Benchmarking and Analysis of Protein Docking Performance in Rosetta v3.2

RosettaDock has been increasingly used in protein docking and design strategies in order to predict the structure of protein-protein interfaces. Here we test capabilities of RosettaDock 3.2, part of the newly developed Rosetta v3.2 modeling suite, against Docking Benchmark 3.0, and compare it with RosettaDock v2.3, the latest version of the previous Rosetta software package. The benchmark contains a diverse set of 116 docking targets including 22 antibody-antigen complexes, 33 enzyme-inhibitor complexes, and 60 ‘other’ complexes. These targets were further classified by expected docking difficulty into 84 rigid-body targets, 17 medium targets, and 14 difficult targets. We carried out local docking perturbations for each target, using the unbound structures when available, in both RosettaDock v2.3 and v3.2. Overall the performances of RosettaDock v2.3 and v3.2 were similar. RosettaDock v3.2 achieved 56 docking funnels, compared to 49 in v2.3. A breakdown of docking performance by protein complex type shows that RosettaDock v3.2 achieved docking funnels for 63% of antibody-antigen targets, 62% of enzyme-inhibitor targets, and 35% of ‘other’ targets. In terms of docking difficulty, RosettaDock v3.2 achieved funnels for 58% of rigid-body targets, 30% of medium targets, and 14% of difficult targets. For targets that failed, we carry out additional analyses to identify the cause of failure, which showed that binding-induced backbone conformation changes account for a majority of failures. We also present a bootstrap statistical analysis that quantifies the reliability of the stochastic docking results. Finally, we demonstrate the additional functionality available in RosettaDock v3.2 by incorporating small-molecules and non-protein co-factors in docking of a smaller target set. This study marks the most extensive benchmarking of the RosettaDock module to date and establishes a baseline for future research in protein interface modeling and structure prediction

RASSF1A–LATS1 signalling stabilizes replication forks by restricting CDK2-mediated phosphorylation of BRCA2

Genomic instability is a key hallmark of cancer leading to tumour heterogeneity and therapeutic resistance. ​BRCA2 has a fundamental role in error-free DNA repair but also sustains genome integrity by promoting ​RAD51 nucleofilament formation at stalled replication forks. ​CDK2 phosphorylates ​BRCA2 (pS3291-​BRCA2) to limit stabilizing contacts with polymerized ​RAD51; however, how replication stress modulates ​CDK2 activity and whether loss of pS3291-​BRCA2 regulation results in genomic instability of tumours are not known. Here we demonstrate that the Hippo pathway kinase ​LATS1 interacts with ​CDK2 in response to genotoxic stress to constrain pS3291-​BRCA2 and support ​RAD51 nucleofilaments, thereby maintaining genomic fidelity during replication stalling. We also show that ​LATS1 forms part of an ​ATR-mediated response to replication stress that requires the tumour suppressor ​RASSF1A. Importantly, perturbation of the ​ATR–​RASSF1A–​LATS1 signalling axis leads to genomic defects associated with loss of ​BRCA2 function and contributes to genomic instability and ‘BRCA-ness’ in lung cancers