Computational Investigation of Increased Virulence and Pathogenesis of SARS-CoV-2 Lineage B.1.1.7

2021 ◽  
Author(s):  
N. Arul Murugan ◽  
Prashanth S. Javali ◽  
Chitra Jeyaraj Pandian ◽  
Muhammad Akhtar Ali ◽  
Vaibhav Srivastava ◽  
...  
Keyword(s):  
Density Functional ◽  
Binding Free Energy ◽  
Intermolecular Hydrogen Bond ◽  
Decomposition Analysis ◽  
Free Energy Calculations ◽  
Spike Protein ◽  
World Health ◽  
Free Energies ◽  
Wild Type ◽  
Host Immune Responses

AbstractNew variants of SARS-CoV-2 are being reported worldwide. More specifically, the variants reported in South Africa (501Y.V2) and United Kingdom (B.1.1.7) were found to be more contagious than the wild type. There are also speculations that the variants might evade the host immune responses induced by currently available vaccines and develop resistance to drugs under consideration. The first step of viral infection in COVID-19, occurs through the interaction of receptor binding domain (RBD) of the spike protein with peptidase domain of the human ACE-2 (hACE-2) receptor. So, possibly the mutations in the RBD domain of spike protein in the new variants could modulate the protein-protein interaction with hACE-2 receptor leading to the increased virulence. In this study, we aim to get molecular level understanding into the mechanism behind the increased infection rate due to such mutations in these variants. We have computationally studied the interaction of the spike protein in both wild-type and B.1.1.7 variant with hACE-2 receptor using combined molecular dynamics and binding free energy calculations using molecular mechanics-Generalized Born surface area (MM-GBSA) approach. The binding free energies computed using configurations from minimization run and low temperature simulation show that mutant variant of spike protein has increased binding affinity for hACE-2 receptor (i.e. ΔΔG(N501Y,A570D) is in the range −20.4 to −21.4 kcal/mol)The residue-wise decomposition analysis and intermolecular hydrogen bond analysis evidenced that the N501Y mutation has increased interaction between RBD of spike protein with ACE-2 receptor. We have also carried out calculations using density functional theory and the results evidenced the increased interaction between three pairs of residues (TYR449 (spike)-ASP38 (ACE-2), TYR453-HIE34 and TYR501-LYS353) in the variant that could be attributed to its increased virulence. The free energies of wild-type and mutant variants of the spike protein computed from MM-GBSA approach suggests that latter variant is stable by about −10.4 kcal/mol when compared to wild type suggesting that it will be retained in the evolution due to increased stability. We demonstrate that with the use of the state-of-the art of computational approaches, we can in advance predict the more virulent nature of variants of SARS-CoV-2 and alert the world health-care system.

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 Alchemical Absolute Protein-Ligand Binding Free Energies for Drug Design

2021 ◽  
Author(s):  
Yuriy Khalak ◽  
Gary Tresdern ◽  
Matteo Aldeghi ◽  
Hannah Magdalena Baumann ◽  
David L. Mobley ◽  
...  
Keyword(s):  
Free Energy ◽  
Drug Discovery ◽  
Drug Design ◽  
Ligand Binding ◽  
Binding Free Energy ◽  
Free Energy Calculations ◽  
Free Energies ◽  
Energy Calculations ◽  
Binding Free Energy Calculations ◽  
Binding Free Energies

The recent advances in relative protein-ligand binding free energy calculations have shown the value of alchemical methods in drug discovery. Accurately assessing absolute binding free energies, although highly desired, remains...

scholarly journals Hit-to-lead and lead optimization binding free energy calculations for G protein-coupled receptors

2020 ◽  
Vol 10 (6) ◽  
pp. 20190128 ◽  
Author(s):  
Shunzhou Wan ◽  
Andrew Potterton ◽  
Fouad S. Husseini ◽  
David W. Wright ◽  
Alexander Heifetz ◽  
...  
Keyword(s):  
G Protein ◽  
Binding Free Energy ◽  
Absolute Error ◽  
Free Energy Calculations ◽  
Lead Optimization ◽  
Receptor Protein ◽  
Enhanced Sampling ◽  
Free Energies ◽  
G Protein Coupled ◽  
Binding Free Energies

We apply the hit-to-lead ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and lead-optimization TIES (thermodynamic integration with enhanced sampling) methods to compute the binding free energies of a series of ligands at the A 1 and A 2A adenosine receptors, members of a subclass of the GPCR (G protein-coupled receptor) superfamily. Our predicted binding free energies, calculated using ESMACS, show a good correlation with previously reported experimental values of the ligands studied. Relative binding free energies, calculated using TIES, accurately predict experimentally determined values within a mean absolute error of approximately 1 kcal mol −1 . Our methodology may be applied widely within the GPCR superfamily and to other small molecule–receptor protein systems.

