eprintid: 10085381 rev_number: 22 eprint_status: archive userid: 608 dir: disk0/10/08/53/81 datestamp: 2019-11-08 16:24:25 lastmod: 2021-09-25 23:08:58 status_changed: 2019-11-08 16:24:25 type: article metadata_visibility: show creators_name: Kandathil, SM creators_name: Garza-Fabre, M creators_name: Handl, J creators_name: Lovell, SC title: Reliable Generation of Native-Like Decoys Limits Predictive Ability in Fragment-Based Protein Structure Prediction ispublished: pub divisions: UCL divisions: B04 divisions: C05 divisions: F48 keywords: conformational sampling, fragment assembly, protein structure prediction, stochastic ranking note: © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). abstract: Our previous work with fragment-assembly methods has demonstrated specific deficiencies in conformational sampling behaviour that, when addressed through improved sampling algorithms, can lead to more reliable prediction of tertiary protein structure when good fragments are available, and when score values can be relied upon to guide the search to the native basin. In this paper, we present preliminary investigations into two important questions arising from more difficult prediction problems. First, we investigated the extent to which native-like conformational states are generated during multiple runs of our search protocols. We determined that, in cases of difficult prediction, native-like decoys are rarely or never generated. Second, we developed a scheme for decoy retention that balances the objectives of retaining low-scoring structures and retaining conformationally diverse structures sampled during the course of the search. Our method succeeds at retaining more diverse sets of structures, and, for a few targets, more native-like solutions are retained as compared to our original, energy-based retention scheme. However, in general, we found that the rate at which native-like structural states are generated has a much stronger effect on eventual distributions of predictive accuracy in the decoy sets, as compared to the specific decoy retention strategy used. We found that our protocols show differences in their ability to access native-like states for some targets, and this may explain some of the differences in predictive performance seen between these methods. There appears to be an interaction between fragment sets and move operators, which influences the accessibility of native-like structures for given targets. Our results point to clear directions for further improvements in fragment-based methods, which are likely to enable higher accuracy predictions. date: 2019-10-15 date_type: published official_url: https://doi.org/10.3390/biom9100612 oa_status: green full_text_type: pub language: eng primo: open primo_central: open_green verified: verified_manual elements_id: 1711859 doi: 10.3390/biom9100612 pii: biom9100612 lyricists_name: Kandathil, Shaun lyricists_id: SMKAN15 actors_name: Nonhebel, Lucinda actors_id: LNONH33 actors_role: owner full_text_status: public publication: Biomolecules volume: 9 number: 10 article_number: 612 event_location: Switzerland issn: 2218-273X citation: Kandathil, SM; Garza-Fabre, M; Handl, J; Lovell, SC; (2019) Reliable Generation of Native-Like Decoys Limits Predictive Ability in Fragment-Based Protein Structure Prediction. Biomolecules , 9 (10) , Article 612. 10.3390/biom9100612 <https://doi.org/10.3390/biom9100612>. Green open access document_url: https://discovery.ucl.ac.uk/id/eprint/10085381/1/Kandathil_OA_biomolecules-09-00612-v2.pdf