Protein-kinase inhibitors: A new treatment pathway for autoimmune and inflammatory diseases?

Novel biomarker discovery through comprehensive proteomic analysis of lupus mouse serum

OBJECTIVES

The difficulty of monitoring organ-specific pathology in systemic lupus erythematosus (SLE) often complicates disease prognostication and treatment. Improved non-invasive biomarkers of active organ pathology, particularly lupus nephritis, would improve patient care. We sought to validate and apply a novel strategy to generate the first comprehensive serum proteome of a lupus mouse model and identify mechanism-linked lupus biomarker candidates for subsequent clinical investigation.

METHODS

Serum levels of 1308 diverse proteins were measured in eight adult female MRL/lpr lupus mice and eight control MRL/mpj mice. ELISA validation confirmed fold increases. Protein enrichment analysis provided biological relevance to findings. Individual protein levels were correlated with measures of lymphoproliferative, humoral, and renal disease.

RESULTS

Four hundred and six proteins were increased in MRL/lpr serum, including proteins increased in human SLE such as VCAM-1, L-selectin, TNFRI/II, TWEAK, CXCL13, MCP-1, IP-10, IL-10, and TARC. Newly validated proteins included IL-6, IL-17, and MDC. Results of pathway enrichment analysis, which revealed enhancement of cytokine signaling and immune cell migration, reinforced the similarity of the MRL/lpr disease to human pathology. Fifty-two proteins positively correlated with at least one measure of lupus-like disease. TECK, TSLP, PDGFR-alpha, and MDC were identified as novel candidate biomarkers of renal disease.

CONCLUSIONS

We successfully validated a novel serum proteomic screening strategy in a spontaneous murine lupus model that highlighted potential new biomarkers. Importantly, we generated a comprehensive snapshot of the serum proteome which will enable identification of other candidates and serve as a reference for future mechanistic and therapeutic studies in lupus.

AIPs-SnTCN: Predicting Anti-Inflammatory Peptides Using fastText and Transformer Encoder-Based Hybrid Word Embedding with Self-Normalized Temporal Convolutional Networks

Inflammation is a biologically resistant response to harmful stimuli, such as infection, damaged cells, toxic chemicals, or tissue injuries. Its purpose is to eradicate pathogenic micro-organisms or irritants and facilitate tissue repair. Prolonged inflammation can result in chronic inflammatory diseases. However, wet-laboratory-based treatments are costly and time-consuming and may have adverse side effects on normal cells. In the past decade, peptide therapeutics have gained significant attention due to their high specificity in targeting affected cells without affecting healthy cells. Motivated by the significance of peptide-based therapies, we developed a highly discriminative prediction model called AIPs-SnTCN to predict anti-inflammatory peptides accurately. The peptide samples are encoded using word embedding techniques such as skip-gram and attention-based bidirectional encoder representation using a transformer (BERT). The conjoint triad feature (CTF) also collects structure-based cluster profile features. The fused vector of word embedding and sequential features is formed to compensate for the limitations of single encoding methods. Support vector machine-based recursive feature elimination (SVM-RFE) is applied to choose the ranking-based optimal space. The optimized feature space is trained by using an improved self-normalized temporal convolutional network (SnTCN). The AIPs-SnTCN model achieved a predictive accuracy of 95.86% and an AUC of 0.97 by using training samples. In the case of the alternate training data set, our model obtained an accuracy of 92.04% and an AUC of 0.96. The proposed AIPs-SnTCN model outperformed existing models with an ∼19% higher accuracy and an ∼14% higher AUC value. The reliability and efficacy of our AIPs-SnTCN model make it a valuable tool for scientists and may play a beneficial role in pharmaceutical design and research academia.

