Machine Learning Analysis of τRAMD Trajectories to Decipher Molecular Determinants of Drug-Target Residence Times

Machine Learning Analysis of τRAMD Trajectories to Decipher Molecular Determinants of Drug-Target Residence Times

Drug-target residence times can impact drug efficacy and safety, and are therefore increasingly being considered during lead optimization. For this purpose, computational methods to predict residence times, τ, for drug-like compounds and to derive structure-kinetic relationships are desirable. A cha...

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Bibliographic Details
Main Authors: Daria B. Kokh, Tom Kaufmann, Bastian Kister, Rebecca C. Wade
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-05-01
Series:Frontiers in Molecular Biosciences
Subjects:
drug-protein residence time
machine learning
drug-target binding kinetics
structure-kinetic relationships (SKRs)
heat shock protein 90 (HSP90)
molecular dynamics simulation
Online Access:https://www.frontiersin.org/article/10.3389/fmolb.2019.00036/full

Internet

https://www.frontiersin.org/article/10.3389/fmolb.2019.00036/full

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