State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China; School of Basic Medical Sciences, Anhui Medical University, Hefei 230032, China; College of Chemistry and Environmental Science, Hebei University, Baoding 071002, China.
Suzhou Geneworks Technology Co., Ltd., Suzhou 215028, China.
Genomics Proteomics Bioinformatics. 2022 Aug;20(4):780-794. doi: 10.1016/j.gpb.2021.10.007. Epub 2022 Mar 23.
After decades of development, protein and peptide drugs have now grown into a major drug class in the marketplace. Target identification and validation are crucial for the discovery of protein and peptide drugs, and bioinformatics prediction of targets based on the characteristics of known target proteins will help improve the efficiency and success rate of target selection. However, owing to the developmental history in the pharmaceutical industry, previous systematic exploration of the target spaces has mainly focused on traditional small-molecule drugs, while studies related to protein and peptide drugs are lacking. Here, we systematically explore the target spaces in the human genome specifically for protein and peptide drugs. Compared with other proteins, both successful protein and peptide drug targets have many special characteristics, and are also significantly different from those of small-molecule drugs in many aspects. Based on these features, we develop separate effective genome-wide target prediction models for protein and peptide drugs. Finally, a user-friendly web server, Predictor Of Protein and PeptIde drugs' therapeutic Targets (POPPIT) (http://poppit.ncpsb.org.cn/), is established, which provides not only target prediction specifically for protein and peptide drugs but also abundant annotations for predicted targets.
经过几十年的发展，蛋白质和肽类药物现已成为市场上的主要药物类别。目标的鉴定和验证对于蛋白质和肽类药物的发现至关重要，基于已知靶蛋白特征的生物信息学靶预测有助于提高靶选择的效率和成功率。然而，由于制药行业的发展历史，以前对靶空间的系统探索主要集中在传统的小分子药物上，而缺乏与蛋白质和肽类药物相关的研究。在这里，我们专门针对蛋白质和肽类药物系统地探索了人类基因组中的靶空间。与其他蛋白质相比，成功的蛋白质和肽类药物靶标具有许多特殊特征，并且在许多方面与小分子药物也有显著不同。基于这些特征，我们为蛋白质和肽类药物分别开发了有效的全基因组靶标预测模型。最后，建立了一个用户友好的网络服务器，蛋白质和肽类药物治疗靶标预测器（POPPIT）（http://poppit.ncpsb.org.cn/），不仅提供了针对蛋白质和肽类药物的靶标预测，还为预测靶标提供了丰富的注释。
