerization in SARS-CoV-2 Mpro can contribute to development of novel drugs against this global health problem as well as other similar proteases. Communicated by Ramaswamy H. Sarma
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Affiliation(s)
- Mustafa Tekpinar
- Unit of Structural Dynamics of Biological Macromolecules, Pasteur Institute, UMR 3528 CNRS, Paris, France
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29
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Bellomo N, Bingham R, Chaplain MAJ, Dosi G, Forni G, Knopoff DA, Lowengrub J, Twarock R, Virgillito ME. A multiscale model of virus pandemic: Heterogeneous interactive entities in a globally connected world. MATHEMATICAL MODELS & METHODS IN APPLIED SCIENCES : M3AS 2020; 30:1591-1651. [PMID: 35309741 PMCID: PMC8932953 DOI: 10.1142/s0218202520500323] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
This paper is devoted to the multidisciplinary modelling of a pandemic initiated by an aggressive virus, specifically the so-called SARS-CoV-2 Severe Acute Respiratory Syndrome, corona virus n.2. The study is developed within a multiscale framework accounting for the interaction of different spatial scales, from the small scale of the virus itself and cells, to the large scale of individuals and further up to the collective behaviour of populations. An interdisciplinary vision is developed thanks to the contributions of epidemiologists, immunologists and economists as well as those of mathematical modellers. The first part of the contents is devoted to understanding the complex features of the system and to the design of a modelling rationale. The modelling approach is treated in the second part of the paper by showing both how the virus propagates into infected individuals, successfully and not successfully recovered, and also the spatial patterns, which are subsequently studied by kinetic and lattice models. The third part reports the contribution of research in the fields of virology, epidemiology, immune competition, and economy focussed also on social behaviours. Finally, a critical analysis is proposed looking ahead to research perspectives.
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Affiliation(s)
- Nicola Bellomo
- Departamento de Matemática Aplicada, University of Granada, Spain
- IMATI CNR, Pavia, Italy, and Politecnico of Torino, Italy
| | - Richard Bingham
- Departments of Mathematics and Biology, York Cross-disciplinary Centre for Systems Analysis, University of York, UK
| | - Mark A. J. Chaplain
- Mathematical Institute, School of Mathematics and Statistics, University of St Andrews, St Andrews KY16 9SS, Scotland, UK
| | - Giovanni Dosi
- Institute of Economics and EMbeDS, Scuola Superiore Sant’Anna, Piazza Martiri della Libertà 33, I-56127, Pisa, Italy
| | | | - Damian A. Knopoff
- Centro de Investigacion y Estudios de Matematica (CONICET) and Famaf (UNC), Medina Allende s/n, 5000, Cordoba, Argentina
| | | | - Reidun Twarock
- Departments of Mathematics and Biology, York Cross-disciplinary Centre for Systems Analysis, University of York, UK
| | - Maria Enrica Virgillito
- Institute of Economics and EMbeDS, Scuola Superiore Sant’Anna, Piazza Martiri della Libertà 33, I-56127, Pisa, Italy
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