SeqMapPDB: A Standalone Pipeline to Identify Representative Structures of Protein Sequences and Mapping Residue Indices in Real-Time at Proteome Scale
Boshen Wang (1), Xue Lei (1), Wei Tian (1), Alan Perez-Rathke (1),, Yan-Yuan Tseng (2), Jie Liang (1) ((1) University of Illinois at Chicago,, Center for Bioinformatics, Quantitative Biology, (2) Wayne State, University, Molecular Medicine, Genetics, of Biochemistry,

TL;DR
SeqMapPDB is a standalone, real-time pipeline that accurately identifies representative protein structures and maps residue indices at proteome scale, addressing limitations of static databases and resolving isomers.
Contribution
It introduces a novel computational pipeline that provides high-quality, comprehensive, and real-time mapping of protein sequences to representative structures, including isomer resolution.
Findings
Provides full sequence coverage with structural mapping
Resolves protein isomers accurately
Operates efficiently at proteome scale in real-time
Abstract
Motivation: 3D structures of proteins provide rich information for understanding their biochemical roles. Identifying the representative protein structures for protein sequences is essential for analysis of proteins at proteome scale. However, there are technical difficulties in identifying the representative structure of a given protein sequence and providing accurate mapping of residue indices. Existing databases of mapping between structures and sequences are usually static that are not suitable for studying proteomes with frequent gene model revisions. They often do not provide reliable and consistent representative structures that maximizes sequence coverage. Furthermore, proteins isomers are usually not properly resolved. Results: To overcome these difficulties, we have developed a computational pipeline called SeqMapPDB to provide high-quality representative PDB structures of…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsGenomics and Phylogenetic Studies · Machine Learning in Bioinformatics · Protein Structure and Dynamics
