Shape-based Machine Learning Models for the Potential Novel COVID-19 Protease Inhibitors Assisted by Molecular Dynamics Simulation

2020 ◽  
Vol 20 (24) ◽  
pp. 2146-2167 ◽  
Author(s):  
Anuraj Nayarisseri ◽  
Ravina Khandelwal ◽  
Maddala Madhavi ◽  
Chandrabose Selvaraj ◽  
Umesh Panwar ◽  
...  
Keyword(s):  
Machine Learning ◽  
Molecular Dynamics ◽  
Protease Inhibitors ◽  
Dynamics Simulation ◽  
The Novel ◽  
Public Health Services ◽  
Dynamic Simulations ◽  
Disease Patterns ◽  
Novel Coronavirus ◽  
Dynamics Simulations

Background: The vast geographical expansion of novel coronavirus and an increasing number of COVID-19 affected cases have overwhelmed health and public health services. Artificial Intelligence (AI) and Machine Learning (ML) algorithms have extended their major role in tracking disease patterns, and in identifying possible treatments. Objective: This study aims to identify potential COVID-19 protease inhibitors through shape-based Machine Learning assisted by Molecular Docking and Molecular Dynamics simulations. Methods: 31 Repurposed compounds have been selected targeting the main coronavirus protease (6LU7) and a machine learning approach was employed to generate shape-based molecules starting from the 3D shape to the pharmacophoric features of their seed compound. Ligand-Receptor Docking was performed with Optimized Potential for Liquid Simulations (OPLS) algorithms to identify highaffinity compounds from the list of selected candidates for 6LU7, which were subjected to Molecular Dynamic Simulations followed by ADMET studies and other analyses. Results: Shape-based Machine learning reported remdesivir, valrubicin, aprepitant, and fulvestrant as the best therapeutic agents with the highest affinity for the target protein. Among the best shape-based compounds, a novel compound identified was not indexed in any chemical databases (PubChem, Zinc, or ChEMBL). Hence, the novel compound was named 'nCorv-EMBS'. Further, toxicity analysis showed nCorv-EMBS to be suitable for further consideration as the main protease inhibitor in COVID-19. Conclusion: Effective ACE-II, GAK, AAK1, and protease 3C blockers can serve as a novel therapeutic approach to block the binding and attachment of the main COVID-19 protease (PDB ID: 6LU7) to the host cell and thus inhibit the infection at AT2 receptors in the lung. The novel compound nCorv- EMBS herein proposed stands as a promising inhibitor to be evaluated further for COVID-19 treatment.

scholarly journals Parameterization of Boronates Using VFFDT and Paramfit for Molecular Dynamics Simulation

Molecules ◽  
2020 ◽  
Vol 25 (9) ◽  
pp. 2196
Author(s):  
Barış Kurt ◽  
Hamdi Temel
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Ab Initio ◽  
Biologically Active ◽  
Dynamics Simulation ◽  
The Novel ◽  
Ab Initio Method ◽  
Crystallographic Structures ◽  
Dynamics Simulations ◽  
Experimental Structure

Boric acid, borate esters, and hydroxy derivatives are biologically active molecules. Thus, performing molecular dynamics simulations of these molecules is vital in terms of drug design, but it is difficult to find directly generated Amber parameters based on an ab initio method for these kinds of molecules in the literature. In this study, Amber parameters for such molecules containing boron were generated based on ab initio calculations using the paramfit program, which applies a combination of genetic and simplex algorithms, and the Visual Force Field Derivation Toolkit (VFFDT) program containing the Seminario method. The minimized structure, after obtaining novel parameters and using the sander program, was compared with the experimental crystallographic structures, and it was observed that the root-mean-square deviation (RMSD) value between the experimental structure and minimized structure agreed reasonably well. In addition, the molecule was heated, and the molecular dynamics simulation was successfully obtained with the novel parameters.

scholarly journals Discovery of Small-Molecule Inhibitors of SARS-CoV-2 Proteins Using a Computational and Experimental Pipeline

2021 ◽  
Vol 8 ◽  
Author(s):  
Edmond Y. Lau ◽  
Oscar A. Negrete ◽  
W. F. Drew Bennett ◽  
Brian J. Bennion ◽  
Monica Borucki ◽  
...  
Keyword(s):  
Machine Learning ◽  
Candesartan Cilexetil ◽  
Selectivity Index ◽  
Spike Protein ◽  
The Novel ◽  
Activity Assay ◽  
Main Protease ◽  
Novel Coronavirus ◽  
Dynamics Simulations ◽  
Protein Assays

A rapid response is necessary to contain emergent biological outbreaks before they can become pandemics. The novel coronavirus (SARS-CoV-2) that causes COVID-19 was first reported in December of 2019 in Wuhan, China and reached most corners of the globe in less than two months. In just over a year since the initial infections, COVID-19 infected almost 100 million people worldwide. Although similar to SARS-CoV and MERS-CoV, SARS-CoV-2 has resisted treatments that are effective against other coronaviruses. Crystal structures of two SARS-CoV-2 proteins, spike protein and main protease, have been reported and can serve as targets for studies in neutralizing this threat. We have employed molecular docking, molecular dynamics simulations, and machine learning to identify from a library of 26 million molecules possible candidate compounds that may attenuate or neutralize the effects of this virus. The viability of selected candidate compounds against SARS-CoV-2 was determined experimentally by biolayer interferometry and FRET-based activity protein assays along with virus-based assays. In the pseudovirus assay, imatinib and lapatinib had IC50 values below 10 μM, while candesartan cilexetil had an IC50 value of approximately 67 µM against Mpro in a FRET-based activity assay. Comparatively, candesartan cilexetil had the highest selectivity index of all compounds tested as its half-maximal cytotoxicity concentration 50 (CC50) value was the only one greater than the limit of the assay (>100 μM).

