scholarly journals In Silico Structure-Based Repositioning of Approved Drugs for Spike Glycoprotein S2 Domain Fusion Peptide of SARS-CoV-2: Rationale from Molecular Dynamics and Binding Free Energy Calculations

mSystems ◽  
2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Nishant Shekhar ◽  
Phulen Sarma ◽  
Manisha Prajapat ◽  
Pramod Avti ◽  
Hardeep Kaur ◽  
...  
Keyword(s):  
Binding Free Energy ◽  
Fusion Peptide ◽  
Free Energy Calculations ◽  
Binding Region ◽  
Drug Molecules ◽  
Protein Binding Region ◽  
Binding Residues ◽  
Approved Drugs ◽  
Peptide Region ◽  
Entry Mechanism

The present study provides the structural identification of the viable binding residues of the SARS-CoV-2 S2 fusion peptide region, which holds prime importance in the virus’s host cell fusion and entry mechanism. The classical molecular mechanics simulations were set on values that mimic physiological standards for a good approximation of the dynamic behavior of selected drugs in biological systems. The drug molecules screened and analyzed here have relevant antiviral properties, which are reported here and which might hint toward their utilization in the coronavirus disease 2019 (COVID-19) pandemic owing to their attributes of binding to the fusion protein binding region shown in this study.

scholarly journals Old Arsenal to Combat New Enemy: Repurposing of Commercially Available FDA Approved Drugs Against Main Protease of SARS-CoV2.

2020 ◽  
Author(s):  
Gagandeep Singh ◽  
vishal srivastava ◽  
Ritpratik Mishra ◽  
Gaurav Goel ◽  
Tapan Chaudhuri
Keyword(s):  
Drug Design ◽  
Binding Free Energy ◽  
Md Simulations ◽  
Docking Studies ◽  
Free Energy Calculations ◽  
World Health ◽  
Main Protease ◽  
Health Organization ◽  
Approved Drugs ◽  
Potential Inhibitors

<p> In lack of vaccination and therapeutic drugs, the ongoing COVID-19 pandemic affected millions of people, causing 1,018,957 deaths worldwide (World health organization; 1<sup>st</sup> October 2020). The conventional drug design pipeline for effective and safer drug development is a costly and time-intensive affair. It takes around ten years in general from identifying a clinical candidate to get the approvals for actual applications. An effective way to cut short drug design pipeline in such emergency cases could be the repurposing of already approved drugs against novel targets. Here in this work, we explored the structure-based drug screening approach to find potential inhibitors of SARS-CoV2 main protease (M<sup>pro</sup>) from the library of already FDA approved commercially available drugs. The site-specific and blind docking studies, in combination, suggest three potential inhibitors of M<sup>pro</sup>, Ergotamine (ZINC000052955754), Nilotinib (ZINC000006716957) and Naldemedine (ZINC000100378061). Molecular dynamics (MD) simulations and binding free energy calculations using the MMPBSA method further reinforced the efficiency of the screened M<sup>pro</sup> inhibitor candidates. The work yields enough evidence to conduct rigorous experimental validation of these drugs before utilizing them for the therapeutic management of SARS-CoV2 infection.</p>

scholarly journals Old Arsenal to Combat New Enemy: Repurposing of Commercially Available FDA Approved Drugs Against Main Protease of SARS-CoV2.

2020 ◽  
Author(s):  
Gagandeep Singh ◽  
vishal srivastava ◽  
Ritpratik Mishra ◽  
Gaurav Goel ◽  
Tapan Chaudhuri
Keyword(s):  
Drug Design ◽  
Binding Free Energy ◽  
Md Simulations ◽  
Docking Studies ◽  
Free Energy Calculations ◽  
World Health ◽  
Main Protease ◽  
Health Organization ◽  
Approved Drugs ◽  
Potential Inhibitors

<p> In lack of vaccination and therapeutic drugs, the ongoing COVID-19 pandemic affected millions of people, causing 1,018,957 deaths worldwide (World health organization; 1<sup>st</sup> October 2020). The conventional drug design pipeline for effective and safer drug development is a costly and time-intensive affair. It takes around ten years in general from identifying a clinical candidate to get the approvals for actual applications. An effective way to cut short drug design pipeline in such emergency cases could be the repurposing of already approved drugs against novel targets. Here in this work, we explored the structure-based drug screening approach to find potential inhibitors of SARS-CoV2 main protease (M<sup>pro</sup>) from the library of already FDA approved commercially available drugs. The site-specific and blind docking studies, in combination, suggest three potential inhibitors of M<sup>pro</sup>, Ergotamine (ZINC000052955754), Nilotinib (ZINC000006716957) and Naldemedine (ZINC000100378061). Molecular dynamics (MD) simulations and binding free energy calculations using the MMPBSA method further reinforced the efficiency of the screened M<sup>pro</sup> inhibitor candidates. The work yields enough evidence to conduct rigorous experimental validation of these drugs before utilizing them for the therapeutic management of SARS-CoV2 infection.</p>

scholarly journals Interactions mechanism of commonly used drugs for the treatment of Covid-19

