Exploring the selectivity of PI3Kα and mTOR inhibitors by 3D-QSAR, molecular dynamics simulations and MM/GBSA binding free energy decomposition

MedChemComm ◽  
2013 ◽  
Vol 4 (11) ◽  
pp. 1482 ◽  
Author(s):  
Feng Wu ◽  
Xueyan Hou ◽  
Hao Luo ◽  
Meng Zhou ◽  
Wenjuan Zhang ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Molecular Dynamics Simulations ◽  
Binding Free Energy ◽  
Mtor Inhibitors ◽  
3D Qsar ◽  
Energy Decomposition ◽  
Free Energy Decomposition ◽  
Dynamics Simulations

Molecular dynamics simulations and binding free energy analysis of DNA minor groove complexes of curcumin

2011 ◽  
Vol 17 (11) ◽  
pp. 2805-2816 ◽  
Author(s):  
Mathew Varghese Koonammackal ◽  
Unnikrishnan Viswambharan Nair Nellipparambil ◽  
Chellappanpillai Sudarsanakumar
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Molecular Dynamics Simulations ◽  
Energy Analysis ◽  
Binding Free Energy ◽  
Minor Groove ◽  
Dna Minor Groove ◽  
Dynamics Simulations ◽  
Free Energy Analysis

scholarly journals Effect of double mutations T790M/L858R on conformation and drug-resistant mechanism of epidermal growth factor receptor explored by molecular dynamics simulations

RSC Advances ◽  
2018 ◽  
Vol 8 (70) ◽  
pp. 39797-39810 ◽  
Author(s):  
Fangfang Yan ◽  
Xinguo Liu ◽  
Shaolong Zhang ◽  
Jing Su ◽  
Qinggang Zhang ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Epidermal Growth Factor Receptor ◽  
Decomposition Method ◽  
Growth Factor Receptor ◽  
Drug Resistant ◽  
Energy Decomposition ◽  
Free Energy Decomposition ◽  
Epidermal Growth ◽  
Dynamics Simulations

The MM-GBSA method coupled with residue-based free energy decomposition method was performed to explore drug-resistant mechanisms of the mutated EGFR.

scholarly journals How quickly can we predict trimethoprim resistance using alchemical free energy methods?

2020 ◽  
Vol 10 (6) ◽  
pp. 20190141
Author(s):  
Philip W. Fowler
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Molecular Dynamics Simulations ◽  
Clinical Microbiology ◽  
Binding Free Energy ◽  
Single Mutation ◽  
Energy Methods ◽  
Synonymous Mutations ◽  
Dynamics Simulations ◽  
Alchemical Free Energy

The emergence of antimicrobial resistance threatens modern medicine and necessitates more personalized treatment of bacterial infections. Sequencing the whole genome of the pathogen(s) in a clinical sample offers one way to improve clinical microbiology diagnostic services, and has already been adopted for tuberculosis in some countries. A key weakness of a genetics clinical microbiology is it cannot return a result for rare or novel genetic variants and therefore predictive methods are required. Non-synonymous mutations in the S. aureus dfrB gene can be successfully classified as either conferring resistance (or not) by calculating their effect on the binding free energy of the antibiotic, trimethoprim. The underlying approach, alchemical free energy methods, requires large numbers of molecular dynamics simulations to be run. We show that a large number ( N = 15) of binding free energies calculated from a series of very short (50 ps) molecular dynamics simulations are able to satisfactorily classify all seven mutations in our clinically derived testset. A result for a single mutation could therefore be returned in less than an hour, thereby demonstrating that this or similar methods are now sufficiently fast and reproducible for clinical use.

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