Advances in protein structure prediction and design
Author:
Publisher
Springer Science and Business Media LLC
Subject
Cell Biology,Molecular Biology
Link
http://www.nature.com/articles/s41580-019-0163-x.pdf
Reference172 articles.
1. Jones, D. T., Singh, T., Kosciolek, T. & Tetchner, S. MetaPSICOV: combining coevolution methods for accurate prediction of contacts and long range hydrogen bonding in proteins. Bioinformatics 31, 999–1006 (2015).
2. Wang, S., Sun, S., Li, Z., Zhang, R. & Xu, J. Accurate de novo prediction of protein contact map by ultra-deep learning model. PLoS Comput. Biol. 13, e1005324 (2017). This paper presents an accurate deep learning method that predicts residue–residue contacts by integrating 1D sequence features with 2D residue covariation and pairwise interaction features.
3. Huang, J. et al. CHARMM36m: an improved force field for folded and intrinsically disordered proteins. Nat. Methods 14, 71–73 (2017).
4. Park, H. et al. Simultaneous optimization of biomolecular energy functions on features from small molecules and macromolecules. J. Chem. Theory Comput. 12, 6201–6212 (2016).
5. Heo, L. & Feig, M. Experimental accuracy in protein structure refinement via molecular dynamics simulations. Proc. Natl Acad. Sci. USA 115, 13276–13281 (2018).
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