2021 ◽  
Vol 34 (3) ◽  
pp. 613-623
Author(s):  
S. Celik ◽  
A. D. Demirag ◽  
A. E. Ozel ◽  
S. Akyuz
Keyword(s):  
Binding Free Energy ◽  
Autodock Vina ◽  
Spike Glycoprotein ◽  
Docking Analysis ◽  
Drug Molecules ◽  
Protease Enzyme ◽  
Main Protease ◽  
Poisson Boltzmann ◽  
Approved Drugs ◽  
Fda Approved Drugs

In this study conformation analysis of seven drugs commonly used in the treatment of COVID-19 was performed. The most stable conformers of the drug molecules were used as initial data for docking analysis. Using the Cavityplus program, the probable most active binding sites of both apo and holo forms of COVID-19 main protease enzyme (Mpro) and spike glycoprotein of SARSCoV-2 receptors were determined. The interaction mechanisms of the 7 FDA approved drugs (arbidol, colchicine, dexamethasone, favipiravir, galidesivir, hydroxychloroquine, remdesivir) were examined using the AutoDock Vina program. The six of the seven drugs were found to be more stable in binding to apo form of COVID-19 Mpro and spike glycoprotein. Moreover, a set of molecular mechanics (MM) Poisson-Boltzmann (PB) surface area (SA) calculations on the investigated drugs-protein systems were performed and the estimated binding free energy of remdesivir and the apo form of Mpro system was found to be the best. The interaction results of FDA drugs with the apo form of COVID-19 Mpro and spike glycoprotein can play an important role for the treatment of COVID-19.                     KEY WORDS: COVID-19, Drugs, Molecular modelling, Conformational analysis, Molecular docking   Bull. Chem. Soc. Ethiop. 2020, 34(3), 613-623. DOI: https://dx.doi.org/10.4314/bcse.v34i3.16

Large-Scale Assessment of Binding Free Energy Calculations in Active Drug Discovery Projects

2020 ◽  
Author(s):  
Christina Schindler ◽  
Hannah Baumann ◽  
Andreas Blum ◽  
Dietrich Böse ◽  
Hans-Peter Buchstaller ◽  
...  
Keyword(s):  
Free Energy ◽  
Drug Discovery ◽  
Large Scale ◽  
Active Drug ◽  
Binding Free Energy ◽  
Free Energy Calculations ◽  
Energy Calculation ◽  
Large Scale Assessment ◽  
New Public ◽  
Binding Free Energy Calculations

Here we present an evaluation of the binding affinity prediction accuracy of the free energy calculation method FEP+ on internal active drug discovery projects and on a large new public benchmark set.<br>

Automated, Accurate, and Scalable Relative Protein-Ligand Binding Free Energy Calculations using Lambda Dynamics

2020 ◽  
Author(s):  
E. Prabhu Raman ◽  
Thomas J. Paul ◽  
Ryan L. Hayes ◽  
Charles L. Brooks III
Keyword(s):  
Free Energy ◽  
Ligand Binding ◽  
Binding Affinity ◽  
Binding Free Energy ◽  
Computational Cost ◽  
Combinatorial Libraries ◽  
Free Energy Calculations ◽  
Lead Optimization ◽  
Efficient Estimation ◽  
Lead Compound

<p>Accurate predictions of changes to protein-ligand binding affinity in response to chemical modifications are of utility in small molecule lead optimization. Relative free energy perturbation (FEP) approaches are one of the most widely utilized for this goal, but involve significant computational cost, thus limiting their application to small sets of compounds. Lambda dynamics, also rigorously based on the principles of statistical mechanics, provides a more efficient alternative. In this paper, we describe the development of a workflow to setup, execute, and analyze Multi-Site Lambda Dynamics (MSLD) calculations run on GPUs with CHARMm implemented in BIOVIA Discovery Studio and Pipeline Pilot. The workflow establishes a framework for setting up simulation systems for exploratory screening of modifications to a lead compound, enabling the calculation of relative binding affinities of combinatorial libraries. To validate the workflow, a diverse dataset of congeneric ligands for seven proteins with experimental binding affinity data is examined. A protocol to automatically tailor fit biasing potentials iteratively to flatten the free energy landscape of any MSLD system is developed that enhances sampling and allows for efficient estimation of free energy differences. The protocol is first validated on a large number of ligand subsets that model diverse substituents, which shows accurate and reliable performance. The scalability of the workflow is also tested to screen more than a hundred ligands modeled in a single system, which also resulted in accurate predictions. With a cumulative sampling time of 150ns or less, the method results in average unsigned errors of under 1 kcal/mol in most cases for both small and large combinatorial libraries. For the multi-site systems examined, the method is estimated to be more than an order of magnitude more efficient than contemporary FEP applications. The results thus demonstrate the utility of the presented MSLD workflow to efficiently screen combinatorial libraries and explore chemical space around a lead compound, and thus are of utility in lead optimization.</p>

