Molecular Diversity最新文献

Alzheimer's disease (AD) is a progressive neurodegenerative disorder in which cholinergic dysfunction plays a central role. Inhibition of acetylcholinesterase and butyrylcholinesterase remains a validated therapeutic approach for managing AD symptoms. Over the past decade (2015-2025), 1,3,4-thiadiazole derivatives have gained considerable attention as promising scaffolds for cholinesterase inhibition owing to their favorable electronic configuration, hydrogen-bonding potential, and metabolic stability. This review comprehensively analyzes recent progress in the synthesis and biological evaluation of 1,3,4-thiadiazole-based cholinesterase inhibitors, with an emphasis on structure-activity relationship trends supported by molecular docking insights. Substitution with electron-withdrawing or heteroaryl groups has been found to enhance the binding affinity toward AChE and BuChE, while some derivatives also exhibit activity against carbonic anhydrase, α-glucosidase, α-amylase, and antioxidant systems, reflecting scaffold versatility. This review further highlights the docking interactions with catalytic residues that validate the observed experimental potency. Finally, key limitations and future directions are discussed, emphasizing rational structure modification, computationally guided design, and green synthetic approaches to develop brain-penetrant and pharmacologically optimized 1,3,4-thiadiazole-based anti-Alzheimer's agents.

We propose FRAIL (Fragment-based Reinforcement Learning for Inhibitors), a generative AI framework that integrates fragment-based molecular design, multi- objective reinforcement learning, and molecular modeling to accelerate inhibitor discovery. Several deep generative models were fine-tuned on FAAH-1 (Fatty Acid Amide Hydrolase 1)-specific dataset and systematically benchmarked, with the best-performing model incorporated into FRAIL. The framework employs a customized reward function that jointly optimizes physicochemical properties and predicted bioactivity (pIC₅₀) to guide molecular generation toward FAAH- favorable chemotypes. FRAIL generated structurally novel, fragment-grown compounds exhibiting high predicted binding affinity, desirable drug-likeness, and synthetic accessibility. These findings demonstrate FRAIL's capability to enhance rational drug design and provide a reproducible pipeline for the discovery of experimentally viable FAAH inhibitors. Our pipeline source code is released in https://github.com/AppliedAI-Lab/FRAIL .

Computational techniques have become powerful tools for studying biological systems, including receptor-ligand (R-L) complexes. In medicinal chemistry, these in silico approaches are widely used for modeling and predicting molecular interactions, as well as for designing new ligands with biological activity. However, obtaining a direct correlation between the structure and activity of a set of active compounds is a challenging task. This study aims to develop a computational pipeline to find a direct correlation between structure and acetylcholinesterase (AChE) inhibitory activity across a structurally diverse set of 224 Amaryllidaceae alkaloids and synthetic derivatives. Standard docking protocols failed to generate reliable correlations with experimental data, and although the inclusion of molecular dynamics (MD) simulations improved performance, the results remained insufficient for robust prediction. Incorporation of quantum theory of atoms in molecules (QTAIM) analyses on MD-refined geometries was essential to capture key R-L interactions, yielding a strong correlation with relative IC₅₀ values (R = - 0.9131). This approach not only explained differences in activity among structurally related compounds but also distinguished active, moderately active, and inactive ligands across multiple alkaloid families. For the first time, a QTAIM analysis is reported providing detailed insights into the molecular interactions stabilizing AChE-ligand complexes, including natural alkaloids, as well as synthetic dual-site inhibitors designed to engage both the catalytic active site and the peripheral anionic site of the enzyme. These findings suggest that simple appropriately combined computational methodologies can yield predictive and explanatory models applicable to chemically diverse scaffolds, supporting the rational design of novel AChE inhibitors.

Dengue infection remains a major global public health challenge, with no specific antiviral therapy currently available. The dengue virus non-structural protein 1 (NS1) exists in both intracellular and secreted forms playing a pivotal role in viral replication, immune evasion, and pathogenesis, particularly by contributing to endothelial disruption and vascular leakage during severe disease, thereby making it a promising therapeutic target. In silico screening identified berberine, betulinic acid, and ursolic acid as top candidates, exhibiting high binding affinities and stable interactions within the NS1 binding pocket. These computational predictions were further validated by biophysical assays, which demonstrated strong and specific binding interactions between the purified NS1 protein and the selected compounds. All three compounds significantly reduced viral genome levels, with the highest inhibition observed for berberine (60%), and followed by betulinic acid (40%) and ursolic acid (28%). Consistently, berberine showed the most potent inhibition of both intracellular and extracellular NS1. Overall, these findings highlight the inhibitory potential of natural compounds against DENV NS1 and provide a strong foundation for the development of NS1-targeted antivirals as a novel therapeutic strategy against dengue infection.

