title: Coarse-grained versus atomistic simulations: realistic interaction free energies for real proteins.
abstract: BACKGROUND
  To assess whether two proteins will interact under physiological conditions, information on the interaction free energy is needed. Statistical learning techniques and docking methods for predicting protein-protein interactions cannot quantitatively estimate binding free energies. Full atomistic molecular simulation methods do have this potential, but are completely unfeasible for large-scale applications in terms of computational cost required. Here we investigate whether applying coarse-grained (CG) molecular dynamics simulations is a viable alternative for complexes of known structure.
  
  
  RESULTS
  We calculate the free energy barrier with respect to the bound state based on molecular dynamics simulations using both a full atomistic and a CG force field for the TCR-pMHC complex and the MP1-p14 scaffolding complex. We find that the free energy barriers from the CG simulations are of similar accuracy as those from the full atomistic ones, while achieving a speedup of >500-fold. We also observe that extensive sampling is extremely important to obtain accurate free energy barriers, which is only within reach for the CG models. Finally, we show that the CG model preserves biological relevance of the interactions: (i) we observe a strong correlation between evolutionary likelihood of mutations and the impact on the free energy barrier with respect to the bound state; and (ii) we confirm the dominant role of the interface core in these interactions. Therefore, our results suggest that CG molecular simulations can realistically be used for the accurate prediction of protein-protein interaction strength.
  
  
  METHODS
  The python analysis framework and data files are available for download at http://www.ibi.vu.nl/downloads/bioinformatics-2013-btt675.tgz.
authors.affiliation: Centre for Integrative Bioinformatics (IBIVU), VU University Amsterdam, Amsterdam Institute for Molecules Medicines and Systems (AIMMS), VU University Amsterdam, Department of Preventive Dentistry, Academic Centre for Dentistry Amsterdam (ACTA), University of Amsterdam and VU University Amsterdam, Netherlands Bioinformatics Centre (NBIC), Geert Grooteplein 28 6525 GA Nijmegen, The Netherlands and Department of Biological Psychology, VU University Amsterdam, 1081 HV Amsterdam, The Netherlands.
authors.forename: Ali
authors.initials: A
authors.lastname: May
authors.forename: René
authors.initials: R
authors.lastname: Pool
authors.forename: Erik
authors.initials: E
authors.lastname: van Dijk
authors.forename: Jochem
authors.initials: J
authors.lastname: Bijlard
authors.forename: Sanne
authors.initials: S
authors.lastname: Abeln
authors.forename: Jaap
authors.initials: J
authors.lastname: Heringa
authors.forename: K Anton
authors.initials: KA
authors.lastname: Feenstra
mesh_terms: D056004:Molecular Dynamics Simulation; D046912:Multiprotein Complexes / Q000737:chemistry / Q000235:genetics; D009154:Mutation; D025941:Protein Interaction Mapping / Q000379:methods*; D013816:Thermodynamics
chemical_list: D046912:Multiprotein Complexes