A comprehensive in silico study towards understanding the inhibitory mechanism of Lactoperoxidase by Dapsone and Propofol

2020 ◽  
Vol 16 ◽  
Author(s):  
Rameez Jabeer Khan ◽  
Rajat Kumar Jha ◽  
Gizachew Muluneh Amera ◽  
Jayaraman Muthukumaran ◽  
Rashmi Prabha Singh ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Md Simulation ◽  
Binding Free Energy ◽  
Protoporphyrin Ix ◽  
Md Simulations ◽  
Prosthetic Group ◽  
Drug Molecules ◽  
Group A ◽  
Complex Forms ◽  
Covalently Linked

Introduction: Lactoperoxidase (LPO) is a member of mammalian heme peroxidase family and is an enzyme of innate immune system. It possesses a covalently linked heme prosthetic group (a derivative of protoporphyrin IX) in its active site. LPO catalyzes the oxidation of halides and pseudohalides in the presence of hydrogen peroxide (H2O2) and shows a broad range of antimicrobial activity. Methods: In this study, we have used two pharmaceutically important drug molecules, namely dapsone and propofol, which are earlier reported as potent inhibitors of LPO. Whereas the stereochemistry and mode of binding of dapsone and propofol to LPO is still not known because of the lack of the crystal structure of LPO with these two drugs. In order to fill this gap, we utilized molecular docking and molecular dynamics (MD) simulation studies of LPO in native and complex forms with dapsone and propofol. Results: From the docking results, the estimated binding free energy (ΔG) of -9.25 kcal/mol (Ki = 0.16 μM) and -7.05 kcal/mol (Ki = 6.79 μM) was observed for dapsone, and propofol, respectively. The standard error of Auto Dock program is 2.5 kcal/mol; therefore, molecular docking results alone were inconclusive. Conclusion: To further validate the docking results, we performed MD simulation on unbound, and two drugs bounded LPO structures. Interestingly, MD simulations results explained that the structural stability of LPO-Propofol complex was higher than LPO-Dapsone complex. The results obtained from this study establish the mode of binding and interaction pattern of the dapsone and propofol to LPO as inhibitors.

scholarly journals Automation of absolute protein-ligand binding free energy calculations for docking refinement and compound evaluation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Germano Heinzelmann ◽  
Michael K. Gilson
Keyword(s):  
Free Energy ◽  
Early Stage ◽  
Binding Free Energy ◽  
Low Cost ◽  
Free Energy Calculations ◽  
Free Energies ◽  
Energy Calculations ◽  
Drug Candidates ◽  
Binding Free Energy Calculations ◽  
Binding Free Energies

AbstractAbsolute binding free energy calculations with explicit solvent molecular simulations can provide estimates of protein-ligand affinities, and thus reduce the time and costs needed to find new drug candidates. However, these calculations can be complex to implement and perform. Here, we introduce the software BAT.py, a Python tool that invokes the AMBER simulation package to automate the calculation of binding free energies for a protein with a series of ligands. The software supports the attach-pull-release (APR) and double decoupling (DD) binding free energy methods, as well as the simultaneous decoupling-recoupling (SDR) method, a variant of double decoupling that avoids numerical artifacts associated with charged ligands. We report encouraging initial test applications of this software both to re-rank docked poses and to estimate overall binding free energies. We also show that it is practical to carry out these calculations cheaply by using graphical processing units in common machines that can be built for this purpose. The combination of automation and low cost positions this procedure to be applied in a relatively high-throughput mode and thus stands to enable new applications in early-stage drug discovery.

scholarly journals In Silico Exploration of Phytoconstituents From Phyllanthus emblica and Aegle marmelos as Potential Therapeutics Against SARS-CoV-2 RdRp

