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Abstract Small angle X‐ray scattering (SAXS) measures comprehensive distance information on a protein's structure, which can constrain and guide computational structure prediction algorithms. Here, we evaluate structure predictions of 11 monomeric and oligomeric proteins for which SAXS data were collected and provided to predictors in the 13th round of the Critical Assessment of protein Structure Prediction (CASP13). The category for SAXS‐assisted predictions made gains in certain areas for CASP13 compared to CASP12. Improvements included higher quality data with size exclusion chromatography‐SAXS (SEC‐SAXS) and better selection of targets and communication of results by CASP organizers. In several cases, we can track improvements in model accuracy with use of SAXS data. For hard multimeric targets where regular folding algorithms were unsuccessful, SAXS data helped predictors to build models better resembling the global shape of the target. For most models, however, no significant improvement in model accuracy at the domain level was registered from use of SAXS data, when rigorously comparing SAXS‐assisted models to the best regular server predictions. To promote future progress in this category, we identify successes, challenges, and opportunities for improved strategies in prediction, assessment, and communication of SAXS data to predictors. An important observation is that, for many targets, SAXS data were inconsistent with crystal structures, suggesting that these proteins adopt different conformation(s) in solution. This CASP13 result, if representative of PDB structures and future CASP targets, may have substantive implications for the structure training databases used for machine learning, CASP, and use of prediction models for biology.
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Resolving Structure of ssDNA in Solution by Fusing Molecular Simulations and Scattering Experiments with Machine Learning
Abstract Single‐stranded DNA (ssDNA) plays a pivotal role in both nanotechnology and various biological processes. Many processes and applications can be better understood with enhanced structural characterization of ssDNA; however, the dynamic nature of the molecule makes accurate characterization with atomistic resolution extremely difficult. This study uses a method that integrates experimental small‐angle X‐ray scatter (SAXS) data and molecular modeling data using a genetic algorithm (GA) to predict an all‐atom conformational ensemble of ssDNA. The results of this study also validate the performance of various AMBER force fields and implicit solvent models for ssDNA. Overall, the results are able to determine the most accurate atomistic representation of poly‐Thymine (polyT) in solution to date that closely matches the experimental SAXS observations enabling a better understanding of the behavior of ssDNA in solution.
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- Award ID(s):
- 2203979
- PAR ID:
- 10480139
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Advanced Theory and Simulations
- Volume:
- 6
- Issue:
- 12
- ISSN:
- 2513-0390
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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