Inferring joint sequence-structural determinants of protein functional specificity
Residues responsible for allostery, cooperativity, and other subtle but functionally important interactions remain difficult to detect. To aid such detection, we employ statistical inference based on the assumption that residues distinguishing a protein subgroup from evolutionarily divergent subgrou...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
eLife Sciences Publications Ltd
2018-01-01
|
| Series: | eLife |
| Subjects: | |
| Online Access: | https://elifesciences.org/articles/29880 |
| _version_ | 1811201647677800448 |
|---|---|
| author | Andrew F Neuwald L Aravind Stephen F Altschul |
| author_facet | Andrew F Neuwald L Aravind Stephen F Altschul |
| author_sort | Andrew F Neuwald |
| collection | DOAJ |
| description | Residues responsible for allostery, cooperativity, and other subtle but functionally important interactions remain difficult to detect. To aid such detection, we employ statistical inference based on the assumption that residues distinguishing a protein subgroup from evolutionarily divergent subgroups often constitute an interacting functional network. We identify such networks with the aid of two measures of statistical significance. One measure aids identification of divergent subgroups based on distinguishing residue patterns. For each subgroup, a second measure identifies structural interactions involving pattern residues. Such interactions are derived either from atomic coordinates or from Direct Coupling Analysis scores, used as surrogates for structural distances. Applying this approach to N-acetyltransferases, P-loop GTPases, RNA helicases, synaptojanin-superfamily phosphatases and nucleases, and thymine/uracil DNA glycosylases yielded results congruent with biochemical understanding of these proteins, and also revealed striking sequence-structural features overlooked by other methods. These and similar analyses can aid the design of drugs targeting allosteric sites. |
| first_indexed | 2024-04-12T02:25:32Z |
| format | Article |
| id | doaj.art-5844c9da722f4888a20f96a980d82052 |
| institution | Directory Open Access Journal |
| issn | 2050-084X |
| language | English |
| last_indexed | 2024-04-12T02:25:32Z |
| publishDate | 2018-01-01 |
| publisher | eLife Sciences Publications Ltd |
| record_format | Article |
| series | eLife |
| spelling | doaj.art-5844c9da722f4888a20f96a980d820522022-12-22T03:52:01ZengeLife Sciences Publications LtdeLife2050-084X2018-01-01710.7554/eLife.29880Inferring joint sequence-structural determinants of protein functional specificityAndrew F Neuwald0https://orcid.org/0000-0002-0086-5755L Aravind1Stephen F Altschul2Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, United States; Department of Biochemistry and Molecular Biology, University of Maryland School of Medicine, Baltimore, United StatesNational Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, United StatesNational Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, United StatesResidues responsible for allostery, cooperativity, and other subtle but functionally important interactions remain difficult to detect. To aid such detection, we employ statistical inference based on the assumption that residues distinguishing a protein subgroup from evolutionarily divergent subgroups often constitute an interacting functional network. We identify such networks with the aid of two measures of statistical significance. One measure aids identification of divergent subgroups based on distinguishing residue patterns. For each subgroup, a second measure identifies structural interactions involving pattern residues. Such interactions are derived either from atomic coordinates or from Direct Coupling Analysis scores, used as surrogates for structural distances. Applying this approach to N-acetyltransferases, P-loop GTPases, RNA helicases, synaptojanin-superfamily phosphatases and nucleases, and thymine/uracil DNA glycosylases yielded results congruent with biochemical understanding of these proteins, and also revealed striking sequence-structural features overlooked by other methods. These and similar analyses can aid the design of drugs targeting allosteric sites.https://elifesciences.org/articles/29880Initial Cluster AnalysisBayesian statisticssequence analysisstructural analysiscomputer algorithms |
| spellingShingle | Andrew F Neuwald L Aravind Stephen F Altschul Inferring joint sequence-structural determinants of protein functional specificity eLife Initial Cluster Analysis Bayesian statistics sequence analysis structural analysis computer algorithms |
| title | Inferring joint sequence-structural determinants of protein functional specificity |
| title_full | Inferring joint sequence-structural determinants of protein functional specificity |
| title_fullStr | Inferring joint sequence-structural determinants of protein functional specificity |
| title_full_unstemmed | Inferring joint sequence-structural determinants of protein functional specificity |
| title_short | Inferring joint sequence-structural determinants of protein functional specificity |
| title_sort | inferring joint sequence structural determinants of protein functional specificity |
| topic | Initial Cluster Analysis Bayesian statistics sequence analysis structural analysis computer algorithms |
| url | https://elifesciences.org/articles/29880 |
| work_keys_str_mv | AT andrewfneuwald inferringjointsequencestructuraldeterminantsofproteinfunctionalspecificity AT laravind inferringjointsequencestructuraldeterminantsofproteinfunctionalspecificity AT stephenfaltschul inferringjointsequencestructuraldeterminantsofproteinfunctionalspecificity |