Consistently predicting protein structure at atomic resolution from sequence alone remains an unsolved challenge in computational biophysics. Even small puzzles involving protein loops excised out of crystallographic structures can become intractable as loop lengths exceed 10 residues and if surrounding side-chain conformations are erased. This article presents a "stepwise ansatz" for recursively enumerating a physically realistic subspace of protein conformations, implemented as a stepwise assembly (SWA) protocol in the Rosetta framework. For 32 of 40 loops that challenged prior approaches, at least one of five lowest energy SWA models agrees with the crystallographic conformation with C \alpha%DIFDELCMD < } %%% RMSD accuracy better than 1.0 \AA%DIFDELCMD < }%%% . SWA successes include hairpin-like loops , cis-Pro touch turns, loops with lengths of up to 24 residues (well outside the range of previous methods), and five blind tests: all four loops of an unreleased 275-residue protein structure and an RNA-binding loop of YbxF, a target in the fourth RNA-puzzle competition. These results establish a systematic and fundamentally distinct approach to all-atom protein structure modeling that consistently outperforms Monte Carlo and refinement-based methods .
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. This article introduces a 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 %DIFDELCMD < } %%% %DIFDELCMD < }%%% 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 a systematic approach to protein structure that can leverage high performance computing and physically realistic energy functions to more consistently achieve atomic resolution .
R
protein
biopolymer
R
an unsolved challenge in computational biophysics. Even small puzzles involving protein loops excised out of crystallographic structures
a difficult problem, even for small sub-segments of large proteins. Such loop prediction challenges, which arise frequently in comparative modeling and protein design,
R
presents a "stepwise ansatz" for recursively enumerating a physically realistic subspace of protein conformations, implemented as a
introduces a 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
D
in the Rosetta framework. For 32 of 40 loops that challenged prior approaches, at least one of five lowest energy SWA models agrees with the crystallographic conformation with C
D
\alpha
D
RMSD accuracy better than 1.0
D
\AA
R
. SWA successes include hairpin-like loops ,
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
R
with lengths of
that pass through tunnels of other side-chains, and loops of lengths
R
(well outside the range of previous methods), and five blind tests: all four loops of an unreleased 275-residue protein structure and an RNA-binding loop of YbxF, a target
. 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
R
a systematic and fundamentally distinct approach to all-atom protein structure modeling that consistently outperforms Monte Carlo and refinement-based methods
all-atom enumeration as a systematic approach to protein structure that can leverage high performance computing and physically realistic energy functions to more consistently achieve atomic resolution