Multistate approaches in computational protein design

Computational protein design (CPD) is a useful tool for protein engineers. It has been successfully applied towards the creation of proteins with increased thermostability, improved binding affinity, novel enzymatic activity, and altered ligand specificity. Traditionally, CPD calculations search and rank sequences using a single fixed protein backbone template in an approach referred to as single‐state design (SSD). While SSD has enjoyed considerable success, certain design objectives require the explicit consideration of multiple conformational and/or chemical states. Cases where a “multistate” approach may be advantageous over the SSD approach include designing conformational changes into proteins, using native ensembles to mimic backbone flexibility, and designing ligand or oligomeric association specificities. These design objectives can be efficiently tackled using multistate design (MSD), an emerging methodology in CPD that considers any number of protein conformational or chemical states as inputs instead of a single protein backbone template, as in SSD. In this review article, recent examples of the successful design of a desired property into proteins using MSD are described. These studies employing MSD are divided into two categories—those that utilized multiple conformational states, and those that utilized multiple chemical states. In addition, the scoring of competing states during negative design is discussed as a current challenge for MSD.

[1]  Gevorg Grigoryan,et al.  Design of a heterospecific, tetrameric, 21-residue miniprotein with mixed alpha/beta structure. , 2005, Structure.

[2]  Eugene A Zhukovsky,et al.  Inactivation of TNF Signaling by Rationally Designed Dominant-Negative TNF Variants , 2003, Science.

[3]  D. Kern,et al.  Dynamic personalities of proteins , 2007, Nature.

[4]  Bruce Randall Donald,et al.  A novel ensemble-based scoring and search algorithm for protein redesign, and its application to modify the substrate specificity of the gramicidin synthetase A phenylalanine adenylation enzyme , 2004, RECOMB.

[5]  Amy E Keating,et al.  Designing specific protein–protein interactions using computation, experimental library screening, or integrated methods , 2012, Protein science : a publication of the Protein Society.

[6]  Stephen L. Mayo,et al.  Design, structure and stability of a hyperthermophilic protein variant , 1998, Nature Structural Biology.

[7]  N. Pokala,et al.  Energy functions for protein design: adjustment with protein-protein complex affinities, models for the unfolded state, and negative design of solubility and specificity. , 2005, Journal of molecular biology.

[8]  P. Harbury,et al.  Automated design of specificity in molecular recognition , 2003, Nature Structural Biology.

[9]  K. Sharp,et al.  Potential energy functions for protein design. , 2007, Current opinion in structural biology.

[10]  Roberto A Chica,et al.  Generation of longer emission wavelength red fluorescent proteins using computationally designed libraries , 2010, Proceedings of the National Academy of Sciences.

[11]  Stephen L. Mayo,et al.  An efficient algorithm for multistate protein design based on FASTER , 2010, J. Comput. Chem..

[12]  S. L. Mayo,et al.  Enzyme-like proteins by computational design , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[13]  Christopher T. Saunders,et al.  Recapitulation of protein family divergence using flexible backbone protein design. , 2005, Journal of molecular biology.

[14]  Eric A. Althoff,et al.  Kemp elimination catalysts by computational enzyme design , 2008, Nature.

[15]  J R Desjarlais,et al.  Side-chain and backbone flexibility in protein core design. , 1999, Journal of molecular biology.

[16]  D. Baker,et al.  A simple physical model for binding energy hot spots in protein–protein complexes , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[17]  D. Baker,et al.  Design of a Novel Globular Protein Fold with Atomic-Level Accuracy , 2003, Science.

[18]  Oliver F. Lange,et al.  Solution structure of a minor and transiently formed state of a T4 lysozyme mutant , 2011, Nature.

[19]  Menachem Fromer,et al.  Dead‐end elimination for multistate protein design , 2007, J. Comput. Chem..

[20]  S. L. Mayo,et al.  DREIDING: A generic force field for molecular simulations , 1990 .

[21]  Roberto A. Chica,et al.  Iterative approach to computational enzyme design , 2012, Proceedings of the National Academy of Sciences.

[22]  Tanja Kortemme,et al.  Assessment of flexible backbone protein design methods for sequence library prediction in the therapeutic antibody Herceptin–HER2 interface , 2011, Protein science : a publication of the Protein Society.

[23]  C. M. Summa,et al.  Computational de novo design, and characterization of an A(2)B(2) diiron protein. , 2002, Journal of molecular biology.

