Mathematical Modeling of Aβ-42 Dimerization Dynamics: Integrating Physics-Based Simulations, Graph-Based Variational Autoencoder-Driven Neural Relational Inference, and Chaos Theory.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by the pathological aggregation of amyloid-beta (Aβ) peptides, particularly Aβ-42, which plays a central role in disease progression. Soluble Aβ dimers have been implicated as the primary neurotoxic species contributing to synaptic dysfunction and cognitive impairment. In this study, we employ a comprehensive computational framework integrating molecular dynamics (MD) simulations, neural relational inference (NRI) modeling, and largest Lyapunov exponent (LLE) analysis to elucidate the molecular mechanisms underlying Aβ-42 dimerization and evaluate the inhibitory potential of small molecules, apigenin and caffeine.

Anti-cancer efficacy of novel lonidamine derivatives: Design, synthesis, in vitro, in vivo, and computational studies targeting hexokinase-2.

Targeting cancer metabolism has emerged as an attractive therapeutic strategy in recent years, despite the "Warburg effect" phenomenon is discovered about a century ago. Based on this phenomenon, cancer cells rely on aerobic glycolysis and require higher rate of glucose consumption compared to normal cells and the hexokinase-2 (HK-2) enzyme catalyzes the first step of glucose metabolism. Consistent with the notion, HK-2 expression is highly elevated in most malignancies and that predicts poor survival in patients.

Beyond Docking: A Multitier Computational Pipeline for USP7 Inhibitor Optimization.

Ubiquitin-specific protease 7 (USP7) is a key deubiquitinating enzyme involved in tumor suppression, DNA repair, and epigenetic regulation. Given its critical role in cancer progression, USP7 has emerged as an attractive therapeutic target. Using similarity-based ligand screening, structurally related analogs of previously identified and validated hit compounds by our research group are selected and grid-based docking simulations are performed, prioritizing molecules with high binding affinity (docking scores < -8.

Employing steered MD simulations for effective virtual screening: Active pharmacophore search by dynamic corrections to target MKK3-MYC interactions.

The protein-protein interaction (PPI) between mitogen-activated protein kinase kinase 3 (MKK3), and MYC is a crucial regulator of oncogenic signaling, particularly in triple-negative breast cancer (TNBC). Despite its clinical significance, effective small molecule inhibitors targeting this interaction remain elusive. In this study, we employed a comprehensive in silico approach integrating dynamic structure-based pharmacophore modeling, virtual screening, molecular docking, and molecular dynamics (MD) simulations to identify potential inhibitors disrupting the MKK3-MYC interaction.

Identifying Potential SOS1 Inhibitors via Virtual Screening of Multiple Small Molecule Libraries against KRAS-SOS1 Interaction.

The RAS-MAPK signaling pathway, crucial for cell proliferation and differentiation, involves key proteins KRAS and SOS1. Mutations in the KRAS and SOS1 genes are implicated in various cancer types, including pancreatic, lung, and juvenile myelomonocytic leukemia. There is considerable interest in identifying inhibitors targeting KRAS and SOS1 to explore potential therapeutic strategies for cancer treatment.