Department of Chemistry, Supercomputing Facility for Bioinformatics & Computational Biology, Indian Institute of Technology, Hauz Khas, New Delhi-110016, India.
Curr Pharm Des. 2013;19(26):4687-700. doi: 10.2174/13816128113199990379.
These are exciting times for bioinformaticians, computational biologists and drug designers with the genome and proteome sequences and related structural databases growing at an accelerated pace. The post-genomic era has triggered high expectations for a rapid and successful treatment of diseases. However, in this biological information rich and functional knowledge poor scenario, the challenges are indeed grand, no less than the assembly of the genome of the whole organism. These include functional annotation of genes, identification of druggable targets, prediction of three-dimensional structures of protein targets from their amino acid sequences, arriving at lead compounds for these targets followed by a transition from bench to bedside. We propose here a "Genome to Hits In Silico" strategy (called Dhanvantari) and illustrate it on Chikungunya virus (CHIKV). "Genome to hits" is a novel pathway incorporating a series of steps such as gene prediction, protein tertiary structure determination, active site identification, hit molecule generation, docking and scoring of hits to arrive at lead compounds. The current state of the art for each of the steps in the pathway is high-lighted and the feasibility of creating an automated genome to hits assembly line is discussed.
这是生物信息学家、计算生物学家和药物设计师的激动人心的时刻,基因组和蛋白质组序列以及相关结构数据库正在以加速的速度增长。后基因组时代引发了对疾病快速和成功治疗的高度期望。然而,在这种生物信息丰富而功能知识匮乏的情况下,挑战确实是巨大的,不亚于整个生物体基因组的组装。这些包括基因的功能注释、可成药靶标的识别、根据其氨基酸序列预测蛋白质靶标的三维结构、为这些靶标找到先导化合物,然后从实验室过渡到临床。我们在这里提出了一种“从基因组到虚拟命中”的策略(称为 Dhanvantari),并在基孔肯雅病毒(CHIKV)上进行了说明。“从基因组到命中”是一种新的途径,包括一系列步骤,如基因预测、蛋白质三级结构测定、活性位点识别、命中分子生成、命中分子对接和评分,以获得先导化合物。该途径中每个步骤的当前技术水平都得到了强调,并讨论了创建自动化基因组到命中组装线的可行性。