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Chinnamadhu A, Ramakrishnan J, Suresh S, Ramadurai P, Poomani K. Dynamics and binding affinity of nucleoside and non-nucleoside inhibitors with RdRp of SARS-CoV-2: a molecular screening, docking, and molecular dynamics simulation study. J Biomol Struct Dyn 2023; 41:10396-10410. [PMID: 36510678 DOI: 10.1080/07391102.2022.2154844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Accepted: 11/29/2022] [Indexed: 12/15/2022]
Abstract
In this COVID-19 pandemic situation, an appropriate drug is urgent to fight against this infectious disease to save lives and prevent mortality. Repurposed drugs and vaccines are the immediate solutions for this medical emergency until discover a new drug to treat this disease. As of now, no specific drug is available to cure this disease completely. Several drug targets were identified in SARS-CoV-2, in which RdRp protein is one of the potential targets to inhibit this virus infection. In-Silico studies plays a vital role to understand the binding nature of the drugs at the atomic level against the disease targets. The present study explores the binding mechanism of reported 53 nucleoside and non-nucleoside RdRp inhibitors and Ivermectin which are in clinical trials. These molecules were screened by molecular docking simulation; in which, the molecules are showing high binding affinity and forming interactions with the key amino acids of active site of RdRp protein are chosen for molecular dynamics simulation (MD) and binding free energy analysis. The results of molecular docking and MD simulation studies reveal that IDX184 is a stable molecule and forms strong interactions with the key amino acids and shows high binding affinity towards RdRp. Hence, IDX184 may also be considered as a potential inhibitor of RdRp after clinical study.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Archana Chinnamadhu
- Laboratory of Biocrystallography and Computational Molecular Biology, Department of Physics, Periyar University, Salem-636011, India
| | - Jaganathan Ramakrishnan
- Laboratory of Biocrystallography and Computational Molecular Biology, Department of Physics, Periyar University, Salem-636011, India
| | - Suganya Suresh
- Laboratory of Biocrystallography and Computational Molecular Biology, Department of Physics, Periyar University, Salem-636011, India
| | - Prakash Ramadurai
- Laboratory of Biocrystallography and Computational Molecular Biology, Department of Physics, Periyar University, Salem-636011, India
| | - Kumaradhas Poomani
- Laboratory of Biocrystallography and Computational Molecular Biology, Department of Physics, Periyar University, Salem-636011, India
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Kumari D, Ranjan P, Chakraborty T. A computational study of potential therapeutics for COVID-19 invoking conceptual density functional theory. Struct Chem 2022; 33:2195-2204. [PMID: 36097582 PMCID: PMC9452875 DOI: 10.1007/s11224-022-02048-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 08/28/2022] [Indexed: 01/18/2023]
Abstract
The pandemic, COVID-19, has caused social and economic disruption at a larger pace all over the world. Identification of an effective drug for the deadliest disease is still an exigency. One of the most promising approaches to combat the lethal disease is use of repurposed drugs. This study provides insights into some of the potential repurposed drugs viz. camostat mesylate, hydroxychloroquine, nitazoxanide, and oseltamivir in terms of the computational quantum chemical method. Properties of these compounds have been elucidated in terms of Conceptual Density Functional Theory (CDFT)-based descriptors, IR spectra, and thermochemical properties. Computed results specify that hydroxychloroquine is the most reactive drug among them. Thermochemical data reveals that camostat mesylate has the utmost heat capacity, entropy, and thermal energy. Our findings indicate that camostat mesylate and hydroxychloroquine may be investigated further as potential COVID-19 therapeutics. We anticipate that the current study will aid the scientific community to design and develop viable therapeutics against COVID-19.
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Affiliation(s)
- Dimple Kumari
- Department of Chemistry and Biochemistry, School of Basic Sciences and Research, Sharda University, 201310, Greater Noida, UP India
| | - Prabhat Ranjan
- Department of Mechatronics Engineering, Manipal University Jaipur, Dehmi Kalan-303007, Rajasthan, India
| | - Tanmoy Chakraborty
- Department of Chemistry and Biochemistry, School of Basic Sciences and Research, Sharda University, 201310, Greater Noida, UP India
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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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Pramanik D, Pawar AB, Roy S, Singh JK. Mechanistic insights of key host proteins and potential repurposed inhibitors regulating SARS-CoV-2 pathway. J Comput Chem 2022; 43:1237-1250. [PMID: 35535951 PMCID: PMC9348233 DOI: 10.1002/jcc.26888] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Revised: 04/03/2022] [Accepted: 04/22/2022] [Indexed: 12/16/2022]
Abstract
The emergence of pandemic situations originated from severe acute respiratory syndrome (SARS)‐CoV‐2 and its new variants created worldwide medical emergencies. Due to the non‐availability of efficient drugs and vaccines at these emergency hours, repurposing existing drugs can effectively treat patients critically infected by SARS‐CoV‐2. Finding a suitable repurposing drug with inhibitory efficacy to a host‐protein is challenging. A detailed mechanistic understanding of the kinetics, (dis)association pathways, key protein residues facilitating the entry–exit of the drugs with targets are fundamental in selecting these repurposed drugs. Keeping this target as the goal of the paper, the potential repurposing drugs, Nafamostat, Camostat, Silmitasertib, Valproic acid, and Zotatifin with host‐proteins HDAC2, CSK22, eIF4E2 are studied to elucidate energetics, kinetics, and dissociation pathways. From an ensemble of independent simulations, we observed the presence of single or multiple dissociation pathways with varying host‐proteins‐drug systems and quantitatively estimated the probability of unbinding through these specific pathways. We also explored the crucial gateway residues facilitating these dissociation mechanisms. Interestingly, the residues we obtained for HDAC2 and CSK22 are also involved in the catalytic activity. Our results demonstrate how these potential drugs interact with the host machinery and the specific target residues, showing involvement in the mechanism. Most of these drugs are in the preclinical phase, and some are already being used to treat severe COVID‐19 patients. Hence, the mechanistic insight presented in this study is envisaged to support further findings of clinical studies and eventually develop efficient inhibitors to treat SARS‐CoV‐2.
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Affiliation(s)
- Debabrata Pramanik
- Department of Chemical Engineering, Indian Institute of Technology Kanpur, Kanpur, India
| | | | - Sudip Roy
- Prescience Insilico Private Limited, Bangalore, India
| | - Jayant Kumar Singh
- Department of Chemical Engineering, Indian Institute of Technology Kanpur, Kanpur, India.,Prescience Insilico Private Limited, Bangalore, India
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