Less is more: Coarse-grained integrative modeling of large biomolecular assemblies with HADDOCK

Abstract

Predicting the 3D structure of protein interactions remains a challenge in the field of computational structural biology. This is in part due to difficulties in sampling the complex energy landscape of multiple interacting flexible polypeptide chains. Coarse-graining approaches, which reduce the number of degrees of freedom of the system, help address this limitation by smoothing the energy landscape, allowing an easier identification of the global energy minimum. They also accelerate the calculations, allowing to model larger assemblies. Here, we present the implementation of the MARTINI coarse-grained force field for proteins into HADDOCK, our integrative modelling platform. Docking and refinement are performed at the coarse-grained level and the resulting models are then converted back to atomistic resolution through a distance restraints-guided morphing procedure. Our protocol, tested on the largest complexes of the protein docking benchmark 5, shows an overall ~7-fold speed increase compared to standard all-atom calculations, while maintaining a similar accuracy and yielding substantially more near-native solutions. To showcase the potential of our method, we performed simultaneous 7 body docking to model the 1:6 KaiC-KaiB complex, integrating mutagenesis and hydrogen/deuterium exchange data from mass spectrometry with symmetry restraints, and validated the resulting models against a recently published cryo-EM structure.between the number of estimated protein-protein interactions and those deposited in the Protein Data Bank 4 can be overcome based solely on experimental methods 5 .Computational docking has come of age as a complement to experimental methods in order to generate 3D models of protein assemblies. In particular, data-or information-driven docking and other integrative approaches are particularly appealing 1,6-8 . While docking performs sufficiently well for small-and medium-sized proteins, applications to large biological systems, either containing large individual molecules or a large number of interactors, are limited by the significant computational cost of thoroughly sampling complex conformational landscapes.Coarse-grained (CG) models mitigate this limitation by grouping atoms into larger "pseudoatoms" or beads 9-11 , thus reducing the number of particles to consider in the computations. These models were used in the very first energy minimization of a protein in 1969 12 and again in the first docking simulation 13 .Since then, several CG models have been developed and applied to study different aspects of protein structural biology 14 . For protein docking in particular, of the CG models developed over the years, three standouts for their performance and/or success in community assessment experiments: Those implemented in ATTRACT, CABS-dock, and RosettaDock. The ATTRACT model 15,16 , developed by Zacharias and coworkers for flexible protein docking, represents the protein backbone by two pseudo-atoms and the side chains by an additional particle (or two in the case of larger amino acids). ...

An overview of data-driven HADDOCK strategies in CAPRI rounds 38-45

“…This target is particularly interesting as its structure was determined with cryo-EM and it is the largest complex featured so far in CAPRI. Therefore, it was an excellent test case for our implementation of the MARTINI coarse grain forcefield into HADDOCK 38 . Using less than ideal information (interface restraints extracted from the top model of the all-atom, server submission) we were able to accurately recreate the full decamer using five dimers with interface restraints specified only between the first two adjacent ones (i.e.…”

“…Our strategies for rounds [38][39][40][41][42][43][44][45] of CAPRI can be grouped in four categories depending on the nature of the target and the availability of information we could use to drive the docking. The first category concerns targets 121, 134 and 135 which featured protein-peptide complexes.…”

MARTINI-Based Protein-DNA Coarse-Grained HADDOCKing

“…Coarse-graining (CG) has been demonstrated to be a valuable alternative to standard atomistic (AA) approaches to alleviate some of those limitations and help the identification of the energy global minima by smoothing out the energy landscape (Hills et al, 2010; Roel-Touris et al, 2019). To this end, CG approaches group several atoms (either a few atoms or entire side chains) into larger “pseudo-atoms” or “beads,” which results into a reduction in the number of degrees of freedom of the system (Kmiecik et al, 2016).…”

“…Historically, the development of CG force fields has followed two directions: (1) Physics-based, parametrized against its atomic counterpart or (2) knowledge-based, taking advantage of the increasing growth of statistical information derived from experimentally determined structures (Hills et al, 2010). Protein or/and protein-nucleic acid coarse-grained approaches have been implemented in several docking/modeling software such as for example: CABS-dock (Blaszczyk et al, 2016) RosettaDock (Gray et al, 2003), IMP (Russel et al, 2012), ATTRACT (Setny et al, 2012), NPDock (Tuszynska et al, 2015), PyRy3D (genesilico.pl/pyry3d), and more recently in HADDOCK (Dominguez et al, 2003; Roel-Touris et al, 2019), our integrative modeling platform.…”

“…In this manuscript, we describe and benchmark the integration of the MARTINI coarse-grained force field for DNA into HADDOCK. It builds upon our recent implementation of a MARTINI coarse-grained protein-protein docking protocol (Roel-Touris et al, 2019) and is further optimized to account for Watson-Crick interactions. Prior to the docking, the input structures are converted into their coarse-grained counterparts and hydrogen-bonding base pairs are automatically detected so that a special set of parameters and restraints are used for those during the docking.…”