Dataset Information

U1A protein-stem loop 2 RNA recognition: prediction of structural differences from protein mutations.

ABSTRACT: Molecular dynamics (MD) simulations were carried out to compare the free and bound structures of wild type U1A protein with several Phe56 mutant U1A proteins that bind the target stem loop 2 (SL2) RNA with a range of affinities. The simulations indicate the free U1A protein is more flexible than the U1A-RNA complex for both wild type and Phe56 mutant systems. A complete analysis of the hydrogen-bonding (HB) and non-bonded (VDW) interactions over the course of the MD simulations suggested that changes in the interactions in the free U1A protein caused by the Phe56Ala and Phe56Leu mutations may stabilize the helical character in loop 3, and contribute to the weak binding of these proteins to SL2 RNA. Compared with wild type, changes in HB and VDW interactions in Phe56 mutants of the free U1A protein are global, and include differences in ?-sheet, loop 1 and loop 3 interactions. In the U1A-RNA complex, the Phe56Ala mutation leads to a series of differences in interactions that resonate through the complex, while the Phe56Leu and Phe56Trp mutations cause local differences around the site of mutation. The long-range networks of interactions identified in the simulations suggest that direct interactions and dynamic processes in both the free and bound forms contribute to complex stability.

SUBMITTER: Kormos BL

PROVIDER: S-EPMC3732173 | biostudies-literature | 2011 Sep

REPOSITORIES: biostudies-literature

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U1A protein-stem loop 2 RNA recognition: prediction of structural differences from protein mutations.

Kormos Bethany L BL Pieniazek Susan N SN Beveridge David L DL Baranger Anne M AM

Biopolymers 20110307 9

Molecular dynamics (MD) simulations were carried out to compare the free and bound structures of wild type U1A protein with several Phe56 mutant U1A proteins that bind the target stem loop 2 (SL2) RNA with a range of affinities. The simulations indicate the free U1A protein is more flexible than the U1A-RNA complex for both wild type and Phe56 mutant systems. A complete analysis of the hydrogen-bonding (HB) and non-bonded (VDW) interactions over the course of the MD simulations suggested that ch ...[more]

PMID: 21384338

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Project description: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.

Dataset Information

U1A protein-stem loop 2 RNA recognition: prediction of structural differences from protein mutations.

Publications

U1A protein-stem loop 2 RNA recognition: prediction of structural differences from protein mutations.

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