Presented herein is a fundamentally new organophosphine-mediated annulation paradigm that converts benzo[c][1,2]dithiol-3-ones and iso(thio)cyanates into pharmacologically relevant 1,3-benzothiazin-4-one architectures through an unconventional S to C-N atom exchange process. Distinct from conventional cyclization approaches, this metal-free strategy offers exceptional advantages including: broad substrate scope (45 examples, up to 96% yield), simple operation (ambient temperature, open flask), mild reaction conditions and exceptional utility in late-stage functionalization of bioactive molecules. Comprehensive mechanistic analysis uncovered a phosphine-mediated S-S bond activation followed by formal [4 + 2] cyclization.

Escitalopram, a selective serotonin reuptake inhibitor (SSRI), treats depression and related anxiety symptoms by enhancing the physiological effects of serotonin (5-HT). This study explored the potential drug-drug interactions (DDIs) of combining escitalopram with flavonoid compounds (kaempferol and quercetin). The inhibitory effects of flavonoids on escitalopram metabolism were studied using human liver microsomes (HLM), rat liver microsomes (RLM) and Sprague-Dawley rats. The concentration of escitalopram and its metabolites were detected by ultra performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS). Our findings revealed that the half-maximal inhibitory concentration (IC₅₀) of kaempferol against escitalopram in HLM and RLM were 14.34 and 8.69 μM, respectively, and both were mixed inhibitory mechanisms, consisting of competitive and non-competitive inhibition in HLM and non-competitive and un-competitive inhibition in RLM, respectively. Moreover, the IC₅₀ of quercetin against escitalopram in HLM and RLM were 11.25 and 8.14 μM, respectively, and the inhibitory mechanisms were both mixed inhibitory mechanisms consisting of non-competitive and un-competitive inhibition. The in vivo results showed that quercetin significantly increased the AUC_(0-t), AUC_(0-∞) and C_max of escitalopram by 0.91-, 0.90- and 1.83-fold, respectively, while kaempferol and quercetin significantly reduced the CL_z/F by 41.3% and 44.7%, respectively. In addition, kaempferol reduced the C_max of N-desmethyl escitalopram by 62.1%. Therefore, the inhibitory effects of kaempferol and quercetin on the metabolism of escitalopram carries the risk of causing DDI and requires caution in combination.

A hormonal disorder that severely affects women's routine physical and emotional life is PCOS (Polycystic Ovary Syndrome). It has been witnessed as a heavily detrimental and most threatening disorder, causing multiple complications, such as type 2 diabetes, cardiovascular disease, and endometrial carcinoma. One of the major causes of PCOS is hyperandrogenism, which results in the dysfunction of the ovaries. The enzyme responsible for such excessive production of androgen is 3-beta hydroxysteroid dehydrogenase-1 (3βHSD1), which is an oxidoreductase that performs multiple functions in steroid metabolism. Trilostane and troglitazone are proposed inhibitors for 3βHSD1 with anticipated side effects. With the aim to identify non-steroidal phytocompounds, structure-based ligand screening against ChEBI was done, which resulted in 3459 compounds. Initially, NAD was docked into the protein to have an active enzyme structure. Then other ligands were docked. Based on a docking score of - 8.0 kcal/mol, ADME properties, and interaction profiling, seven compounds-Aphidicolin, Sagequinone methide A, Premarrubiin, Hoda acetal, Ophiopogonanone A, Brosimacutin C, and Cremastranone-were listed out. All these seven compounds were reported with medicinal importance in the literature. Hence, the stability of protein-ligand complexes was analyzed in detail through 200 ns MD simulation. Results from this study establish these compounds as leads for drug development to combat PCOS.

We have recently demonstrated that 7-O-methylpunctatin (MP), a novel homoisoflavonoid, suppresses inflammation-induced arterial pathogenesis. However, the precise biochemical mechanisms underlying its atheroprotective effects remain elusive. In this study, we employed various in silico studies to elucidate MP's plausible potential and the specific molecular pathways through which it exerts its influence on atherosclerosis. Our analysis of MP's pharmacokinetic, physicochemical, and toxicological properties revealed a profile characterized by favorable absorption, efficient metabolism and excretion, and minimal toxicity. Through target identification and protein-protein interaction analyses, we identified ALOX5 as a pivotal hub gene-an enzyme critically involved in the pathogenesis of atherosclerosis. Furthermore, we identified ten transcription factors and four kinases as potential targets. Molecular mechanics/generalized-born surface area calculations, complemented by time-scale molecular dynamics simulations, revealed that MP binds to ALOX5 with high affinity, modulating its structural stability, rigidity, compactness, overall folding pattern, and residual correlations and motions. These findings corroborate previous in vitro and in vivo investigations that underscore the anti-atherosclerotic effects of ALOX5 inhibition, thereby positioning MP as a promising therapeutic candidate for combating atherosclerosis.