Molecular Diversity最新文献

Cancer remains one of the leading causes of death worldwide, with the rising incidence of breast cancer being a significant public health concern. Poly (ADP-ribose) polymerase-1 (PARP-1) has emerged as a promising therapeutic target for breast cancer treatment due to its crucial role in DNA repair. This study aimed to discover novel, targeted, and non-toxic PARP-1 inhibitors using an integrated approach that combines machine learning-based screening, molecular docking simulations, and quantum mechanical calculations. We trained a widely used machine learning models, Random Forest, using bioactivity data from known PARP-1 inhibitors. After evaluating the performance, it was used to screen an FDA-approved drug library, successfully identifying Atazanavir, Brexpiprazole, Raltegravir, and Nisoldipine as potential PARP-1 inhibitors. These compounds were further validated through molecular docking and all-atom molecular dynamics simulations, highlighting their potential for breast cancer therapy. The binding free energies indicated that Atazanavir at - 41.86 kJ/mol and Brexpiprazole at - 45.44 kJ/mol exhibited superior binding affinity compared to the control drug at - 30.42 kJ/mol, highlighting their promise as candidates for breast cancer therapy. Subsequent optimized geometries and electron density mappings of the two molecular structures revealed a Gibbs free energy of - 2334.610 Ha for the first molecule and - 1682.278316 Ha for the second, confirming enhanced stability compared to the standard drug. This study not only highlights the efficacy of machine learning in drug discovery but also underscores the importance of quantum mechanics in validating molecular stability, setting a robust foundation for future pharmacological explorations. Additionally, this approach could revolutionize the drug repurposing process by significantly reducing the time and cost associated with traditional drug development methods. Our results establish a promising basis for subsequent research aimed at optimizing these PARP-1 inhibitors for clinical use, potentially offering more effective treatment options for breast cancer patients.

Peroxisome proliferator-activated receptor gamma (PPARγ) plays a critical role in adipocyte differentiation and enhances insulin sensitivity. In contemporary drug discovery, in silico design strategies offer significant advantages by revealing essential structural insights for lead optimization. The study is guided by two main objectives: (i) a ligand-based approach to explore the chemical space of PPARγ modulators followed by molecular docking ensembles (MDEs) to investigate ligand-binding interactions, (ii) the development of a supervised ML model for a large dataset of compounds targeting PPARγ. Additionally, the combination of chemical space networks with ML models enables the rapid screening and prediction of PPARγ modulators. These modeling analyses will assist medicinal chemists in designing more potent PPARγ modulators. To further enhance accessibility for the scientific community, we developed an online tool, "PGMP_v1," aimed at prospective screening for PPARγ modulators. The tool "PGMP_v1" is available at the provided link https://github.com/Amincheminfom/PGMP_v1 . The integration of these computational methods has uncovered crucial structural motifs that are essential for PPARγ activity, advancing the development of more effective modulators in the future.

Influenza is a highly contagious respiratory illness that imposes a significant global burden. Antiviral neuraminidase inhibitors (NAIs) such as oseltamivir (OC) have been proven essential, but the emergence of resistant viral strains necessitates the development of novel therapies. This study explored the potential of natural products as alternative NAIs. We used virtual screening against the Chinese Ethnic Characteristic Drug Database, followed by Quantum Mechanics/Molecular Mechanics Generalized Born Surface Area (QM/MM-GBSA) rescoring with ligands treated as QM region. Compounds preserved from docking-based virtual screening were reranked based on QM/MM-GBSA scores, and the top 15 compounds with binding free energy lower than that of native inhibitor OC were selected for NA inhibitory assay. Among the tested compounds, compounds T6S0444 (Salvianolic acid A) demonstrated significant inhibitory activity against both wild-type and H274Y-mutated influenza NAs, suggesting their potential as novel anti-influenza agents. Specifically, compound T6S0444 exhibited greater inhibitory activity against N2-H274Y than the wild-type N2, with IC₅₀ values of 5.3 ± 0.4 µM and 12.8 ± 1.2 µM, respectively. This distinctive selectivity for mutant viral strains is not observed in current antiviral drugs for influenza. Furthermore, these compounds demonstrated low cytotoxicity, indicating their potential as safe anti-influenza agents. In summary, we have identified a promise NA inhibitor, T6S0444, a potential therapeutic for the treatment of oseltamivir-resistant influenza.

