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Document Figure 6 The combination of structure-based design and combinatorial chemistry can facilitate the generation of recombined compounds to rapidly produce potent compounds with maximum chemical and structural diversity. to provide information regarding how substituents are interacting with the target and when binding modes change. This information may be essential if SAR models are to remain predictive over large numbers of compounds. Page 534 The integrated drug discovery process utilizes as much information as is available to find and optimize initial lead compounds. Because the automated synthesis of large libraries of compounds requires reliable and versatile chemical reactions, initial libraries are designed to discover new chemical lead classes or to develop SAR models. Both library and substituent designs evolve as hits are encountered and the structures of target—inhibitor complexes are determined. Single modifications on both the template and substituents may be made during the process based on the structures of target—lead complexes. When sufficient SAR data has accumulated and the structures of target complexes with key templates and substituents have been determined, potent compounds with the desired “drug like” compositions are designed and synthesized using a structure-based recombination strategy (Figure 6). The integration of these recent advances in drug discovery offers the possibility to substantially decrease the time required to find initial leads and develop them into prototype drugs. Similarly, the interval required to produce preclinical development compounds and backup candidates is also expected to shrink. Perhaps most interesting is the potential of this integrated technology, which is ultimately based on an abstract information model of the biological process, to dramatically increase the reliability of successful drug development http://legacy.netlibrary.com/nlreader/nlReader.dll?bookid=12640&filename=Page_534.html (1 of 2) [4/9/2004 12:50:22 AM]
Document Page 535 by factoring in and refining important drug properties concurrently with the optimization of drug affinity and specificity for a specific molecular receptor. This objective is achieved by integrating assays and computational models that relate to important drug development issues (e.g., oral absorption, optimal pharmacokinetics, minimal toxicity, etc.) directly into the iterative design process. V. Chemi-Informatics The development of methods that can optimize the parallel refinement of drug potency and pharmacological properties is a key objective in enhancing the efficiency and productivity of drug discovery. To address this problem and to handle the dramatic increase in experimental data generated using robotic synthesis and assay methodologies, advanced informatics systems are required to collect and exploit data relating to the properties of the chemicals being produced. These systems will amplify the synergy between structure-based design and combinatorial chemistry and provide a means for reducing the aggregate failure rate of development candidates. The poor success rate for preclinical development candidates (about 1 in 20) results from our limited ability to predict such drug properties as intestinal absorption, excretion, metabolism, toxicity, efficacy, and side effects. Rendering the prediction more difficult is the certainty that these drug properties are composite properties that result from the operation of many biological processes. Recently, progress has been made towards understanding the underlying molecular basis for some of the individual components that contribute to the observed drug properties. For instance, the absorption of compounds into Caco-2 cells in culture may be predictive of intestinal absorption [29–31]. Retention times of compounds during artificial membrane chromatography has also been correlated with oral absorption [32]. Recently, molecular transporters have been identified, cloned, and characterized that are responsible for the absorption of dipeptides and the excretion of organic cations [33,34]. The enzymatic basis for the metabolism of xenobiotics (cytochrome P450, glutathione transferase, etc.) has been known for some time, at least in part. In fact, many of the individual components of the composite biological processes can be developed into high-throughput assays, providing the opportunity to collect SAR data and develop SAR models. These observations, together with the integrated structure-based design and combinatorial chemical technology described here, define a comprehensive new strategy for drug discovery that has the potential to reduce the aggregate failure rate for development candidates (Figure 4). The creation of virtual libraries of compounds that are readily accessible through the use of automated http://legacy.netlibrary.com/nlreader/nlReader.dll?bookid=12640&filename=Page_535.html [4/9/2004 12:50:24 AM]
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Structure-based Drug Design 14 Stru
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