Computational design of conformation-biasing mutations to alter protein functions
Stanford University · SLAC National Accelerator Laboratory · +3 more institutions
Abstract
Conformational biasing (CB) is a rapid and streamlined computational method that uses contrastive scoring by inverse folding models to predict protein variants biased toward desired conformational states. We successfully validated CB across seven diverse datasets, identifying variants of K-Ras, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein, the β2 adrenergic receptor, and Src kinase with improved conformation-specific functions such as enhanced binding or enzymatic activity. Applying CB to the enzyme lipoic acid ligase (LplA), we uncovered a previously unknown mechanism controlling its promiscuous activity. Variants biased toward an "open" conformation state became more…
Citation impact
- FWCI
- 56.44
- Percentile
- 100%
- References
- 79
Authors
6Topics & keywords
- DNA ligase
- Enzyme
- Folding (DSP implementation)
- Protein design
- Protein folding
- Molecular dynamics
- Mechanism (biology)
- Protein structure