scholarly journals How Does Arbidol Inhibit the Novel Coronavirus SARS-CoV-2? Atomistic Insights from Molecular Dynamics Simulations

2020 ◽  
Author(s):  
Aditya Padhi ◽  
Aniruddha Seal ◽  
Timir Tripathi
Keyword(s):  
Molecular Dynamics ◽  
Global Economy ◽  
Md Simulation ◽  
Treatment Guidelines ◽  
Host Cells ◽  
Virus Binding ◽  
Drug Candidates ◽  
Fusion Inhibition ◽  
Novel Coronavirus ◽  
Dynamics Simulations

<p>The COVID-19 pandemic is spreading at an alarming rate, posing an unprecedented threat to the global economy and human health. Broad-spectrum antivirals are currently being administered for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) treatment. China's prevention and treatment guidelines suggest the use of an anti-influenza drug, Arbidol, for the clinical treatment of COVID-19. Reports indicate that Arbidol could neutralize the SARS-CoV-2. Monotherapy with Arbidol is found superior to Lopinavir-Ritonavir or Favipiravir in the treatment of COVID-19. In the SARS-CoV-2, Arbidol acts upon interfering in virus binding to host cells. However, the detailed understanding of Arbidol induced inhibition of SARS-CoV-2 is not known. Here, we present atomistic insights into the Arbidol-induced SARS-CoV-2 membrane fusion inhibition and propose a model of inhibition. Molecular dynamics (MD) simulation-based analyses demonstrate that Arbidol binds and stabilizes at the receptor-binding domain (RBD)/ACE2 interface with a high affinity. It forms stronger intermolecular interactions with RBD than ACE2. Analyses of the detailed decomposition of energy components and binding affinities revealed a substantial increase in the affinity between RBD and ACE2 in the Arbidol-bound RBD/ACE2 complex, suggesting that Arbidol could generate favorable interactions between them. Based on our MD simulation results, we propose that the binding of Arbidol induced structural rigidity in the virus glycoprotein resulting in restriction of the conformational rearrangements associated with membrane attachment and virus entry.Further, key residues of RBD and ACE2 that interacted with Arbidol were identified, opening the doors for the development of therapeutic strategies and higher efficacy Arbidol derivatives or lead drug candidates.</p>

scholarly journals How Does Arbidol Inhibit the Novel Coronavirus SARS-CoV-2? Atomistic Insights from Molecular Dynamics Simulations

2020 ◽  
Author(s):  
Aditya Padhi ◽  
Aniruddha Seal ◽  
Timir Tripathi
Keyword(s):  
Molecular Dynamics ◽  
Global Economy ◽  
Md Simulation ◽  
Treatment Guidelines ◽  
Host Cells ◽  
Virus Binding ◽  
Drug Candidates ◽  
Fusion Inhibition ◽  
Novel Coronavirus ◽  
Dynamics Simulations

<p>The COVID-19 pandemic is spreading at an alarming rate, posing an unprecedented threat to the global economy and human health. Broad-spectrum antivirals are currently being administered for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) treatment. China's prevention and treatment guidelines suggest the use of an anti-influenza drug, Arbidol, for the clinical treatment of COVID-19. Reports indicate that Arbidol could neutralize the SARS-CoV-2. Monotherapy with Arbidol is found superior to Lopinavir-Ritonavir or Favipiravir in the treatment of COVID-19. In the SARS-CoV-2, Arbidol acts upon interfering in virus binding to host cells. However, the detailed understanding of Arbidol induced inhibition of SARS-CoV-2 is not known. Here, we present atomistic insights into the Arbidol-induced SARS-CoV-2 membrane fusion inhibition and propose a model of inhibition. Molecular dynamics (MD) simulation-based analyses demonstrate that Arbidol binds and stabilizes at the receptor-binding domain (RBD)/ACE2 interface with a high affinity. It forms stronger intermolecular interactions with RBD than ACE2. Analyses of the detailed decomposition of energy components and binding affinities revealed a substantial increase in the affinity between RBD and ACE2 in the Arbidol-bound RBD/ACE2 complex, suggesting that Arbidol could generate favorable interactions between them. Based on our MD simulation results, we propose that the binding of Arbidol induced structural rigidity in the virus glycoprotein resulting in restriction of the conformational rearrangements associated with membrane attachment and virus entry.Further, key residues of RBD and ACE2 that interacted with Arbidol were identified, opening the doors for the development of therapeutic strategies and higher efficacy Arbidol derivatives or lead drug candidates.</p>

scholarly journals Contributions of Molecular Dynamics Simulations to Elastohydrodynamic Lubrication