scholarly journals Predicting binding free energies: Frontiers and benchmarks

2016 ◽  
Author(s):  
David L. Mobley ◽  
Michael K. Gilson
Keyword(s):  
Molecular Design ◽  
Early Stage ◽  
Binding Free Energy ◽  
Research Community ◽  
Free Energy Calculations ◽  
Binding Affinities ◽  
Free Energies ◽  
Biomolecular Complexes ◽  
Binding Free Energy Calculations ◽  
Binding Free Energies

Binding free energy calculations based on molecular simulations provide predicted affinities for biomolecular complexes. These calculations begin with a detailed description of a system, including its chemical composition and the interactions between its components. Simulations of the system are then used to compute thermodynamic information, such as binding affinities. Because of their promise for guiding molecular design, these calculations have recently begun to see widespread applications in early stage drug discovery. However, many challenges remain to make them a robust and reliable tool. Here, we briefly explain how the calculations work, highlight key challenges, and argue for the development of accepted benchmark test systems that will help the research community generate and evaluate progress.Manuscript version 1.1.1 pre-release See https://github.com/mobleylab/benchmarksets for all versions.

scholarly journals A replica exchange umbrella sampling (REUS) approach to predict host–guest binding free energies in SAMPL8 challenge

2021 ◽  
Author(s):  
Mahdi Ghorbani ◽  
Phillip S. Hudson ◽  
Michael R. Jones ◽  
Félix Aviat ◽  
Rubén Meana-Pañeda ◽  
...  
Keyword(s):  
Free Energy ◽  
Binding Free Energy ◽  
Umbrella Sampling ◽  
Free Energy Calculations ◽  
Replica Exchange ◽  
Free Energies ◽  
Guest Binding ◽  
Binding Free Energy Calculations ◽  
Force Field Parameters ◽  
Binding Free Energies

AbstractIn this study, we report binding free energy calculations of various drugs-of-abuse to Cucurbit-[8]-uril as part of the SAMPL8 blind challenge. Force-field parameters were obtained from force-matching with different quantum mechanical levels of theory. The Replica Exchange Umbrella Sampling (REUS) approach was used with a cylindrical restraint to enhance the sampling of host–guest binding. Binding free energy was calculated by pulling the guest molecule from one side of the symmetric and cylindrical host, then into and through the host, and out the other side (bidirectional) as compared to pulling only to the bound pose inside the cylindrical host (unidirectional). The initial results with force-matched MP2 parameter set led to RMSE of 4.68 $${\text{kcal}}/{\text{mol}}$$ kcal / mol from experimental values. However, the follow-up study with CHARMM generalized force field parameters and force-matched PM6-D3H4 parameters resulted in RMSEs from experiment of $$2.65$$ 2.65 and $$1.72 {\text{kcal}}/{\text{mol}}$$ 1.72 kcal / mol , respectively, which demonstrates the potential of REUS for accurate binding free energy calculation given a more suitable description of energetics. Moreover, we compared the free energies for the so called bidirectional and unidirectional free energy approach and found that the binding free energies were highly similar. However, one issue in the bidirectional approach is the asymmetry of profile on the two sides of the host. This is mainly due to the insufficient sampling for these larger systems and can be avoided by longer sampling simulations. Overall REUS shows great promise for binding free energy calculations.

scholarly journals An Effective MM/GBSA Protocol for Absolute Binding Free Energy Calculations: A Case Study on SARS-CoV-2 Spike Protein and the Human ACE2 Receptor

Molecules ◽  
2021 ◽  
Vol 26 (8) ◽  
pp. 2383
Author(s):  
Negin Forouzesh ◽  
Nikita Mishra
Keyword(s):  
Free Energy ◽  
Binding Free Energy ◽  
Normal Mode Analysis ◽  
Free Energy Calculations ◽  
Spike Protein ◽  
Upper And Lower Bounds ◽  
Mode Analysis ◽  
Implicit Solvent ◽  
Energy Calculation ◽  
Generalized Born

The binding free energy calculation of protein–ligand complexes is necessary for research into virus–host interactions and the relevant applications in drug discovery. However, many current computational methods of such calculations are either inefficient or inaccurate in practice. Utilizing implicit solvent models in the molecular mechanics generalized Born surface area (MM/GBSA) framework allows for efficient calculations without significant loss of accuracy. Here, GBNSR6, a new flavor of the generalized Born model, is employed in the MM/GBSA framework for measuring the binding affinity between SARS-CoV-2 spike protein and the human ACE2 receptor. A computational protocol is developed based on the widely studied Ras–Raf complex, which has similar binding free energy to SARS-CoV-2/ACE2. Two options for representing the dielectric boundary of the complexes are evaluated: one based on the standard Bondi radii and the other based on a newly developed set of atomic radii (OPT1), optimized specifically for protein–ligand binding. Predictions based on the two radii sets provide upper and lower bounds on the experimental references: −14.7(ΔGbindBondi)<−10.6(ΔGbindExp.)<−4.1(ΔGbindOPT1) kcal/mol. The consensus estimates of the two bounds show quantitative agreement with the experiment values. This work also presents a novel truncation method and computational strategies for efficient entropy calculations with normal mode analysis. Interestingly, it is observed that a significant decrease in the number of snapshots does not affect the accuracy of entropy calculation, while it does lower computation time appreciably. The proposed MM/GBSA protocol can be used to study the binding mechanism of new variants of SARS-CoV-2, as well as other relevant structures.

