ABSTRACT
Drug discovery and development constitute a laborious and costly undertaking. The success of a drug hinges not only good efficacy but also acceptable absorption, distribution, metabolism, elimination, and toxicity (ADMET) properties. Overall, up to 50% of drug development failures have been contributed from undesirable ADMET profiles. As a multiple parameter objective, the optimization of the ADMET properties is extremely challenging owing to the vast chemical space and limited human expert knowledge. In this study, a freely available platform called Chemical Molecular Optimization, Representation and Translation (ChemMORT) is developed for the optimization of multiple ADMET endpoints without the loss of potency (https://cadd.nscc-tj.cn/deploy/chemmort/). ChemMORT contains three modules: Simplified Molecular Input Line Entry System (SMILES) Encoder, Descriptor Decoder and Molecular Optimizer. The SMILES Encoder can generate the molecular representation with a 512-dimensional vector, and the Descriptor Decoder is able to translate the above representation to the corresponding molecular structure with high accuracy. Based on reversible molecular representation and particle swarm optimization strategy, the Molecular Optimizer can be used to effectively optimize undesirable ADMET properties without the loss of bioactivity, which essentially accomplishes the design of inverse QSAR. The constrained multi-objective optimization of the poly (ADP-ribose) polymerase-1 inhibitor is provided as the case to explore the utility of ChemMORT.
Subject(s)
Deep Learning , Humans , Drug Development , Drug Discovery , Poly(ADP-ribose) Polymerase InhibitorsABSTRACT
In the process of drug discovery, one of the key problems is how to improve the biological activity and ADMET properties starting from a specific structure, which is also called structural optimization. Based on a starting scaffold, the use of deep generative model to generate molecules with desired drug-like properties will provide a powerful tool to accelerate the structural optimization process. However, the existing generative models remain challenging in extracting molecular features efficiently in 3D space to generate drug-like 3D molecules. Moreover, most of the existing ADMET prediction models made predictions of different properties through a single model, which can result in reduced prediction accuracy on some datasets. To effectively generate molecules from a specific scaffold and provide basis for the structural optimization, the 3D-SMGE (3-Dimensional Scaffold-based Molecular Generation and Evaluation) work consisting of molecular generation and prediction of ADMET properties is presented. For the molecular generation, we proposed 3D-SMG, a novel deep generative model for the end-to-end design of 3D molecules. In the 3D-SMG model, we designed the cross-aggregated continuous-filter convolution (ca-cfconv), which is used to achieve efficient and low-cost 3D spatial feature extraction while ensuring the invariance of atomic space rotation. 3D-SMG was proved to generate valid, unique and novel molecules with high drug-likeness. Besides, the proposed data-adaptive multi-model ADMET prediction method outperformed or maintained the best evaluation metrics on 24 out of 27 ADMET benchmark datasets. 3D-SMGE is anticipated to emerge as a powerful tool for hit-to-lead structural optimizations and accelerate the drug discovery process.
ABSTRACT
BACKGROUND: Drug discovery and development is the extremely costly and time-consuming process of identifying new molecules that can interact with a biomarker target to interrupt the disease pathway of interest. In addition to binding the target, a drug candidate needs to satisfy multiple properties affecting absorption, distribution, metabolism, excretion, and toxicity (ADMET). Artificial intelligence approaches provide an opportunity to improve each step of the drug discovery and development process, in which the first question faced by us is how a molecule can be informatively represented such that the in-silico solutions are optimized. RESULTS: This study introduces a novel hybrid SMILES-fragment tokenization method, coupled with two pre-training strategies, utilizing a Transformer-based model. We investigate the efficacy of hybrid tokenization in improving the performance of ADMET prediction tasks. Our approach leverages MTL-BERT, an encoder-only Transformer model that achieves state-of-the-art ADMET predictions, and contrasts the standard SMILES tokenization with our hybrid method across a spectrum of fragment library cutoffs. CONCLUSION: The findings reveal that while an excess of fragments can impede performance, using hybrid tokenization with high frequency fragments enhances results beyond the base SMILES tokenization. This advancement underscores the potential of integrating fragment- and character-level molecular features within the training of Transformer models for ADMET property prediction.