2021 ◽  
Vol 15 ◽  
pp. 117793222110274
Author(s):  
Khushboo Pandey ◽  
Kiran Bharat Lokhande ◽  
K Venkateswara Swamy ◽  
Shuchi Nagar ◽  
Manjusha Dake
Keyword(s):  
Molecular Docking ◽  
Binding Affinity ◽  
Simulation Analysis ◽  
Binding Free Energy ◽  
Free Energy Calculations ◽  
Molecular Field ◽  
Hydroxyl Groups ◽  
Phyllanthus Emblica ◽  
Inhibitory Potential ◽  
Novel Drug

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) worldwide has increased the importance of computational tools to design a drug or vaccine in reduced time with minimum risk. Earlier studies have emphasized the important role of RNA-dependent RNA polymerase (RdRp) in SARS-CoV-2 replication as a potential drug target. In our study, comprehensive computational approaches were applied to identify potential compounds targeting RdRp of SARS-CoV-2. To study the binding affinity and stability of the phytocompounds from Phyllanthus emblica and Aegel marmelos within the defined binding site of SARS-CoV-2 RdRp, they were subjected to molecular docking, 100 ns molecular dynamics (MD) simulation followed by post-simulation analysis. Furthermore, to assess the importance of features involved in the strong binding affinity, molecular field-based similarity analysis was performed. Based on comparative molecular docking and simulation studies of the selected phytocompounds with SARS-CoV-2 RdRp revealed that EBDGp possesses a stronger binding affinity (−23.32 kcal/mol) and stability than other phytocompounds and reference compound, Remdesivir (−19.36 kcal/mol). Molecular field-based similarity profiling has supported our study in the validation of the importance of the presence of hydroxyl groups in EBDGp, involved in increasing its binding affinity toward SARS-CoV-2 RdRp. Molecular docking and dynamic simulation results confirmed that EBDGp has better inhibitory potential than Remdesivir and can be an effective novel drug for SARS-CoV-2 RdRp. Furthermore, binding free energy calculations confirmed the higher stability of the SARS-CoV-2 RdRp-EBDGp complex. These results suggest that the EBDGp compound may emerge as a promising drug against SARS-CoV-2 and hence requires further experimental validation.

scholarly journals Molecular modeling study on the drug resistance mechanism of NS5B polymerase to TMC647055

2016 ◽  
Vol 94 (2) ◽  
pp. 147-158 ◽  
Author(s):  
Huiqun Wang ◽  
Wei Cui ◽  
Chenchen Guo ◽  
Bo-Zhen Chen ◽  
Mingjuan Ji
Keyword(s):  
Drug Resistance ◽  
Free Energy ◽  
Rational Design ◽  
Binding Free Energy ◽  
Resistance Mechanism ◽  
Free Energy Calculations ◽  
Side Chain ◽  
Free Energy Decomposition ◽  
Hcv Ns5b ◽  
Ns5b Polymerase

NS5B polymerase plays an important role in viral replication machinery. TMC647055 (TMC) is a novel and potent non-nucleoside inhibitor of the HCV NS5B polymerase. However, mutations that result in drug resistance to TMC have been reported. In this study, we used molecular dynamics (MD) simulations, binding free energy calculations, and free energy decomposition to investigate the drug resistance mechanism of HCV to TMC resulting from L392I, P495T, P495S, and P495L mutations in NS5B polymerase. From the calculated results we determined that the decrease in the binding affinity between TMC and NS5BL392I polymerase is mainly caused by the extra methyl group at the CB atom of Ile. The polarity of the side-chain of residue 495 has no distinct influence on residue 495 binding with TMC, whereas the smaller size of the side-chain of residue 495 causes a substantial decrease in the van der Walls interaction between TMC and residue 495. Moreover, the longer length of the side-chain of residue 495 has a significant effect on the electrostatic interaction between TMC and Arg-503. Finally, we performed the same calculations and detailed analysis on other 3 mutations (L392V, P495V, and P495I). The results further confirmed our conclusions. The computational results not only reveal the drug resistance mechanism between TMC647055 and NS5B polymerase, but also provide valuable information for the rational design of more potent non-nucleoside inhibitors targeting HCV NS5B polymerase.

Assessing the ligand selectivity of sphingosine kinases using molecular dynamics and MM-PBSA binding free energy calculations

2016 ◽  
Vol 12 (4) ◽  
pp. 1174-1182 ◽  
Author(s):  
Liang Fang ◽  
Xiaojian Wang ◽  
Meiyang Xi ◽  
Tianqi Liu ◽  
Dali Yin
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Model Building ◽  
Binding Free Energy ◽  
Homology Model ◽  
Free Energy Calculations ◽  
Dynamics Simulation ◽  
Ligand Selectivity ◽  
Sphingosine Kinases ◽  
Binding Free Energy Calculations

Three residues of SK1 were identified important for selective SK1 inhibitory activity via SK2 homology model building, molecular dynamics simulation, and MM-PBSA studies.

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