Sugaya Nobuyoshi, Ikeda Kazuyoshi, Tashiro Toshiyuki, Takeda Shizu, Otomo Jun, Ishida Yoshiko, Shiratori Akiko, Toyoda Atsushi, Noguchi Hideki, Takeda Tadayuki, Kuhara Satoru, Sakaki Yoshiyuki, Iwayanagi Takao
PharmaDesign, Inc,, 2-19-8 Hatchobori, Chuo-ku, Tokyo, 104-0032, Japan.
BMC Pharmacol. 2007 Aug 20;7:10. doi: 10.1186/1471-2210-7-10.
Protein-protein interactions (PPIs) are challenging but attractive targets for small chemical drugs. Whole PPIs, called the 'interactome', have been emerged in several organisms, including human, based on the recent development of high-throughput screening (HTS) technologies. Individual PPIs have been targeted by small drug-like chemicals (SDCs), however, interactome data have not been fully utilized for exploring drug targets due to the lack of comprehensive methodology for utilizing these data. Here we propose an integrative in silico approach for discovering candidates for drug-targetable PPIs in interactome data.
Our novel in silico screening system comprises three independent assessment procedures: i) detection of protein domains responsible for PPIs, ii) finding SDC-binding pockets on protein surfaces, and iii) evaluating similarities in the assignment of Gene Ontology (GO) terms between specific partner proteins. We discovered six candidates for drug-targetable PPIs by applying our in silico approach to original human PPI data composed of 770 binary interactions produced by our HTS yeast two-hybrid (HTS-Y2H) assays. Among them, we further examined two candidates, RXRA/NRIP1 and CDK2/CDKN1A, with respect to their biological roles, PPI network around each candidate, and tertiary structures of the interacting domains.
An integrative in silico approach for discovering candidates for drug-targetable PPIs was applied to original human PPIs data. The system excludes false positive interactions and selects reliable PPIs as drug targets. Its effectiveness was demonstrated by the discovery of the six promising candidate target PPIs. Inhibition or stabilization of the two interactions may have potential therapeutic effects against human diseases.
蛋白质-蛋白质相互作用(PPI)是小分子化学药物具有挑战性但颇具吸引力的靶点。基于高通量筛选(HTS)技术的最新发展,包括人类在内的几种生物体中已经出现了完整的PPI,即“相互作用组”。尽管个别PPI已成为小分子类药物化学物质(SDC)的作用靶点,但由于缺乏利用这些数据的综合方法,相互作用组数据尚未被充分用于探索药物靶点。在此,我们提出一种综合的计算机方法,用于在相互作用组数据中发现可作为药物靶点的PPI候选物。
我们新颖的计算机筛选系统包括三个独立的评估程序:i)检测负责PPI的蛋白质结构域,ii)在蛋白质表面寻找SDC结合口袋,以及iii)评估特定伴侣蛋白之间基因本体(GO)术语分配的相似性。通过将我们的计算机方法应用于由我们的高通量酵母双杂交(HTS-Y2H)实验产生的770个二元相互作用组成的原始人类PPI数据,我们发现了六个可作为药物靶点的PPI候选物。其中,我们进一步研究了两个候选物RXRA/NRIP1和CDK2/CDKN1A的生物学作用、每个候选物周围的PPI网络以及相互作用结构域的三级结构。
一种用于发现可作为药物靶点的PPI候选物的综合计算机方法被应用于原始人类PPI数据。该系统排除了假阳性相互作用,并选择可靠的PPI作为药物靶点。发现的六个有前景的候选靶点PPI证明了其有效性。抑制或稳定这两种相互作用可能对人类疾病具有潜在的治疗作用。