Detection and analysis of disease-associated single nucleotide polymorphism influencing post-translational modification

Kim, Yul; Kang, Chang Soo; Min, Bumki; Yi, Gwan‐Su

doi:10.1186/1755-8794-8-s2-s7

Cited by 29 publications

(26 citation statements)

References 31 publications

(31 reference statements)

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“…Thus, we only consider two well-recognized features, protein interactions and conserved local sequence around phosphorylation sites. Since genetic variation changes phosphorylation sites or their interacting kinases [ 31 , 32 ], many methods have emerged to quantify the effects of SNVs (single nucleotide variants) on protein phosphorylation. ActiveDriver identified a specific p-site region in a given protein that has a significantly different mutation rate than expected, thereby finding cancer driver mutations [ 33 , 34 ].…”

Section: Discussionmentioning

confidence: 99%

KSP: an integrated method for predicting catalyzing kinases of phosphorylation sites in proteins

2020

BMC Genomics

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Background Protein phosphorylation by kinases plays crucial roles in various biological processes including signal transduction and tumorigenesis, thus a better understanding of protein phosphorylation events in cells is fundamental for studying protein functions and designing drugs to treat diseases caused by the malfunction of phosphorylation. Although a large number of phosphorylation sites in proteins have been identified using high-throughput phosphoproteomic technologies, their specific catalyzing kinases remain largely unknown. Therefore, computational methods are urgently needed to predict the kinases that catalyze the phosphorylation of these sites. Results We developed KSP, a new algorithm for predicting catalyzing kinases for experimentally identified phosphorylation sites in human proteins. KSP constructs a network based on known protein-protein interactions and kinase-substrate relationships. Based on the network, it computes an affinity score between a phosphorylation site and kinases, and returns the top-ranked kinases of the score as candidate catalyzing kinases. When tested on known kinase-substrate pairs, KSP outperforms existing methods including NetworKIN, iGPS, and PKIS. Conclusions We developed a novel accurate tool for predicting catalyzing kinases of known phosphorylation sites. It can work as a complementary network approach for sequence-based phosphorylation site predictors.

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Section: Discussionmentioning

confidence: 99%

KSP: an integrated method for predicting catalyzing kinases of phosphorylation sites in proteins

2020

BMC Genomics

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“…It is reported that about 60% of Mendelian diseases are caused by amino acid substitutions [48]. A potential effect of SAVs on protein function is the disruption of PTMs [49]. For example, the potential for phosphorylation sites to be affected by amino acid variants is high, and there have been numerous examples of diseases associated naturally occurring variants that impact the phosphorylation status of proteins [50].…”

Section: Ptm-associated Mutation Collectionmentioning

confidence: 99%

PRISMOID: a comprehensive 3D structure database for post-translational modifications and mutations with functional impact

Fan

Marquez‐Lago

et al. 2019

Briefings in Bioinformatics

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Post-translational modifications (PTMs) play very important roles in various cell signaling pathways and biological process. Due to PTMs’ extremely important roles, many major PTMs have been studied, while the functional and mechanical characterization of major PTMs is well documented in several databases. However, most currently available databases mainly focus on protein sequences, while the real 3D structures of PTMs have been largely ignored. Therefore, studies of PTMs 3D structural signatures have been severely limited by the deficiency of the data. Here, we develop PRISMOID, a novel publicly available and free 3D structure database for a wide range of PTMs. PRISMOID represents an up-to-date and interactive online knowledge base with specific focus on 3D structural contexts of PTMs sites and mutations that occur on PTMs and in the close proximity of PTM sites with functional impact. The first version of PRISMOID encompasses 17 145 non-redundant modification sites on 3919 related protein 3D structure entries pertaining to 37 different types of PTMs. Our entry web page is organized in a comprehensive manner, including detailed PTM annotation on the 3D structure and biological information in terms of mutations affecting PTMs, secondary structure features and per-residue solvent accessibility features of PTM sites, domain context, predicted natively disordered regions and sequence alignments. In addition, high-definition JavaScript packages are employed to enhance information visualization in PRISMOID. PRISMOID equips a variety of interactive and customizable search options and data browsing functions; these capabilities allow users to access data via keyword, ID and advanced options combination search in an efficient and user-friendly way. A download page is also provided to enable users to download the SQL file, computational structural features and PTM sites’ data. We anticipate PRISMOID will swiftly become an invaluable online resource, assisting both biologists and bioinformaticians to conduct experiments and develop applications supporting discovery efforts in the sequence–structural–functional relationship of PTMs and providing important insight into mutations and PTM sites interaction mechanisms. The PRISMOID database is freely accessible at http://prismoid.erc.monash.edu/. The database and web interface are implemented in MySQL, JSP, JavaScript and HTML with all major browsers supported.

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“…It is reported that about 60% of Mendelian diseases are caused by amino acid substitutions [47]. A potential effect of SAVs on protein function is the disruption of PTMs [48]. For example, the potential for phosphorylation sites to be affected by amino acid variants is high and there have been numerous examples of diseases associated naturally occurring variants that impact the phosphorylation status of proteins [49].…”

Section: Ptm-associated Mutation Collectionmentioning

confidence: 99%

PRISMOID: a comprehensive 3D structure database for post-translational modifications and mutations with functional impact

Fan

Marquez‐Lago

et al. 2019

Preprint

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Detection and analysis of disease-associated single nucleotide polymorphism influencing post-translational modification

Cited by 29 publications

References 31 publications

KSP: an integrated method for predicting catalyzing kinases of phosphorylation sites in proteins

KSP: an integrated method for predicting catalyzing kinases of phosphorylation sites in proteins

PRISMOID: a comprehensive 3D structure database for post-translational modifications and mutations with functional impact

PRISMOID: a comprehensive 3D structure database for post-translational modifications and mutations with functional impact

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