Literature DB >> 27624663

Constructing Interconsistent, Reasonable, and Predictive Models for Both the Kinetic and Thermodynamic Properties of HIV-1 Protease Inhibitors.

Sujun Qu1, Shuheng Huang2, Xianchao Pan2, Li Yang1,2, Hu Mei1,2.   

Abstract

Accumulated evidence suggests that the in vivo biological potency of a ligand is more strongly correlated with the binding/unbinding kinetics than the equilibrium thermodynamics of the protein-ligand interaction (PLI). However, the existing experimental and computational techniques are largely insufficient and limited in large-scale measurements or accurate predictions of the kinetic properties of PLI. In this work, elaborate efforts have been made to develop interconsistent, reasonable, and predictive models of the association rate constant (kon), dissociation rate constant (koff), and equilibrium dissociation constant (KD) of a series of HIV protease inhibitors with different structural skeletons. The results showed that nine Volsurf descriptors derived from water (OH2) and hydrophobic (DRY) probes are key molecular determinants for the kinetic and thermodynamic properties of HIV-1 protease inhibitors. To the best of our knowledge, this is the first time that interconsistent and reasonable models with strong prediction power have been established for both the kinetic and thermodynamic properties of HIV protease inhibitors.

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Year:  2016        PMID: 27624663     DOI: 10.1021/acs.jcim.6b00326

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  5 in total

Review 1.  Application of viromics: a new approach to the understanding of viral infections in humans.

Authors:  Mageshbabu Ramamurthy; Sathish Sankar; Rajesh Kannangai; Balaji Nandagopal; Gopalan Sridharan
Journal:  Virusdisease       Date:  2017-12-05

2.  Public Data Set of Protein-Ligand Dissociation Kinetic Constants for Quantitative Structure-Kinetics Relationship Studies.

Authors:  Huisi Liu; Minyi Su; Hai-Xia Lin; Renxiao Wang; Yan Li
Journal:  ACS Omega       Date:  2022-05-26

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

Authors:  Daria B Kokh; Tom Kaufmann; Bastian Kister; Rebecca C Wade
Journal:  Front Mol Biosci       Date:  2019-05-24

4.  In Silico Prediction of the Dissociation Rate Constants of Small Chemical Ligands by 3D-Grid-Based VolSurf Method.

Authors:  Shuheng Huang; Linxin Chen; Hu Mei; Duo Zhang; Tingting Shi; Zuyin Kuang; Yu Heng; Lei Xu; Xianchao Pan
Journal:  Int J Mol Sci       Date:  2020-04-02       Impact factor: 5.923

5.  Ritonavir and xk263 Binding-Unbinding with HIV-1 Protease: Pathways, Energy and Comparison.

Authors:  Jianan Sun; Mark Anthony V Raymundo; Chia-En A Chang
Journal:  Life (Basel)       Date:  2022-01-13
  5 in total

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