Chica, R. A. | bioRxiv Science

bioRxiv2018

ProtaBank: A repository for protein design and engineering data

We present ProtaBank, a repository for storing, querying, analyzing, and sharing protein design and engineering data in an actively maintained and updated database. ProtaBank provides a format to describe and compare all types of protein mutational data, spanning a wide range of properties and techniques. It features a user-friendly web interface and programming layer that streamlines data deposition and allows for batch input and queries. The database schema design incorporates a standard format for reporting protein sequences and experimental data that facilitates comparison of results across different data sets. A suite of analysis and visualization tools are provided to facilitate discovery, to guide future designs, and to benchmark and train new predictive tools and algorithms. ProtaBank will provide a valuable resource to the protein engineering community by storing and safeguarding newly generated data, allowing for fast searching and identification of relevant data from the existing literature, and exploring correlations between disparate data sets. ProtaBank invites researchers to contribute data to the database to make it accessible for search and analysis. ProtaBank is available at https://protabank.org.\n\nImpactThe ProtaBank database provides a central repository for researchers to store, query, analyze, and share all types of protein engineering data. This modern database will serve a pivotal role in organizing protein engineering data and leveraging the increasingly large amounts of mutational data being generated. Together with the analysis tools, it will help scientists gain insights into sequence-function relationships, support the development of new predictive tools and algorithms, and facilitate future protein engineering efforts.\n\nAbbreviations

bioinformatics↗

bioRxiv2017

Rational design of proteins that exchange on functional timescales

Proteins are intrinsically dynamic molecules that can exchange between multiple conformational states, enabling them to carry out complex molecular processes with extreme precision and efficiency. Attempts to design novel proteins with tailored functions have mostly failed to yield efficiencies matching those found in nature because standard methods do not allow for the design of exchange between necessary conformational states on a functionally-relevant timescale. Here, we develop a broadly-applicable computational method to engineer protein dynamics that we term meta-multistate design. We used this methodology to design spontaneous exchange between two novel conformations introduced into the global fold of Streptococcal protein G domain {beta}1. The designed proteins, named DANCERs, for Dynamic And Native Conformational ExchangeRs, are stably folded and exchange between predicted conformational states on the millisecond timescale. The successful introduction of defined dynamics on functional timescales opens the door to new applications requiring a protein to spontaneously access multiple conformational states.

biophysics↗