Optimization-based molecular dynamics studies of SARS-CoV-2 molecular structures : research on COVID- 19 / Jiapu Zhang.
Zhang, Jiapu, author.
2023
RA644.C67
Available Online

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Title Optimization-based molecular dynamics studies of SARS-CoV-2 molecular structures : research on COVID- 19 / Jiapu Zhang.
Author Zhang, Jiapu, author.
ISBN 9783031367731 (electronic bk.)
3031367731 (electronic bk.)
9783031367724
3031367723
DOI https://doi.org/10.1007/978-3-031-36773-1
Published Cham : Springer, [2023]
Copyright ©2023
Language English
Description 1 online resource (xx, 953 pages) : illustrations.
Item Number 10.1007/978-3-031-36773-1 doi
Call Number RA644.C67
Dewey Decimal Classification 616.2/414401
Summary COVID-19 has brought us extensive research databases in the fields of biophysics, biology, and bioinformatics. To extract valuable structural bioinformatic information of SARS-CoV-2 structural and nonstructural proteins, it is necessary to work with large-scale datasets of molecular dynamics (MD) trajectories that need to be optimized. This monograph serves as a comprehensive guide to optimization-based MD studies of the molecular structures of SARS-CoV-2 proteins and RNA. The book begins by performing local optimization, taking into account the three-body movement and optimizing the noncovalent bonds of each molecular structure. The optimized structures reach a transition state that offers the best stability and lowest energy. The optimization process utilizes a hybrid strategy that combines mathematical optimization with various local search algorithms. This approach significantly reduces data volume while eliminating irrelevant bioinformatics data. To gain a thorough understanding of molecular stability and the mechanism of action, it is essential to consider not only static NMR, X-ray, or cryo-EM structures but also dynamic information obtained through MD or Quantum Mechanics/Molecular Mechanics (QM/MM) simulations. These simulations capture the internal motions and dynamic processes of molecules. Furthermore, for each protein, the structural bioinformatics obtained from the optimized structure is validated by analyzing large-scale MD trajectory databases, which are openly and freely available online. The analysis includes key structural bioinformatics aspects such as salt bridge electrostatic interactions, hydrogen bonds, van der Waals interactions, and hydrophobic interactions specific to each SARS-CoV-2 molecular structure. The book also delves into discussions on drugs, vaccines, and the origins of the virus. Additionally, pandemic mathematical models, including those incorporating time delays, are explored. This book is particularly valuable for professionals working in practical computing roles within computational biochemistry, computational biophysics, optimization and molecular dynamics, structural bioinformatics, biological mathematics, and related fields. It serves as an accessible introduction to these disciplines and is also an excellent teaching resource for students.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed October 23, 2023).
Series Springer series in biophysics ; v. 23. 1868-2561
Available in Other Form Print version: 9783031367724
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1 Papain-Like cysteine protease (PLpro)
2 3C-Like protease (3CLpro)
3 RNA-dependent RNA polymerase (RdRp)
4 RNA-helicase
5 RNA-helicase binding with [RdRp, NSP7, NSP8a, NSP8b, pRNA, tRNA, ADP-Mg2+, ATP-Mg2+]
6 RNA-helicase binding with [ADP-Mg2+, ATP-Mg2+, and RNA]
7 Spike (S) glycoprotein
8 Spike (S) glycoprotein D614G mutant
9 Spike (S) glycoprotein N501Y mutant
10 Spike (S) glycoprotein N165A-and-N234A mutant
11 SARS (SARS-CoV-1)
12 MERS-coronavirus (MERS)
13 Human-ACE2, human-L6, human-L6R, human-nAChRs
14 PLpro binding with 12 compounds
15 3CLpro binding with N3/Lopinavir/Ritonavir
16 3CLpro dimer binding with 7 HIV-inhibitors and Others
17 Spike RBDs binding with 50 drugs
18 Human ACE2 ectodomain binding with 78 drugs
19 Spike-and-ACE2 binding with 100 drugs
20 Envelope protein (E-protein)
21 Membrane glycoprotein (M-protein)
22 Nucleocapsid phosphoprotein (N-protein)
23 SARS-CoV-2 RNA genome
24 NSP7, NSP8, NSP9, NSP10, NSP16, NSP14
25 NSP15
26 Other mutants
27 Vaccines and Drugs
28 Pandemic Mathematical Models, Epidemiology and Virus Origins
A Mathematical Optimization Algorithms and Free Energy Calculations
References
Index.

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