Back to the Future: Can physical models of passive membrane permeability help reduce drug candidate attrition and move us beyond QSPR?

Department of Chemistry & Biochemistry, University of California San Diego, La Jolla, California 92093-0340.
Chemical Biology &amp Drug Design (Impact Factor: 2.47). 10/2012; DOI: 10.1111/cbdd.12074
Source: PubMed

ABSTRACT It is widely recognized that ADMET (Adsorption, Distribution, Metabolism, Excretion - Toxicology) liabilities kill the majority of drug candidates that progress to clinical trials. The development of computational models to predict small molecule membrane permeability is therefore of considerable scientific and public health interest. Empirical qualitative structure permeability relationship (QSPR) models of permeability have been a mainstay in industrial applications, but lack a deep understanding of the underlying biological physics. Others and we have shown that implicit solvent models to predict passive permeability for small molecules exhibit mediocre predictive performance when validated across experimental test sets. Given the vast increase in computer power, more efficient parallelization schemes, and extension of current atomistic simulation codes to general use graphical processing units (GPUs), the development and application of physical models based on all-atom simulations may now be feasible. Preliminary results from rigorous free energy calculations using all-atom simulations indicate that performance relative to implicit solvent models may be improved, but many outstanding questions remain. Here we review the current state of the art physical models for passive membrane permeability prediction, and present a prospective look at promising new directions for all-atom approaches. © 2012 John Wiley & Sons A/S.

  • [Show abstract] [Hide abstract]
    ABSTRACT: The advent of silicon chip based technologies for genome sequencing promises continuing exponential falls in the reagent costs of sequencing. When every patient has a full genome sequence as part of their medical records the science of drug discovery and drug design must adapt and improve to meet this challenge. This series covers computational, and experimental approaches for small molecules and biologics. From the virtual patient - a computational model of a complete human being, through in silico screening to RNA editing and antibody directed therapies.
    Chemical Biology &amp Drug Design 01/2013; 81(1):1-4. · 2.47 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Free energy calculations are vital for our understanding of biological processes on an atomistic scale and can offer insight to various mechanisms. However, in some cases, degrees of freedom (DOFs) orthogonal to the reaction coordinate have high energy barriers and/or long equilibration times, which prohibit proper sampling. Here we identify these orthogonal DOFs when studying the transfer of a solute from water to a model membrane. Important DOFs are identified in bulk liquids of different dielectric nature with metadynamics simulations and are used as reaction coordinates for the translocation process, resulting in two- and three-dimensional space of reaction coordinates. The results are in good agreement with experiments and elucidate the pitfalls of using one-dimensional reaction coordinates. The calculations performed here offer the most detailed free energy landscape of solutes embedded in lipid bilayers to date and show that free energy calculations can be used to study complex membrane translocation phenomena.
    Journal of Physical Chemistry Letters 10/2013; 4:1781–1787. · 6.59 Impact Factor