title: Coupling Protein Side-Chain and Backbone Flexibility Improves the Re-design of Protein-Ligand Specificity.
abstract: Interactions between small molecules and proteins play critical roles in regulating and facilitating diverse biological functions, yet our ability to accurately re-engineer the specificity of these interactions using computational approaches has been limited. One main difficulty, in addition to inaccuracies in energy functions, is the exquisite sensitivity of protein-ligand interactions to subtle conformational changes, coupled with the computational problem of sampling the large conformational search space of degrees of freedom of ligands, amino acid side chains, and the protein backbone. Here, we describe two benchmarks for evaluating the accuracy of computational approaches for re-engineering protein-ligand interactions: (i) prediction of enzyme specificity altering mutations and (ii) prediction of sequence tolerance in ligand binding sites. After finding that current state-of-the-art "fixed backbone" design methods perform poorly on these tests, we develop a new "coupled moves" design method in the program Rosetta that couples changes to protein sequence with alterations in both protein side-chain and protein backbone conformations, and allows for changes in ligand rigid-body and torsion degrees of freedom. We show significantly increased accuracy in both predicting ligand specificity altering mutations and binding site sequences. These methodological improvements should be useful for many applications of protein-ligand design. The approach also provides insights into the role of subtle conformational adjustments that enable functional changes not only in engineering applications but also in natural protein evolution.
authors.affiliation: Graduate Program in Bioinformatics, University of California San Francisco, San Francisco, California, United States of America.
authors.forename: Noah
authors.initials: N
authors.lastname: Ollikainen
authors.affiliation: DSM Biotechnology Center, Alexander Fleminglaan 1, Delft, The Netherlands.
authors.forename: René M
authors.initials: RM
authors.lastname: de Jong
authors.affiliation: Graduate Program in Bioinformatics, University of California San Francisco, San Francisco, California, United States of America; California Institute for Quantitative Biosciences (QB3), University of California San Francisco, San Francisco, California, United States of America; Department of Bioengineering and Therapeutic Science, University of California San Francisco, San Francisco, California, United States of America.
authors.forename: Tanja
authors.initials: T
authors.lastname: Kortemme
mesh_terms: D000595:Amino Acid Sequence; D001665:Binding Sites; D019295:Computational Biology / Q000379:methods*; D008024:Ligands; D008958:Models, Molecular; D008969:Molecular Sequence Data; D018583:Pliability; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*; D013379:Substrate Specificity
chemical_list: D008024:Ligands; D011506:Proteins