A Combined Molecular Dynamics, Rigidity Analysis Approach for Studying Protein Complexes

Proteins form complexes when they bind to other molecules, which is often accompanied by a conformation change in one or both interacting partners. Details of how a compound associates with a target protein can be used to better design medicines that therapeutically regulate disease-causing proteins. Experimental and computational techniques for studying the binding process are available, however many of them are time and money intensive, or are computationally expensive, and hence cannot be done on a large dataset. In this work, we present a hybrid, computationally efficient approach for studying the stability of protein complex. We use short Molecular Dynamics (MD) simulations to generate a small ensemble of protein-complex conformations, whose flexibility we then analyze using an efficient graph-theoretic method implemented in the KINARI software. For our dataset of proteins, we show that our combined MD-rigidity analysis approach provides information about the stability of the protein-complex that would not be attained by either of the two methods alone.

[1]  B. O’Malley,et al.  Transcriptional activation by the estrogen receptor requires a conformational change in the ligand binding domain. , 1993, Molecular endocrinology.

[2]  B. Hendrickson,et al.  Regular ArticleAn Algorithm for Two-Dimensional Rigidity Percolation: The Pebble Game , 1997 .

[3]  Jacobs,et al.  Generic rigidity percolation: The pebble game. , 1995, Physical review letters.

[4]  Arthur J. Olson,et al.  AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading , 2009, J. Comput. Chem..

[5]  D S Goodsell,et al.  Automated docking of flexible ligands: Applications of autodock , 1996, Journal of molecular recognition : JMR.

[6]  Audrey Lee-St. John,et al.  Pebble game algorithms and sparse graphs , 2007, Discret. Math..

[7]  D. Jacobs,et al.  Protein flexibility predictions using graph theory , 2001, Proteins.

[8]  Yang Li,et al.  KINARI-Web: a server for protein rigidity analysis , 2011, Nucleic Acids Res..

[9]  Michael R. Shirts,et al.  Atomistic protein folding simulations on the submillisecond time scale using worldwide distributed computing. , 2003, Biopolymers.

[10]  Peter M. Kasson,et al.  GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit , 2013, Bioinform..

[11]  M. Karplus,et al.  Dynamics of ligand binding to heme proteins. , 1979, Journal of molecular biology.

[12]  Bernard Bendriem,et al.  In vivo imaging of oligonucleotides with positron emission tomography , 1998, Nature Medicine.

[13]  Karin M Reinisch,et al.  Structure of the La motif: a winged helix domain mediates RNA binding via a conserved aromatic patch , 2004, The EMBO journal.

[14]  B. Hendrickson,et al.  An Algorithm for Two-Dimensional Rigidity Percolation , 1997 .

[15]  Stephen A. Wells,et al.  Inhibition of HIV-1 protease: the rigidity perspective , 2012, Bioinform..

[16]  Shawn M. Sweeney,et al.  Mapping the Ligand-binding Sites and Disease-associated Mutations on the Most Abundant Protein in the Human, Type I Collagen* , 2002, The Journal of Biological Chemistry.

[17]  Albert C. Pan,et al.  Structure and Dynamics of the M3 Muscarinic Acetylcholine Receptor , 2012, Nature.