Subject(s)
Drug Discovery , Drug Discovery/methods , Artificial Intelligence , Small Molecule Libraries/chemistry , Small Molecule Libraries/pharmacology , Computer Simulation , Pharmaceutical Preparations/metabolism , Pharmaceutical Preparations/chemistryABSTRACT
BACKGROUND: Drug design is a challenging and important task that requires the generation of novel and effective molecules that can bind to specific protein targets. Artificial intelligence algorithms have recently showed promising potential to expedite the drug design process. However, existing methods adopt multi-objective approaches which limits the number of objectives. RESULTS: In this paper, we expand this thread of research from the many-objective perspective, by proposing a novel framework that integrates a latent Transformer-based model for molecular generation, with a drug design system that incorporates absorption, distribution, metabolism, excretion, and toxicity prediction, molecular docking, and many-objective metaheuristics. We compared the performance of two latent Transformer models (ReLSO and FragNet) on a molecular generation task and show that ReLSO outperforms FragNet in terms of reconstruction and latent space organization. We then explored six different many-objective metaheuristics based on evolutionary algorithms and particle swarm optimization on a drug design task involving potential drug candidates to human lysophosphatidic acid receptor 1, a cancer-related protein target. CONCLUSION: We show that multi-objective evolutionary algorithm based on dominance and decomposition performs the best in terms of finding molecules that satisfy many objectives, such as high binding affinity and low toxicity, and high drug-likeness. Our framework demonstrates the potential of combining Transformers and many-objective computational intelligence for drug design.
Subject(s)
Algorithms , Drug Design , Humans , Molecular Docking Simulation , Receptors, Lysophosphatidic Acid/metabolism , Receptors, Lysophosphatidic Acid/chemistry , Artificial IntelligenceABSTRACT
The rise of pyrazinamide (PZA)-resistant strains of Mycobacterium tuberculosis (MTB) poses a major challenge to conventional tuberculosis (TB) treatments. PZA, a cornerstone of TB therapy, must be activated by the mycobacterial enzyme pyrazinamidase (PZase) to convert its active form, pyrazinoic acid, which targets the ribosomal protein S1. Resistance, often associated with mutations in the RpsA protein, complicates treatment and highlights a critical gap in the understanding of structural dynamics and mechanisms of resistance, particularly in the context of the G97D mutation. This study utilizes a novel integration of computational techniques, including multiscale biomolecular and molecular dynamics simulations, physicochemical and medicinal chemistry predictions, quantum computations and virtual screening from the ZINC and Chembridge databases, to elucidate the resistance mechanism and identify lead compounds that have the potential to improve treatment outcomes for PZA-resistant MTB, namely ZINC15913786, ZINC20735155, Chem10269711, Chem10279789 and Chem10295790. These computational methods offer a cost-effective, rapid alternative to traditional drug trials by bypassing the need for organic subjects while providing highly accurate insight into the binding sites and efficacy of new drug candidates. The need for rapid and appropriate drug development emphasizes the need for robust computational analysis to justify further validation through in vitro and in vivo experiments.
Subject(s)
Mycobacterium tuberculosis , Tuberculosis, Multidrug-Resistant , Tuberculosis , Humans , Pyrazinamide/chemistry , Pyrazinamide/metabolism , Pyrazinamide/pharmacology , Mycobacterium tuberculosis/genetics , Antitubercular Agents/chemistry , Antitubercular Agents/metabolism , Antitubercular Agents/pharmacology , Tuberculosis/microbiology , Mutation , Microbial Sensitivity TestsABSTRACT
Gastric cancer is considered a class 1 carcinogen that is closely linked to infection with Helicobacter pylori (H. pylori), which affects over 1 million people each year. However, the major challenge to fight against H. pylori and its associated gastric cancer due to drug resistance. This research gap had led our research team to investigate a potential drug candidate targeting the Helicobacter pylori-carcinogenic TNF-alpha-inducing protein. In this study, a total of 45 daidzein derivatives were investigated and the best 10 molecules were comprehensively investigated using in silico approaches for drug development, namely pass prediction, quantum calculations, molecular docking, molecular dynamics simulations, Lipinski rule evaluation, and prediction of pharmacokinetics. The molecular docking study was performed to evaluate the binding affinity between the target protein and the ligands. In addition, the stability of ligand-protein complexes was investigated by molecular dynamics simulations. Various parameters were analysed, including root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), hydrogen bond analysis, principal component analysis (PCA) and dynamic cross-correlation matrix (DCCM). The results has confirmed that the ligand-protein complex CID: 129661094 (07) and 129664277 (08) formed stable interactions with the target protein. It was also found that CID: 129661094 (07) has greater hydrogen bond occupancy and stability, while the ligand-protein complex CID 129664277 (08) has greater conformational flexibility. Principal component analysis revealed that the ligand-protein complex CID: 129661094 (07) is more compact and stable. Hydrogen bond analysis revealed favourable interactions with the reported amino acid residues. Overall, this study suggests that daidzein derivatives in particular show promise as potential inhibitors of H. pylori.
