Assessing the accuracy of ancestral protein reconstruction methods.
The phylogenetic inference of ancestral protein sequences is a powerful technique for the study of molecular evolution, but any conclusions drawn from such studies are only as good as the accuracy of the reconstruction method. Every inference method leads to errors in the ancestral protein sequence,...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2006-06-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.0020069 |
| _version_ | 1818939536802054144 |
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| author | Paul D Williams David D Pollock Benjamin P Blackburne Richard A Goldstein |
| author_facet | Paul D Williams David D Pollock Benjamin P Blackburne Richard A Goldstein |
| author_sort | Paul D Williams |
| collection | DOAJ |
| description | The phylogenetic inference of ancestral protein sequences is a powerful technique for the study of molecular evolution, but any conclusions drawn from such studies are only as good as the accuracy of the reconstruction method. Every inference method leads to errors in the ancestral protein sequence, resulting in potentially misleading estimates of the ancestral protein's properties. To assess the accuracy of ancestral protein reconstruction methods, we performed computational population evolution simulations featuring near-neutral evolution under purifying selection, speciation, and divergence using an off-lattice protein model where fitness depends on the ability to be stable in a specified target structure. We were thus able to compare the thermodynamic properties of the true ancestral sequences with the properties of "ancestral sequences" inferred by maximum parsimony, maximum likelihood, and Bayesian methods. Surprisingly, we found that methods such as maximum parsimony and maximum likelihood that reconstruct a "best guess" amino acid at each position overestimate thermostability, while a Bayesian method that sometimes chooses less-probable residues from the posterior probability distribution does not. Maximum likelihood and maximum parsimony apparently tend to eliminate variants at a position that are slightly detrimental to structural stability simply because such detrimental variants are less frequent. Other properties of ancestral proteins might be similarly overestimated. This suggests that ancestral reconstruction studies require greater care to come to credible conclusions regarding functional evolution. Inferred functional patterns that mimic reconstruction bias should be reevaluated. |
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| format | Article |
| id | doaj.art-d3fa1c21a4164cd5bbb7cdc3649257f3 |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-20T06:25:19Z |
| publishDate | 2006-06-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-d3fa1c21a4164cd5bbb7cdc3649257f32022-12-21T19:50:19ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582006-06-0126e6910.1371/journal.pcbi.0020069Assessing the accuracy of ancestral protein reconstruction methods.Paul D WilliamsDavid D PollockBenjamin P BlackburneRichard A GoldsteinThe phylogenetic inference of ancestral protein sequences is a powerful technique for the study of molecular evolution, but any conclusions drawn from such studies are only as good as the accuracy of the reconstruction method. Every inference method leads to errors in the ancestral protein sequence, resulting in potentially misleading estimates of the ancestral protein's properties. To assess the accuracy of ancestral protein reconstruction methods, we performed computational population evolution simulations featuring near-neutral evolution under purifying selection, speciation, and divergence using an off-lattice protein model where fitness depends on the ability to be stable in a specified target structure. We were thus able to compare the thermodynamic properties of the true ancestral sequences with the properties of "ancestral sequences" inferred by maximum parsimony, maximum likelihood, and Bayesian methods. Surprisingly, we found that methods such as maximum parsimony and maximum likelihood that reconstruct a "best guess" amino acid at each position overestimate thermostability, while a Bayesian method that sometimes chooses less-probable residues from the posterior probability distribution does not. Maximum likelihood and maximum parsimony apparently tend to eliminate variants at a position that are slightly detrimental to structural stability simply because such detrimental variants are less frequent. Other properties of ancestral proteins might be similarly overestimated. This suggests that ancestral reconstruction studies require greater care to come to credible conclusions regarding functional evolution. Inferred functional patterns that mimic reconstruction bias should be reevaluated.https://doi.org/10.1371/journal.pcbi.0020069 |
| spellingShingle | Paul D Williams David D Pollock Benjamin P Blackburne Richard A Goldstein Assessing the accuracy of ancestral protein reconstruction methods. PLoS Computational Biology |
| title | Assessing the accuracy of ancestral protein reconstruction methods. |
| title_full | Assessing the accuracy of ancestral protein reconstruction methods. |
| title_fullStr | Assessing the accuracy of ancestral protein reconstruction methods. |
| title_full_unstemmed | Assessing the accuracy of ancestral protein reconstruction methods. |
| title_short | Assessing the accuracy of ancestral protein reconstruction methods. |
| title_sort | assessing the accuracy of ancestral protein reconstruction methods |
| url | https://doi.org/10.1371/journal.pcbi.0020069 |
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