The wf-BAKER-UNRES Branch

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Prediction of protein structure with the UNRES force field aided by contact- and secondary-structure prediction derived from evolutionarily related proteins
A.G. Lipska, M.A. Mozolewska, P. Krupa, R. Ślusarz, M. Ślusarz, and A. Liwo, Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland,
M.D. Wiśniewska, Centre of New Technologies, University of Warsaw, Banacha 2c Str., 02-097 Warsaw, Poland,
S. Ovchinnikov and D. Baker, Department of Biochemistry, and Molecular and Cellular Biology Program, University of Washington, Seattle, WA 98195, USA, and
S.N. Crivelli, Department of Computer Science, UC Davis, One Shields Ave., Davis, CA 95616, USA.

We applied a similar approach to that of wfCPUNK group, in which secondary- and contact-prediction information was implemented to aid conformational search with the physics-based united-residue (UNRES) [1] force field. However, in this branch secondary structure predictions were obtained from PsiPred and contact prediction was carried out by GREMLIN.

In the UNRES model1, a polypeptide chain is represented by a sequence of alpha-carbon atoms connected by virtual bonds with attached side chains. Two interaction sites are used to represent each amino acid: the united peptide group (p) located in the middle between two consecutive alpha-carbon atoms and the united side chain (SC). The interactions of this simplified model are described by the UNRES potential derived from the generalized cluster-cumulant expansion of a restricted free energy (RFE) function of polypeptide chains. The cumulant expansion enabled us to determine the functional forms of the multibody terms in UNRES. The effective energy function depends on temperature and has been parameterized to reproduce structure and thermodynamics of selected training proteins [2,3]. The prediction procedure involved a restrained conformational search by Multiplexed Replica Exchange Molecular Dynamics (MREMD) [4] with the UNRES force field followed by Weighted-Histogram Analysis Method (WHAM) analysis was used to calculate relative free energy of each structure of last slice of the MREMD simulation3 and a cluster analysis was employed to cluster the structures from a MREMD simulation. Five clusters with lowest free energies were chosen as prediction candidates. The conformations closest to the respective average structures corresponding to the found clusters were converted to all-atom structures and then refined by performing short restrained MD runs with the AMBER12 force field to give the models which were subsequently submitted.
Contact prediction, from which the restraints were derived, were carried out with the GREMLIN [5] method. GREMLIN works by constructing a global statistical model that simultaneously captures the conservation and co-evolution patterns in the input multiple sequence alignment. The alignments were generated using HHblits [6] and Jackhammer [7] with varying e-value and number of iterations. Strongly co-evolving residue pairs as identified by this approach, were used as restraint in modeling.

We postpone the assessment of the approach until the official release of CASP12 results.

The UNRES package is available at GREMLIN is available at

1. Liwo,A., Czaplewski,C., Ołdziej,S., Rojas,A.V., Kaźmierkiewicz,R., Makowski,M., Murarka, R.K. & Scheraga,H.A. (2008) Simulation of protein structure and dynamics with the coarse-grained UNRES force field. In: Coarse-Graining of Condensed Phase and Biomolecular Systems., ed. G. Voth, Taylor & Francis, Chapter 8, pp. 107-122.
2. Liwo,A., Khalili,M., Czaplewski,C., Kalinowski,S., Ołdziej,S., Wachucik,K. & Scheraga,H.A. (2007) Modification and optimization of the united-residue (UNRES) potential energy function for canonical simulations. I. Temperature dependence of the effective energy function and tests of the optimization method with single training proteins. J. Pys. Chem. B 111, 260-285.
3. Zaborowski,B., Jagieła,D., Czaplewski,C., Hałabis,A., Lewandowska,A., Żmudzińska,W., Ołdziej,S., Karczyńska,A., Omieczynski,C., Wirecki,T. & Liwo.A. (2015) A maximum-likelihood approach to force-field calibration. J. Chem. Inf. Model. 55, 2050-2070.
4. Czaplewski,C., Kalinowski,S., Liwo,A. & Scheraga,H.A. (2009) Application of multiplexed replica exchange molecular dynamics to the UNRES force field: Tests with α and α+β proteins. J Chem. Theory Comput. 5, 627-640.
5. Kamisetty,H., Ovchinnikov,S & Baker D. (2013) Assessing the utility of coevolution-based residue-residue contact predictions in a sequence- and structure-rich era. Proc. Natl. Acad. Sci. U.S.A., 110, 16674-16679
6. Remmert,M., Biegert,A., Hauser,A. & Söding,J. (2011) HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment. Nat Methods, 9, 173-175.
7. Eddy,S.R. (2009) A new generation of homology search tools based on probabilistic inference. Genome Inform., 23, 205-211.