May 10, 2016

Toward High-Throughput Predictive Modeling of Protein Binding/Unbinding Kinetics

Journal of Chemical Information and Modeling
See Hong Chiu, Lei Xie

Abstract

One of the unaddressed challenges in drug discovery is that drug potency determined in vitro is not a reliable indicator of drug activity in vivo. Accumulated evidence suggests that in vivo activity is more strongly correlated with the binding/unbinding kinetics than the equilibrium thermodynamics of protein-ligand interactions (PLIs). However, existing experimental and computational techniques are insufficient in studying the molecular details of kinetics processes of PLIs on a large scale. Consequently, we not only have limited mechanistic understanding of the kinetic processes but also lack a practical platform for high-throughput screening and optimization of drug leads on the basis of their kinetic properties. For the first time, we address this unmet need by integrating coarse-grained normal mode analysis with multitarget machine learning (MTML). To test our method, HIV-1 protease is used as a model system. We find that computational models based on the residue normal mode directionality displacement of PLIs can not only recapitulate the results from all-atom molecular dynamics simulations but also predict protein-ligand binding/unbinding kinetics accurately. When this is combined with energetic features, the accuracy of ...Continue Reading

  • References39
  • Citations7

Mentioned in this Paper

Thermodynamics
Molecular Dynamics
In Vivo
Protein Binding
Static Electricity
Ligand Binding
High Throughput Screening
Drug Potency
Plasma Protein Binding Capacity
Pharmacologic Substance

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