Reliable Generation of Native-Like Decoys Limits Predictive Ability in Fragment-Based Protein Structure Prediction

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...

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Main Authors: Shaun M. Kandathil, Mario Garza-Fabre, Julia Handl, Simon C. Lovell
Format: Article
Language:English
Published: MDPI AG 2019-10-01
Series:Biomolecules
Subjects:
Online Access:https://www.mdpi.com/2218-273X/9/10/612
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spelling doaj-568aaa3f81874cfdb5bd924fc8a873ec2020-11-25T01:39:23ZengMDPI AGBiomolecules2218-273X2019-10-0191061210.3390/biom9100612biom9100612Reliable Generation of Native-Like Decoys Limits Predictive Ability in Fragment-Based Protein Structure PredictionShaun M. Kandathil0Mario Garza-Fabre1Julia Handl2Simon C. Lovell3Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester M13 9PL, UKCinvestav Unidad Tamaulipas, Km 5.5 Carretera Cd. Victoria-Soto La Marina, Cd. Victoria 87130, MexicoDecision and Cognitive Sciences Research Centre, Alliance Manchester Business School, The University of Manchester, Manchester M13 9PL, UKDivision of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester M13 9PL, UKOur 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.https://www.mdpi.com/2218-273X/9/10/612protein structure predictionfragment assemblyconformational samplingstochastic ranking
collection DOAJ
language English
format Article
sources DOAJ
author Shaun M. Kandathil
Mario Garza-Fabre
Julia Handl
Simon C. Lovell
spellingShingle Shaun M. Kandathil
Mario Garza-Fabre
Julia Handl
Simon C. Lovell
Reliable Generation of Native-Like Decoys Limits Predictive Ability in Fragment-Based Protein Structure Prediction
Biomolecules
protein structure prediction
fragment assembly
conformational sampling
stochastic ranking
author_facet Shaun M. Kandathil
Mario Garza-Fabre
Julia Handl
Simon C. Lovell
author_sort Shaun M. Kandathil
title Reliable Generation of Native-Like Decoys Limits Predictive Ability in Fragment-Based Protein Structure Prediction
title_short Reliable Generation of Native-Like Decoys Limits Predictive Ability in Fragment-Based Protein Structure Prediction
title_full Reliable Generation of Native-Like Decoys Limits Predictive Ability in Fragment-Based Protein Structure Prediction
title_fullStr Reliable Generation of Native-Like Decoys Limits Predictive Ability in Fragment-Based Protein Structure Prediction
title_full_unstemmed Reliable Generation of Native-Like Decoys Limits Predictive Ability in Fragment-Based Protein Structure Prediction
title_sort reliable generation of native-like decoys limits predictive ability in fragment-based protein structure prediction
publisher MDPI AG
series Biomolecules
issn 2218-273X
publishDate 2019-10-01
description 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.
topic protein structure prediction
fragment assembly
conformational sampling
stochastic ranking
url https://www.mdpi.com/2218-273X/9/10/612
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