eprintid: 1460206 rev_number: 58 eprint_status: archive userid: 608 dir: disk0/01/46/02/06 datestamp: 2015-03-20 16:29:34 lastmod: 2021-09-20 00:06:45 status_changed: 2015-03-20 16:29:34 type: article metadata_visibility: show item_issues_count: 0 creators_name: Jones, DT creators_name: Singh, T creators_name: Kosciolek, T creators_name: Tetchner, S title: MetaPSICOV: combining coevolution methods for accurate prediction of contacts and long range hydrogen bonding in proteins. divisions: UCL divisions: B02 divisions: C08 divisions: B04 divisions: C05 divisions: F48 note: This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. MetaPSICOV is available as a freely available web server at http://bioinf.cs.ucl.ac.uk/MetaPSICOV. Raw data (predicted contact lists and 3D models) and source code can be downloaded from http://bioinf.cs.ucl.ac.uk/downloads/MetaPSICOV. abstract: Recent developments of statistical techniques to infer direct evolutionary couplings between residue pairs have rendered covariation-based contact prediction a viable means for accurate 3D modelling of proteins, with no information other than the sequence required. To extend the usefulness of contact prediction, we have designed a new meta-predictor (MetaPSICOV) which combines three distinct approaches for inferring covariation signals from multiple sequence alignments, considers a broad range of other sequence-derived features and, uniquely, a range of metrics which describe both the local and global quality of the input multiple sequence alignment. Finally, we use a two-stage predictor, where the second stage filters the output of the first stage. This two-stage predictor is additionally evaluated on its ability to accurately predict the long range network of hydrogen bonds, including correctly assigning the donor and acceptor residues. date: 2014-11-26 official_url: http://dx.doi.org/10.1093/bioinformatics/btu791 vfaculties: VENG oa_status: green full_text_type: other primo: open primo_central: open_green article_type_text: JOURNAL ARTICLE verified: verified_manual elements_source: PubMed elements_id: 996068 doi: 10.1093/bioinformatics/btu791 pii: btu791 language_elements: ENG lyricists_name: Jones, David lyricists_name: Singh, Tanya lyricists_id: DTJON81 lyricists_id: TSING03 full_text_status: public publication: Bioinformatics issn: 1367-4803 citation: Jones, DT; Singh, T; Kosciolek, T; Tetchner, S; (2014) MetaPSICOV: combining coevolution methods for accurate prediction of contacts and long range hydrogen bonding in proteins. Bioinformatics 10.1093/bioinformatics/btu791 <https://doi.org/10.1093/bioinformatics%2Fbtu791>. Green open access document_url: https://discovery.ucl.ac.uk/id/eprint/1460206/1/metapsicov_v8.18.pdf document_url: https://discovery.ucl.ac.uk/id/eprint/1460206/3/metapsicov_supplementary_v0.03.pdf