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Kinases and Phosphatases
Special Issues
Research on Protein Phosphorylation in Genetic Diseases
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Research on Protein Phosphorylation in Genetic Diseases

A special issue of Kinases and Phosphatases (ISSN 2813-3757).

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 11250

Special Issue Editors

Dr. Mauro Salvi

E-Mail Website
Guest Editor
Department of Biomedical Sciences, University of Padova, Padova, Italy
Interests: protein phosphorylation; acidic protein kinases; tyrosine kinases; kinase inhibitors, signal transduction; post-translational modifications; cancer; cystic fibrosis
Special Issues, Collections and Topics in MDPI journals
Dr. Christian Borgo

E-Mail Website
Guest Editor
Department of Biomedical Sciences, University of Padova, Via U. Bassi 58/B, 35131 Padova, Italy
Interests: chronic myeloid leukemia; cystic fibrosis; glucose metabolism; drug-resistance; phosphorylation; protein kinase inhibitors; protein kinase ck2; CFTR
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Protein phosphorylation is the most recurrent post-translational modification by which the properties of eukaryotic proteins can be reversibly changed. In a protein, the phosphorylation extent of tyrosine, serine, and threonine sites are regulated by the balance of the action of protein kinases and protein phosphatases. In humans, over 500 protein kinases generate a huge phosphoproteome including more than 200,000 individual phosphosites, and approximately 200 phosphatases are involved in their dephosphorylation. It is well known that an aberrant phosphorylation could take part to the pathogenesis of several human diseases, such as cancer, neurodegenerative diseases, diabetes. Likewise, inherited mutations in genes of specific protein kinases or phosphatases have been identified as the cause of different genetic diseases, such as Pfeiffer syndrome, Crouzon syndrome, Raine syndrome, Donohue syndrome, Noonan syndrome etc. Moreover, also pathological proteins involved in genetic disorders have been shown to have an aberrant function due to the alteration of their phosphorylation state, caused by the disease-associated mutation, including α-synuclein, tau, APP. In this perspective, over the years there has been a progressive interest in the development of drugs that target specific protein kinases and or phosphatases for the treatment of various genetic disorders. This Special Issue will cover the recent progress in all of the areas related to the involvement of protein phosphorylation in genetic diseases. Both original research articles and reviews are welcome.

Dr. Mauro Salvi
Dr. Christian Borgo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Kinases and Phosphatases is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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Published Papers (2 papers)

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Research

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33 pages, 5262 KiB  
Article
Site-Specific Phosphorylation of RTK KIT Kinase Insert Domain: Interactome Landscape Perspectives
by Julie Ledoux and Luba Tchertanov
Kinases Phosphatases 2023, 1(1), 39-71; https://doi.org/10.3390/kinasesphosphatases1010005 - 15 Feb 2023
Viewed by 2585
Abstract
The kinase insert domain (KID) of RTK KIT is a key recruitment region for downstream signalling proteins (DSPs). KID, as a multisite phosphorylation region, provides alternative recognition sites for DSPs and activates them by binding a phosphotyrosine (pY) to their SH2 domains. Significant [...] Read more.
The kinase insert domain (KID) of RTK KIT is a key recruitment region for downstream signalling proteins (DSPs). KID, as a multisite phosphorylation region, provides alternative recognition sites for DSPs and activates them by binding a phosphotyrosine (pY) to their SH2 domains. Significant steric, biochemical, and biophysical requirements must be fulfilled by each pair of interacting proteins as the adaptation of their configurations is mandatory for the selective activation of DSPs. The accurate 3D atomistic models obtained by modelling and molecular dynamics (MD) simulations of phosphorylated KID (p-KID) have been delivered to describe KID INTERACTOME. By taking phosphorylated KIDpY721 and the N-terminal SH2 domain of phosphatidylinositol 3-kinase (PI3K), a physiological partner of KID, we showed the two proteins are intrinsically disordered. Using 3D models of both proteins, we probe alternative orientations of KIDpY721 relative to the SH2 binding pocket using automatic docking (HADDOCK) and intuitive user-guided docking. This modelling yields to two possible models of the functionally related non-covalent complex KIDpY721/SH2, where one can be regarded as the first precursor to probe PI3K activation via KIT KID. We suggest that such generation of a KID/SH2 complex is best suited for future studies of the post-transduction effects of RTK KIT. Full article
(This article belongs to the Special Issue Research on Protein Phosphorylation in Genetic Diseases)
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Review

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24 pages, 831 KiB  
Review
Recent Advancements in Computational Drug Design Algorithms through Machine Learning and Optimization
by Soham Choudhuri, Manas Yendluri, Sudip Poddar, Aimin Li, Koushik Mallick, Saurav Mallik and Bhaswar Ghosh
Kinases Phosphatases 2023, 1(2), 117-140; https://doi.org/10.3390/kinasesphosphatases1020008 - 5 May 2023
Cited by 18 | Viewed by 7691
Abstract
The goal of drug discovery is to uncover new molecules with specific chemical properties that can be used to cure diseases. With the accessibility of machine learning techniques, the approach used in this search has become a significant component in computer science in [...] Read more.
The goal of drug discovery is to uncover new molecules with specific chemical properties that can be used to cure diseases. With the accessibility of machine learning techniques, the approach used in this search has become a significant component in computer science in recent years. To meet the Precision Medicine Initiative’s goals and the additional obstacles that they have created, it is vital to develop strong, consistent, and repeatable computational approaches. Predictive models based on machine learning are becoming increasingly crucial in preclinical investigations. In discovering novel pharmaceuticals, this step substantially reduces expenses and research times. The human kinome contains various kinase enzymes that play vital roles through catalyzing protein phosphorylation. Interestingly, the dysregulation of kinases causes various human diseases, viz., cancer, cardiovascular disease, and several neuro-degenerative disorders. Thus, inhibitors of specific kinases can treat those diseases through blocking their activity as well as restoring normal cellular signaling. This review article discusses recent advancements in computational drug design algorithms through machine learning and deep learning and the computational drug design of kinase enzymes. Analyzing the current state-of-the-art in this sector will offer us a sense of where cheminformatics may evolve in the near future and the limitations and beneficial outcomes it has produced. The approaches utilized to model molecular data, the biological problems addressed, and the machine learning algorithms employed for drug discovery in recent years will be the emphasis of this review. Full article
(This article belongs to the Special Issue Research on Protein Phosphorylation in Genetic Diseases)
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