Chemotargets社がFDAと共同研究契約を締結2018年1月15日にChemotargets社はFDAと共同研究契約を締結したことを発表しました。 FDA-CDER (Center for Drug Evaluation and Research)とChemotargets社による5年間の共同研究は、Chemotargets CLARITYを使用してCDERにおける医薬品の安全性評価を強化することを目的としています。低分子のオン・ターゲットとオフ・ターゲットに関する活性、そして予測される代謝物を同定するためにChemotargets CLARITYを活用し、その有用性と性能を評価していきます。 詳細は Chemotargets CLARITYの製品情報はこちらをご覧下さい。 |
Database AutoPH4: pharmacophore analysis of multiple protein structures
Chris Williams (Chemical Computing Group ULC)
Abstract: An automated approach to summarize pocket shapes and binding hot-spots from a collection of protein structures is presented. Pocket shapes are described using pocket volumes derived from Alpha Sites and molecular surfaces. Binding hot-spots are located using pharmacophore features generated by AutoPH4. Collections of pocket volumes and pharmacophores are analyzed using feature densities which map onto a universal grid the fraction of structures that possess a given feature at each point in space. Regions with high pharmacophore feature densities identify the most persistent interaction binding hot-spots over the collection of structures. Pocket volume densities detect and classify binding site regions into core pockets and sub-pocket regions. Fingerprints that represent pocket shape, sub-pocket presence and pharmacophore feature presence are derived and used to cluster and classify multiple protein structures using standard fingerprint clustering tools. Application of the method to fragment-based drug design, minor pocket detection, selectivity mapping, binding-mode classification and custom docking scoring function creation is presented.
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