Novel, provable algorithms for efficient ensemble-based computational protein design and their application to the redesign of the c-Raf-RBD:KRas protein-protein interface

The K* algorithm provably approximates partition functions for a set of states (e.g., protein, ligand, and protein-ligand complex) to a user-specified accuracy ε. Often, reaching an ε-approximation for a particular set of partition functions takes a prohibitive amount of time and space. To alleviate some of this cost, we introduce two algorithms into the osprey suite for protein design: fries, a Fast Removal of Inadequately Energied Sequences, and EWAK*, an Energy Window Approximation to K*. In combination, these algorithms provably retain calculational accuracy while limiting the input sequence space and the conformations included in each partition function calculation to only the most energetically favorable. This combined approach leads to significant speed-ups compared to the previous state-of-the-art multi-sequence algorithm, BBK*. As a proof of concept, we used these new algorithms to redesign the protein-protein interface (PPI) of the c-Raf-RBD:KRas complex. The Ras-binding domain of the protein kinase c-Raf (c-Raf-RBD) is the tightest known binder of KRas, a historically “undruggable” protein implicated in difficult-to-treat cancers including pancreatic ductal adenocarcinoma (PDAC). fries/EWAK* accurately retrospectively predicted the effect of 38 out of 41 different sets of mutations in the PPI of the c-Raf-RBD:KRas complex. Notably, these mutations include mutations whose effect had previously been incorrectly predicted using other computational methods. Next, we used fries/EWAK* for prospective design and discovered a novel point mutation that improves binding of c-Raf-RBD to KRas in its active, GTP-bound state (KRasGTP). We combined this new mutation with two previously reported mutations (which were also highly-ranked by osprey) to create a new variant of c-Raf-RBD, c-Raf-RBD(RKY). fries/EWAK* in osprey computationally predicted that this new variant would bind even more tightly than the previous best-binding variant, c-Raf-RBD(RK). We measured the binding affinity of c-Raf-RBD(RKY) using a bio-layer interferometry (BLI) assay and found that this new variant exhibits single-digit nanomolar affinity for KRasGTP, confirming the computational predictions made with fries/EWAK*. This study steps through the advancement and development of computational protein design by presenting theory, new algorithms, accurate retrospective designs, new prospective designs, and biochemical validation. Author summary Computational structure-based protein design is an innovative tool for redesigning proteins to introduce a particular or novel function. One such possible function is improving the binding of one protein to another, which can increase our understanding of biomedically important protein systems toward the improvement or development of novel therapeutics. Herein we introduce two novel, provable algorithms, fries and EWAK*, for more efficient computational structure-based protein design as well as their application to the redesign of the c-Raf-RBD:KRas protein-protein interface. These new algorithms speed up computational structure-based protein design while maintaining accurate calculations, allowing for larger, previously infeasible protein designs. Using fries and EWAK* within the osprey suite, we designed the tightest known binder of KRas, an “undruggable” cancer target. This new variant of a KRas-binding domain, c-Raf-RBD, should serve as an important tool to probe the protein-protein interface between KRas and its effectors as work continues toward an effective therapeutic targeting KRas.

[1]  S. Subbiah,et al.  Prediction of protein side-chain conformation by packing optimization. , 1991, Journal of molecular biology.

[2]  Bruce R Donald,et al.  Allosteric inhibition of the protein-protein interaction between the leukemia-associated proteins Runx1 and CBFbeta. , 2007, Chemistry & biology.

[3]  Young Do Kwon,et al.  Enhanced Potency of a Broadly Neutralizing HIV-1 Antibody In Vitro Improves Protection against Lentiviral Infection In Vivo , 2014, Journal of Virology.

[4]  Simon de Givry,et al.  A new framework for computational protein design through cost function network optimization , 2013, Bioinform..

[5]  M. Engelhard,et al.  Cell‐free synthesis of the Ras‐binding domain of c‐Raf‐1: binding studies to fluorescently labelled H‐Ras , 1999, FEBS letters.

[6]  Lee,et al.  New Monte Carlo algorithm: Entropic sampling. , 1993, Physical review letters.

[7]  Bruce Randall Donald,et al.  BBK* (Branch and Bound over K*): A Provable and Efficient Ensemble-Based Algorithm to Optimize Stability and Binding Affinity over Large Sequence Spaces , 2017, RECOMB.

[8]  Mona Singh,et al.  A Semidefinite Programming Approach to Side Chain Positioning with New Rounding Strategies , 2004, INFORMS J. Comput..

[9]  Pablo Gainza,et al.  OSPREY Predicts Resistance Mutations Using Positive and Negative Computational Protein Design. , 2017, Methods in molecular biology.

[10]  Y Li,et al.  Design of epitope-specific probes for sera analysis and antibody isolation , 2012, Retrovirology.

[11]  Bruce Randall Donald,et al.  Algorithms in Structural Molecular Biology , 2011 .

[12]  J. Desai,et al.  Phase 1 study evaluating the safety, tolerability, pharmacokinetics (PK), and efficacy of AMG 510, a novel small molecule KRASG12C inhibitor, in advanced solid tumors. , 2019, Journal of Clinical Oncology.

