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This study aims to identify N-aryl-benzimidazolone analogs as potential inhibitors of the HSP90 protein, which is involved in various diseases. For this, we used computational techniques such as pharmacophoric modeling, virtual screening, in silico ADMET prediction, and molecular dynamics simulations. A target-based pharmacophore model (ADDRR) was developed from the MEY ligand to identify the main binding features. This model was used to screen approximately 30,994 similar compounds, leading to the identification of 3019 candidates. Among these, five compounds (L1, L2, L3, L4, and L5) showed strong binding affinity, with docking scores lower than the reference ligand MEY (−7.94 kcal/mol). The ADMET properties of these compounds were favorable, confirming their potential as drug candidates. The two top-performing compounds in the docking studies demonstrated high stability in dynamics studies, the results demonstrated remarkable stability of the ligand−protein complexes, as evidenced by favorable values of metrics such as RMSD, RMSF, Rg, and SASA. These findings provide a promising foundation for further experimental validation and the potential development of effective HSP90 inhibitors. [ABSTRACT FROM AUTHOR]

Influenza represents a profoundly transmissible viral ailment primarily afflicting the respiratory system. Neuraminidase inhibitors constitute a class of antiviral therapeutics employed in the management of influenza. These inhibitors impede the liberation of the viral neuraminidase protein, thereby impeding viral dissemination from the infected cell to host cells. As such, neuraminidase has emerged as a pivotal target for mitigating influenza and its associated complications. Here, we apply a de novo hybridization approach based on a breed-centric methodology to elucidate novel neuraminidase inhibitors. The breed technique amalgamates established ligand frameworks with the shared target, neuraminidase, resulting in innovative inhibitor constructs. Molecular docking analysis revealed that the seven synthesized breed molecules (designated Breeds 1–7) formed more robust complexes with the neuraminidase receptor than conventional clinical neuraminidase inhibitors such as zanamivir, oseltamivir, and peramivir. Pharmacokinetic evaluations of the seven breed molecules (Breeds 1–7) demonstrated favorable bioavailability and optimal permeability, all falling within the specified parameters for human application. Molecular dynamics simulations spanning 100 nanoseconds corroborated the stability of these breed molecules within the active site of neuraminidase, shedding light on their structural dynamics. Binding energy assessments, which were conducted through MM-PBSA analysis, substantiated the enduring complexes formed by the seven types of molecules and the neuraminidase receptor. Last, the investigation employed a reaction-based enumeration technique to ascertain the synthetic pathways for the synthesis of the seven breed molecules.

Background: Artemisia annua, a plant with antiviral potential, has shown promise against various viral infections, yet its mechanisms of action are not fully understood. This study explores A. annua's antiviral effects using network pharmacology and molecular docking, focusing on key active compounds and their interactions with viral protein targets, particularly within the JAK-STAT signaling pathway—a critical mediator of immune responses to viral infections. Methods: From the TCMSP database, we identified eight active compounds and 335 drug targets for A. annua, with 19 intersecting targets between A. annua compounds and viral proteins. A protein–protein interaction (PPI) network highlighted 10 key hub genes, analyzed further through Gene Ontology (GO) and KEGG pathways to understand their immune and antiviral roles. ADMET properties of the active compound Patuletin (MOL004112) were assessed, followed by 200 ns molecular dynamics simulations to examine its stability in complex with JAK2. Results: PPI analysis identified JAK2, MAPK3, MAPK1, JAK1, PTPN1, HSPA8, TYK2, RAF1, MAPT, and HMOX1 as key hub genes, with JAK2 emerging as a critical regulator of immune and antiviral pathways. ADMET analysis confirmed Patuletin's favorable pharmacokinetic properties, and molecular dynamics simulations showed a stable Patuletin-JAK2 complex, with FEL analysis indicating minimal disruption to JAK2's intrinsic flexibility. Conclusions: These findings highlight JAK2 as a promising target in the antiviral activity of A. annua compounds, particularly Patuletin, supporting its potential as an antiviral agent and providing a foundation for further research on A. annua's therapeutic applications. [ABSTRACT FROM AUTHOR]

Huperzine A (HUP) plays a crucial role in Alzheimer's therapy by enhancing cognitive function through increased cholinergic activity as a reversible acetylcholinesterase (AChE) inhibitor. Despite some limitations being seen in AChE inhibitors, ongoing research remains dedicated to finding innovative and more effective treatments for Alzheimer's disease. To achieve the goal of the discovery of potential HUP analogues with improved physicochemical properties, less toxic properties, and high biological activity, many in silico methods were applied. Based on the acetylcholinesterase–ligand complex, an e-pharmacophore model was developed. Subsequently, a virtual screening involving a collection of 1762 natural compounds, sourced from the PubChem database, was performed. This screening yielded 131 compounds that exhibited compatibility with the established pharmacophoric hypothesis. These selected ligands were then subjected to molecular docking within the active site of the 4EY5 receptor. As a result, we identified four compounds that displayed remarkable docking scores and exhibited low free binding energy to the target. These top four compounds, CID_162895946, CID_44461278, CID_44285285, and CID_81108419, were submitted to ADMET prediction and molecular dynamic simulations, yielding encouraging findings in terms of their pharmacokinetic characteristics and stability. Finally, the molecular dynamic simulation, cross-dynamic correlation matrix, free energy landscape, and MM-PBSA calculations demonstrated that two ligands from the selected ligands formed very resilient complexes with the enzyme acetylcholinesterase, with significant binding affinity. Therefore, these two compounds are recommended for further experimental research as possible (AChE) inhibitors. [ABSTRACT FROM AUTHOR]