Structure-based discovery of novel ROCK2 inhibitors using integrated virtual screening, molecular dynamics, metadynamics and absolute binding free energy calculations

Discovery of Potent CDK2 Inhibitors Through Structure-Based Virtual Screening and MD Simulation Studies.

Overall, MD1-MD5 demonstrated excellent binding, structural stability, and pharmacokinetic properties, making them strong candidates for future CDK2-targeted anticancer research.

Structure-based virtual screening, multi-score docking, and molecular dynamics simulation of novel small molecules targeting the epidermal growth factor receptor for potential management of oral squamous cell carcinoma

Structure-based discovery of potent SMO inhibitors guided by MM/GBSA binding free energies in hedgehog-driven cancers.

The Hedgehog (Hh) signaling pathway, crucial for embryonic development and tissue homeostasis, is frequently dysregulated in cancers, making its core component, the Smoothened (SMO) receptor, a prime therapeutic target. This study employed an integrative computational strategy to identify novel SMO inhibitors. Virtual screening of the ZINC database highlighted ZINC000299767263 (ZINC7263) as a top candidate, exhibiting a Glide score of -10.86 and MM/GBSA binding energy of -65.3 kJ/mol, comparable to the FDA-approved inhibitor Vismodegib. Molecular docking revealed critical interactions with SMO residues Asp384, Arg400, and Gln477, supported by hydrophobic contacts with Phe484 and Trp480. Molecular dynamics simulations (200 ns) demonstrated stable binding, with root-mean-square deviation (RMSD) and fluctuation (RMSF) analyses confirming complex stability. Free energy decomposition underscored contributions from Asp384, Arg400, and Gln477, aligning with Vismodegib's binding mechanism. ZINC7263 adhered to drug-likeness criteria (Lipinski's rule of five, Jorgensen's rule of three) and exhibited favorable pharmacokinetics, including high oral absorption (89.45%) and blood-brain barrier permeability (logBB = -1.01). Induced-fit docking further validated its binding mode, highlighting a conserved interaction profile. These findings position ZINC7263 as a novel, potent SMO inhibitor with a stable binding affinity, dynamic interaction stability, and promising preclinical potential for targeting Hh-driven cancers. Its unique scaffold and optimized pharmacokinetic profile advocate for advanced in vitro and in vivo studies to translate these computational insights into therapeutic applications.

Identification of the Potential of Plant-Derived Agents to Act as KRAS G12D Inhibitors Through Molecular Docking, Molecular Dynamics Simulations, and MMGBSA.

INTRODUCTION/OBJECTIVE The KRAS G12D mutation is a significant oncogenic factor that promotes cell proliferation and tumor development, particularly in pancreatic cancer. Inhibiting the mutated form of the KRAS protein is a critical strategy in cancer treatment. While molecules like MRTX1133 show promise, the limited efficacy and safety of current treatment options highlight the need to discover new and safer therapeutic candidates. METHODS Approximately 1000 plant-derived bioactive compounds downloaded from the literature and Dr. Duke's database were filtered according to Lipinski's Rules and pharmacokinetic properties to create a set of 425 candidate molecules. Geometry optimization and QSAR parameters were calculated using Spartan software, and molecular docking and binding affinities were calculated using AutoDock Vina. MRTX1133 was used as a reference in the evaluations. Protein-ligand interaction maps were generated, and key interaction residues were identified using BIOVIA Discovery Studio. Molecular dynamics simulations of 200 ns were performed using Schrödinger-Desmond for the six compounds with the best binding affinities, and MMGBSA binding free energy calculations were performed. RESULTS The results showed that Isochlorogenic acid, Coniferin, Neochlorogenic acid, Cryptochlorogenic acid, Gamma-L-glutamyl-L-phenylalanine, and Chlorogenic acid demonstrated good bonding affinity to KRAS G12D with -11.0, -9.8, -9.5, -9.1, -9, and -8.9 Kcal.mol-1, respectively, compared to MRTX1133 (-8.3 Kcal.mol-1), exhibiting favorable physicochemical profiles and revealing their potential as KRAS G12D inhibitors. Based on bonding scores and QSAR data, four of the six selected molecules (Coniferin, Gamma-Lglutamyl- L-phenylalanine, Isochlorogenic acid, and Neochlorogenic acid) formed stable protein-ligand complexes with mean RMSD values < 2.5 Å during 200 ns MD simulations. MMGBSA analysis confirmed the binding free energies, and the compound giving the strongest interaction was determined to be Coniferin with ΔG_bind = -72.53 ± 5.24 Kcal.mol-1. Superior docking scores and stable MD trajectories demonstrate that the selected plant-derived compounds, especially Coniferin, effectively interact with the KRAS G12D binding pocket via suitable hydrophobic and hydrogen-bond contacts. These findings suggest that natural compounds can provide structurally diverse and potentially safer alternatives compared to synthetic inhibitors; however, experimental validation is necessary to confirm their inhibitory potential and selectivity. DISCUSSION According to the MMGBSA results, these compounds have suitable binding free energy values comparable to the reference, with Coniferin as the strongest plant-derived candidate with ΔGbind = -72.53 ± 5.24 Kcal/mol-. CONCLUSION As a result of this in silico study, coniferin, neochlorogenic acid, and chlorogenic acid have been identified as potential precursor molecules for KRAS G12D inhibition. Isochlorogenic acid was excluded due to its dynamic instability. These plant-derived compounds require further experimental validation as potential anticancer agents targeting KRAS G12D mutations.

Identification of novel EGFR inhibitors for glioblastoma through pharmacophore-guided virtual screening and molecular dynamics

The pharmacophore-based screening and docking analysis identified eleven promising EGFR-binding compounds, of which eight demonstrated optimal ADMET characteristics and stable interactions within the active site during molecular dynamics simulations, suggesting their potential efficacy as EGFR inhibitors.

Novel Phosphodiesterase‑2 Inhibitors Discovered via Structure-Based Virtual Screening Targeting the Allosteric GAF‑B Domain.

Phosphodiesterase-2 (PDE2) regulates intracellular cAMP and cGMP signaling and is an important therapeutic target. In this study, we performed the first virtual screening campaign targeting the allosteric GAF-B domain of PDE2 to identify novel allosteric inhibitors. Unlike conventional virtual screening methods based mainly on calculated binding energies, our approach incorporated binding mode analysis to rerank the top 5000 compounds according to the number of hydrogen-bonding and π-π stacking interactions with GAF-B residues. Experimental testing identified various novel PDE2 inhibitors, including compound 1 (IC5 0 = 0.77 μM) selective for PDE2 over other PDE isoforms. The reranking strategy yielded high hit rates of 62%, 51%, 29%, and 14% at inhibition thresholds of 25%, 30%, 40%, and 50%, respectively. These findings demonstrate that incorporation of binding mode analysis into virtual screening workflows can substantially improve hit identification and may provide a valuable strategy for future virtual screening campaigns against PDE2 and other therapeutic targets.