[13]  H. Maruta,et al.  The minimal fragments of c-Raf-1 and NF1 that can suppress v-Ha-Ras-induced malignant phenotype. , 1994, The Journal of biological chemistry.

[14]  J. Richardson,et al.  The penultimate rotamer library , 2000, Proteins.

[15]  S. Nosé A molecular dynamics method for simulations in the canonical ensemble , 2002 .

[16]  Alfred Wittinghofer,et al.  Quantitative Analysis of the Complex between p21 and the Ras-binding Domain of the Human Raf-1 Protein Kinase (*) , 1995, The Journal of Biological Chemistry.

[17]  Bruce Randall Donald,et al.  Minimization-Aware Recursive K^* K ∗ ( MARK^* MARK ∗ ): A Novel, Provable Algorithm that Accelerates Ensemble-Based Protein Design and Provably Approximates the Energy Landscape , 2019, RECOMB.

[18]  Roland Seifert,et al.  Faculty Opinions recommendation of K-Ras(G12C) inhibitors allosterically control GTP affinity and effector interactions. , 2013 .

[19]  Pablo Gainza,et al.  Algorithms for protein design. , 2016, Current opinion in structural biology.

[20]  Bruce Randall Donald,et al.  Improved Pruning algorithms and Divide-and-Conquer strategies for Dead-End Elimination, with application to protein design , 2006, ISMB.

[21]  S. Tzeng,et al.  Protein activity regulation by conformational entropy , 2012, Nature.

[22]  Gudrun Horn,et al.  Differential Interaction of the Ras Family GTP-binding Proteins H-Ras, Rap1A, and R-Ras with the Putative Effector Molecules Raf Kinase and Ral-Guanine Nucleotide Exchange Factor , 1996, The Journal of Biological Chemistry.

[23]  Oz Sharabi,et al.  What makes Ras an efficient molecular switch: a computational, biophysical, and structural study of Ras-GDP interactions with mutants of Raf. , 2010, Journal of molecular biology.

[24]  H. Kalbitzer,et al.  Improved Binding of Raf to Ras·GDP Is Correlated with Biological Activity* , 2009, The Journal of Biological Chemistry.

[25]  C. Der,et al.  Drugging RAS: Know the enemy , 2017, Science.

[26]  Bruce Randall Donald,et al.  Dead-End Elimination with Backbone Flexibility , 2007, ISMB/ECCB.

[27]  S. Michnick,et al.  Massive sequence perturbation of a small protein. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[28]  John C. Hunter,et al.  Biochemical and Structural Analysis of Common Cancer-Associated KRAS Mutations , 2015, Molecular Cancer Research.

[29]  Pablo Gainza,et al.  Osprey: Protein Design with Ensembles, Flexibility, and Provable Algorithms , 2022 .

[30]  S. Nosé A molecular dynamics method for simulations in the canonical ensemble , 1984 .

[31]  Bruce R Donald,et al.  Redesigning the PheA domain of gramicidin synthetase leads to a new understanding of the enzyme's mechanism and selectivity. , 2006, Biochemistry.

[32]  Neal Rosen,et al.  Allele-specific inhibitors inactivate mutant KRAS G12C by a trapping mechanism , 2016, Science.

[33]  R. Nussinov,et al.  Allosteric effects of the oncogenic RasQ61L mutant on Raf-RBD. , 2015, Structure.

[34]  Qi Sun,et al.  Discovery of small molecules that bind to K-Ras and inhibit Sos-mediated activation. , 2012, Angewandte Chemie.

[35]  A. Wittinghofer,et al.  Quantitative structure-activity analysis correlating Ras/Raf interaction in vitro to Raf activation in vivo , 1996, Nature Structural Biology.

[36]  Pablo Gainza,et al.  Compact Representation of Continuous Energy Surfaces for More Efficient Protein Design. , 2015, Journal of chemical theory and computation.

[37]  Bruce Randall Donald,et al.  CATS (Coordinates of Atoms by Taylor Series): protein design with backbone flexibility in all locally feasible directions , 2017, Bioinform..

[38]  Bruce Randall Donald,et al.  LUTE (Local Unpruned Tuple Expansion): Accurate Continuously Flexible Protein Design with General Energy Functions and Rigid-rotamer-like Efficiency , 2017, RECOMB.

[39]  Bruce R Donald,et al.  Minimization-Aware Recursive K*: A Novel, Provable Algorithm that Accelerates Ensemble-Based Protein Design and Provably Approximates the Energy Landscape , 2019, J. Comput. Biol..

[40]  F. Walker,et al.  Point Mutants of c-Raf-1 RBD with Elevated Binding to v-Ha-Ras* , 2000, The Journal of Biological Chemistry.

[41]  D. Fletcher,et al.  Quantitative biophysical analysis defines key components modulating recruitment of the GTPase KRAS to the plasma membrane , 2018, The Journal of Biological Chemistry.

[42]  Jens Meiler,et al.  ROSETTA3: an object-oriented software suite for the simulation and design of macromolecules. , 2011, Methods in enzymology.

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

[44]  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.