[24]  Loren L Looger,et al.  Computational design of receptors for an organophosphate surrogate of the nerve agent soman. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[25]  J. K. Lassila,et al.  Conformational diversity and computational enzyme design. , 2010, Current opinion in chemical biology.

[26]  D. Baker,et al.  Computational redesign of endonuclease DNA binding and cleavage specificity , 2006, Nature.

[27]  Stephen L Mayo,et al.  A de novo designed protein–protein interface , 2007, Protein science : a publication of the Protein Society.

[28]  Jasmine L. Gallaher,et al.  Computational Design of an Enzyme Catalyst for a Stereoselective Bimolecular Diels-Alder Reaction , 2010, Science.

[29]  David Baker,et al.  Computer-based redesign of a protein folding pathway , 2001, Nature Structural Biology.

[30]  Bruce R Donald,et al.  Predicting resistance mutations using protein design algorithms , 2010, Proceedings of the National Academy of Sciences.

[31]  Mattias Johansson,et al.  Genetic Variability of the mTOR Pathway and Prostate Cancer Risk in the European Prospective Investigation on Cancer (EPIC) , 2011, PloS one.

[32]  L Serrano,et al.  Elucidating the folding problem of alpha-helices: local motifs, long-range electrostatics, ionic-strength dependence and prediction of NMR parameters. , 1998, Journal of molecular biology.

[33]  Roberto A Chica,et al.  Semi-rational approaches to engineering enzyme activity: combining the benefits of directed evolution and rational design. , 2005, Current opinion in biotechnology.

[34]  M. Karplus,et al.  Effective energy function for proteins in solution , 1999, Proteins.

[35]  Gevorg Grigoryan,et al.  Design of protein-interaction specificity affords selective bZIP-binding peptides , 2009, Nature.

[36]  Colin A. Smith,et al.  A simple model of backbone flexibility improves modeling of side-chain conformational variability. , 2008, Journal of molecular biology.

[37]  Benjamin D Allen,et al.  Computational protein design promises to revolutionize protein engineering. , 2007, BioTechniques.

[38]  Alexander D. MacKerell,et al.  All-atom empirical potential for molecular modeling and dynamics studies of proteins. , 1998, The journal of physical chemistry. B.

[39]  T. Baker,et al.  Specificity versus stability in computational protein design. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[40]  J. Marvin,et al.  Conversion of a maltose receptor into a zinc biosensor by computational design , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[41]  Alex Nisthal,et al.  Experimental library screening demonstrates the successful application of computational protein design to large structural ensembles , 2010, Proceedings of the National Academy of Sciences.

[42]  Eric A. Althoff,et al.  De Novo Computational Design of Retro-Aldol Enzymes , 2008, Science.

[43]  Andrew Leaver-Fay,et al.  A Generic Program for Multistate Protein Design , 2011, PloS one.

[44]  Hidetoshi Kono,et al.  Computational design and characterization of a monomeric helical dinuclear metalloprotein. , 2003, Journal of molecular biology.

[45]  P. Harbury,et al.  Design of protein-ligand binding based on the molecular-mechanics energy model. , 2008, Journal of molecular biology.

[46]  Julia M. Shifman,et al.  Exploring the origins of binding specificity through the computational redesign of calmodulin , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[47]  B. Kuhlman,et al.  Computational design of a single amino acid sequence that can switch between two distinct protein folds. , 2006, Journal of the American Chemical Society.

[48]  A. Keating,et al.  Comprehensive Identification of Human bZIP Interactions with Coiled-Coil Arrays , 2003, Science.

[49]  Ian W. Davis,et al.  The backrub motion: how protein backbone shrugs when a sidechain dances. , 2006, Structure.

[50]  Tanja Kortemme,et al.  Control of protein signaling using a computationally designed GTPase/GEF orthogonal pair , 2012, Proceedings of the National Academy of Sciences.

[51]  Amy E Keating,et al.  X‐ray vs. NMR structures as templates for computational protein design , 2009, Proteins.

[52]  Geoffrey K. Hom,et al.  Full-sequence computational design and solution structure of a thermostable protein variant. , 2007, Journal of molecular biology.

[53]  D. Baker,et al.  A large scale test of computational protein design: folding and stability of nine completely redesigned globular proteins. , 2003, Journal of molecular biology.

[54]  Gevorg Grigoryan,et al.  Design of a Heterospecific, Tetrameric, 21-Residue Miniprotein with Mixed α/β Structure , 2005 .

[55]  C. Craik,et al.  Trapping Moving Targets with Small Molecules , 2009, Science.