HGDiscovery: An online tool providing functional and phenotypic information on novel variants of homogentisate 1,2- dioxigenase
Alkaptonuria (AKU), a rare genetic disorder, is characterized by the accumulation of homogentisic acid (HGA) in the body. Affected individuals lack functional levels of an enzyme required to breakdown HGA. Mutations in the homogentisate 1,2-dioxygenase (HGD) gene cause AKU and they are responsible f...
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Elsevier
2022-01-01
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Series: | Current Research in Structural Biology |
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Online Access: | http://www.sciencedirect.com/science/article/pii/S2665928X22000241 |
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author | Malancha Karmakar Vittoria Cicaloni Carlos H.M. Rodrigues Ottavia Spiga Annalisa Santucci David B. Ascher |
author_facet | Malancha Karmakar Vittoria Cicaloni Carlos H.M. Rodrigues Ottavia Spiga Annalisa Santucci David B. Ascher |
author_sort | Malancha Karmakar |
collection | DOAJ |
description | Alkaptonuria (AKU), a rare genetic disorder, is characterized by the accumulation of homogentisic acid (HGA) in the body. Affected individuals lack functional levels of an enzyme required to breakdown HGA. Mutations in the homogentisate 1,2-dioxygenase (HGD) gene cause AKU and they are responsible for deficient levels of functional HGD, which, in turn, leads to excess levels of HGA. Although HGA is rapidly cleared from the body by the kidneys, in the long term it starts accumulating in various tissues, especially cartilage. Over time (rarely before adulthood), it eventually changes the color of affected tissue to slate blue or black. Here we report a comprehensive mutation analysis of 111 pathogenic and 190 non-pathogenic HGD missense mutations using protein structural information. Using our comprehensive suite of graph-based signature methods, mCSM complemented with sequence-based tools, we studied the functional and molecular consequences of each mutation on protein stability, interaction and evolutionary conservation. The scores generated from the structure and sequence-based tools were used to train a supervised machine learning algorithm with 89% accuracy. The empirical classifier was used to generate the variant phenotype for novel HGD missense mutations. All this information is deployed as a user friendly freely available web server called HGDiscovery (https://biosig.lab.uq.edu.au/hgdiscovery/). |
first_indexed | 2024-04-13T04:38:22Z |
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id | doaj.art-09d4b2fbbc3e4c9c8c87bcee86a8dfe2 |
institution | Directory Open Access Journal |
issn | 2665-928X |
language | English |
last_indexed | 2024-04-13T04:38:22Z |
publishDate | 2022-01-01 |
publisher | Elsevier |
record_format | Article |
series | Current Research in Structural Biology |
spelling | doaj.art-09d4b2fbbc3e4c9c8c87bcee86a8dfe22022-12-22T03:02:05ZengElsevierCurrent Research in Structural Biology2665-928X2022-01-014271277HGDiscovery: An online tool providing functional and phenotypic information on novel variants of homogentisate 1,2- dioxigenaseMalancha Karmakar0Vittoria Cicaloni1Carlos H.M. Rodrigues2Ottavia Spiga3Annalisa Santucci4David B. Ascher5Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia; Systems and Computational Biology, Bio21 Institute, University of Melbourne, Melbourne, Victoria, AustraliaComputational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia; Systems and Computational Biology, Bio21 Institute, University of Melbourne, Melbourne, Victoria, Australia; Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, ItalyComputational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia; Systems and Computational Biology, Bio21 Institute, University of Melbourne, Melbourne, Victoria, Australia; School of Chemistry and Molecular Biology, University of Queensland, Brisbane, Queensland, AustraliaDepartment of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, ItalyDepartment of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, ItalyComputational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia; Systems and Computational Biology, Bio21 Institute, University of Melbourne, Melbourne, Victoria, Australia; School of Chemistry and Molecular Biology, University of Queensland, Brisbane, Queensland, Australia; Corresponding author. Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, Victoria, AustraliaAlkaptonuria (AKU), a rare genetic disorder, is characterized by the accumulation of homogentisic acid (HGA) in the body. Affected individuals lack functional levels of an enzyme required to breakdown HGA. Mutations in the homogentisate 1,2-dioxygenase (HGD) gene cause AKU and they are responsible for deficient levels of functional HGD, which, in turn, leads to excess levels of HGA. Although HGA is rapidly cleared from the body by the kidneys, in the long term it starts accumulating in various tissues, especially cartilage. Over time (rarely before adulthood), it eventually changes the color of affected tissue to slate blue or black. Here we report a comprehensive mutation analysis of 111 pathogenic and 190 non-pathogenic HGD missense mutations using protein structural information. Using our comprehensive suite of graph-based signature methods, mCSM complemented with sequence-based tools, we studied the functional and molecular consequences of each mutation on protein stability, interaction and evolutionary conservation. The scores generated from the structure and sequence-based tools were used to train a supervised machine learning algorithm with 89% accuracy. The empirical classifier was used to generate the variant phenotype for novel HGD missense mutations. All this information is deployed as a user friendly freely available web server called HGDiscovery (https://biosig.lab.uq.edu.au/hgdiscovery/).http://www.sciencedirect.com/science/article/pii/S2665928X22000241AlkaptonuriaStructural bioinformaticsMachine learningPrecision medicineRare genetic disorder |
spellingShingle | Malancha Karmakar Vittoria Cicaloni Carlos H.M. Rodrigues Ottavia Spiga Annalisa Santucci David B. Ascher HGDiscovery: An online tool providing functional and phenotypic information on novel variants of homogentisate 1,2- dioxigenase Current Research in Structural Biology Alkaptonuria Structural bioinformatics Machine learning Precision medicine Rare genetic disorder |
title | HGDiscovery: An online tool providing functional and phenotypic information on novel variants of homogentisate 1,2- dioxigenase |
title_full | HGDiscovery: An online tool providing functional and phenotypic information on novel variants of homogentisate 1,2- dioxigenase |
title_fullStr | HGDiscovery: An online tool providing functional and phenotypic information on novel variants of homogentisate 1,2- dioxigenase |
title_full_unstemmed | HGDiscovery: An online tool providing functional and phenotypic information on novel variants of homogentisate 1,2- dioxigenase |
title_short | HGDiscovery: An online tool providing functional and phenotypic information on novel variants of homogentisate 1,2- dioxigenase |
title_sort | hgdiscovery an online tool providing functional and phenotypic information on novel variants of homogentisate 1 2 dioxigenase |
topic | Alkaptonuria Structural bioinformatics Machine learning Precision medicine Rare genetic disorder |
url | http://www.sciencedirect.com/science/article/pii/S2665928X22000241 |
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