2021 ◽  
Vol 69 (1) ◽  
Author(s):  
James P. Ewen ◽  
Hugh A. Spikes ◽  
Daniele Dini
Keyword(s):  
Molecular Dynamics ◽  
Shear Rate ◽  
Experimental Design ◽  
Md Simulation ◽  
Elastohydrodynamic Lubrication ◽  
Quantitative Agreement ◽  
Coupling Methods ◽  
Fundamental Understanding ◽  
Shear Heating ◽  
Dynamics Simulations

AbstractThe prediction of friction under elastohydrodynamic lubrication (EHL) conditions remains one of the most important and controversial areas of tribology. This is mostly because the pressure and shear rate conditions inside EHL contacts are particularly severe, which complicates experimental design. Over the last decade, molecular dynamics (MD) simulation has played an increasingly significant role in our fundamental understanding of molecular behaviour under EHL conditions. In recent years, MD simulation has shown quantitative agreement with friction and viscosity results obtained experimentally, meaning that they can, either in isolation or through the use of multiscale coupling methods, begin to be used to test and inform macroscale models for EHL problems. This is particularly useful under conditions that are relevant inside machine components, but are difficult to obtain experimentally without uncontrollable shear heating.

scholarly journals How does temperature affect the dynamics of SARS-CoV-2 M proteins? Insights from Molecular Dynamics Simulations

2021 ◽  
Author(s):  
Soumya Lipsa Rath ◽  
Madhusmita Tripathy ◽  
Nabanita Mandal
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Membrane Lipids ◽  
Membrane System ◽  
Host Cells ◽  
Coarse Grained ◽  
M Protein ◽  
Effect Of Temperature ◽  
M Proteins ◽  
Dynamics Simulations

Enveloped viruses, in general, have several transmembrane proteins and glycoproteins, which assist the virus in entry and attachment onto the host cells. These proteins also play a significant role in determining the shape and size of the newly formed virus particles. The lipid membrane and the embedded proteins affect each other in non-trivial ways during the course of the viral life cycle. Unravelling the nature of the protein-protein and protein-lipid interactions, under various environmental and physiological conditions, could therefore prove to be crucial in development of therapeutics. Here, we study the M protein of SARS-CoV-2 to understand the effect of temperature on the properties of the protein-membrane system. The membrane embedded dimeric M proteins were studied using atomistic and coarse-grained molecular dynamics simulations at temperatures ranging between 10 and 50 ˚C. While temperature induced fluctuations should be monotonic, we observe a steady rise in the protein dynamics up to 40 ˚C, beyond which it surprisingly reverts back to the low temperature behaviour. Detailed investigation reveals disordering of the membrane lipids in the presence of the protein, which induces additional curvature around the transmembrane region. Coarse-grained simulations indicate temperature dependent aggregation of M protein dimers. Our study clearly indicates that the dynamics of membrane lipids and integral M protein of SARS-CoV-2 enables it to better associate and aggregate only at a certain temperature range (i.e., ~30 to 40 ˚C). This can have important implications in the protein aggregation and subsequent viral budding/fission processes.   

Computational Discovery of SARS-CoV-2 NSP 16 Drug Candidates Based on Pharmacophore Modeling and Molecular Dynamics Simulation

2021 ◽  
Vol 20 (04) ◽  
pp. 377-390
Author(s):  
Zahra Hesari ◽  
Samaneh Zolghadri ◽  
Sajad Moradi ◽  
Mohsen Shahlaei ◽  
Elham Tazikeh-Lemeski
Keyword(s):  
Molecular Dynamics ◽  
Study Drug ◽  
Pharmacophore Modeling ◽  
Binding Energies ◽  
Dynamics Simulation ◽  
Structural Protein ◽  
Drug Candidates ◽  
Computational Discovery ◽  
Approved Drugs ◽  
Dynamics Simulations

Non-Structural Protein 16 (NSP-16) is one of the most suitable targets for discovery of drugs for corona viruses including SARS-CoV-2. In this study, drug discovery of SARS-CoV-2 nsp-16 has been accomplished by pharmacophore-based virtual screening among some analogs (FDA approved drugs) and marine natural plants (MNP). The comparison of the binding energies and the inhibition constants was determined using molecular docking method. Three compounds including two FDA approved (Ibrutinib, Idelalisib) and one MNP (Kumusine) were selected for further investigation using the molecular dynamics simulations. The results indicated that Ibrutinib and Idelalisib are oral medications while Kumusine, with proper hydrophilic and solubility properties, is an appropriate candidate for nsp-16 inhibitor and can be effective to control COVID-19 disease.

