Villoutreix Bruno O, Renault Nicolas, Lagorce David, Sperandio Olivier, Montes Matthieu, Miteva Maria A
INSERM U648, University Paris V, 45 rue des Sts Peres, 75006 Paris, France.
Curr Protein Pept Sci. 2007 Aug;8(4):381-411. doi: 10.2174/138920307781369391.
In today's research environment, a wealth of experimental/theoretical structural data is available and the number of therapeutically relevant macromolecular structures is growing rapidly. This, coupled with the huge number of small non-peptide potential drug candidates easily available (over 7 million compounds), highlight the need of using computer-aided techniques for the efficient identification and optimization of novel hit compounds. Virtual (or in silico) ligand screening based on the three-dimensional structure of macromolecular targets (SB-VLS) is firmly established as an important approach to identify chemical entities that have a high likelihood of binding to a target molecule to elicit desired biological responses. A myriad of free applications and services facilitating the drug discovery process have been posted on the Web. In this review, we cite over 350 URLs that are useful for SB-VLS projects and essentially free for academic groups. We attempt to provide links for in silico ADME/tox prediction tools, compound collections, some ligand-based methods, characterization/simulation of 3D targets and homology modeling tools, druggable pocket predictions, active site comparisons, analysis of macromolecular interfaces, protein docking tools to help identify binding pockets and protein-ligand docking/scoring methods. As such, we aim at providing both, methods pertaining to the field of Structural Bioinformatics (defined here as tools to study macromolecules) and methods pertaining to the field of Chemoinformatics (defined here as tools to make better decisions faster in the arena of drug/lead identification and optimization). We also report several recent success stories using these free computer methods. This review should help readers finding free computer tools useful for their projects. Overall, we are confident that these tools will facilitate rapid and cost-effective identification of new hit compounds. The URLs presented in this review will be updated regularly at www.vls3d.com in the coming months, "Links" section.
在当今的研究环境中,有大量的实验/理论结构数据可用,且与治疗相关的大分子结构数量正在迅速增长。这一点,再加上易于获取的大量小型非肽类潜在药物候选物(超过700万种化合物),凸显了使用计算机辅助技术来高效识别和优化新型先导化合物的必要性。基于大分子靶标的三维结构进行虚拟(或计算机模拟)配体筛选(结构-基于虚拟筛选,SB-VLS)已牢固确立为一种重要方法,用于识别极有可能与靶分子结合以引发所需生物学反应的化学实体。众多有助于药物发现过程的免费应用程序和服务已发布在网络上。在本综述中,我们引用了350多个对SB-VLS项目有用且对学术团体基本免费的网址。我们试图提供用于计算机模拟的ADME/毒性预测工具、化合物库、一些基于配体的方法、三维靶标的表征/模拟和同源建模工具、可成药口袋预测、活性位点比较、大分子界面分析、蛋白质对接工具以帮助识别结合口袋以及蛋白质-配体对接/评分方法的链接。因此,我们旨在提供与结构生物信息学领域(在此定义为研究大分子的工具)相关的方法以及与化学信息学领域(在此定义为在药物/先导物识别和优化领域更快做出更好决策的工具)相关的方法。我们还报告了使用这些免费计算机方法的几个近期成功案例。本综述应有助于读者找到对其项目有用的免费计算机工具。总体而言,我们相信这些工具将有助于快速且经济高效地识别新的先导化合物。本综述中呈现的网址将在未来几个月在www.vls3d.com的“链接”部分定期更新。