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001482580 019__ $$a1404446050
001482580 020__ $$a9783031367731$$q(electronic bk.)
001482580 020__ $$a3031367731$$q(electronic bk.)
001482580 020__ $$z9783031367724
001482580 020__ $$z3031367723
001482580 0247_ $$a10.1007/978-3-031-36773-1$$2doi
001482580 035__ $$aSP(OCoLC)1405816882
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001482580 050_4 $$aRA644.C67
001482580 08204 $$a616.2/414401$$223/eng/20231023
001482580 1001_ $$aZhang, Jiapu,$$eauthor.
001482580 24510 $$aOptimization-based molecular dynamics studies of SARS-CoV-2 molecular structures :$$bresearch on COVID- 19 /$$cJiapu Zhang.
001482580 264_1 $$aCham :$$bSpringer,$$c[2023]
001482580 264_4 $$c©2023
001482580 300__ $$a1 online resource (xx, 953 pages) :$$billustrations.
001482580 336__ $$atext$$btxt$$2rdacontent
001482580 337__ $$acomputer$$bc$$2rdamedia
001482580 338__ $$aonline resource$$bcr$$2rdacarrier
001482580 4901_ $$aSpringer series in biophysics,$$x1868-2561 ;$$vvolume 23
001482580 504__ $$aIncludes bibliographical references and index.
001482580 5050_ $$a1 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.
001482580 506__ $$aAccess limited to authorized users.
001482580 520__ $$aCOVID-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.
001482580 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed October 23, 2023).
001482580 650_6 $$aCOVID-19$$xAspect moléculaire.
001482580 650_6 $$aStructure moléculaire.
001482580 650_6 $$aDynamique moléculaire.
001482580 650_0 $$aCOVID-19 (Disease)$$xMolecular aspects.
001482580 650_0 $$aMolecular structure.$$0(DLC)sh 85086594
001482580 650_0 $$aMolecular dynamics.
001482580 655_0 $$aElectronic books.
001482580 77608 $$iPrint version: $$z3031367723$$z9783031367724$$w(OCoLC)1381294171
001482580 830_0 $$aSpringer series in biophysics ;$$vv. 23.$$x1868-2561
001482580 852__ $$bebk
001482580 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-36773-1$$zOnline Access$$91397441.1
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001482580 980__ $$aEBOOK
001482580 982__ $$aEbook
001482580 983__ $$aOnline
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