Identifying MurI uncompetitive inhibitors by correlating decomposed binding energies with bioactivity

RSC Advances ◽  
2015 ◽  
Vol 5 (51) ◽  
pp. 40536-40545 ◽  
Author(s):  
Xiu Le ◽  
Qiong Gu ◽  
Jun Xu
Keyword(s):  
Binding Energies ◽  
New Method ◽  
Free Energies ◽  
Binding Free Energies

MurI uncompetitive inhibitors can be virtually identified by a new method that correlates decomposed binding free energies with the bioactivity.

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.

scholarly journals Omicron: A heavily mutated SARS-CoV-2 variant exhibits stronger binding to ACE2 and potently escape approved COVID-19 therapeutic antibodies

2021 ◽  
Author(s):  
Masaud Shah ◽  
Hyun Goo Woo
Keyword(s):  
South Africa ◽  
Electrostatic Potential ◽  
Binding Energies ◽  
Phase Iii ◽  
Therapeutic Antibodies ◽  
Free Energies ◽  
Significant Drop ◽  
Phase Iii Clinical Trials ◽  
Computational Mutagenesis ◽  
Binding Free Energies

AbstractThe new SARS-CoV-2 variant of concern “Omicron” was recently (Nov. 24th. 2021) spotted in South Africa and already spread around the world due to its enhanced transmissibility. The variant became conspicuous as it harbors more than thirty mutations in the spike protein with 15 mutations in the RBD region alone, potentially dampening the potency of therapeutic antibodies and enhancing the ACE2 binding. More worrying, Omicron infections have been reported in individuals who have received vaccines jabs in South Africa and Hong Kong. Here, we investigated the binding strength of Omicron with ACE2 and seven monoclonal antibodies that are either approved by FDA for COVID-19 therapy or undergoing phase III clinical trials. Computational mutagenesis and binding free energies could confirm that Omicron Spike binds ACE2 stronger than prototype SARS-CoV-2. Notably, three substitutions, i.e., T478K, Q493K, and Q498R, significantly contribute to the binding energies and doubled electrostatic potential of the RBDOmic-ACE2 complex. Instead of E484K substitution that helped neutralization escape of Beta, Gamma, and Mu variants, Omicron harbors E484A substitution. Together, T478K, Q493K, Q498R, and E484A substitutions contribute to a significant drop in the electrostatic potential energies between RBDOmic-mAbs, particularly in Etesevimab, Bamlanivimab, and CT-p59. CDR diversification could help regain the neutralization strength of these antibodies; however, we could not conduct this analysis to this end. Conclusively, our findings suggest that Omicron binds ACE2 with greater affinity, enhancing its infectivity and transmissibility. Mutations in the Spike are prudently devised by the virus that enhances the receptor binding and weakens the mAbs binding to escape the immune response.

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 Protein-ligand free energies of binding from full-protein DFT calculations: convergence and choice of exchange-correlation functional

2021 ◽  
Author(s):  
Lennart Gundelach ◽  
Christofer S Tautermann ◽  
Thomas Fox ◽  
Chris-Kriton Skylaris
Keyword(s):  
Drug Discovery ◽  
Ligand Binding ◽  
Dft Calculations ◽  
Quantum Mechanical ◽  
Free Energies ◽  
Ligand Interaction ◽  
Exchange Correlation ◽  
Ligand Free ◽  
Protein Ligand Interaction ◽  
Binding Free Energies

The accurate prediction of protein-ligand binding free energies with tractable computational methods has the potential to revolutionize drug discovery. Modeling the protein-ligand interaction at a quantum mechanical level, instead of...

A computational analysis of the binding free energies of apoptosis signal-regulating kinase 1 inhibitors from different chemotypes

2021 ◽  
pp. 1-11
Author(s):  
Galyna P. Volynets ◽  
Larysa V. Pletnova ◽  
Vladislav M. Sapelkin ◽  
Oleksandr V. Savytskyi ◽  
Sergiy M. Yarmoluk
Keyword(s):  
Computational Analysis ◽  
Free Energies ◽  
Binding Free Energies

scholarly journals Doxorubicin Encapsulation in Carbon Nanotubes Having Haeckelite or Stone–Wales Defects as Drug Carriers: A Molecular Dynamics Approach

Molecules ◽  
2021 ◽  
Vol 26 (6) ◽  
pp. 1586
Author(s):  
Leonor Contreras ◽  
Ignacio Villarroel ◽  
Camila Torres ◽  
Roberto Rozas
Keyword(s):  
Carbon Nanotubes ◽  
Molecular Dynamics ◽  
Drug Delivery Systems ◽  
Nitrogen Doping ◽  
Drug Carriers ◽  
Acidic Ph ◽  
Free Energies ◽  
Interaction Forces ◽  
Chiral Nanotubes ◽  
Binding Free Energies

Doxorubicin (DOX), a recognized anticancer drug, forms stable associations with carbon nanotubes (CNTs). CNTs when properly functionalized have the ability to anchor directly in cancerous tumors where the release of the drug occurs thanks to the tumor slightly acidic pH. Herein, we study the armchair and zigzag CNTs with Stone–Wales (SW) defects to rank their ability to encapsulate DOX by determining the DOX-CNT binding free energies using the MM/PBSA and MM/GBSA methods implemented in AMBER16. We investigate also the chiral CNTs with haeckelite defects. Each haeckelite defect consists of a pair of square and octagonal rings. The armchair and zigzag CNT with SW defects and chiral nanotubes with haeckelite defects predict DOX-CNT interactions that depend on the length of the nanotube, the number of present defects and nitrogen doping. Chiral nanotubes having two haeckelite defects reveal a clear dependence on the nitrogen content with DOX-CNT interaction forces decreasing in the order 0N > 4N > 8N. These results contribute to a further understanding of drug-nanotube interactions and to the design of new drug delivery systems based on CNTs.

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