Protein Structure Refinement Guided by Atomic Packing Frustration Analysis
Recent advances in machine learning, bioinformatics and the understanding of the folding problem have enabled efficient predictions of protein structures with moderate accuracy, even for targets when there is little information from templates. All-atom molecular dynamics simulations provide a route to refine such predicted structures, but unguided atomic simulations, even when lengthy in time, often fail to eliminate incorrect structural features that would allow the structure to become more energetically favorable owing to the necessity of making large scale motions and overcoming energy barriers for side chain repacking. In this study, we show that localizing packing frustration at atomic resolution by examining the statistics of the energetic changes that occur when the local environment of a site is changed allows one to identify the most likely locations of incorrect contacts. The global statistics of atomic resolution frustration in structures that have been predicted using various algorithms provide strong indicators of structural quality when tested over a database of 20 targets from previous CASP experiments. Residues that are more correctly located turn out to be more minimally frustrated than more poorly positioned sites. These observations provide a diagnosis of both global and local quality of predicted structures, and thus can be used as guidance in all-atom refinement simulations of the 20 targets. Refinement simulations guided by frustration turn out to be quite efficient and significantly improve the quality of the structures. ### Competing Interest Statement The authors have declared no competing interest.
- Downloaded 234 times
- Download rankings, all-time:
- Site-wide: 151,217
- In biophysics: 5,601
- Year to date:
- Site-wide: 144,396
- Since beginning of last month:
- Site-wide: 98,192
Downloads over time
Distribution of downloads per paper, site-wide
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!