scholarly journals Molecular Dynamics Simulations and Empirical Observations on Soy Lecithin Liposome Preparation

2018 ◽  
Vol 16 (2) ◽  
pp. 222 ◽  
Author(s):  
Rini Dwiastuti ◽  
Muhammad Radifar ◽  
Marchaban Marchaban ◽  
Sri Noegrohati ◽  
Enade Perdana Istyastono
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Molecular Dynamic ◽  
Dynamics Simulation ◽  
Coarse Grained ◽  
Molecular Dynamic Simulations ◽  
Soy Lecithin ◽  
Dynamic Simulations ◽  
Liposome Size ◽  
Dynamics Simulations

Soy lecithin is a phospholipid often used in liposome formulations. Determination of water and phospholipid composition is one of the problems in the liposome formulation. This study is using molecular dynamics simulation and empirical observation in producing liposome preparations. Phospholipids 1,2-dilauroyl-sn-glycero-3-phosphoethanolamine (DLPE) were objected in molecular dynamics simulations using Coarse Grained Molecular Dynamics (CGMD) approaches. The result showed that the molecular dynamic simulations could be employed to predict the liposome size. The molecular dynamic simulations resulted in liposome size of 71.22 ± 2.54 nm, which was located within the range of the liposome size resulted from the empirical observations (95.99 ± 43.02 nm). Moreover, similar liposome forms were observed on both results of molecular dynamics simulations and empirical approaches.

Multicanonical Molecular Dynamics Simulation Study of the Liquid-Solid and Solid-Solid Transitions in Lennard-Jones Clusters

2011 ◽  
Author(s):  
Toshihiro Kaneko ◽  
Kenji Yasuoka ◽  
Ayori Mitsutake ◽  
Xiao Cheng Zeng
Keyword(s):  
Molecular Dynamics ◽  
Heat Capacity ◽  
Transition Temperature ◽  
Peak Position ◽  
Temperature Curve ◽  
Dynamics Simulation ◽  
Lennard Jones ◽  
Dynamics Simulations ◽  
First Time ◽  
Good Agreement

Multicanonical molecular dynamics simulations are applied, for the first time, to study the liquid-solid and solid-solid transitions in Lennard-Jones (LJ) clusters. The transition temperatures are estimated based on the peak position in the heat capacity versus temperature curve. For LJ31, LJ58 and LJ98, our results on the solid-solid transition temperature are in good agreement with previous ones. For LJ309, the predicted liquid-solid transition temperature is also in agreement with previous result.

scholarly journals Reactive molecular dynamics simulation of the high-temperature pyrolysis of 2,2′,2′′,4,4′,4′′,6,6′,6′′-nonanitro-1,1′:3′,1′′-terphenyl (NONA)

RSC Advances ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 5507-5515
Author(s):  
Liang Song ◽  
Feng-Qi Zhao ◽  
Si-Yu Xu ◽  
Xue-Hai Ju
Keyword(s):  
Molecular Dynamics ◽  
High Temperature ◽  
Molecular Dynamics Simulation ◽  
Molecular Dynamics Simulations ◽  
Dynamics Simulation ◽  
Reactive Molecular Dynamics ◽  
Ring Compounds ◽  
Fused Ring ◽  
Dynamics Simulations

The bimolecular and fused ring compounds are found in the high-temperature pyrolysis of NONA using ReaxFF molecular dynamics simulations.

Molecular Dynamics Simulation Study of Lecithin Inhibiting Hydrate-Dissociation

2017 ◽  
Vol 890 ◽  
pp. 252-259
Author(s):  
Le Wang ◽  
Guan Cheng Jiang ◽  
Xin Lin ◽  
Xian Min Zhang ◽  
Qi Hui Jiang
Keyword(s):  
Molecular Dynamics ◽  
Water Movement ◽  
Simulation Analysis ◽  
Mass Density ◽  
Dynamics Simulation ◽  
Dissociation Process ◽  
Hydrate Dissociation ◽  
Hydrocarbon Chains ◽  
Dynamics Simulations ◽  
Mass Density Profile

Molecular dynamics simulations are used to study the dissociation inhibiting mechanism of lecithin for structure I hydrates. Adsorption characteristics of lecithin and PVP (poly (N-vinylpyrrolidine)) on the hydrate surfaces were performed in the NVT ensemble at temperatures of 277K and the hydrate dissociation process were simulated in the NPT ensemble at same temperature. The results show that hydrate surfaces with lecithin is more stable than the ones with PVP for the lower potential energy. The conformation of lecithin changes constantly after the balanced state is reached while the PVP molecular dose not. Lecithin molecule has interaction with lecithin nearby and hydrocarbon-chains of lecithin molecules will form a network to prevent the diffusion of water and methane molecules, which will narrow the available space for hydrate methane and water movement. Compared with PVP-hydrate simulation, analysis results (snapshots and mass density profile) of the dissociation simulations show that lecithin-hydrate dissociates more slowly.

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