Godinez-Macias Karla P, Chen Daisy, Wallis J Lincoln, Siegel Miles G, Adam Anna, Bopp Selina, Carolino Krypton, Coulson Lauren B, Durst Greg, Thathy Vandana, Esherick Lisl, Farringer Madeline A, Flannery Erika L, Forte Barbara, Liu Tiqing, Godoy Magalhaes Luma, Gupta Anil K, Istvan Eva S, Jiang Tiantian, Kumpornsin Krittikorn, Lobb Karen, McLean Kyle J, Moura Igor M R, Okombo John, Payne N Connor, Plater Andrew, Rao Srinivasa P S, Siqueira-Neto Jair L, Somsen Bente A, Summers Robert L, Zhang Rumin, Gilson Michael K, Gamo Francisco-Javier, Campo Brice, Baragaña Beatriz, Duffy James, Gilbert Ian H, Lukens Amanda K, Dechering Koen J, Niles Jacquin C, McNamara Case W, Cheng Xiu, Birkholtz Lyn-Marie, Bronkhorst Alfred W, Fidock David A, Wirth Dyann F, Goldberg Daniel E, Lee Marcus C S, Winzeler Elizabeth A
Department of Pediatrics, University of California, San Diego, La Jolla, CA USA.
Panorama Global, 2101 4th Ave, Ste 2100, Seattle, WA USA.
NPJ Drug Discov. 2025;2(1):3. doi: 10.1038/s44386-025-00006-5. Epub 2025 Mar 4.
Identification of novel drug targets is a key component of modern drug discovery. While antimalarial targets are often identified through the mechanism of action studies on phenotypically derived inhibitors, this method tends to be time- and resource-consuming. The discoverable target space is also constrained by existing compound libraries and phenotypic assay conditions. Leveraging recent advances in protein structure prediction, we systematically assessed the genome and identified 867 candidate protein targets with evidence of small-molecule binding and blood-stage essentiality. Of these, 540 proteins showed strong essentiality evidence and lack inhibitors that have progressed to clinical trials. Expert review and rubric-based scoring of this subset based on additional criteria such as selectivity, structural information, and assay developability yielded 27 high-priority antimalarial target candidates. This study also provides a genome-wide data resource for and implements a generalizable framework for systematically evaluating and prioritizing novel pathogenic disease targets.
鉴定新型药物靶点是现代药物发现的关键组成部分。虽然抗疟靶点通常是通过对表型衍生抑制剂的作用机制研究来确定的，但这种方法往往耗费时间和资源。可发现的靶点空间也受到现有化合物库和表型分析条件的限制。利用蛋白质结构预测的最新进展，我们系统地评估了基因组，并确定了867个具有小分子结合证据和血液阶段必需性的候选蛋白质靶点。其中，540种蛋白质显示出强有力的必需性证据，且缺乏已进入临床试验阶段的抑制剂。基于选择性、结构信息和分析可开发性等附加标准，对该子集进行专家评审和基于评分标准的评分，产生了27个高优先级抗疟靶点候选物。本研究还提供了全基因组数据资源，并实施了一个可推广的框架，用于系统地评估新型致病疾病靶点并对其进行优先级排序。
