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Next-generation sequencing techniques provide an unprecedented characterisation of human Variants of Unknown Significance (VUS). Single-residue variations are collected in public databases and associated to diseases and phenotypes. However, for detailing at molecular level mechanisms involved in the onset of diseases, variants need structural and functional annotation. Here we propose a new portal called Bioinformatic Sweeties, collecting resources ranging from databases for human protein annotation to computational methods for predicting impact of variants. The tools, included in the portal, allow computing different protein properties, ranging from solvent accessible surface to stability and interactions and do not require login or installation. The portal, speeding up the variant characterisation process, is available at: https://bioinformaticsweeties.biocomp.unibo.it | Next-generation sequencing techniques provide an unprecedented characterisation of human Variants of Unknown Significance (VUS). Single-residue variations are collected in public databases and associated to diseases and phenotypes. However, for detailing at molecular level mechanisms involved in the onset of diseases, variants need structural and functional annotation. Here we propose a new portal called Bioinformatic Sweeties, collecting resources ranging from databases for human protein annotation to computational methods for predicting impact of variants. The tools, included in the portal, allow computing different protein properties, ranging from solvent accessible surface to stability and interactions and do not require login or installation. The portal, speeding up the variant characterisation process, is available at: https://bioinformaticsweeties.biocomp.unibo.it | ||
==Declarations== | |||
===Funding=== | |||
GB: Project title: "National Center for HPC, Big Data and Quantum Computing", code: CN00000013, CUP: J33C22001170001. Funded by the European Union - NextGenerationEU, PNRR - Mission 4 - Component 2 - Investment 1.4 "Strengthening research structures and creation of "national R&D champions" on some Key Enabling Technologies" D.D. 3138 of 12/16/2021 corrected with D.D. 3175 of 12/18/2021. | |||
===Conflict of Interest Declaration=== | |||
The authors declare no conflict of interest. | |||
==References== | |||
<ol class="references"> | |||
<li>Richards, S. et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet. Med. Off. J. Am. Coll. Med. Genet. 17, 405–424 (2015). | |||
<li>UniProt: the Universal Protein Knowledgebase in 2023 | Nucleic Acids Research | Oxford Academic. https://academic.oup.com/nar/article/51/D1/D523/6835362?login=true. | |||
<li>Landrum, M. J. et al. ClinVar: improving access to variant interpretations and supporting evidence. Nucleic Acids Res. 46, D1062–D1067 (2018). | |||
<li>DisGeNET knowledge platform for disease genomics: 2019 update | Nucleic Acids Research | Oxford Academic. https://academic.oup.com/nar/article/48/D1/D845/5611674?login=true. | |||
<li>ISPRED4: interaction sites PREDiction in protein structures with a refining grammar model | Bioinformatics | Oxford Academic. https://academic.oup.com/bioinformatics/article/33/11/1656/2953248. | |||
<li>Manfredi, M., Savojardo, C., Martelli, P. L. & Casadio, R. ISPRED-SEQ: Deep Neural Networks and Embeddings for Predicting Interaction Sites in Protein Sequences. J. Mol. Biol. 435, 167963 (2023). | |||
<li>Manfredi, M., Savojardo, C., Martelli, P. L. & Casadio, R. E-SNPs&GO: embedding of protein sequence and function improves the annotation of human pathogenic variants. Bioinformatics 38, 5168–5174 (2022). | |||
<li>INPS: predicting the impact of non-synonymous variations on protein stability from sequence | Bioinformatics | Oxford Academic. https://academic.oup.com/bioinformatics/article/31/17/2816/183893. | |||
<li>INPS-MD: a web server to predict stability of protein variants from sequence and structure | Bioinformatics | Oxford Academic.</li> https://academic.oup.com/bioinformatics/article/32/16/2542/1743481.</li> | |||
<li>Touw, W. G. et al. A series of PDB-related databanks for everyday needs. Nucleic Acids Res. 43, D364–D368 (2015).</li> | |||
<li>Kabsch, W. & Sander, C. Dictionary of protein secondary structure: Pattern recognition of hydrogen-bonded and geometrical features. Biopolymers 22, 2577–2637 (1983).</li> | |||
<li>Mapping human disease-associated enzymes into Reactome allows characterization of disease groups and their interactions | Scientific Reports. https://www.nature.com/articles/s41598-022-22818-5.</li> | |||
<li>MultifacetedProtDB: a database of human proteins with multiple functions | Nucleic Acids Research | Oxford Academic. </li>https://academic.oup.com/nar/article/52/D1/D494/7288824.</li> | |||
<li>Babbi, G. et al. eDGAR: a database of Disease-Gene Associations with annotated Relationships among genes. BMC Genomics 18, 554 (2017).</li> | |||
<li>Babbi, G., Martelli, P. L. & Casadio, R. PhenPath: a tool for characterizing biological functions underlying different phenotypes. BMC Genomics 20, 548 (2019).</li> | |||
<li>Thöny, B. et al. Hyperphenylalaninemia with high levels of 7-biopterin is associated with mutations in the PCBD gene encoding the bifunctional protein pterin-4a-carbinolamine dehydratase and transcriptional coactivator (DCoH). Am. J. Hum. Genet. 62, 1302–1311 (1998).</li> | |||
<li>Ferrè, S. et al. Mutations in PCBD1 Cause Hypomagnesemia and Renal Magnesium Wasting. J. Am. Soc. Nephrol. 25, 574 (2014).</li> | |||
<li>Oughtred, R. et al. The BioGRID database: A comprehensive biomedical resource of curated protein, genetic, and chemical interactions. Protein Sci. 30, 187–200 (2021).</li> | |||
