Computational Prediction of Binding Affinity for CYP1A2-Ligand Complexes Using Empirical Free Energy Calculations

2010 ◽  
Vol 38 (8) ◽  
pp. 1347-1354 ◽  
Author(s):  
Poongavanam Vasanthanathan ◽  
Lars Olsen ◽  
Flemming Steen Jørgensen ◽  
Nico P. E. Vermeulen ◽  
Chris Oostenbrink
Keyword(s):  
Free Energy ◽  
Binding Affinity ◽  
Computational Prediction ◽  
Free Energy Calculations ◽  
Energy Calculations

scholarly journals Computational Prediction of Mutational Effects on the SARS-CoV-2 Binding by Relative Free Energy Calculations

2020 ◽  
Author(s):  
Junjie Zou ◽  
Jian Yin ◽  
Lei Fang ◽  
Mingjun Yang ◽  
Tianyuan Wang ◽  
...  
Keyword(s):  
Free Energy ◽  
Computational Prediction ◽  
Free Energy Calculations ◽  
Alanine Scanning Mutagenesis ◽  
Angiotensin Converting Enzyme 2 ◽  
Energy Calculations ◽  
Relative Free Energy ◽  
Protein Interfaces ◽  
Computational Alanine Scanning ◽  
Entry Receptor

<p>The ability of coronaviruses to infect humans is invariably associated with their binding strengths to human receptor proteins. Both SARS-CoV-2, initially named 2019-nCoV, and SARS-CoV were reported to utilize angiotensin-converting enzyme 2 (ACE2) as an entry receptor in human cells. To better understand the interplay between SARS-CoV-2 and ACE2, we performed computational alanine scanning mutagenesis on the “hotspot” residues at protein-protein interfaces using relative free energy calculations. Our data suggest that the mutations in SARS-CoV-2 lead to a greater binding affinity relative to SARS-CoV. In addition, our free energy calculations provide insight into the infectious ability of viruses on a physical basis, and also provide useful information for the design of antiviral drugs.</p>

scholarly journals Assessment of Binding Affinity via Alchemical Free-Energy Calculations

2020 ◽  
Vol 60 (6) ◽  
pp. 3120-3130 ◽  
Author(s):  
Maximilian Kuhn ◽  
Stuart Firth-Clark ◽  
Paolo Tosco ◽  
Antonia S. J. S. Mey ◽  
Mark Mackey ◽  
...  
Keyword(s):  
Free Energy ◽  
Binding Affinity ◽  
Free Energy Calculations ◽  
Energy Calculations ◽  
Alchemical Free Energy ◽  
Alchemical Free Energy Calculations

scholarly journals Determining the Binding Affinity of Toxoplasma ROP Proteins to a Membrane using Free Energy Calculations

2012 ◽  
Vol 102 (3) ◽  
pp. 472a
Author(s):  
Nwamaka O. Onyeozili ◽  
Keith M. Callenberg ◽  
Siyu C. Xiao ◽  
Jon P. Boyle ◽  
Michael Grabe
Keyword(s):  
Free Energy ◽  
Binding Affinity ◽  
Free Energy Calculations ◽  
Energy Calculations

scholarly journals Computational Prediction of Mutational Effects on the SARS-CoV-2 Binding by Relative Free Energy Calculations

2020 ◽  
Author(s):  
Junjie Zou ◽  
Jian Yin ◽  
Lei Fang ◽  
Mingjun Yang ◽  
Tianyuan Wang ◽  
...  
Keyword(s):  
Free Energy ◽  
Computational Prediction ◽  
Free Energy Calculations ◽  
Alanine Scanning Mutagenesis ◽  
Angiotensin Converting Enzyme 2 ◽  
Energy Calculations ◽  
Relative Free Energy ◽  
Protein Interfaces ◽  
Computational Alanine Scanning ◽  
Entry Receptor

<p>The ability of coronaviruses to infect humans is invariably associated with their binding strengths to human receptor proteins. Both SARS-CoV-2, initially named 2019-nCoV, and SARS-CoV were reported to utilize angiotensin-converting enzyme 2 (ACE2) as an entry receptor in human cells. To better understand the interplay between SARS-CoV-2 and ACE2, we performed computational alanine scanning mutagenesis on the “hotspot” residues at protein-protein interfaces using relative free energy calculations. Our data suggest that the mutations in SARS-CoV-2 lead to a greater binding affinity relative to SARS-CoV. In addition, our free energy calculations provide insight into the infectious ability of viruses on a physical basis, and also provide useful information for the design of antiviral drugs.</p>

scholarly journals Computational Prediction of Mutational Effects on SARS-CoV-2 Binding by Relative Free Energy Calculations

