Bioinformatics in protein kinases regulatory network and drug discovery

Inhibitors targeting the autophosphorylation of serine/threonine kinase of Streptococcus suis show potent antimicrobial activity

Antimicrobial resistance (AMR) is a global concern threatening public health. Developing novel antibiotics is one of the effective strategies to tackle AMR. Serine/threonine kinases (STKs) have been recently shown to play critical roles in the physiology and pathogenesis of several important bacterial pathogens which are regarded as a promising antimicrobial drug target. We previously reported the roles of STK in the regulation of bacterial cell division, metabolism, and pathogenesis in Streptococcus suis, an important zoonotic bacterial pathogen. In this study, we firstly identified the Thr167 and Ser175 residues in the activation loop of S. suis STK (ssSTK) as the kinase autophosphorylation sites. Phenotyping results demonstrated that the autophosphorylation deficient strain resembled the stk deletion strain showing essentiality for bacterial growth in minimal medium, abnormal morphology, and decreased virulence when compared with the wild-type S. suis SC19 strain. Based on these findings, we established an ssSTK inhibitor screening approach by measuring the growth of S. suis in a minimal medium and testing the autophosphorylation inhibition by measuring the consumption of ATP in an enzymatic reaction by ssSTK. A series of inhibitors against ssSTK are identified from a commercial kinase inhibitors library, including Staurosporine, K252a, AT9283, and APY29. These inhibitors showed antimicrobial activity in vitro. Moreover, by using Galleria mellonella larvae infection assay, compound APY29 displayed in vivo efficacy against S. suis infection. Additionally, it was predicted by molecular docking that these inhibitors could interact with ssSTK. Collectively, our data illustrated the essential roles of ssSTK autophosphorylation in the physiology and pathogenicity of S. suis and consider these inhibitors as promising antimicrobial lead compounds.

Alveolar Regeneration in COVID-19 Patients: A Network Perspective

A viral infection involves entry and replication of viral nucleic acid in a host organism, subsequently leading to biochemical and structural alterations in the host cell. In the case of SARS-CoV-2 viral infection, over-activation of the host immune system may lead to lung damage. Albeit the regeneration and fibrotic repair processes being the two protective host responses, prolonged injury may lead to excessive fibrosis, a pathological state that can result in lung collapse. In this review, we discuss regeneration and fibrosis processes in response to SARS-CoV-2 and provide our viewpoint on the triggering of alveolar regeneration in coronavirus disease 2019 (COVID-19) patients.

Pattern and Dynamics of FLT3 Duplications

FMS-like tyrosine kinase 3 (FLT3) is mutated in ∼30% of patients that suffer from acute myeloid leukemia (AML). In about 25% of all AML patients, in-frame insertions are observed in the sequence. Most of those insertions are internal tandem duplications (ITDs) of a sequence from the protein. The characteristics of such mutations in terms of length, sequence, and location were hitherto studied in different populations, but not in a comprehensive mutation database. Here, in-frame insertions into the FLT3 gene were extracted from the Catalogue of Somatic Mutations in Cancer (COSMIC) database. These were analyzed with respect to the length, location, and sequence of the mutations. Furthermore, characteristic strings (sequences) of different lengths were identified. Mutations were shown to occur most often in the juxtamembrane zipper (JM-Z) domain of FLT3, followed by the hinge domain and first tyrosine kinase domain (TKD1), upstream of the phosphate-binding loop (P-loop). Interestingly, there are specific hot spot residues where insertions are more likely to occur. The insertions vary in length between one and 67 amino acids, with the largest insertions spanning the phosphate binding loop. Insertions that occur downstream of the P-loop are shorter. Our analysis further shows that acidic and aromatic residues are enriched in the insertions. Finally, molecular dynamics simulations were run for FLT3 with ITD insertions in the hinge and tyrosine kinase domains. On the basis of the findings, a mechanism is proposed for activation by ITDs, according to which there is no direct coupling between the length of the insertion and the activity of the mutated protein. The effect of insertions on the sensitivity of FLT3 to kinase inhibitors is discussed based on our findings.

Construction of Quantitative Structure Activity Relationship (QSAR) Models to Predict Potency of Structurally Diversed Janus Kinase 2 Inhibitors

Janus kinase 2 (JAK2) inhibitors represent a promising therapeutic class of anticancer agents against many myeloproliferative disorders. Bioactivity data on pIC50 of 2229 JAK2 inhibitors were employed in the construction of quantitative structure-activity relationship (QSAR) models. The models were built from 100 data splits using decision tree (DT), support vector machine (SVM), deep neural network (DNN) and random forest (RF). The predictive power of RF models were assessed via 10-fold cross validation, which afforded excellent predictive performance with R2 and RMSE of 0.74 ± 0.05 and 0.63 ± 0.05, respectively. Moreover, test set has excellent performance of R2 (0.75 ± 0.03) and RMSE (0.62 ± 0.04). In addition, Y-scrambling was utilized to evaluate the possibility of chance correlation of the predictive model. A thorough analysis of the substructure fingerprint count was conducted to provide insights on the inhibitory properties of JAK2 inhibitors. Molecular cluster analysis revealed that pyrazine scaffolds have nanomolar potency against JAK2.