scholarly journals Structural Influence and Interactive Binding Behavior of Dopamine and Norepinephrine on the Greek-Key-Like Core of α-Synuclein Protofibril Revealed by Molecular Dynamics Simulations

Processes ◽  
2019 ◽  
Vol 7 (11) ◽  
pp. 850
Author(s):  
Yu Zou ◽  
Zhiwei Liu ◽  
Zhiqiang Zhu ◽  
Zhenyu Qian
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Therapeutic Strategy ◽  
Binding Capacity ◽  
Salt Bridges ◽  
Drug Candidates ◽  
Binding Behavior ◽  
Dynamics Simulations ◽  
Structural Influence ◽  
Β Sheet

The pathogenesis of Parkinson’s disease (PD) is closely associated with the aggregation of α-synuclein (αS) protein. Finding the effective inhibitors of αS aggregation has been considered as the primary therapeutic strategy for PD. Recent studies reported that two neurotransmitters, dopamine (DA) and norepinephrine (NE), can effectively inhibit αS aggregation and disrupt the preformed αS fibrils. However, the atomistic details of αS-DA/NE interaction remain unclear. Here, using molecular dynamics simulations, we investigated the binding behavior of DA/NE molecules and their structural influence on αS44–96 (Greek-key-like core of full length αS) protofibrillar tetramer. Our results showed that DA/NE molecules destabilize αS protofibrillar tetramer by disrupting the β-sheet structure and destroying the intra- and inter-peptide E46–K80 salt bridges, and they can also destroy the inter-chain backbone hydrogen bonds. Three binding sites were identified for both DA and NE molecules interacting with αS tetramer: T54–T72, Q79–A85, and F94–K96, and NE molecules had a stronger binding capacity to these sites than DA. The binding of DA/NE molecules to αS tetramer is dominantly driven by electrostatic and hydrogen bonding interactions. Through aromatic π-stacking, DA and NE molecules can bind to αS protofibril interactively. Our work reveals the detailed disruptive mechanism of protofibrillar αS oligomer by DA/NE molecules, which is helpful for the development of drug candidates against PD. Given that exercise as a stressor can stimulate DA/NE secretion and elevated levels of DA/NE could delay the progress of PD, this work also enhances our understanding of the biological mechanism by which exercise prevents and alleviates PD.

Measuring the Spontaneous Curvature of Bilayer Membranes by Molecular Dynamics Simulations

2013 ◽  
Vol 13 (4) ◽  
pp. 1093-1106 ◽  
Author(s):  
Han Wang ◽  
Dan Hu ◽  
Pingwen Zhang
Keyword(s):  
Molecular Dynamics ◽  
Md Simulation ◽  
Molecular Mechanisms ◽  
Bilayer Membrane ◽  
Spontaneous Curvature ◽  
Bilayer Membranes ◽  
Bead Diameter ◽  
The Mean ◽  
Dynamics Simulations ◽  
Theoretical Results

AbstractWe propose a mathematically rigorous method to measure the spontaneous curvature of a bilayer membrane by molecular dynamics (MD) simulation, which provides description of the molecular mechanisms that cause the spontaneous curvature. As a main result, for the membrane setup investigated, the spontaneous curvature is proved to be a constant plus twice the mean curvature of the membrane in its tensionless ground state. The spontaneous curvature due to the built-in transbilayer asymmetry of the membrane in terms of lipid shape is studied by the proposed method. A linear dependence of the spontaneous curvature with respect to the head-bead diameter difference and the lipid mixing ratio is discovered. The consistency with the theoretical results provides evidence supporting the validity of our method.

IMD: A Software Package for Molecular Dynamics Studies on Parallel Computers

1997 ◽  
Vol 08 (05) ◽  
pp. 1131-1140 ◽  
Author(s):  
J. Stadler ◽  
R. Mikulla ◽  
H.-R. Trebin
Keyword(s):  
Molecular Dynamics ◽  
Software Package ◽  
Large Scale ◽  
Md Simulation ◽  
Parallel Computers ◽  
Massively Parallel ◽  
Massively Parallel Computers ◽  
Communication Scheme ◽  
And Performance ◽  
Dynamics Simulations

We report on implementation and performance of the program IMD, designed for short range molecular dynamics simulations on massively parallel computers. After a short explanation of the cell-based algorithm, its extension to parallel computers as well as two variants of the communication scheme are discussed. We provide performance numbers for simulations of different sizes and compare them with values found in the literature. Finally we describe two applications, namely a very large scale simulation with more than 1.23×109 atoms, to our knowledge the largest published MD simulation up to this day and a simulation of a crack propagating in a two-dimensional quasicrystal.