scholarly journals Computational Study of Scorpion Venom (Lychas Mucronatus) Activity as Antimicrobial Peptides (AMPs) to the SARS-CoV-2 Main Protease for the Future Coronavirus Disease (COVID-19) Inhibitors

Molekul ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. 125
Author(s):  
Taufik Muhammad Fakih
Keyword(s):  
Antimicrobial Peptides ◽  
Computational Study ◽  
Binding Free Energy ◽  
Scorpion Venom ◽  
Computational Approach ◽  
Free Energy Calculations ◽  
World Health ◽  
Peptide Docking ◽  
Main Protease ◽  
Molecular Stability

The 2019 coronavirus pandemic disease (COVID-19) is still declared a global pandemic by the World Health Organization (WHO). Therefore, an effort that is considered effective in finding therapeutic agents is needed to prevent the spread of COVID-19 infection. One of the steps that can be chosen is by utilizing antimicrobial peptides (AMPs) from animal venom by targeting the specific receptor of SARS-CoV-2, namely the main protease (Mpro). Through this research, a computational approach will be conducted to predict antiviral activity, including protein-peptide docking using PatchDock algorithm, to identify, evaluate, and explore the affinity and molecular interactions of four types of antimicrobial peptides (AMPs), such as Mucroporin, Mucroporin-M1, Mucroporin-S1, and Mucroporin-S2 derived from scorpion venom (Lychas mucronatus) against main protease (Mpro) SARS-CoV-2. These results were then confirmed using protein-peptide interaction dynamics simulations for 50 ns using Gromacs 2016 to observe the molecular stability to the binding site of SARS-CoV-2 Mpro. Based on protein-peptide docking simulations, it was proven that the Mucroporin S-1 peptides have a good affinity against the active site area of SARS-CoV-2 Mpro, with an ACE score of −779.56 kJ/mol. Interestingly, Mucroporin-S1 was able to maintain the stability of its interactions based on the results of RMSD, RMSF, and MM/PBSA binding free energy calculations. The results of the computational approach predict that the Mucroporin-S1 peptide is expected to be useful for further research in the development of new antiviral-based AMPs for the COVID-19 infectious disease. 

scholarly journals An Approach to Alchemical Binding Free-Energy Calculations Using Coupled Topologies

2018 ◽  
Author(s):  
David Huggins
Keyword(s):  
Free Energy ◽  
Binding Free Energy ◽  
Bound State ◽  
Free Energy Calculations ◽  
Test Case ◽  
Free Energies ◽  
Energy Calculations ◽  
Binding Free Energy Calculations ◽  
Good Agreement ◽  
Absolute Binding Free Energy

<p>We present an approach to performing alchemical binding free energies which we term coupled topologies. Simultaneously coupling a molecule in the bound state while decoupling it in the unbound state allows us to calculate free energy changes where the system changes charge, without the need to correct for simulation artifacts. This solves a longstanding problem in computing free energy changes. The approach is applied to separated topology relative binding free energy calculations, but is appropriate for single topology calculations and dual topology calculations as well as absolute binding free energy calculations. We apply the method to small-molecule inhibitors of AmpC β-lactamase and show the coupled topologies approach yields results that are in excellent agreement with experiment and good agreement with a state-of-the-art separated topology approach. The promising results on this test case suggest that the coupled topologies approach will be a useful addition to the available arsenal of free-energy methods.</p>

scholarly journals A simple model for predicting the free energy of binding between anthracycline antibiotics and DNA.

2000 ◽  
Vol 47 (1) ◽  
pp. 1-9 ◽  
Author(s):  
W R Rudnicki ◽  
M Kurzepa ◽  
T Szczepanik ◽  
W Priebe ◽  
B Lesyng
Keyword(s):  
Free Energy ◽  
Theoretical Model ◽  
Density Functional ◽  
Binding Free Energy ◽  
Binding Energies ◽  
Free Energies ◽  
Anthracycline Antibiotics ◽  
Free Energy Of Binding ◽  
Derivatives Of ◽  
Binding Free Energies

A theoretical model for predicting the free energy of binding between anthracycline antibiotics and DNA was developed using the electron density functional (DFT) and molecular mechanics (MM) methods. Partial DFT-ESP charges were used in calculating the MM binding energies for complexes formed between anthracycline antibiotics and oligodeoxynucleotides. These energies were then compared with experimental binding free energies. The good correlation between the experimental and theoretical energies allowed us to propose a model for predicting the binding free energy for derivatives of anthracycline antibiotics and for quickly screening new anthracycline derivatives.

Sign in / Sign up

Export Citation Format

Share Document