2020 ◽  
Vol 60 (12) ◽  
pp. 5794-5802 ◽  
Author(s):  
Junjie Zou ◽  
Jian Yin ◽  
Lei Fang ◽  
Mingjun Yang ◽  
Tianyuan Wang ◽  
...  
Keyword(s):  
Free Energy ◽  
Computational Prediction ◽  
Free Energy Calculations ◽  
Energy Calculations ◽  
Relative Free Energy

scholarly journals Molecular Environment Specific Atomic Charges Improve Binding Affinity Predictions of SAMPL5 Host-Guest Systems

2021 ◽  
Author(s):  
Duvan Gonzalez ◽  
Luis Macaya ◽  
Esteban Vöhringer-Martinez
Keyword(s):  
Free Energy ◽  
Force Field ◽  
Binding Affinity ◽  
Free Energy Calculations ◽  
Atomic Charges ◽  
Binding Affinity Prediction ◽  
Energy Calculations ◽  
Affinity Prediction ◽  
Alchemical Free Energy ◽  
Alchemical Free Energy Calculations

<div> <div> <div> <p>Host-guest systems are widely used in benchmarks as model systems to improve computational methods for absolute binding free energy predictions. Recent advances in sampling algorithms for alchemical free energy calculations and the increase in computational power have made their binding affinity prediction primarily dependent on the quality of the force field. Here, we propose a new methodology to derive the atomic charges of host-guest systems based on QM/MM calculations and the MBIS partitioning of the polarized electron density. A newly developed interface between the OpenMM and ORCA software package provides D-MBIS charges that best represent the guest’s average electrostatic interactions in the hosts or the solvent. The simulation workflow also calculates the average energy required to polarize the guest in the bound and unbound state. Alchemical free energy calculations using the GAFF force field parameters with D-MBIS charges improve the binding affinity prediction of six guests bound to two octa-acid hosts compared to the AM1-BCC charge set after correction with the average energetic polarization cost. This correction results from the difference in the energetic polarization cost between the bound and unbound state and contributes significantly to the binding affinity of anionic guests. </p></div></div></div><div><div><div> </div> </div> </div>

scholarly journals Computational Prediction of Mutational Effects on the SARS-CoV-2 Binding by Relative Free Energy Calculations

2020 ◽  
Author(s):  
Junjie Zou ◽  
Jian Yin ◽  
Lei Fang ◽  
Mingjun Yang ◽  
Tianyuan Wang ◽  
...  
Keyword(s):  
Free Energy ◽  
Computational Prediction ◽  
Free Energy Calculations ◽  
Alanine Scanning Mutagenesis ◽  
Angiotensin Converting Enzyme 2 ◽  
Energy Calculations ◽  
Relative Free Energy ◽  
Protein Interfaces ◽  
Computational Alanine Scanning ◽  
Entry Receptor

<p>The ability of coronaviruses to infect humans is invariably associated with their binding strengths to human receptor proteins. Both SARS-CoV-2, initially named 2019-nCoV, and SARS-CoV were reported to utilize angiotensin-converting enzyme 2 (ACE2) as an entry receptor in human cells. To better understand the interplay between SARS-CoV-2 and ACE2, we performed computational alanine scanning mutagenesis on the “hotspot” residues at protein-protein interfaces using relative free energy calculations. Our data suggest that the mutations in SARS-CoV-2 lead to a greater binding affinity relative to SARS-CoV. In addition, our free energy calculations provide insight into the infectious ability of viruses on a physical basis, and also provide useful information for the design of antiviral drugs.</p>

scholarly journals Computational Prediction of Mutational Effects on the SARS-CoV-2 Binding by Relative Free Energy Calculations

2020 ◽  
Author(s):  
Junjie Zou ◽  
Jian Yin ◽  
Lei Fang ◽  
Mingjun Yang ◽  
Tianyuan Wang ◽  
...  
Keyword(s):  
Free Energy ◽  
Computational Prediction ◽  
Free Energy Calculations ◽  
Alanine Scanning Mutagenesis ◽  
Angiotensin Converting Enzyme 2 ◽  
Energy Calculations ◽  
Relative Free Energy ◽  
Protein Interfaces ◽  
Computational Alanine Scanning ◽  
Entry Receptor

<p>The ability of coronaviruses infecting humans is invariably associated with their binding strengths to human receptor proteins. Both SARS-CoV-2, initially named 2019-nCoV, and SARS-CoV were reported to utilize angiotensin-converting enzyme 2 (ACE2) as entry receptor of human cells. To better understand the interplay between SARS-CoV-2 and ACE2, we performed computational alanine scanning mutagenesis, on the “hotspot” residues at protein-protein interfaces, by relative free energy calculations. Our results suggested that the binding strengths of SARS-CoV and SARS-CoV-2 to the host receptor are comparable. Free energy calculations showed a promise in assessing the infectious ability of viruses on a physical basis, and can also provide useful information for the design of antiviral drugs.</p>

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