A Framework to Simplify Combined Sampling Strategies in Rosetta

A core task in computational structural biology is the search of conformational space for low energy configurations of a biological macromolecule. Because conformational space has a very high dimensionality, the most successful search methods integrate some form of prior knowledge into a general sampling algorithm to reduce the effective dimensionality. However, integrating multiple types of constraints can be challenging. To streamline the incorporation of diverse constraints, we developed the Broker: an extension of the Rosetta macromolecular modeling suite that can express a wide range of protocols using constraints by combining small, independent modules, each of which implements a different set of constraints. We demonstrate expressiveness of the Broker through several code vignettes. The framework enables rapid protocol development in both biomolecular design and structural modeling tasks and thus is an important step towards exposing the rich functionality of Rosetta’s core libraries to a growing community of users addressing a diverse set of tasks in computational biology.

[1]  Ben M. Webb,et al.  Putting the Pieces Together: Integrative Modeling Platform Software for Structure Determination of Macromolecular Assemblies , 2012, PLoS biology.

[2]  Anna Walsh STUDIES IN MOLECULAR DYNAMICS , 1965 .

[3]  Oliver F Lange,et al.  Robust and highly accurate automatic NOESY assignment and structure determination with Rosetta , 2014, Journal of biomolecular NMR.

[4]  D. van der Spoel,et al.  GROMACS: A message-passing parallel molecular dynamics implementation , 1995 .

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

[6]  C Kooperberg,et al.  Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and Bayesian scoring functions. , 1997, Journal of molecular biology.

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

[8]  D. Baker,et al.  RosettaRemodel: A Generalized Framework for Flexible Backbone Protein Design , 2011, PloS one.

[9]  Berk Hess,et al.  LINCS: A linear constraint solver for molecular simulations , 1997, J. Comput. Chem..

[10]  D. Baker,et al.  Improved chemical shift based fragment selection for CS-Rosetta using Rosetta3 fragment picker , 2013, Journal of Biomolecular NMR.

[11]  David Baker,et al.  Prediction of the structure of symmetrical protein assemblies , 2007, Proceedings of the National Academy of Sciences.

[12]  Jens Meiler,et al.  ROSETTALIGAND: Protein–small molecule docking with full side‐chain flexibility , 2006, Proteins.

[13]  C. Bugg,et al.  Structure of ubiquitin refined at 1.8 A resolution. , 1987, Journal of molecular biology.

[14]  C. Ponting,et al.  The natural history of protein domains. , 2002, Annual review of biophysics and biomolecular structure.

[15]  E. Coutsias,et al.  Sub-angstrom accuracy in protein loop reconstruction by robotics-inspired conformational sampling , 2009, Nature Methods.

[16]  Stewart A. Adcock,et al.  Molecular dynamics: survey of methods for simulating the activity of proteins. , 2006, Chemical reviews.

[17]  David Baker,et al.  Proof of principle for epitope-focused vaccine design , 2014, Nature.

[18]  D. Baker,et al.  Computation-Guided Backbone Grafting of a Discontinuous Motif onto a Protein Scaffold , 2011, Science.

[19]  Yang Zhang,et al.  I-TASSER: a unified platform for automated protein structure and function prediction , 2010, Nature Protocols.

[20]  B. Alder,et al.  Studies in Molecular Dynamics. I. General Method , 1959 .

[21]  D. Baker,et al.  Simultaneous prediction of protein folding and docking at high resolution , 2009, Proceedings of the National Academy of Sciences.

[22]  Oliver F. Lange,et al.  Determination of solution structures of proteins up to 40 kDa using CS-Rosetta with sparse NMR data from deuterated samples , 2012, Proceedings of the National Academy of Sciences.

[23]  Jeffrey J. Gray,et al.  SnugDock: Paratope Structural Optimization during Antibody-Antigen Docking Compensates for Errors in Antibody Homology Models , 2010, PLoS Comput. Biol..

[24]  David Baker,et al.  Protein-protein docking with backbone flexibility. , 2007, Journal of molecular biology.

[25]  Conrad C. Huang,et al.  UCSF Chimera—A visualization system for exploratory research and analysis , 2004, J. Comput. Chem..

[26]  Ruth Nussinov,et al.  Combinatorial docking approach for structure prediction of large proteins and multi-molecular assemblies , 2005, Physical biology.

[27]  Jens Meiler,et al.  New algorithms and an in silico benchmark for computational enzyme design , 2006, Protein science : a publication of the Protein Society.

[28]  P. Kollman,et al.  Settle: An analytical version of the SHAKE and RATTLE algorithm for rigid water models , 1992 .

[29]  Sergey Lyskov,et al.  PyRosetta: a script-based interface for implementing molecular modeling algorithms using Rosetta , 2010, Bioinform..

[30]  Adrian A Canutescu,et al.  Cyclic coordinate descent: A robotics algorithm for protein loop closure , 2003, Protein science : a publication of the Protein Society.

[31]  F. Dimaio,et al.  Improved low-resolution crystallographic refinement with Phenix and Rosetta , 2014 .

[32]  D. W. Noid Studies in Molecular Dynamics , 1976 .

[33]  K Fidelis,et al.  A large‐scale experiment to assess protein structure prediction methods , 1995, Proteins.

[34]  Oliver F. Lange,et al.  Consistent blind protein structure generation from NMR chemical shift data , 2008, Proceedings of the National Academy of Sciences.

[35]  David Baker,et al.  Improved beta‐protein structure prediction by multilevel optimization of nonlocal strand pairings and local backbone conformation , 2006, Proteins.

[36]  D. Baker,et al.  Computational Design of High-Affinity Epitope Scaffolds by Backbone Grafting of a Linear Epitope , 2011, Journal of Molecular Biology.

[37]  A. Plückthun,et al.  Yet another numbering scheme for immunoglobulin variable domains: an automatic modeling and analysis tool. , 2001, Journal of molecular biology.

[38]  Andrew M Wollacott,et al.  Prediction of structures of multidomain proteins from structures of the individual domains , 2006, Protein science : a publication of the Protein Society.

[39]  William R Schief,et al.  Computational design of protein antigens that interact with the CDR H3 loop of HIV broadly neutralizing antibody 2F5 , 2014, Proteins.

[40]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.

[41]  Brian D. Weitzner,et al.  Blind prediction performance of RosettaAntibody 3.0: Grafting, relaxation, kinematic loop modeling, and full CDR optimization , 2014, Proteins.

[42]  Jeffrey J. Gray,et al.  Structure prediction of domain insertion proteins from structures of individual domains. , 2008, Structure.

[43]  David Baker,et al.  Resolution-adapted recombination of structural features significantly improves sampling in restraint-guided structure calculation , 2011, Proteins.

[44]  Oliver F. Lange,et al.  NMR Structure Determination for Larger Proteins Using Backbone-Only Data , 2010, Science.

[45]  Jeffrey J. Gray,et al.  Protein-protein docking with simultaneous optimization of rigid-body displacement and side-chain conformations. , 2003, Journal of molecular biology.

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

[47]  Jens Meiler,et al.  RosettaScripts: A Scripting Language Interface to the Rosetta Macromolecular Modeling Suite , 2011, PloS one.

[48]  C. Dominguez,et al.  HADDOCK: a protein-protein docking approach based on biochemical or biophysical information. , 2003, Journal of the American Chemical Society.

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

[50]  David Baker,et al.  High-resolution comparative modeling with RosettaCM. , 2013, Structure.