Journal of Molecular BiologyBioinformaticsPeer-reviewed journal article
TMVisDB: Annotation and 3D-visualization of transmembrane proteins
Tobias OlenyiiD, Céline MarquetiD, Anastasia Grekova, Leen HouriiD, Michael HeinzingeriD, Christian DallagoiD, Burkhard RostiD
Abstract
Since the rise of cellular life, transmembrane proteins (TMPs) have been crucial to various cellular processes through their central role as gates and gatekeepers. Despite their importance, experimental high-resolution structures for TMPs remain underrepresented due to experimental challenges. Given its performance leap, structure predictions have begun to close the gap. However, identifying the membrane regions and topology in three-dimensional structure files on a large scale still requires additional in silico predictions. Here, we introduce TMVisDB to sieve through millions of predicted structures for TMPs. This resource enables both browsing through 46 million predicted TMPs and visualizing them along with their topological annotations without having to tap into costly predictions of the AlphaFold3-style. TMVisDB joins AlphaFoldDB structure predictions and transmembrane topology predictions from the protein language model (pLM) based method TMbed. We showcase the utility of TMVisDB for the analysis of proteins through two use cases, namely the B-lymphocyte antigen CD20 (Homo sapiens) and the cellulose synthase (Novosphingobium sp. P6W). We demonstrate the value of TMVisDB for large-scale analyses through findings pertaining to all TMPs predicted for the human proteome. TMVisDB is freely available at https://tmvisdb.rostlab.org
- organism: human
- assay: protein structure
- research focus: database / resource
- approach: statistical model
- Citations
- 4
- FWCI
- 1.20
- Field percentile
- top 26%
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