Structural basis of focal adhesion targeting domain-mediated signaling in cardiac hypertrophy

Targeting focal adhesion kinase (FAK) in cancer therapy: A recent update on inhibitors and PROTAC degraders

Focal adhesion kinase (FAK) is considered as a pivotal intracellular non-receptor tyrosine kinase, and has garnered significant attention as a promising target for anticancer drug development. As of early 2024, a total of 12 drugs targeting FAK have been approved for clinical or preclinical studies worldwide, including three PROTAC degraders. In recent three years (2021-2023), significant progress has been made in designing targeted FAK anticancer agents, including the development of a novel benzenesulfofurazan type NO-releasing FAK inhibitor and the first-in-class dual-target inhibitors simultaneously targeting FAK and HDACs. Given the pivotal role of FAK in the discovery of anticancer drugs, as well as the notable advancements achieved in FAK inhibitors and PROTAC degraders in recent years, this review is underbaked to present a comprehensive overview of the function and structure of FAK. Additionally, the latest findings on the inhibitors and PROTAC degraders of FAK from the past three years, along with their optimization strategies and anticancer activities, were summarized, which might help to provide novel insights for the development of novel targeted FAK agents with promising anticancer potential and favorable pharmacological profiles.

The structural basis of BCR-ABL recruitment of GRB2 in chronic myelogenous leukemia

BCR-ABL drives chronic myeloid leukemia (CML). BCR binding to GRB2 transduces signaling via the Ras/MAPK pathway. Despite considerable data confirming the binding, molecular-level understanding of exactly how the two proteins interact, and especially, what are the determinants of the specificity of the SH2^GRB2 domain-pBCR recognition are still open questions. Yet, this is vastly important for understanding binding selectivity, and for predicting the phosphorylated receptors, or peptides, that are likely to bind. Here, we uncover these determinants and ascertain to what extent they relate to the affinity of the interaction. Toward this end, we modeled the complexes of the phosphorylated BCR (pBCR) and SH2^GRB2 and other pY/Y-peptide-SH2 complexes and compared their specificity and affinity. We observed that pBCR's ₁₇₆FpYVNV₁₈₀ motif is favorable and specific to SH2^GRB2, similar to pEGFR, but not other complexes. SH2^GRB2 contains two binding pockets: pY-binding recognition pocket triggers binding, and the specificity pocket whose interaction is governed by N179 in pBCR and W121 in SH2^GRB2. Our proposed motif with optimal affinity to SH2^GRB2 is E/D-pY-E/V-N-I/L. Collectively, we provide the structural basis of BCR-ABL recruitment of GRB2, outline its specificity hallmarks, and delineate a blueprint for prediction of BCR-binding scaffolds and for therapeutic peptide design.

In Silico Screening to Identify Inhibitors of Growth Factor Receptor 2-Focal Adhesion Kinase Interaction for Therapeutic Treatment of Pathological Cardiac Hypertrophy

The focal adhesion kinase-growth factor receptor 2 (FAK-Grb2) protein-protein interaction is implicated in pathogenesis of stress-induced cardiac hypertrophy. The focal adhesion targeting (FAT) domain of FAK unfolds to form a structural intermediate that interacts with a multibinding hot spot in the SH2 domain of Grb2. Disruption of the Grb2-FAT interaction is a therapeutic strategy for prevention of pathological cardiac hypertrophy. A pharmacophore was generated on the basis of structural and electrostatic properties of FAT bound to FAK using the Forge tool (Cresset). This pharmacophore was used as a query for Blaze server (Cresset) to screen a selectively enriched chemical library of 4,32,508 small molecules. The compounds selected were further filtered by hierarchical flexible docking approach using AutoDock v4. From the favorably docked compounds, five were selected on the basis of good adsorption, distribution, metabolism, excretion, and toxicity (ADMET) properties using SwissADME, MedChem Designer v.3, and MOLINSPIRATION. Stability of the binding mode of the inhibitors was further confirmed by molecular dynamic simulation study with AMBER v15 for a simulation time of 50 ns in aqueous environment. PM2307 was identified as the best inhibitor in terms of pharmacophoric features, dock score, and in silico ADMET analysis. The calculated binding affinity of PM2307 was better than that of the FAT-Grb2 complex as well as a previously reported small molecule inhibitor. PM2307 is also a quinolyl derivative sharing a similar scaffold with ofloxacin drugs, asserting its drug-like properties. Thus, it was proposed as a lead compound for development of drugs for pathological cardiac hypertrophy.

Looking "Under the Hood" of Cellular Mechanotransduction with Computational Tools: A Systems Biomechanics Approach across Multiple Scales

Signal modulation has been developed in living cells throughout evolution to promote utilizing the same machinery for multiple cellular functions. Chemical and mechanical modules of signal transmission and transduction are interconnected and necessary for organ development and growth. However, due to the high complexity of the intercommunication of physical intracellular connections with biochemical pathways, there are many missing details in our overall understanding of mechanotransduction processes, i.e., the process by which mechanical signals are converted to biochemical cascades. Cell-matrix adhesions are mechanically coupled to the nucleus through the cytoskeleton. This modulated and tightly integrated network mediates the transmission of mechanochemical signals from the extracellular matrix to the nucleus. Various experimental and computational techniques have been utilized to understand the basic mechanisms of mechanotransduction, yet many aspects have remained elusive. Recently, in silico experiments have made important contributions to the field of mechanobiology. Herein, computational modeling efforts devoted to understanding integrin-mediated mechanotransduction pathways are reviewed, and an outlook is presented for future directions toward using suitable computational approaches and developing novel techniques for addressing important questions in the field of mechanotransduction.