LZerD Protein-Protein Docking Webserver Enhanced With de novo Structure Prediction

• Main Authors: Charles Christoffer, Vijay Bharadwaj, Ryan Luu, Daisuke Kihara
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2021-08-01
• Series: Frontiers in Molecular Biosciences
• Subjects: web server; LZerD; structure modeling; protein bioinformatics; protein-protein docking; protein structure prediction
• Online Access: https://www.frontiersin.org/articles/10.3389/fmolb.2021.724947/full

Protein-protein docking is a useful tool for modeling the structures of protein complexes that have yet to be experimentally determined. Understanding the structures of protein complexes is a key component for formulating hypotheses in biophysics regarding the functional mechanisms of complexes. Protein-protein docking is an established technique for cases where the structures of the subunits have been determined. While the number of known structures deposited in the Protein Data Bank is increasing, there are still many cases where the structures of individual proteins that users want to dock are not determined yet. Here, we have integrated the AttentiveDist method for protein structure prediction into our LZerD webserver for protein-protein docking, which enables users to simply submit protein sequences and obtain full-complex atomic models, without having to supply any structure themselves. We have further extended the LZerD docking interface with a symmetrical homodimer mode. The LZerD server is available at https://lzerd.kiharalab.org/.