Atomic-Accuracy Prediction of Protein Loop Structures through an RNA-Inspired Ansatz

By Rhiju Das. 2012

21 citations recorded by the source corpus.

Consistently predicting biopolymer structure at atomic resolution from sequence alone remains a difficult problem, even for small sub-segments of large proteins. Such loop prediction challenges, which arise frequently in comparative modeling and protein design, can become intractable as loop lengths exceed 10 residues and if surrounding side-chain conformations are erased. Current approaches, such as the protein local optimization protocol or kinematic inversion closure (KIC) Monte Carlo, involve stages that coarse-grain proteins, simplifying modeling but precluding a systematic search of all-atom configurations. This article introduces an alternative modeling strategy based on a ‘stepwise ansatz’, recently developed for RNA modeling, which posits that any realistic all-atom molecular conformation can be built up by residue-by-residue stepwise enumeration. When harnessed to a dynamic-programming-like recursion in the Rosetta framework, the resulting stepwise assembly (SWA) protocol enables enumerative sampling of a 12 residue loop at a significant but achievable cost of thousands of CPU-hours. In a previously established benchmark, SWA recovers crystallographic conformations with sub-Angstrom accuracy for 19 of 20 loops, compared to 14 of 20 by KIC modeling with a comparable expenditure of computational power. Furthermore, SWA gives high accuracy results on an additional set of 15 loops highlighted in the biological literature for their irregularity or unusual length. Successes include cis-Pro touch turns, loops that pass through tunnels of other side-chains, and loops of lengths up to 24 residues. Remaining problem cases are traced to inaccuracies in the Rosetta all-atom energy function. In five additional blind tests, SWA achieves sub-Angstrom accuracy models, including the first such success in a protein/RNA binding interface, the YbxF/kink-turn interaction in the fourth ‘RNA-puzzle’ competition. These results establish all-atom enumeration as an unusually systematic approach to ab initio protein structure modeling that can leverage high performance computing and physically realistic energy functions to more consistently achieve atomic accuracy.

Subfields: Materials Chemistry, Molecular Biology

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Citations in the corpus

Accurate structure prediction of CDR H3 loops enabled by a novel structure-based C-terminal constraint (2016, methodology): “One such method available in Rosetta is stepwise assembly (54), which builds the loop one residue at a time.”
RNA-Puzzles Round IV: 3D structure predictions of four ribozymes and two aptamers (2020, methodology): “In RNA-Puzzles Round I (Cruz et al. 2012), the Major group tested MC-Fold/MCSym (Parisien and Major 2008), while the Das group applied their Rosetta SWA (Das 2013) algorithm.”
Pairing a high-resolution statistical potential with a nucleobase-centric sampling algorithm for improving RNA model refinement (2021, unknown): “3C) is an example that 1 Å near-native structure is the global minimum in BRiQ, whereas the lowest energy conformation in Rosetta-SWM is around 3.5 Å.”
RNA-Puzzles Round III: 3D RNA structure prediction of five riboswitches and one ribozyme (2017, background): “…largely automated after identifying secondary structure, possible templates, and experimentally guided constraints, as noted below: Puzzle 4 This protein/RNA modeling provided an opportunity to test highresolution stepwise assembly of the RNA-contacting protein loop and is described in Das (2013).”
RosettaAntibodyDesign (RAbD): A general framework for computational antibody design (2017, methodology): “Rosetta uses CCD internally for many of its loop modeling protocols[55,56] as well as to generally close a region of a protein where a break in the”