Eugene McDermott Center for Human Growth and Development, University of Texas Southwestern Medical Center, 6001 Forest Park Rd, Dallas, TX 75390, USA.
Department of Biophysics, University of Texas Southwestern Medical Center, 6001 Forest Park Rd, Dallas, TX 75390, USA.
Database (Oxford). 2023 Mar 14;2023. doi: 10.1093/database/baad008.
Transmembrane proteins (TMPs), with diverse cellular functions, are difficult targets for structural determination. Predictions of TMPs and the locations of transmembrane segments using computational methods could be unreliable due to the potential for false positives and false negatives and show inconsistencies across different programs. Recent advances in protein structure prediction methods have made it possible to identify TMPs and their membrane-spanning regions using high-quality structural models. We developed the AlphaFold Transmembrane proteins (AFTM) database of candidate human TMPs by identifying transmembrane regions in AlphaFold structural models of human proteins and their domains using the positioning of proteins in membranes, version 3 program, followed by automatic corrections inspired by manual analysis of the results. We compared our results to annotations from the UniProt database and the Human Transmembrane Proteome (HTP) database. While AFTM did not identify transmembrane regions in some single-pass TMPs, it identified more transmembrane regions for multipass TMPs than UniProt and HTP. AFTM also showed more consistent results with experimental structures, as benchmarked against the Protein Data Bank Transmembrane proteins (PDBTM) database. In addition, some proteins previously annotated as TMPs were suggested to be non-TMPs by AFTM. We report the results of AFTM together with those of UniProt, HTP, TmAlphaFold, PDBTM and Membranome in the online AFTM database compiled as a comprehensive resource of candidate human TMPs with structural models. Database URL http://conglab.swmed.edu/AFTM.
跨膜蛋白（TMPs）具有多种细胞功能，是结构确定的困难靶点。使用计算方法预测 TMPs 和跨膜片段的位置可能不可靠，因为存在假阳性和假阴性的可能性，并且在不同的程序之间显示出不一致性。最近蛋白质结构预测方法的进展使得使用高质量的结构模型来识别 TMPs 及其跨膜区域成为可能。我们通过使用膜中蛋白质的定位版本 3 程序在 AlphaFold 结构模型中识别人类蛋白质及其结构域的跨膜区域，开发了候选人类 TMPs 的 AlphaFold 跨膜蛋白 (AFTM) 数据库，随后受手动分析结果启发自动进行了校正。我们将我们的结果与 UniProt 数据库和人类跨膜蛋白质组（HTP）数据库的注释进行了比较。虽然 AFTM 没有在一些单通道 TMPs 中识别跨膜区域，但它比 UniProt 和 HTP 识别更多的多通道 TMP 跨膜区域。AFTM 还与实验结构的一致性更好，与蛋白质数据库跨膜蛋白（PDBTM）数据库进行基准测试。此外，一些以前被注释为 TMPs 的蛋白质被 AFTM 提示为非 TMPs。我们报告了 AFTM 的结果，以及 UniProt、HTP、TmAlphaFold、PDBTM 和 Membranome 的结果，这些结果都包含在在线 AFTM 数据库中，该数据库是一个具有结构模型的候选人类 TMPs 的综合资源。数据库网址：http://conglab.swmed.edu/AFTM。