Identifying Interactions Between Long Noncoding RNAs and Diseases Based on Computational Methods

With the development and improvement of next-generation sequencing technology, a great number of noncoding RNAs have been discovered. Long noncoding RNAs (lncRNAs) are the biggest kind of noncoding RNAs with more than 200 nt nucleotides in length. There are increasing evidences showing that lncRNAs play key roles in many biological processes. Therefore, the mutation and dysregulation of lncRNAs have close association with a number of complex human diseases. Identifying the most likely interaction between lncRNAs and diseases becomes a fundamental challenge in human health. A common view is that lncRNAs with similar function tend to be related to phenotypic similar diseases. In this chapter, we firstly introduce the concept of lncRNA, their biological features, and available data resources. Further, the recent computational approaches are explored to identify interactions between long noncoding RNAs and diseases, including their advantages and disadvantages. The key issues and potential future works of predicting interactions between long noncoding RNAs and diseases are also discussed.

Drug repurposing: Ibrutinib exhibits immunosuppressive potential in organ transplantation

Long-term administration of classic immunosuppressants can induce severe adverse effects. The development of novel immunosuppressants confronts great challenges and opportunities. Ibrutinib, an approved drug for B-cell lineages and chronic graft versus host disease (cGVHD), exhibits immunosuppressive efficacy in autoimmune diseases. Ibrutinib's potential as an immunosuppressant in organ transplantation has not been investigated to date. In a xeno-artery patch model ex vivo, ibrutinib inhibited the proliferation of PBMCs (POD 14-42), mainly CD3⁺CD4⁺ and CD3⁺CD8⁺ T cells ex vivo. The secretion of cytokines (IL-6, IL-2 and IFN-γ) was suppressed in response to ibrutinib. In allo-skin transplantation models, ibrutinib delayed the rejection of grafted skins. Ibrutinib decreased the amount of T/B cells and lymphocyte infiltration. Altogether, ibrutinib exhibited immunosuppressive potential through cytokine regulation and T cell inhibition ex vivo and in vitro. Repositioning of ibrutinib as an immunosuppressant will greatly facilitate novel immunosuppressant development.

In-silico design and molecular docking evaluation of peptides derivatives from bacteriocins and porcine beta defensin-2 as inhibitors of Hepatitis E virus capsid protein

Hepatitis E virus (HEV) is considered the main etiological agent that causes acute hepatitis. It is estimated that 20 million cases occur annually worldwide, reaching mortality rates of 28% in pregnant women. To date, available treatments and vaccines have not been entirely effective. In this study, six antiviral peptides derived from the sequences of porcine Beta-Defensin-2 and bacteriocins Nisin and Subtilosin were generate using in silico tools in order to propose new antiviral agents. Through the use of molecular docking, interactions between the HEV capsid protein and the six new antiviral peptide candidates were evaluated. A peptide of 15 residues derived from Subtilosin showed the best docking energy (-7.0 kcal/mol) with the capsid protein. This is the first report to our knowledge involving a non-well study viral protein interacting with peptides susceptibles to being synthesized, and that could be subsequently evaluated in vitro; moreover, this study provide novel information on the nature of the dimerization pocket of the HEV capsid protein, and could help to understand the first steps in the viral replication cycle, needed for the virus entry to the host cell.

High quality, small molecule-activity datasets for kinase research

Kinases regulate cell growth, movement, and death. Deregulated kinase activity is a frequent cause of disease. The therapeutic potential of kinase inhibitors has led to large amounts of published structure activity relationship (SAR) data. Bioactivity databases such as the Kinase Knowledgebase (KKB), WOMBAT, GOSTAR, and ChEMBL provide researchers with quantitative data characterizing the activity of compounds across many biological assays. The KKB, for example, contains over 1.8M kinase structure-activity data points reported in peer-reviewed journals and patents. In the spirit of fostering methods development and validation worldwide, we have extracted and have made available from the KKB 258K structure activity data points and 76K associated unique chemical structures across eight kinase targets. These data are freely available for download within this data note.

High quality, small molecule-activity datasets for kinase research

Kinases regulate cell growth, movement, and death. Deregulated kinase activity is a frequent cause of disease. The therapeutic potential of kinase inhibitors has led to large amounts of published structure activity relationship (SAR) data. Bioactivity databases such as the Kinase Knowledgebase (KKB), WOMBAT, GOSTAR, and ChEMBL provide researchers with quantitative data characterizing the activity of compounds across many biological assays. The KKB, for example, contains over 1.8M kinase structure-activity data points reported in peer-reviewed journals and patents. In the spirit of fostering methods development and validation worldwide, we have extracted and have made available from the KKB 258K structure activity data points and 76K associated unique chemical structures across eight kinase targets. These data are freely available for download within this data note.

High quality, small molecule-activity datasets for kinase research

Kinases regulate cell growth, movement, and death. Deregulated kinase activity is a frequent cause of disease. The therapeutic potential of kinase inhibitors has led to large amounts of published structure activity relationship (SAR) data. Bioactivity databases such as the Kinase Knowledgebase (KKB), WOMBAT, GOSTAR, and ChEMBL provide researchers with quantitative data characterizing the activity of compounds across many biological assays. The KKB, for example, contains over 1.8M kinase structure-activity data points reported in peer-reviewed journals and patents. In the spirit of fostering methods development and validation worldwide, we have extracted and have made available from the KKB 258K structure activity data points and 76K associated unique chemical structures across eight kinase targets. These data are freely available for download within this data note.