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Each year vast international resources are wasted on irreproducible research. The scientific community has been slow to adopt standard software engineering practices, despite the increases in high-dimensional data, complexities of workflows, and computational environments. Here we show how scientific software applications can be created in a reproducible manner when simple design goals for reproducibility are met. We describe the implementation of a test server framework and 40 scientific benchmarks, covering numerous applications in Rosetta bio-macromolecular modeling. High performance computing cluster integration allows these benchmarks to run continuously and automatically. Detailed protocol captures are useful for developers and users of Rosetta and other macromolecular modeling tools. The framework and design concepts presented here are valuable for developers and users of any type of scientific software and for the scientific community to create reproducible methods. Specific examples highlight the utility of this framework, and the comprehensive documentation illustrates the ease of adding new tests in a matter of hours.

Chemical modifications of RNA have key roles in many biological processes1–3. N7-methylguanosine (m7G) is required for integrity and stability of a large subset of tRNAs4–7. The methyltransferase 1–WD repeat-containing protein 4 (METTL1–WDR4) complex is the methyltransferase that modifies G46 in the variable loop of certain tRNAs, and its dysregulation drives tumorigenesis in numerous cancer types8–14. Mutations in WDR4 cause human developmental phenotypes including microcephaly15–17. How METTL1–WDR4 modifies tRNA substrates and is regulated remains elusive18. Here we show, through structural, biochemical and cellular studies of human METTL1–WDR4, that WDR4 serves as a scaffold for METTL1 and the tRNA T-arm. Upon tRNA binding, the αC region of METTL1 transforms into a helix, which together with the α6 helix secures both ends of the tRNA variable loop. Unexpectedly, we find that the predicted disordered N-terminal region of METTL1 is part of the catalytic pocket and essential for methyltransferase activity. Furthermore, we reveal that S27 phosphorylation in the METTL1 N-terminal region inhibits methyltransferase activity by locally disrupting the catalytic centre. Our results provide a molecular understanding of tRNA substrate recognition and phosphorylation-mediated regulation of METTL1–WDR4, and reveal the presumed disordered N-terminal region of METTL1 as a nexus of methyltransferase activity.Structures of the human METTL1–WDR4 complex are revealed, providing molecular insights into substrate recognition, modification and catalytic regulation by the N7-methylguanosine methyltransferase complex. [ABSTRACT FROM AUTHOR]

Critical Assessment of PRediction of Interactions (CAPRI) rounds 37 through 45 introduced larger complexes, new macromolecules, and multistage assemblies. For these rounds, we used and expanded docking methods in Rosetta to model 23 target complexes. We successfully predicted 14 target complexes and recognized and refined near‐native models generated by other groups for two further targets. Notably, for targets T110 and T136, we achieved the closest prediction of any CAPRI participant. We created several innovative approaches during these rounds. Since round 39 (target 122), we have used the new RosettaDock 4.0, which has a revamped coarse‐grained energy function and the ability to perform conformer selection during docking with hundreds of pregenerated protein backbones. Ten of the complexes had some degree of symmetry in their interactions, so we tested Rosetta SymDock, realized its shortcomings, and developed the next‐generation symmetric docking protocol, SymDock2, which includes docking of multiple backbones and induced‐fit refinement. Since the last CAPRI assessment, we also developed methods for modeling and designing carbohydrates in Rosetta, and we used them to successfully model oligosaccharide‐protein complexes in round 41. Although the results were broadly encouraging, they also highlighted the pressing need to invest in (a) flexible docking algorithms with the ability to model loop and linker motions and in (b) new sampling and scoring methods for oligosaccharide‐protein interactions. [ABSTRACT FROM AUTHOR]

ABSTRACT The 28th-35th rounds of the Critical Assessment of PRotein Interactions (CAPRI) served as a practical benchmark for our RosettaDock protein-protein docking protocols, highlighting strengths and weaknesses of the approach. We achieved acceptable or better quality models in three out of 11 targets. For the two α-repeat protein-green fluorescent protein (αrep-GFP) complexes, we used a novel ellipsoidal partial-global docking method (Ellipsoidal Dock) to generate models with 2.2 Å/1.5 Å interface RMSD, capturing 49%/42% of the native contacts, for the 7-/5-repeat αrep complexes. For the DNase-immunity protein complex, we used a new predictor of hydrogen-bonding networks, HBNet with Bridging Waters, to place individual water models at the complex interface; models were generated with 1.8 Å interface RMSD and 12% native water contacts recovered. The targets for which RosettaDock failed to create an acceptable model were typically difficult in general, as six had no acceptable models submitted by any CAPRI predictor. The UCH-L5-RPN13 and UCH-L5-INO80G de-ubiquitinating enzyme-inhibitor complexes comprised inhibitors undergoing significant structural changes upon binding, with the partners being highly interwoven in the docked complexes. Our failure to predict the nucleosome-enzyme complex in Target 95 was largely due to tight constraints we placed on our model based on sparse biochemical data suggesting two specific cross-interface interactions, preventing the correct structure from being sampled. While RosettaDock's three successes show that it is a state-of-the-art docking method, the difficulties with highly flexible and multi-domain complexes highlight the need for better flexible docking and domain-assembly methods. Proteins 2017; 85:479-486. © 2016 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Targeted protein degradation and induced proximity refer to strategies that leverage the recruitment of proteins to facilitate their modification, regulation or degradation. As prospective design of glues remains challenging, unbiased discovery methods are needed to unveil hidden chemical targets. Here we establish a high throughput affinity purification mass spectrometry workflow in cell lysates for the unbiased identification of molecular glue targets. By mapping the targets of 20 CRBN-binding molecular glues, we identify 298 protein targets and demonstrate the utility of enrichment methods for identifying novel targets overlooked using established methods. We use a computational workflow to estimate target confidence and perform a biochemical screen to identify a lead compound for the new non-ZF target PPIL4. Our study provides a comprehensive inventory of targets chemically recruited to CRBN and delivers a robust and scalable workflow for identifying new drug-induced protein interactions in cell lysates., Competing Interests: E.S.F. is a founder, scientific advisory board (SAB) member, and equity holder of Civetta Therapeutics, Proximity Therapeutics, Stelexis Biosciences, and Neomorph, Inc. (also board of directors). He is an equity holder and SAB member for Avilar Therapeutics, Photys Therapeutics, and Ajax Therapeutics and an equity holder in Lighthorse Therapeutics and Anvia Therapeutics. E.S.F. is a consultant to Novartis, EcoR1 capital, Odyssey and Deerfield. The Fischer lab receives or has received research funding from Deerfield, Novartis, Ajax, Interline, Bayer and Astellas. K.A.D receives or has received consulting fees from Kronos Bio and Neomorph Inc. N.S.G. is a founder, science advisory board member (SAB) and equity holder in Syros, C4, Allorion, Lighthorse, Inception, Matchpoint, Shenandoah (board member), Larkspur (board member) and Soltego (board member). The Gray lab receives or has received research funding from Novartis, Takeda, Astellas, Taiho, Jansen, Kinogen, Arbella, Deerfield, Springworks, Interline and Sanofi.