Safety and efficacy in the nursing care of people with rheumatic diseases on janus kinase inhibitor therapy

Nurses's support of patients needs an evidence base as much as that of specialists management. However, some more practical aspects need specific questions that are not addressed in medical societies' recommendations. Our objective was to investigate the effect of Janus kinase inhibitors (jakinibs) on efficacy, safety, infections, cardiovascular risk, vaccination, pregnancy and lactation, interactions, surgery, and switch in adult patients with rheumatic diseases. We used the methodology for rapid reviews. Medline was searched for systematic reviews of randomised clinical trials and longitudinal observational studies reporting on the target aspects, without limits, yielding 540 titles, of which 70 articles were selected for detailed reading after the screening of title and abstract. In the case of no systematic review being published on a specific question, we resorted to the information provided by primary studies. The efficacy and safety profiles are similar to that of TNF-inhibitors to which they are compared in most studies; however, there is an increased risk of herpes zoster infections with jakinibs. The evidence on pregnancy, surgery and switches between jakinibs is very limited, although, so far, there are no major issues to inform patients about or to implement specific measures. In general, evidence to support nursing management in patients being treated with jakinibs is of moderate quality and scarce, ought to the recent incursion of jakinibs as a treatment.

Lipid metabolism in autoimmune rheumatic disease: implications for modern and conventional therapies

Suppressing inflammation has been the primary focus of therapies in autoimmune rheumatic diseases (AIRDs), including rheumatoid arthritis and systemic lupus erythematosus. However, conventional therapies with low target specificity can have effects on cell metabolism that are less predictable. A key example is lipid metabolism; current therapies can improve or exacerbate dyslipidemia. Many conventional drugs also require in vivo metabolism for their conversion into therapeutically beneficial products; however, drug metabolism often involves the additional formation of toxic by-products, and rates of drug metabolism can be heterogeneous between patients. New therapeutic technologies and research have highlighted alternative metabolic pathways that can be more specifically targeted to reduce inflammation but also to prevent undesirable off-target metabolic consequences of conventional antiinflammatory therapies. This Review highlights the role of lipid metabolism in inflammation and in the mechanisms of action of AIRD therapeutics. Opportunities for cotherapies targeting lipid metabolism that could reduce immunometabolic complications and potential increased cardiovascular disease risk in patients with AIRDs are discussed.

Bruton tyrosine kinase inhibitors as potential therapeutic agents for COVID-19: A review

Coronavirus disease 2019 (COVID-19) is first detected in December 2019 in Wuhan, China which is a new pandemic caused by SARS-COV-2 that has greatly affected the whole world. Bruton tyrosine kinase (BTK) inhibitors are drugs that are used for the management of cancer, and are being repurposed for COVID-19. BTK regulates macrophage and B cell activation, development, survival, and signaling. Inhibition of BTK has revealed an ameliorative effect on lung injury in patients with severe COVID-19. Thus, this review aimed to summarize evidence regarding the role of Bruton tyrosine kinase inhibitors against COVID-19. To include findings from diverse studies, publications related to BTK inhibitors and Covid-19 were searched from the databases such as SCOPUS, Web of Science, Medline, Google Scholar, PubMed, and Elsevier, using English key terms. Both experimental and clinical studies suggest that targeting excessive host inflammation with a BTK inhibitor is a potential therapeutic strategy in the treatment of patients with severe COVID-19. Currently, BTK inhibitors such as ibrutinib and acalabrutinib have shown a protective effect against pulmonary injury in a small series group of COVID-19 infected patients. Small molecule inhibitors like BTK inhibitors, targeting a wide range of pro-inflammatory singling pathways, may a key role in the management of COVID-19.

Small Molecule Inhibitors in the Treatment of Rheumatoid Arthritis and Beyond: Latest Updates and Potential Strategy for Fighting COVID-19

