Center for Bioinformatics and Quantitative Biology, and Richard and Loan Hill Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USA.
Salk Institute for Biological Studies, La Jolla, CA 92037, USA.
Nucleic Acids Res. 2024 Jul 5;52(W1):W194-W199. doi: 10.1093/nar/gkae415.
Geometric and topological properties of protein structures, including surface pockets, interior cavities and cross channels, are of fundamental importance for proteins to carry out their functions. Computed Atlas of Surface Topography of proteins (CASTp) is a widely used web server for locating, delineating, and measuring these geometric and topological properties of protein structures. Recent developments in AI-based protein structure prediction such as AlphaFold2 (AF2) have significantly expanded our knowledge on protein structures. Here we present CASTpFold, a continuation of CASTp that provides accurate and comprehensive identifications and quantifications of protein topography. It now provides (i) results on an expanded database of proteins, including the Protein Data Bank (PDB) and non-singleton representative structures of AlphaFold2 structures, covering 183 million AF2 structures; (ii) functional pockets prediction with corresponding Gene Ontology (GO) terms or Enzyme Commission (EC) numbers for AF2-predicted structures and (iii) pocket similarity search function for surface and protein-protein interface pockets. The CASTpFold web server is freely accessible at https://cfold.bme.uic.edu/castpfold/.
蛋白质结构的几何和拓扑性质，包括表面口袋、内部腔和交叉通道，对于蛋白质执行其功能至关重要。蛋白质表面形貌计算图谱（CASTp）是一个广泛使用的网络服务器，用于定位、描绘和测量蛋白质结构的这些几何和拓扑性质。基于人工智能的蛋白质结构预测的最新进展，如 AlphaFold2（AF2），大大扩展了我们对蛋白质结构的了解。这里我们提出了 CASTpFold，它是 CASTp 的延续，提供了蛋白质形貌的准确和全面的识别和量化。它现在提供了（i）在扩展的蛋白质数据库上的结果，包括蛋白质数据库（PDB）和 AlphaFold2 结构的非单一样本代表结构，涵盖了 1.83 亿个 AF2 结构；（ii）对 AF2 预测结构的功能口袋预测，以及相应的基因本体（GO）术语或酶委员会（EC）编号；（iii）用于表面和蛋白质-蛋白质界面口袋的口袋相似性搜索功能。CASTpFold 网络服务器可在 https://cfold.bme.uic.edu/castpfold/ 免费访问。
