Discovery of potent and selective reversible Bruton's tyrosine kinase inhibitors

Constructing Innovative Covalent and Noncovalent Compound Libraries: Insights from 3D Protein-Ligand Interactions

Noncovalent interactions between small-molecule drugs and protein targets assume a pivotal role in drug design. Moreover, the design of covalent inhibitors, forming covalent bonds with amino acid residues, requires rational reactivity for their covalent warheads, presenting a key challenge as well. Understanding the intricacies of these interactions provides a more comprehensive understanding of molecular binding mechanisms, thereby guiding the rational design of potent inhibitors. In this study, we adopted the fragment-based drug design approach, introducing a novel methodology to extract noncovalent and covalent fragments according to distinct three-dimensional (3D) interaction modes from noncovalent and covalent compound libraries. Additionally, we systematically replaced existing ligands with rational fragment substitutions, based on the spatial orientation of fragments in 3D space. Furthermore, we adopted a molecular generation approach to create innovative covalent inhibitors. This process resulted in the recombination of a noncovalent compound library and several covalent compound libraries, constructed by two commonly encountered covalent amino acids: cysteine and serine. We utilized noncovalent ligands in KLIFS and covalent ligands in CovBinderInPDB as examples to recombine noncovalent and covalent libraries. These recombined compound libraries cover a substantial portion of the chemical space present in the original compound libraries and exhibit superior performance in terms of molecular scaffold diversity compared to the original compound libraries and other 11 commercial libraries. We also recombined BTK-focused libraries, and 23 compounds within our libraries have been validated by former researchers to possess potential biological activity. The establishment of these compound libraries provides valuable resources for virtual screening of covalent and noncovalent drugs targeting similar molecular targets.

Recent research of BTK inhibitors: Methods of structural design, pharmacological activities, manmade derivatives and structure-activity relationship

Protein kinases constitute the largest group within the kinase family, and mutations and translocations of protein kinases due to genetic alterations are intimately linked to the pathogenesis of numerous diseases. Bruton's tyrosine kinase (BTK) is a member of the protein kinases and plays a pivotal role in the development and function of B cells. BTK belongs to the tyrosine TEC family. The aberrant activation of BTK is closely associated with the pathogenesis of B-cell lymphoma. Consequently, BTK has always been a critical target for treating hematological malignancies. To date, two generations of small-molecule covalent irreversible BTK inhibitors have been employed to treat malignant B-cell tumors, and have exhibited clinical efficacy in hitherto refractory diseases. However, these drugs are covalent BTK inhibitors, which inevitably lead to drug resistance after prolonged use, resulting in poor tolerance in patients. The third-generation non-covalent BTK inhibitor Pirtobrutinib has obtained approval for marketing in the United States, thereby circumventing drug resistance caused by C481 mutation. Currently, enhancing safety and tolerance constitutes the primary issue in developing novel BTK inhibitors. This article systematically summarizes recently discovered covalent and non-covalent BTK inhibitors and classifies them according to their structures. This article also provides a detailed discussion of binding modes, structural features, pharmacological activities, advantages and limitations of typical compounds within each structure type, providing valuable references and insights for developing safer, more effective and more targeted BTK inhibitors in future studies.

Machine learning-based classification models for non-covalent Bruton's tyrosine kinase inhibitors: predictive ability and interpretability

In this study, we built classification models using machine learning techniques to predict the bioactivity of non-covalent inhibitors of Bruton's tyrosine kinase (BTK) and to provide interpretable and transparent explanations for these predictions. To achieve this, we gathered data on BTK inhibitors from the Reaxys and ChEMBL databases, removing compounds with covalent bonds and duplicates to obtain a dataset of 3895 inhibitors of non-covalent. These inhibitors were characterized using MACCS fingerprints and Morgan fingerprints, and four traditional machine learning algorithms (decision trees (DT), random forests (RF), support vector machines (SVM), and extreme gradient boosting (XGBoost)) were used to build 16 classification models. In addition, four deep learning models were developed using deep neural networks (DNN). The best model, Model D_4, which was built using XGBoost and MACCS fingerprints, achieved an accuracy of 94.1% and a Matthews correlation coefficient (MCC) of 0.75 on the test set. To provide interpretable explanations, we employed the SHAP method to decompose the predicted values into the contributions of each feature. We also used K-means dimensionality reduction and hierarchical clustering to visualize the clustering effects of molecular structures of the inhibitors. The results of this study were validated using crystal structures, and we found that the interaction between the BTK amino acid residue and the important features of clustered scaffold was consistent with the known properties of the complex crystal structures. Overall, our models demonstrated high predictive ability and a qualitative model can be converted to a quantitative model to some extent by SHAP, making them valuable for guiding the design of new BTK inhibitors with desired activity.

