Kolte Baban S, Londhe Sanjay R, Solanki Bhushan R, Gacche Rajesh N, Meshram Rohan J
Bioinformatics Centre, Savitribai Phule Pune University, Pune, 411007, India.
Tech Mahindra Pvt Ltd, Pune, 411006, India.
J Mol Graph Model. 2018 Mar;80:95-103. doi: 10.1016/j.jmgm.2017.12.020. Epub 2018 Jan 6.
Finding novel chemical agents for targeting disease associated drug targets often requires screening of large number of new chemical libraries. In silico methods are generally implemented at initial stages for virtual screening. Filtering of such compound libraries on physicochemical and substructure ground is done to ensure elimination of compounds with undesired chemical properties. Filtering procedure, is redundant, time consuming and requires efficient bioinformatics/computer manpower along with high end software involving huge capital investment that forms a major obstacle in drug discovery projects in academic setup. We present an open source resource, FilTer BaSe- a chemoinformatics platform (http://bioinfo.net.in/filterbase/) that host fully filtered, ready to use compound libraries with workable size. The resource also hosts a database that enables efficient searching the chemical space of around 348,000 compounds on the basis of physicochemical and substructure properties. Ready to use compound libraries and database presented here is expected to aid a helping hand for new drug developers and medicinal chemists.
寻找针对疾病相关药物靶点的新型化学药剂通常需要筛选大量新的化学文库。计算机辅助方法通常在初始阶段用于虚拟筛选。基于物理化学和子结构对这类化合物文库进行筛选,以确保排除具有不良化学性质的化合物。筛选过程繁琐、耗时,需要高效的生物信息学/计算机人力以及涉及巨额资本投资的高端软件,这在学术机构的药物发现项目中构成了主要障碍。我们展示了一个开源资源——FilTer BaSe,一个化学信息学平台(http://bioinfo.net.in/filterbase/),它拥有经过充分筛选、大小合适且可供直接使用的化合物文库。该资源还拥有一个数据库,能够基于物理化学和子结构性质高效搜索约348,000种化合物的化学空间。这里展示的可供直接使用的化合物文库和数据库有望为新药开发者和药物化学家提供帮助。