The development of biological disease-modifying antirheumatic drugs (bDMARDs) and target synthetic DMARDs (tsDMARDs), also known as small molecule inhibitors, represent a breakthrough in rheumatoid arthritis (RA) treatment. The tsDMARDs are a large family of small molecules targeting mostly the several types of kinases, which are essential in downstream signaling of pro-inflammatory molecules. This review highlights current challenges associated with the treatment of RA using small molecule inhibitors targeting intracellular JAKs/MAPKs/NF-κB/SYK-BTK signaling pathways. Indeed, we have provided the latest update on development of small molecule inhibitors, their clinical efficacy and safety as a strategy for RA treatment. On the other hand, we have highlighted the risk and adverse effects of tsDMARDs administration including, among others, infections and thromboembolism. Therefore, performance of blood tests or viral infection screening should be recommended before the tsDMARDs administration. Interestingly, recent events of SARS-CoV-2 outbreak have demonstrated the potential use of small molecule inhibitors not only in RA treatment, but also in fighting COVID-19 via blocking the viral entry, preventing of hyperimmune activation and reducing cytokine storm. Thus, small molecule inhibitors, targeting wide range of pro-inflammatory singling pathways, may find wider implications not only for the management of RA but also in the controlling of COVID-19.

Pharmacophore modeling of JAK1: A target infested with activity-cliffs

Janus kinase 1 (JAK1) is protein kinase involved in autoimmune diseases (AIDs). JAK1 inhibitors have shown promising results in treating AIDs. JAK1 inhibitors are known to exhibit regions of SAR discontinuity or activity cliffs (ACs). ACs represent fundamental challenge to successful QSAR/pharmacophore modeling because QSAR modeling rely on the basic premise that activity is a smooth continuous function of structure. We propose that ACs exist because active ACs members exhibit subtle, albeit critical, enthalpic features absent from their inactive twins. In this context we compared the performances of two computational modeling workflows in extracting valid pharmacophores from 151 diverse JAK1 inhibitors that include ACs: QSAR-guided pharmacophore selection versus docking-based comparative intermolecular contacts analysis (db-CICA). The two methods were judged based on the receiver operating characteristic (ROC) curves of their corresponding pharmacophore models and their abilities to distinguish active members among established JAK1 ACs. db-CICA modeling significantly outperformed ligand-based pharmacophore modeling. The resulting optimal db-CICA pharmacophore was used as virtual search query to scan the National Cancer Institute (NCI) database for novel JAK1 inhibitory leads. The most active hit showed IC₅₀ of 1.04 μM. This study proposes the use of db-CICA modeling as means to extract valid pharmacophores from SAR data infested with ACs.

C─H⋯O hydrogen bonds in kinase-inhibitor interfaces

C─H⋯O hydrogen bonds constitute a unique class of cohesive interactions. Their properties are similar to those of canonical H-bonds, although their energy is significantly lower, typically in the 0.5-2.5 kcal/mol range. Polarised C─H groups, such as those adjacent to electronegative groups, or within aromatic moieties, are particularly strong donors. C─H⋯O bonds are ubiquitous in nucleic acids and in proteins, notably stabilizing the β-sheet secondary structure. They have also been observed in numerous protein-ligand interactions. Here, we analysed crystal structures, deposited in the Protein Data Bank, of complexes of FDA-approved protein kinase inhibitors with cognate kinases, to assess the possible role of C─H^inhibitor ⋯O^protein hydrogen bonds. The conserved hinge motif of protein kinases with two solvent-exposed carbonyl groups and one exposed backbone amide, is well known to be involved in canonical H-bonding with inhibitors. We now find that in virtually all complexes where the inhibitor interacts with the hinge backbone, at least one of the hinge carbonyl groups accepts an H-bond from a C─H inhibitor group, which is either aromatic or adjacent to an electronegative group. These observations are important for design of hinge-binding scaffolds of novel kinase inhibitors for therapeutic use.