Discoidin domain receptors (DDR) are categorized under tyrosine kinase receptors (RTKs) and play a crucial role in various etiological conditions such as cancer, fibrosis, atherosclerosis, osteoarthritis, and inflammatory diseases. The structural domain rearrangement of DDR1 and DDR2 involved six domains of interest namely N-terminal DS, DS-like, intracellular juxtamembrane, transmembrane juxtamembrane, extracellular juxtamembrane intracellular kinase domain, and the tail portion contains small C-tail linkage. DDR has not been explored to a wide extent to be declared as a prime target for any particular pathological condition. Very few scientific data are available so there is a need to study the receptors and their inhibitors. Still, there did not exist FDA-approved small molecules targeting DDR1 and DDR2 receptors so there is an urgent need to develop potent small molecules. Further, the structural features and ligand specificities encourage the researchers to be fascinated about the DDR and explore them for the mentioned biological conditions. Therefore, in the last few years, researchers have been involved in investigating the potent DDR inhibitors. The current review provides an outlook on the anatomy and physiology of DDR, focusing on the structural features of DDR receptors and the mechanism of signaling pathways. We have also compiled the evolutionary development status of DDR inhibitors according to their chemical classes, biological activity, selectivity, and structure-activity relationship. From biological activity analysis, it was revealed that compounds 64a (selectivity: DDR1) and 103a (selectivity: DDR2) were the most potent candidates with excellent activity with IC₅₀ values of 4.67 and 3.2 nM, respectively.

Nanobodies or variable antigen-binding domains (V_HH) derived from heavy chain-only antibodies (HcAb) occurring in the Camelidae family offer certain superior physicochemical characteristics like enhanced stability, solubility, and low immunogenicity compared to conventional antibodies. Their efficient antigen-binding capabilities make them a preferred choice for next-generation small biologics. In the present work, we design an anti-SARS-CoV-2 bi-paratopic nanobody drug conjugate by screening a nanobody database. SAbDab-nano database was screened based on the physicochemical properties and SARS-CoV-2 binding affinity of the documented nanobodies. Molecular docking, computational modeling, in silico site-directed mutagenesis, and MD simulations were performed to construct an effective nanobody bi-paratope. The construct's physicochemical properties were assessed, and its structural integrity was validated through model energy refinement and quality assessment. The triple-mutant (N78Q K116N T123F) nanobody, based on the bioinformatics analysis, exhibited enhanced binding efficiency against its targets: SARS CoV-2 WT RB (- 353.3), NRP1 (- 376.5) and Omicron RBD (- 380.8), compared to the WT nanobody (SARS CoV-2 WT RBD = - 337.5, NRP1 = - 361.5, Omicron RBD = - 359.5). In silico evaluation also predicted that the construct would demonstrate efficient solubility, high thermostability (Tm 67.4 °C), low molecular weight of 29.36 KDa, and non-toxic, non-allergenic properties. Anti-SARS-CoV-2 neutralizing nanobody-based therapeutics, as demonstrated through this computational work, represents a promising alternative to traditional COVID-19 prophylaxis.

Quinoline is a highly privileged scaffold with significant pharmacological potential. Introducing a carbonyl group into the quinoline ring generates a quinolone ring, which exhibits promising biological properties. Incorporating a carboxamide linkage at different positions within the quinoline and quinolone frameworks has proven an effective strategy for enhancing pharmacological properties, particularly anticancer potency. Consequently, various scientific communities have explored quinoline and quinolone carboxamides for their anticancer activities, introducing modifications at key positions. This review article aims to compile the anticancer activity of various quinoline and quinolone carboxamide derivatives, accompanied by a detailed structure-activity relationship (SAR) analysis. It also categorizes the data into activities of isolated/fused quinoline and quinolone carboxamide derivatives, which were further subclassified based on the mechanisms of anticancer action. Among the numerous derivatives studied, compounds 8, 19, 31, 34, 40, 68, 108, 116, and 132 have emerged as the most potent anticancer agents, making them strong candidates for further drug design and development. The mechanisms underlying the anticancer activity of these potent compounds have been identified as inhibitors of topoisomerase (8, 19, 31, and 34), protein kinase (40, 108, and 116), human dihydroorotate dehydrogenase (68), and as a cannabinoid receptor 2 agonist (132). We anticipate this review will be valuable to researchers engaged in the structural design and development of quinoline and quinolone carboxamide-based anticancer drugs with high efficacy.

Melanoma, a highly aggressive skin cancer, remains a significant cause of mortality despite advancements in therapeutic strategies. There is an urgent demand for developing vaccines that can elicit strong and comprehensive immune responses against this malignancy. Achieving this goal is crucial to enhance the efficacy of immunological defense mechanisms in combating this disease. This research provides a thorough examination of the design, optimization, and validation of a multi-epitope vaccine (MEV) construct. Using computational and in silico methods, the study specifically targets key immune receptors including MHC-I, MHC-I, and TLR4. The MEV construct was codon-optimized and effectively cloned into the E. coli pET-28a(+) vector to improve expression efficiency. To assess the stability and flexibility of the vaccine constructs in complex with their target receptors, molecular dynamics (MD) simulations were performed. The findings showed that the MHC-I-MEV complex demonstrated the greatest stability, with the MHC-II-MEV and TLR4-MEV complexes following instability. Immune simulation analyses revealed robust immune responses, evidenced by significant antibody production and the activation of cell mediated immune responses. These results highlight the MEV construct's potential as a versatile vaccine candidate, capable of eliciting strong and diverse immune responses. The integration of structural and energetic analyses, combined with immune simulation, provides a solid foundation for further experimental validation and therapeutic development.

