scholarly journals Structure-Activity Relationship in TLR4 Mutations: Atomistic Molecular Dynamics Simulations and Residue Interaction Network Analysis

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Muhammad Ayaz Anwar ◽  
Sangdun Choi
Keyword(s):  
Molecular Dynamics ◽  
Network Analysis ◽  
Molecular Dynamics Simulations ◽  
Interaction Network ◽  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Structure Activity ◽  
Residue Interaction ◽  
Dynamics Simulations

scholarly journals Free Energy Landscapes and Residue Network Analysis for Six SARS-CoV-2 Targets in Complex with Plausible Phytochemical Inhibitors from Withania Somnifera: 1 µS Molecular Dynamics Simulations

2021 ◽  
Author(s):  
Pratap Kumar Parida ◽  
Dipak Paul ◽  
Debamitra Chakravorty
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Molecular Dynamics Simulations ◽  
Withania Somnifera ◽  
Minimum Energy ◽  
Interaction Network ◽  
Energy Landscapes ◽  
Residue Interaction ◽  
Free Energy Landscapes ◽  
Dynamics Simulations

The pandemic is here to stay- evident from the second wave that is severely affecting global population. Though vaccination is now available, the population size restricts its efficacy, especially in the third world countries. Therefore, to avoid a third wave, natural preventive therapeutics are the need of the hour. In this work the efficiency of phytochemicals from <i>Withania somnifera</i> to bind to a total of six SARS-CoV-2 targets have been shown.1 µs molecular dynamics simulations and essential dynamic analyses shed light on the changes induced by the phytochemicals and highlights their multipotent capabilities- 27-Hydroxywithanolide B was able to bind to three targets. Relative free energy of binding for all the phytochemicals were calculated by MM/PBSA. Minimum energy structures were extracted from their free energy landscapes and were subjected to PSN-ENM-NMA and network centrality analysis. Results showed that the phytochemical binding changes the residue-residue interaction network. Network communities increase while hubs and links decrease. Metapath rewiring occurs through residues Phe456 in spike protein, Thr26 and Tyr118 in main protease, Val49 and Phe156 in NSP3, Leu98 in NSP9, Leu4345 in NSP10, Phe440 and Phe843 in NSP12. This work tries to understand the mechanism of possible inhibition by the phytochemicals to combat SARS-CoV-2 with their capability of targeting multiple proteins. The insight from this study can be of great relevance to explore the changes in network properties induced by reported potential inhibitors against SARS-CoV-2 targets.

scholarly journals Free Energy Landscapes and Residue Network Analysis for Six SARS-CoV-2 Targets in Complex with Plausible Phytochemical Inhibitors from Withania Somnifera: 1 µS Molecular Dynamics Simulations

2021 ◽  
Author(s):  
Pratap Kumar Parida ◽  
Dipak Paul ◽  
Debamitra Chakravorty
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Molecular Dynamics Simulations ◽  
Withania Somnifera ◽  
Minimum Energy ◽  
Interaction Network ◽  
Energy Landscapes ◽  
Residue Interaction ◽  
Free Energy Landscapes ◽  
Dynamics Simulations

The pandemic is here to stay- evident from the second wave that is severely affecting global population. Though vaccination is now available, the population size restricts its efficacy, especially in the third world countries. Therefore, to avoid a third wave, natural preventive therapeutics are the need of the hour. In this work the efficiency of phytochemicals from <i>Withania somnifera</i> to bind to a total of six SARS-CoV-2 targets have been shown.1 µs molecular dynamics simulations and essential dynamic analyses shed light on the changes induced by the phytochemicals and highlights their multipotent capabilities- 27-Hydroxywithanolide B was able to bind to three targets. Relative free energy of binding for all the phytochemicals were calculated by MM/PBSA. Minimum energy structures were extracted from their free energy landscapes and were subjected to PSN-ENM-NMA and network centrality analysis. Results showed that the phytochemical binding changes the residue-residue interaction network. Network communities increase while hubs and links decrease. Metapath rewiring occurs through residues Phe456 in spike protein, Thr26 and Tyr118 in main protease, Val49 and Phe156 in NSP3, Leu98 in NSP9, Leu4345 in NSP10, Phe440 and Phe843 in NSP12. This work tries to understand the mechanism of possible inhibition by the phytochemicals to combat SARS-CoV-2 with their capability of targeting multiple proteins. The insight from this study can be of great relevance to explore the changes in network properties induced by reported potential inhibitors against SARS-CoV-2 targets.

Allosteric pathway identification through network analysis: from molecular dynamics simulations to interactive 2D and 3D graphs

2014 ◽  
Vol 169 ◽  
pp. 303-321 ◽  
Author(s):  
Ariane Allain ◽  
Isaure Chauvot de Beauchêne ◽  
Florent Langenfeld ◽  
Yann Guarracino ◽  
Elodie Laine ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Network Analysis ◽  
Molecular Dynamics Simulations ◽  
Large Scale ◽  
Allosteric Regulation ◽  
Local Perturbation ◽  
Modular Network ◽  
Allosteric Coupling ◽  
Dynamics Simulations

Allostery is a universal phenomenon that couples the information induced by a local perturbation (effector) in a protein to spatially distant regulated sites. Such an event can be described in terms of a large scale transmission of information (communication) through a dynamic coupling between structurally rigid (minimally frustrated) and plastic (locally frustrated) clusters of residues. To elaborate a rational description of allosteric coupling, we propose an original approach – MOdular NETwork Analysis (MONETA) – based on the analysis of inter-residue dynamical correlations to localize the propagation of both structural and dynamical effects of a perturbation throughout a protein structure. MONETA uses inter-residue cross-correlations and commute times computed from molecular dynamics simulations and a topological description of a protein to build a modular network representation composed of clusters of residues (dynamic segments) linked together by chains of residues (communication pathways). MONETA provides a brand new direct and simple visualization of protein allosteric communication. A GEPHI module implemented in the MONETA package allows the generation of 2D graphs of the communication network. An interactive PyMOL plugin permits drawing of the communication pathways between chosen protein fragments or residues on a 3D representation. MONETA is a powerful tool for on-the-fly display of communication networks in proteins. We applied MONETA for the analysis of communication pathways (i) between the main regulatory fragments of receptors tyrosine kinases (RTKs), KIT and CSF-1R, in the native and mutated states and (ii) in proteins STAT5 (STAT5a and STAT5b) in the phosphorylated and the unphosphorylated forms. The description of the physical support for allosteric coupling by MONETA allowed a comparison of the mechanisms of (a) constitutive activation induced by equivalent mutations in two RTKs and (b) allosteric regulation in the activated and non-activated STAT5 proteins. Our theoretical prediction based on results obtained with MONETA was validated for KIT by in vitro experiments. MONETA is a versatile analytical and visualization tool entirely devoted to the understanding of the functioning/malfunctioning of allosteric regulation in proteins – a crucial basis to guide the discovery of next-generation allosteric drugs.

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