Structural Complementarity of Bruton’s Tyrosine Kinase and Its Inhibitors for Implication in B-Cell Malignancies and Autoimmune Diseases

Bruton’s tyrosine kinase (BTK) is a critical component in B-cell receptor (BCR) signaling and is also expressed in haematogenic and innate immune cells. Inhibition of BTK hyperactivity is implicated in B-cell malignancies and autoimmune diseases. This review derives the structural complementarity of the BTK-kinase domain and its inhibitors from recent three-dimensional structures of inhibitor-bound BTK in the protein data bank (PDB). Additionally, this review analyzes BTK-mediated effector responses of B-cell development and antibody production. Covalent inhibitors contain an α, β-unsaturated carbonyl moiety that forms a covalent bond with Cys481, stabilizing αC-helix in inactive-out conformation which inhibits Tyr551 autophosphorylation. Asn484, located two carbons far from Cys481, influences the stability of the BTK-transition complex. Non-covalent inhibitors engage the BTK-kinase domain through an induced-fit mechanism independent of Cys481 interaction and bind to Tyr551 in the activation kink resulting in H3 cleft, determining BTK selectivity. Covalent and non-covalent binding to the kinase domain of BTK shall induce conformational changes in other domains; therefore, investigating the whole-length BTK conformation is necessary to comprehend BTK’s autophosphorylation inhibition. Knowledge about the structural complementarity of BTK and its inhibitors supports the optimization of existing drugs and the discovery of drugs for implication in B-cell malignancies and autoimmune diseases.

Bruton's Tyrosine Kinase Inhibitors (BTKIs): Review of Preclinical Studies and Evaluation of Clinical Trials

In the last few decades, there has been a growing interest in Bruton's tyrosine kinase (BTK) and the compounds that target it. BTK is a downstream mediator of the B-cell receptor (BCR) signaling pathway and affects B-cell proliferation and differentiation. Evidence demonstrating the expression of BTK on the majority of hematological cells has led to the hypothesis that BTK inhibitors (BTKIs) such as ibrutinib can be an effective treatment for leukemias and lymphomas. However, a growing body of experimental and clinical data has demonstrated the significance of BTK, not just in B-cell malignancies, but also in solid tumors, such as breast, ovarian, colorectal, and prostate cancers. In addition, enhanced BTK activity is correlated with autoimmune disease. This gave rise to the hypothesis that BTK inhibitors can be beneficial in the therapy of rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), multiple sclerosis (MS), Sjögren's syndrome (SS), allergies, and asthma. In this review article, we summarize the most recent findings regarding this kinase as well as the most advanced BTK inhibitors that have been developed to date and their clinical applications mainly in cancer and chronic inflammatory disease patients.

Research progress on the synthesis and pharmacology of 1,3,4-oxadiazole and 1,2,4-oxadiazole derivatives: a mini review

Oxadiazole is a five-membered heterocyclic compound containing two nitrogen atoms and one oxygen atom. The 1,3,4-oxadiazole and 1,2,4-oxadiazole have favourable physical, chemical, and pharmacokinetic properties, which significantly increase their pharmacological activity via hydrogen bond interactions with biomacromolecules. In recent years, oxadiazole has been demonstrated to be the biologically active unit in a number of compounds. Oxadiazole derivatives exhibit antibacterial, anti-inflammatory, anti-tuberculous, anti-fungal, anti-diabetic and anticancer activities. In this paper, we report a series of compounds containing oxadiazole rings that have been published in the last three years only (2020-2022) as there was no report or their activities described in any article in 2019, which will be useful to scientists in research fields of organic synthesis, medicinal chemistry, and pharmacology.

Combining structure-based pharmacophore modeling and machine learning for the identification of novel BTK inhibitors

Bruton's tyrosine kinase (BTK) is a critical enzyme which is involved in multiple signaling pathways that regulate cellular survival, activation, and proliferation, making it a major cancer therapeutic target. We applied the novel integrated structure-based pharmacophore modeling, machine learning, and other in silico studies to screen the Korean chemical database (KCB) to identify the potential BTK inhibitors (BTKi). Further evaluation of these inhibitors on three different human cancer cell lines showed significant cell growth inhibitory activity. Among the 13 compounds shortlisted, four demonstrated consistent cell inhibition activity among breast, gastric, and lung cancer cells (IC50 below 3 μM). The selected compounds also showed significant kinase inhibition activity (IC50 below 5 μM). The current study suggests the potential of these inhibitors for targeting BTK malignant tumors.