Cystitis glandularis (CG) is a chronic hyperplastic disorder of the bladder, and the available clinical drug therapy is insufficient currently. Glycyrrhetinic acid (GA), a bioactive compound extracted from the roots of Glycyrrhiza glabra, is found with beneficial actions, including anti-inflammatory and anti-oxidative effects. We previously reported that GA relieves CG symptoms in animal model, implying the potential application of GA to treat CG. However, the action mechanisms of GA against CG remain unclear. In this study, we aimed to identify the pivotal targets and therapeutic effects of GA through integrated bioinformatics analysis and experimental validation. Integrated bioinformatics analysis screened eleven potential therapeutic targets for GA against CG, and seven pivotal targets were identified subsequently. Enrichment gene analysis revealed GA exhibiting biological activities against CG via regulating multiple pharmacological targets and molecular pathways associated with inflammatory reaction and oxidative stress. Molecular docking computation revealed potent affinity and interaction between GA and prostaglandin-endoperoxide synthase 2 (PTGS2) and mucin 1 (MUC1) proteins in CG. To validate biochemically, increased mRNA and protein expressions of PTGS2 and MUC1 were observed in human CG samples. Compared to CG mice, GA-treated CG mice exhibited reduced inflammatory cytokine contents and downregulated PTGS2 and MUC1 mRNA and protein levels. These integrated findings suggest the potential therapeutic effects of GA against CG via the regulation of targeting genes and pathways. However, further studies are necessary to perform and facilitate the clinical application of GA for treating CG.

Alzheimer's disease (AD) is a degenerative neurological disorder defined by the formation of β-amyloid (Aβ) plaques and neurofibrillary tangles within the brain. Current pharmacological treatments for AD only provide symptomatic relief, and there is a lack of definitive disease-modifying therapies. Chemical chaperones, such as 4-Phenylbutyric acid (4PBA) and Tauroursodeoxycholic acid, have shown neuroprotective effects in animal and cell culture models. However, their therapeutic application is limited due to low bioavailability and poor ability to cross the blood-brain barrier. The study aims to design and identify novel derivatives of 4PBA analogs & bile acids using computational molecular docking, ADME/pharmacokinetic predictions, and molecular dynamic (MD) simulations to develop potential anti-aggregation compounds targeting Aβ, a key player in AD pathology. A comprehensive library of 25,802 derivatives was created using 3PPA, 3MPP, 5PVA, IPA, and bile acid scaffolds, which were examined for their pharmacokinetic characteristics and binding affinities with the Aβ protein. Molecular docking and ADME predictions revealed IPA-1 and DCA-1 as leading candidates due to their robust binding interactions with the Aβ protein, along with minimal toxicity, high solubility, and good absorption profiles. Further, MD analysis over an extended period at 100 ns confirmed the better stability of IPA-1 and DCA-1 during interaction with the protein. These findings highlight promising drug candidates, necessitating further validation through cell and animal studies.

Cyclotides are a class of plant-derived cyclic peptides having a distinctive structure with a cyclic cystine knot (CCK) motif. They are stable molecules that naturally play a role in plant defense. Till date, more than 750 cyclotides have been reported among diverse plant taxa belonging to Cucurbitaceae, Violaceae, Rubiaceae, Solanaceae, and Fabaceae. These native cyclotides exhibit several bioactivities, such as anti-bacterial, anti-HIV, anti-fungal, pesticidal, cytotoxic, and hemolytic activities which have immense significance in agriculture and therapeutics. The general mode of action of cyclotides is related to their structure, where their hydrophobic face penetrates the cell membrane and disrupts it to exhibit anti-microbial, cytotoxic, or hemolytic activities. Thus, the structure-activity relationship is of significance in cyclotides. Further, owing to their, small size, stability, and potential to interact and cross the membrane barrier of cells, they make promising choices for developing peptide-based biologics. However, challenges, such as production complexity, pharmacokinetic limitations, and off-target effects hinder their development. Advancements in cyclotide engineering, such as peptide grafting, ligand conjugation, and nanocarrier integration, heterologous production along with computational design optimization, can help overcome these challenges. Given the potential of these cyclic peptides, the present review focuses on the diversity, bioactivities, and structure-activity relationships of cyclotides, and advancements in cyclotides engineering emphasizing their unique attributes for diverse medical and biotechnological applications.