<li>Orchard, S. et al. The MIntAct project—IntAct as a common curation platform for 11 molecular interaction databases. Nucleic Acids Res. 42, D358–D363 (2014).</li> | |||
</ol> | |||
[[Category:Open Access]] | [[Category:Open Access]] |
Latest revision as of 15:51, 25 March 2024
Published |
March 6, 2024 |
Title |
Bioinformatic Sweeties: a unified portal for characterizing human proteins and their variants |
Authors |
Giulia Babbi, Matteo Manfredi, Elisa Bertolini, Castrense Savojardo, Pier Luigi Martelli, Rita Casadio |
DOI |
10.62684/HDYO1899 |
Keywords |
protein annotation, functional annotation, variant annotation, predictors, diseases |
Downloads |
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Giulia Babbi, Matteo Manfredi, Elisa Bertolini, Castrense Savojardo, Pier Luigi Martelli, Rita Casadio
Biocomputing Group, University of Bologna
Correspondence to: Rita Casadio, rita.casadio@unibo.it
Abstract
Next-generation sequencing techniques provide an unprecedented characterisation of human Variants of Unknown Significance (VUS). Single-residue variations are collected in public databases and associated to diseases and phenotypes. However, for detailing at molecular level mechanisms involved in the onset of diseases, variants need structural and functional annotation. Here we propose a new portal called Bioinformatic Sweeties, collecting resources ranging from databases for human protein annotation to computational methods for predicting impact of variants. The tools, included in the portal, allow computing different protein properties, ranging from solvent accessible surface to stability and interactions and do not require login or installation. The portal, speeding up the variant characterisation process, is available at: https://bioinformaticsweeties.biocomp.unibo.it
Declarations
Funding
GB: Project title: "National Center for HPC, Big Data and Quantum Computing", code: CN00000013, CUP: J33C22001170001. Funded by the European Union - NextGenerationEU, PNRR - Mission 4 - Component 2 - Investment 1.4 "Strengthening research structures and creation of "national R&D champions" on some Key Enabling Technologies" D.D. 3138 of 12/16/2021 corrected with D.D. 3175 of 12/18/2021.
Conflict of Interest Declaration
The authors declare no conflict of interest.
References
- Richards, S. et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet. Med. Off. J. Am. Coll. Med. Genet. 17, 405–424 (2015).
- UniProt: the Universal Protein Knowledgebase in 2023 | Nucleic Acids Research | Oxford Academic. https://academic.oup.com/nar/article/51/D1/D523/6835362?login=true.
- Landrum, M. J. et al. ClinVar: improving access to variant interpretations and supporting evidence. Nucleic Acids Res. 46, D1062–D1067 (2018).
- DisGeNET knowledge platform for disease genomics: 2019 update | Nucleic Acids Research | Oxford Academic. https://academic.oup.com/nar/article/48/D1/D845/5611674?login=true.
- ISPRED4: interaction sites PREDiction in protein structures with a refining grammar model | Bioinformatics | Oxford Academic. https://academic.oup.com/bioinformatics/article/33/11/1656/2953248.
- Manfredi, M., Savojardo, C., Martelli, P. L. & Casadio, R. ISPRED-SEQ: Deep Neural Networks and Embeddings for Predicting Interaction Sites in Protein Sequences. J. Mol. Biol. 435, 167963 (2023).
- Manfredi, M., Savojardo, C., Martelli, P. L. & Casadio, R. E-SNPs&GO: embedding of protein sequence and function improves the annotation of human pathogenic variants. Bioinformatics 38, 5168–5174 (2022).
- INPS: predicting the impact of non-synonymous variations on protein stability from sequence | Bioinformatics | Oxford Academic. https://academic.oup.com/bioinformatics/article/31/17/2816/183893.
- INPS-MD: a web server to predict stability of protein variants from sequence and structure | Bioinformatics | Oxford Academic. https://academic.oup.com/bioinformatics/article/32/16/2542/1743481.
- Touw, W. G. et al. A series of PDB-related databanks for everyday needs. Nucleic Acids Res. 43, D364–D368 (2015).
- Kabsch, W. & Sander, C. Dictionary of protein secondary structure: Pattern recognition of hydrogen-bonded and geometrical features. Biopolymers 22, 2577–2637 (1983).
- Mapping human disease-associated enzymes into Reactome allows characterization of disease groups and their interactions | Scientific Reports. https://www.nature.com/articles/s41598-022-22818-5.
- MultifacetedProtDB: a database of human proteins with multiple functions | Nucleic Acids Research | Oxford Academic. https://academic.oup.com/nar/article/52/D1/D494/7288824.
- Babbi, G. et al. eDGAR: a database of Disease-Gene Associations with annotated Relationships among genes. BMC Genomics 18, 554 (2017).
- Babbi, G., Martelli, P. L. & Casadio, R. PhenPath: a tool for characterizing biological functions underlying different phenotypes. BMC Genomics 20, 548 (2019).
- Thöny, B. et al. Hyperphenylalaninemia with high levels of 7-biopterin is associated with mutations in the PCBD gene encoding the bifunctional protein pterin-4a-carbinolamine dehydratase and transcriptional coactivator (DCoH). Am. J. Hum. Genet. 62, 1302–1311 (1998).
- Ferrè, S. et al. Mutations in PCBD1 Cause Hypomagnesemia and Renal Magnesium Wasting. J. Am. Soc. Nephrol. 25, 574 (2014).
- Oughtred, R. et al. The BioGRID database: A comprehensive biomedical resource of curated protein, genetic, and chemical interactions. Protein Sci. 30, 187–200 (2021).
- Orchard, S. et al. The MIntAct project—IntAct as a common curation platform for 11 molecular interaction databases. Nucleic Acids Res. 42, D358–D363 (2014).