{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T20:33:34Z","timestamp":1772138014079,"version":"3.50.1"},"reference-count":37,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2021,12,14]],"date-time":"2021-12-14T00:00:00Z","timestamp":1639440000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,1,17]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Accurate protein side-chain modeling is crucial for protein folding and protein design. In the past decades, many successful methods have been proposed to address this issue. However, most of them depend on the discrete samples from the rotamer library, which may have limitations on their accuracies and usages. In this study, we report an open-source toolkit for protein side-chain modeling, named OPUS-Rota4. It consists of three modules: OPUS-RotaNN2, which predicts protein side-chain dihedral angles; OPUS-RotaCM, which measures the distance and orientation information between the side chain of different residue pairs and OPUS-Fold2, which applies the constraints derived from the first two modules to guide side-chain modeling. OPUS-Rota4 adopts the dihedral angles predicted by OPUS-RotaNN2 as its initial states, and uses OPUS-Fold2 to refine the side-chain conformation with the side-chain contact map constraints derived from OPUS-RotaCM. Therefore, we convert the side-chain modeling problem into a side-chain contact map prediction problem. OPUS-Fold2 is written in Python and TensorFlow2.4, which is user-friendly to include other differentiable energy terms. OPUS-Rota4 also provides a platform in which the side-chain conformation can be dynamically adjusted under the influence of other processes. We apply OPUS-Rota4 on 15 FM predictions submitted by AlphaFold2 on CASP14, the results show that the side chains modeled by OPUS-Rota4 are closer to their native counterparts than those predicted by AlphaFold2 (e.g. the residue-wise RMSD for all residues and core residues are 0.588 and 0.472 for AlphaFold2, and 0.535 and 0.407 for OPUS-Rota4).<\/jats:p>","DOI":"10.1093\/bib\/bbab529","type":"journal-article","created":{"date-parts":[[2021,11,18]],"date-time":"2021-11-18T07:10:15Z","timestamp":1637219415000},"source":"Crossref","is-referenced-by-count":16,"title":["OPUS-Rota4: a gradient-based protein side-chain modeling framework assisted by deep learning-based predictors"],"prefix":"10.1093","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0758-9693","authenticated-orcid":false,"given":"Gang","family":"Xu","sequence":"first","affiliation":[{"name":"Multiscale Research Institute of Complex Systems Fudan University Shanghai, 200433, China"},{"name":"Zhangjiang Fudan International Innovation Center Fudan University Shanghai, 201210, China"},{"name":"Shanghai AI Laboratory Shanghai, 200030, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qinghua","family":"Wang","sequence":"additional","affiliation":[{"name":"Verna and Marrs Mclean Department of Biochemistry and Molecular Biology Baylor College of Medicine Houston, Texas 77030, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianpeng","family":"Ma","sequence":"additional","affiliation":[{"name":"Multiscale Research Institute of Complex Systems Fudan University Shanghai, 200433, China"},{"name":"Zhangjiang Fudan International Innovation Center Fudan University Shanghai, 201210, China"},{"name":"Shanghai AI Laboratory Shanghai, 200030, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2021,12,15]]},"reference":[{"key":"2022012000322519600_ref1","doi-asserted-by":"crossref","first-page":"5154","DOI":"10.1021\/acs.jctc.9b00309","article-title":"OPUS-Rota2: an improved fast and accurate side-chain modeling method","volume":"15","author":"Xu","year":"2019","journal-title":"J Chem Theory Comput"},{"key":"2022012000322519600_ref2","doi-asserted-by":"crossref","first-page":"3758","DOI":"10.1093\/bioinformatics\/btaa234","article-title":"FASPR: an open-source tool for fast and accurate protein side-chain packing","volume":"36","author":"Huang","year":"2020","journal-title":"Bioinformatics"},{"key":"2022012000322519600_ref3","doi-asserted-by":"crossref","first-page":"1576","DOI":"10.1110\/ps.035022.108","article-title":"OPUS-Rota: a fast and accurate method for side-chain modeling","volume":"17","author":"Lu","year":"2008","journal-title":"Protein 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