<b>Proteome-wide identification and comparison of drug pockets for discovering new drug indications and side effects</b>

Drug development faces significant financial and time challenges, highlighting the need for more efficient strategies. This study evaluated the druggability of the entire human proteome using Fpocket. We identified 15,043 druggable pockets in 20,255 predicted protein structures, significantly expanding the estimated druggable proteome from 3,000 to over 11,000 proteins. Notably, many druggable pockets were found in less-studied proteins, suggesting untapped therapeutic opportunities. Pairwise pocket similarity analysis identified 220,312 similar pocket pairs, with 3,241 pairs across different protein families, indicating shared drug-binding potential. In addition, 62,077 significant matches were found between druggable pockets and 1,872 known drug pockets, highlighting candidates for drug repositioning. We repositioned progesterone to ADGRD1 for pemphigus and breast cancer, and estradiol to ANO2 for shingles and medulloblastoma, which were validated by molecular docking. To assess safety, off-target effects were analyzed for the drugs such as axitinib, linking newly identified targets with known side effects. For axitinib, 127 new targets were identified and 46 out of 48 documented side effects were linked to these targets. These findings demonstrate the utility of pocket similarity in drug repositioning, target expansion, and improved drug safety evaluation, offering new avenues for the discovery of new indications and side effects of existing drugs.药物研发面临着高昂的资金与时间成本挑战，凸显出对更高效研发策略的迫切需求。本研究借助Fpocket工具，对完整人类蛋白质组的可药物结合口袋（druggable pocket）进行了成药性评估。我们在20255个预测蛋白质结构中共识别出15043个可药物结合口袋，将已估算的可药物靶向蛋白质组规模从3000个蛋白质大幅拓展至11000余个。值得注意的是，诸多可药物结合口袋存在于研究较少的蛋白质中，这意味着存在尚未被开发的治疗潜力。通过口袋两两相似性分析，我们共识别出220312对相似口袋，其中3241对来自不同蛋白质家族，表明这些口袋共享药物结合潜力。此外，在可药物结合口袋与1872个已知药物口袋之间共发现62077个显著匹配位点，为药物重定位（drug repositioning）提供了候选靶点。我们将孕酮重定位用于天疱疮与乳腺癌的ADGRD1靶点，将雌二醇重定位用于带状疱疹与髓母细胞瘤的ANO2靶点，并通过分子对接（molecular docking）验证了上述结果。为评估药物安全性，我们针对阿昔替尼（axitinib）等药物开展了脱靶效应（off-target effect）分析，将新识别的靶点与已知药物不良反应相关联。针对阿昔替尼，我们共识别出127个新靶点，且48项已记录的不良反应中有46项与这些新靶点存在关联。本研究结果证实了口袋相似性分析在药物重定位、靶点拓展以及优化药物安全性评估中的应用价值，为发现现有药物的新适应症与不良反应提供了全新路径。