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From crystal structures and their analysis to the in silico prediction of toxic phenomena

Authors: Max Dobler, Markus A. Lill and Angelo Vedani
Journal: Helvetica Chimica Acta
Year: 2003
Issue: 86
Pages: 1554–1568

Biographics Laboratory 3R, Friedensgasse 35, 4056 Basel, Switzerland.

Dedicated to Professor Jack D. Dunitz, mentor and friend, in honour of his 80. birthday.

While the development of potential drug molecules based on the known three-dimensional structure of the macromolecular target is doubtless one of the more potent approaches to rational drug design, the estimation of associated changes in the free energy of ligand binding is all but trivial. Major obstacles include the treatment of long-range electrostatic effects and charge transfer, the calculation of solvation energies, the treatment of entropic effects and the quantification of induced fit. In the last decade, a number of computational concepts have nonetheless matured into powerful tools for the development of drug candidate molecules. These concepts have mainly focussed on the binding of the small molecule to a bioregulator. More recently, need has aroused to develop tools for a safe prediction of more complex phenomena such as metabolism, toxicity, and bioavailability.

In this account we describe the ongoing development of a virtual laboratory on the Internet to allow for a reliable in silico estimation of harmful effects triggered by drugs, chemicals and their metabolites. In the recent past, the Biographics Laboratory 3R has developed the underlying technology (5D-QSAR) and compiled a pilot project including the models of five receptor systems known to mediate adverse effects (the aryl hydrocarbon, 5HT2A, cannabinoid, GABAA, and estrogen receptor, respectively) and validated them against 280 compounds (drugs, chemicals, toxins). Within this setup we could demonstrate that our virtual laboratory is able to both recognize toxic compounds substantially different from those used in the training set as well as to classify harmless compounds as being non-toxic. This suggests that our approach can be used for the prediction of adverse effects of drug molecules and chemicals. It is the aim to provide free access to this technology - particularly to universities, hospitals and regulatory bodies as it bears a significant potential to recognize hazardous compounds early in the development process and hence improve resource and waste management and reduce animal testing.

The contributions of the honoree to this concept are manifold. A thorough analysis of small-molecule crystal structures has lead to the development of a directional force field for optimizing ligand-receptor complexes. The understanding of phenomena such as induced fit or dynamic binding have been pioneered by Professor Dunitz' analyses of dynamic properties extracted from "crystal statics". His more recent contributions to the understanding of solvation effects and entropic contributions to ligand binding are still teaching us important lessons on how to model small-molecule protein complexes.