PreAIP: Computational Prediction of Anti-inflammatory Peptides by Integrating Multiple Complementary Features

Numerous inflammatory diseases and autoimmune disorders by therapeutic peptides have received substantial consideration; however, the exploration of anti-inflammatory peptides via biological experiments is often a time-consuming and expensive task. The development of novel in silico predictors is desired to classify potential anti-inflammatory peptides prior to in vitro investigation. Herein, an accurate predictor, called PreAIP (Predictor of Anti-Inflammatory Peptides) was developed by integrating multiple complementary features. We systematically investigated different types of features including primary sequence, evolutionary and structural information through a random forest classifier. The final PreAIP model achieved an AUC value of 0.833 in the training dataset via 10-fold cross-validation test, which was better than that of existing models. Moreover, we assessed the performance of the PreAIP with an AUC value of 0.840 on a test dataset to demonstrate that the proposed method outperformed the two existing methods. These results indicated that the PreAIP is an accurate predictor for identifying AIPs and contributes to the development of AIPs therapeutics and biomedical research. The curated datasets and the PreAIP are freely available at http://kurata14.bio.kyutech.ac.jp/PreAIP/.

Kinase inhibitors: the road ahead

Receptor tyrosine kinase signalling pathways have been successfully targeted to inhibit proliferation and angiogenesis for cancer therapy. However, kinase deregulation has been firmly demonstrated to play an essential role in virtually all major disease areas. Kinase inhibitor drug discovery programmes have recently broadened their focus to include an expanded range of kinase targets and therapeutic areas. In this Review, we provide an overview of the novel targets, biological processes and disease areas that kinase-targeting small molecules are being developed against, highlight the associated challenges and assess the strategies and technologies that are enabling efficient generation of highly optimized kinase inhibitors.

Oxindole-based SYK and JAK3 dual inhibitors for rheumatoid arthritis: designing, synthesis and biological evaluation

Aim: Autoimmune disorders have complex pathophysiology and focus is laid on the development of multitargeted agents. Two well-established kinases: SYK and JAK3, were considered to design dual inhibitors as potential therapeutics using various molecular-modeling approaches. Mehodology: Pharmacophore models for SYK and JAK3 were generated using oxindole-based inhibitors. Furthermore, an in-house database was designed that was screened against the best selected models. The obtained hits were employed for docking analysis and subjected to MM-GBSA analysis and molecular dynamic simulation. Results: Top five oxindole derivatives were synthesized and evaluated for in vitro SYK and JAK3 activity. The most active compound 4a was evaluated for in vivo antiarthritic activity. It showed significant anti-arthritic activity. Conclusion: Thus, the designed inhibitors resulted in potential therapeutic agents for rheumatoid arthritis.

Pyridazinone: an attractive lead for anti-inflammatory and analgesic drug discovery

In spite of the availability of a large number of anti-inflammatory and analgesic agents, fighting pain and inflammation remains a common problem. The current review article discusses the need of novel therapeutic targets for risk-free anti-inflammatory and analgesic therapy and summarizes some new agents in various stages of drug discovery pipeline. Pyridazin-3(2H)-ones are nitrogen-rich heterocyclic compounds of considerable medicinal interest due to their diverse biological activities. The current review article focuses on progressive development of this attractive scaffold for the design and synthesis of new pyridazinone-based anti-inflammatory and analgesic agents. Mechanistic insights into the anti-inflammatory and analgesic properties of pyridazinone derivatives and various synthetic techniques used for their synthesis are also described.

Chemical Proteomics and Structural Biology Define EPHA2 Inhibition by Clinical Kinase Drugs

The receptor tyrosine kinase EPHA2 (Ephrin type-A receptor 2) plays important roles in oncogenesis, metastasis, and treatment resistance, yet therapeutic targeting, drug discovery, or investigation of EPHA2 biology is hampered by the lack of appropriate inhibitors and structural information. Here, we used chemical proteomics to survey 235 clinical kinase inhibitors for their kinase selectivity and identified 24 drugs with submicromolar affinities for EPHA2. NMR-based conformational dynamics together with nine new cocrystal structures delineated drug-EPHA2 interactions in full detail. The combination of selectivity profiling, structure determination, and kinome wide sequence alignment allowed the development of a classification system in which amino acids in the drug binding site of EPHA2 are categorized into key, scaffold, potency, and selectivity residues. This scheme should be generally applicable in kinase drug discovery, and we anticipate that the provided information will greatly facilitate the development of selective EPHA2 inhibitors in particular and the repurposing of clinical kinase inhibitors in general.