Roy Burman, S. S. | Search bioRxiv

bioRxiv2018

Flexible backbone assembly and refinement of symmetrical homomeric complexes

Symmetrical homomeric proteins are ubiquitous in every domain of life, and information about their structure is essential to decipher function. The size of these complexes often makes them intractable to high-resolution structure determination experiments. Computational docking algorithms offer a promising alternative for modeling large complexes with arbitrary symmetry. Accuracy of existing algorithms, however, is limited by backbone inaccuracies when using homology-modeled monomers. Here, we present Rosetta SymDock2 with a broad search of symmetrical conformational space using a six-dimensional coarse-grained score function followed by an all-atom flexible-backbone refinement, which we demonstrate to be essential for physically-realistic modeling of tightly packed complexes. In global docking of a benchmark set of complexes of different point symmetries -- staring from homology-modeled monomers -- we successfully dock (defined as predicting three near-native structures in the five top-scoring models) 19 out of 31 cyclic complexes and 5 out of 12 dihedral complexes.\n\nHighlightsO_LISymDock2 is an algorithm to assemble symmetric protein structures from monomers\nC_LIO_LICoarse-grained score function discriminates near-native conformations\nC_LIO_LIFlexible backbone refinement is necessary to create realistic all-atom models\nC_LIO_LIResults improve six-fold and outperform other symmetric docking algorithms\nC_LI\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC=\"FIGDIR/small/409730_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (64K):\norg.highwire.dtl.DTLVardef@1e4834borg.highwire.dtl.DTLVardef@167bd2eorg.highwire.dtl.DTLVardef@1b52510org.highwire.dtl.DTLVardef@1945a02_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2017

Efficient Flexible Backbone Protein-Protein Docking for Challenging Targets

Computational prediction of protein-protein complex structures facilitates a fundamental understanding of biological mechanisms and enables therapeutics design. Binding-induced conformational changes challenge all current computational docking algorithms by exponentially increasing the conformational space to be explored. To restrict this search to relevant space, some computational docking algorithms exploit the inherent flexibility of the protein monomers to simulate conformational selection from pre-generated ensembles. As the ensemble size expands with increased protein flexibility, these methods struggle with efficiency and high false positive rates. Here, we develop and benchmark a method that efficiently samples large conformational ensembles of flexible proteins and docks them using a novel, six-dimensional, coarse-grained score function. A strong discriminative ability allows an eight-fold higher enrichment of nearnative candidate structures in the coarse-grained phase compared to a previous method. Further, the method adapts to the diversity of backbone conformations in the ensemble by modulating sampling rates. It samples 100 conformations each of the ligand and the receptor backbone while increasing computational time by only 20-80%. In a benchmark set of 88 proteins of varying degrees of flexibility, the expected success rate for blind predictions after resampling is 77% for rigid complexes, 49% for moderately flexible complexes, and 31% for highly flexible complexes. These success rates on flexible complexes are a substantial step forward from all existing methods. Additionally, for highly flexible proteins, we demonstrate that when a suitable conformer generation method exists, RosettaDock 4.0 can dock the complex successfully.\n\nSignificancePredicting binding-induced conformational plasticity in protein backbones remains a principal challenge in computational protein-protein docking. To date, there are no methods that can reliably dock proteins that undergo more than 1 [A] root-mean-squared-deviation of the backbones of the interface residues upon binding. Here, we present a method that samples backbone motions and scores conformations rapidly, obtaining-for the first time-successful docking of nearly 50% of flexible target complexes with backbone conformational change up to 2.2 [A] RMSD. This method will be applicable to a broader range of protein docking problems, which in turn will help us understand biomolecular assembly and protein function.

biophysics↗