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Fourth European Workshop in Drug Design
May 25 - June 01, 2003
Case studies
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In silico models for ADME and cytochrome P450-mediated drug metabolism
Gabriele Cruciani, University of Perugia, Italy
The last years have seen remarkable advances in drug research, amazing development in drug design, and explosion of new computational methods in drug discovery. However, these progresses have done very little to shorten the road that goes from hits to leads to candidates to drugs1.
In fact the percentage of successful candidates compound to the total number of candidates entering the development phase remained fairly constant over the last two decades. The increased productivity of pharmaceutical industries has been negatively counterbalanced by the increased demand on the quality of the candidates.
To reduce the time-consuming development and high rate of attrition of active compounds ultimately doomed by hidden defects, medicinal chemists have come to integrate pharmacokinetic and metabolic considerations into drug design. The two major strategies used in pharmacokinetic lead optimisation are high-throughput physicochemical techniques and in silico virtual screening2.
HT-physicochemical techniques measure molecular properties of great pharmacokinetic relevance on a huge number of candidates. Conversely, in the latter strategy, numerous efforts are aimed at generating new methods and novel computable molecular descriptors applicable in structure-pharmacokinetic and metabolic relationships.
Molecular properties calculated from 3D Molecular Interaction Fields are such a novel and original approach to correlate 3D molecular structures with physicochemical pharmacokinetic and metabolic properties, to predict success of preclinical drug candidates.
The Case-Study will present and illustrate newly developed procedures to transform the information present in 3D molecular fields into powerful descriptors that are convenient to use and easy to interpret. Practical exercitations will be focused on the current status of in silico models for ADME predictions3, and on new approach for predicting cytochrome P450-mediated drug metabolism4.
References:
1. Testa B, Cruciani G, Structure “Metabolism Relations and the Challenge of Predicting Biotranformation, in : Pharmacokinetic Optimazation in Drug Research, B.Testa et al. Eds. Wiley p. 65-84 (2001).
2. Testa B, Pharmacokinetic Lead Optimazation: Fine Art vs. Blind Technology, in: Pharmacokinetic Optimazation in Drug Research, B.Testa et al. Eds. Wiley p. 615-625 (2001).
3. Cruciani, G., P. Crivori, P. A. Carrupt & B. Testa: Molecular fields in quantitative structure-permeation relationships: the VolSurf approach. J. Mol. Struct.: THEOCHEM 2000, 503, 17-30.
4. Zamora I., Afzelius L, Cruciani G. Site of Metabolism Prediction: Cytochrome P450 2C9 Case Study. J.Med.Chem2003, in press.
Combinatorial Chemical Genomics Workshop
Johanna M. Jansen and Eric Martin, Chiron Corporation, USA
This case study will address the following problem: "Presented with several genes from a hypothetical functional genomics program that were up-regulated under conditions of interest, design a combinatorial library with an enhanced probability of producing hits for 1 of the targets".
The students will use bioinformatics tools to evaluate and select the target sequence with a domain most similar to a published 3-D crystal structure. A homology model will be built, followed by virtual screening to find low molecular weight, heterocyclic fragments that complement the active site. The intramolecular interactions of these potential scaffolds will be evaluated, and a virtual library will be designed, enumerated, and filtered for "drug-like" properties.
A final round of docking this virtual library will be followed by an analysis, selection, and refinement cycle, yielding a proposed library ready for synthesis.
Ligand-based Design/Cheminformatics Workshop: Lead Generation and Lead Optimization of NMDA-NR1/2B Subtype Selective Antagonists
Wolfgang Guba, Olivier Roche, and Thierry Langer
F. Hoffmann-La Roche Ltd, Switzerland, University of Innsbruck, Austria
N-methyl-D-aspartate (NMDA) receptors are involved in a variety of physiological and pathophysiological processes in the central nervous system. NR1/2B subtype selective antagonists of the NMDA receptor have been shown to be effective in preclinical models of cerebral ischemia and traumatic brain injury1.
In order to demonstrate typical strategies and techniques in the arena of ligand-based design and cheminformatics a case study has been compiled from current literature2 and data3,4 from F. Hoffmann-La Roche Ltd in Basel, Switzerland. The participants will be able to use these data in a retrospective way for simulating the efficiency of different approaches in the lead generation and optimization of NR1/2B subtype selective NMDA receptor antagonists.
Initially, a virtual screening campaign starting from non-specific seed structures will be carried out. Various similarity metrics and 3D pharmacophore modeling will be among the tools to detect NMDA antagonists within the (hypothetical) compound stock of a pharmaceutical company. Structure-activity relationships will be used to guide the design of biased libraries for lead exploration.
An important issue in the lead optimization program is the inhibition of the hERG potassium channel which may lead to sudden death by cardiac arrhythmia. Therefore, an attempt will be made to use publicly available hERG data5 for developing an in-silico filter to (retrospectively) guide Medicinal Chemistry efforts for reducing the hERG liability of NR1/2B subtype selective NMDA receptor antagonists.
References:
1. Menniti, F.; Chenard, B.; Collins, M.; Ducat, M.; Shalaby, I.; White, F. CP-101,606, a potent neuroprotectant selective for forebrain neurons. Eur. J. Pharmacol. 1997, 331, 117-126.
2. Nikam, S. S.; Meltzer, L. T. NR2B Selective NMDA Receptor Antagonists. Current Pharmaceutical Design2002, 8, 845-855 (and references cited herein).
3. Jaeschke, G.; Alanine, A.; Bourson, A.; Buettelmann, B.; Fischer, H.; Gill, R.; Heitz, M.-P.; Huwyler, J.; Kemp, J. A.; Kansy, M.; Mutel, V.; Pinard, E.; Trube, G.; Wyler, R. Synthesis and Biological Evaluation of b-Aminosulfones as Novel NMDA-NR1/2B Subtype Selective Antagonists, oral presentation at the XVII International Symposium on Medicinal Chemistry in Barcelona, 2002.
4. Pinard, E.; Alanine, A.; Bourson, A.; Buettelmann, B.; Heitz, M.-P.; Mutel, V.; Gill, R.; Trube, G.; Wyler, R. 4-Aminoquinolines as a Novel Class of NR1/2B Subtype Selective NMDA Receptor Antagonists. Bioorg. Med. Chem. Lett.2002, 12, 2615-2619.
5. Roche, O.; Trube, G.; Zuegge, J.; Pflimlin, P.; Alanine, A.; Schneider, G. A Virtual Screening Method for Prediction of the hERG Potassium Channel Liability of Compound Libraries. ChemBioChem2002, 3, 455-459.
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