scholarly journals Scalable Analysis of Authentic Viral Envelopes on FRONTERA

2020 ◽  
Author(s):  
Fabio González-Arias ◽  
Tyler Reddy ◽  
John E. Stone ◽  
Jodi A. Hadden-Perilla ◽  
Juan R. Perilla
Keyword(s):  
Large Scale ◽  
Viral Envelope ◽  
Host Cells ◽  
Parallel Computer ◽  
Modeling And Analysis ◽  
Large Scale Analysis ◽  
Viral Envelopes ◽  
Novel Coronavirus ◽  
Dynamics Simulations ◽  
Scalable Analysis

AbstractEnveloped viruses infect host cells via fusion of their viral envelope with the plasma membrane. Upon cell entry, viruses gain access to all the macromolecular machinery necessary to replicate, assemble, and bud their progeny from the infected cell. By employing molecular dynamics simulations to characterize the dynamical and chemical-physical properties of viral envelopes, researchers can gain insights into key determinants of viral infection and propagation. Here, the Frontera supercomputer is leveraged for large-scale analysis of authentic viral envelopes, whose lipid compositions are complex and realistic. VMD with support for MPI is employed on the massive parallel computer to overcome previous computational limitations and enable investigation into virus biology at an unprecedented scale. The modeling and analysis techniques applied to authentic viral envelopes at two levels of particle resolution are broadly applicable to the study of other viruses, including the novel coronavirus that causes COVID-19. A framework for carrying out scalable analysis of multi-million particle MD simulation trajectories on Frontera is presented, expanding the the utility of the machine in humanity’s ongoing fight against infectious disease.

scholarly journals Neural relational inference to learn allosteric long-range interactions in proteins from molecular dynamics simulations

2021 ◽  
Author(s):  
Jingxuan Zhu ◽  
Juexin Wang ◽  
Weiwei Han ◽  
Dong Xu
Keyword(s):  
Molecular Dynamics ◽  
Long Range ◽  
Md Simulation ◽  
Biological Process ◽  
Dynamic Networks ◽  
Md Simulations ◽  
Amino Acid Mutation ◽  
Long Range Interactions ◽  
Decoder Architecture ◽  
Dynamics Simulations

Abstract Protein allostery is a biological process facilitated by spatially long-range intra-protein communication, whereby ligand binding or amino acid mutation at a distant site affects the active site remotely. Molecular dynamics (MD) simulation provides a powerful computational approach to probe the allosteric effect. However, current MD simulations cannot reach the time scales of whole allosteric processes. The advent of deep learning made it possible to evaluate both spatially short and long-range communications for understanding allostery. For this purpose, we applied a neural relational inference (NRI) model based on a graph neural network (GNN), which adopts an encoder-decoder architecture to simultaneously infer latent interactions to probe protein allosteric processes as dynamic networks of interacting residues. From the MD trajectories, this model successfully learned the long-range interactions and pathways that can mediate the allosteric communications between the two distant sites in the Pin1, SOD1, and MEK1 systems.

scholarly journals Altering the solubility of the antibiotic candidate Nisin – a computational study

2020 ◽  
Author(s):  
Preeti Pandey ◽  
Ulrich H.E. Hansmann ◽  
Feng Wang
Keyword(s):  
Molecular Dynamics ◽  
Amino Acids ◽  
Antimicrobial Activity ◽  
Broad Spectrum ◽  
Bacterial Resistance ◽  
Force Fields ◽  
Computational Study ◽  
Food Preservative ◽  
Drug Candidates ◽  
Dynamics Simulations

AbstractThe growing bacterial resistance to available antibiotics makes it necessary to look for new drug candidates. An example is a lanthionine-containing nisin, which has a broad spectrum of antimicrobial activity. While nisin is widely utilized as a food preservative, its poor solubility and low stability at physiological pH hinder its use as an antibiotic. As the solubility of nisin is controlled by the residues of the hinge region, we have performed molecular dynamics simulations of various mutants and studied their effects on nisin’s solubility. These simulations are complicated by the presence of two uncommon residues (dehydroalanine and dehydrobutyrine) in the peptide. The primary goal of the present study is to derive rules for designing new mutants that will be more soluble at physiological pH and, therefore, may serve as a basis for the future antibiotic design. Another aim of our study is to evaluate whether existing force fields can model the solubility of these amino acids accurately, in order to motivate further developments of force fields to account for solubility information.

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