[45]  Rina Dechter,et al.  Dynamic Importance Sampling for Anytime Bounds of the Partition Function , 2017, NIPS.

[46]  M. Gilson,et al.  The statistical-thermodynamic basis for computation of binding affinities: a critical review. , 1997, Biophysical journal.

[47]  Kevan M. Shokat,et al.  K-Ras(G12C) inhibitors allosterically control GTP affinity and effector interactions , 2013, Nature.

[48]  W. K. Hastings,et al.  Monte Carlo Sampling Methods Using Markov Chains and Their Applications , 1970 .

[49]  S. Michnick,et al.  Massive sequence perturbation of the Raf ras binding domain reveals relationships between sequence conservation, secondary structure propensity, hydrophobic core organization and stability. , 2006, Journal of molecular biology.

[50]  Bracken M. King,et al.  Efficient Computation of Small-Molecule Configurational Binding Entropy and Free Energy Changes by Ensemble Enumeration , 2013, Journal of chemical theory and computation.

[51]  Bruce Randall Donald,et al.  Fast search algorithms for computational protein design , 2016, J. Comput. Chem..

[52]  S. L. Mayo,et al.  De novo protein design: fully automated sequence selection. , 1997, Science.

[53]  Mark A Hallen,et al.  Dead‐end elimination with perturbations (DEEPer): A provable protein design algorithm with continuous sidechain and backbone flexibility , 2013, Proteins.

[54]  Bruce Randall Donald,et al.  Algorithm for backrub motions in protein design , 2008, ISMB.

[55]  D. Baker,et al.  Native protein sequences are close to optimal for their structures. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[56]  David A. Scott,et al.  Potent and Selective Covalent Quinazoline Inhibitors of KRAS G12C. , 2017, Cell chemical biology.

[57]  S. Neidle,et al.  Equilibrium and Kinetic Measurements Reveal Rapidly Reversible Binding of Ras to Raf (*) , 1996, The Journal of Biological Chemistry.

[58]  Bruce Randall Donald,et al.  comets (Constrained Optimization of Multistate Energies by Tree Search): A Provable and Efficient Protein Design Algorithm to Optimize Binding Affinity and Specificity with Respect to Sequence , 2016, J. Comput. Biol..

[59]  P. Zarrinkar,et al.  Targeting KRAS Mutant Cancers with a Covalent G12C-Specific Inhibitor , 2018, Cell.

[60]  Thomas Schiex,et al.  Guaranteed Weighted Counting for Affinity Computation: Beyond Determinism and Structure , 2016, CP.

[61]  Jeffrey W. Martin,et al.  OSPREY 3.0: Open-Source Protein Redesign for You, with Powerful New Features , 2018, bioRxiv.

[62]  Amy C. Anderson,et al.  Computational structure-based redesign of enzyme activity , 2009, Proceedings of the National Academy of Sciences.

[63]  Pablo Gainza,et al.  Fast gap‐free enumeration of conformations and sequences for protein design , 2015, Proteins.

[64]  Thomas Schiex,et al.  Deterministic Search Methods for Computational Protein Design. , 2017, Methods in molecular biology.

[65]  Bruce Randall Donald,et al.  A Novel Minimized Dead-End Elimination Criterion and Its Application to Protein Redesign in a Hybrid Scoring and Search Algorithm for Computing Partition Functions over Molecular Ensembles , 2006, RECOMB.

[66]  Daniele Sciretti,et al.  Computational protein design with side‐chain conformational entropy , 2009, Proteins.

[67]  John C Hunter,et al.  In situ selectivity profiling and crystal structure of SML-8-73-1, an active site inhibitor of oncogenic K-Ras G12C , 2014, Proceedings of the National Academy of Sciences.

[68]  Thomas Schiex,et al.  Guaranteed Discrete Energy Optimization on Large Protein Design Problems. , 2015, Journal of chemical theory and computation.

[69]  Yi Liu,et al.  Selective Inhibition of Oncogenic KRAS Output with Small Molecules Targeting the Inactive State. , 2016, Cancer discovery.

[70]  Bruce Randall Donald,et al.  Protein Design Using Continuous Rotamers , 2012, PLoS Comput. Biol..

[71]  Gwo-Yu Chuang,et al.  Antibodies VRC01 and 10E8 Neutralize HIV-1 with High Breadth and Potency Even with Ig-Framework Regions Substantially Reverted to Germline , 2014, The Journal of Immunology.

[72]  Pablo Gainza,et al.  Protein design algorithms predict viable resistance to an experimental antifolate , 2014, Proceedings of the National Academy of Sciences.

[73]  Ralf Janknecht,et al.  Ras/Rap effector specificity determined by charge reversal , 1996, Nature Structural Biology.

[74]  Bruce Randall Donald,et al.  Computational Design of a PDZ Domain Peptide Inhibitor that Rescues CFTR Activity , 2012, PLoS Comput. Biol..

[75]  B Catimel,et al.  c-Raf-1 RBD associates with a subset of active v-H-Ras. , 2000, Biochemistry.

[76]  A R Leach,et al.  Exploring the conformational space of protein side chains using dead‐end elimination and the A* algorithm , 1998, Proteins.