Drug discovery is an intricate and costly process. Repurposing existing drugs and active compounds offers a viable pathway to develop new therapies for various diseases. By leveraging publicly available biomedical information, it is possible to predict compounds’ activity and identify their potential targets across diverse organisms. In this study, we aimed to assess the antiplasmodial activity of compounds from the Repurposing, Focused Rescue, and Accelerated Medchem (ReFRAME) library using in vitro and bioinformatics approaches. We assessed the in vitro antiplasmodial activity of the compounds using blood-stage and liver-stage drug susceptibility assays. We used protein sequences of known targets of the ReFRAME compounds with high antiplasmodial activity (EC50 < 10 uM) to conduct a protein-pairwise search to identify similar Plasmodium falciparum 3D7 proteins (from PlasmoDB) using NCBI protein BLAST. We further assessed the association between the compounds' in vitro antiplasmodial activity and level of similarity between their known and predicted P. falciparum target proteins using simple linear regression analyses. BLAST analyses revealed 735 P. falciparum proteins that were similar to the 226 known protein targets associated with the ReFRAME compounds. Antiplasmodial activity of the compounds was positively associated with the degree of similarity between the compounds’ known targets and predicted P. falciparum protein targets (percentage identity, E value, and bit score), the number of the predicted P. falciparum targets, and their respective mutagenesis index and fitness scores (R2 between 0.066 and 0.92, P < 0.05). Compounds predicted to target essential P. falciparum proteins or those with a druggability index of 1 showed the highest antiplasmodial activity. This is the first study to demonstrate a correlation between in vitro antipathogenic activity of compounds and target similarity across species. Our findings indicate that leveraging protein-target similarity may accelerate the drug repurposing process for many diseases by predicting compounds’ activity and their prospective targets in different organisms.

中文翻译：

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蛋白质靶点相似性是体外抗病原体活性的积极预测因子：恶性疟原虫的药物再利用策略


药物发现是一个复杂且昂贵的过程。重新利用现有药物和活性化合物为开发针对各种疾病的新疗法提供了一条可行的途径。通过利用公开的生物医学信息，可以预测化合物的活性并确定其在不同生物体中的潜在目标。在这项研究中，我们的目的是使用体外和生物信息学方法评估来自再利用、聚焦救援和加速 Medchem (ReFRAME) 库的化合物的抗疟原虫活性。我们使用血液阶段和肝脏阶段药物敏感性测定评估了化合物的体外抗疟原虫活性。我们使用具有高抗疟原虫活性 (EC50 < 10 uM) 的 ReFRAME 化合物的已知靶标的蛋白质序列进行蛋白质配对搜索，以使用 NCBI 蛋白质 BLAST 鉴定相似的恶性疟原虫 3D7 蛋白质（来自 PlasmoDB）。我们使用简单的线性回归分析进一步评估了化合物的体外抗疟原虫活性与其已知和预测的恶性疟原虫靶蛋白之间的相似性水平之间的关联。 BLAST 分析显示 735 种恶性疟原虫蛋白与 ReFRAME 化合物相关的 226 种已知蛋白靶点相似。化合物的抗疟原虫活性与化合物的已知靶标和预测的恶性疟原虫蛋白靶标之间的相似程度（百分比同一性、E值和位得分）、预测的恶性疟原虫靶标的数量及其它们的数量呈正相关。各自的诱变指数和适应度得分（R2在0.066和0.92之间，P < 0.05）。预计靶向恶性疟原虫必需蛋白或成药性指数为 1 的化合物显示出最高的抗疟原虫活性。 这是第一项证明化合物的体外抗病原体活性与物种间目标相似性之间相关性的研究。我们的研究结果表明，利用蛋白质靶点相似性可以通过预测化合物的活性及其在不同生物体中的预期靶点来加速许多疾病的药物再利用过程。