Subject(s)
Helicobacter pylori , Isoflavones , Molecular Docking Simulation , Molecular Dynamics Simulation , Helicobacter pylori/drug effects , Helicobacter pylori/metabolism , Isoflavones/pharmacology , Isoflavones/chemistry , Isoflavones/metabolism , Humans , Hydrogen Bonding , Ligands , Protein Binding , Principal Component Analysis , Helicobacter Infections/microbiology , Helicobacter Infections/drug therapy , Bacterial Proteins/metabolism , Bacterial Proteins/chemistry , Bacterial Proteins/antagonists & inhibitors , Stomach Neoplasms/microbiology , Stomach Neoplasms/drug therapyABSTRACT
Spinocerebellar ataxia (SCA) is a rare neurological illness inherited dominantly that causes severe impairment and premature mortality. While each rare disease may affect individuals infrequently, collectively they pose a significant healthcare challenge. It is mainly carried out due to the expansion of RNA triplet (CAG) repeats, although missense or point mutations can also be induced. Unfortunately, there is no cure; only symptomatic treatments are available. To date, SCA has about 48 subtypes, the most common of these being SCA 1, 2, 3, 6, 7, 12, and 17 having CAG repeats. Using molecular docking and molecular dynamics (MD) simulation, this study seeks to investigate effective natural herbal neuroprotective compounds against CAG repeats, which are therapeutically significant in treating SCA. Initially, virtual screening followed by molecular docking was used to estimate the binding affinity of neuroprotective natural compounds toward CAG repeats. The compound with the highest binding affinity, somniferine, was then chosen for MD simulation. The structural stability, interaction mechanism, and conformational dynamics of CAG repeats and somniferine were investigated via MD simulation. The MD study revealed that during the simulation period, the interaction between CAG repeats and somniferine stabilizes and results in fewer conformational variations. This in silico study suggests that Somniferine can be used as a therapeutic medication against RNA CAG repeats in SCA.
Subject(s)
Molecular Docking Simulation , Molecular Dynamics Simulation , Humans , Drug Discovery/methods , RNA/chemistry , RNA/metabolism , Spinocerebellar Ataxias/genetics , Spinocerebellar Ataxias/drug therapy , Spinocerebellar Ataxias/metabolism , Trinucleotide Repeat Expansion , Trinucleotide Repeats , Neuroprotective Agents/pharmacology , Neuroprotective Agents/chemistryABSTRACT
Plants are a treasure trove of biological materials containing a wide range of potential phytochemicals that are target-specific, rapidly biodegradable, and environmentally friendly, with multiple medicinal effects. Unfortunately, the development of resistance to synthetic pesticides and antibiotics led to the discovery of new antibiotics, antioxidants, and biopesticides. This has also led to the creation of new medications that work very well. The current study aimed to prove that ornamental plants contain specialized active substances that are used in several biological processes. Mosquitoes, one of the deadliest animals on the planet, cause millions of fatalities each year by transmitting several human illnesses. Phytochemicals are possible biological agents for controlling pests that are harmful. The potential of leaf extracts of Bougainvillea glabra, Delonix regia, Lantana camara, and Platycladus orientalis against Culex pipiens and microbial agents was evaluated. Acetone extracts had more toxic effects against Cx. pipiens larvae (99.0-100 %, 72 h post-treatment), and the LC50 values were 142.8, 189.5, 95.4, and 71.1 ppm for B. glabra, D. regia, L. camara, and P. orientalis, respectively. Plant extracts tested in this study showed high insecticidal, antimicrobial, and antioxidant potential. GC-MS and HPLC analyses showed a higher number of terpenes, flavonoids, and phenolic compounds. The ADME analysis of element, caryophyllene oxide, caryophyllene, and copaene showed that they were similar to drugs and that they were better absorbed by the body and able to pass through the blood-brain barrier. Our results confirm the ability of ornamental plants to have promising larvicidal and antimicrobial activity and biotechnology.
ABSTRACT
Mutations in glucokinase (GCK) can either enhance or inhibit insulin secretion, leading to different forms of diabetes, including gestational diabetes. While many glucokinase activators (GKAs) have been explored as treatments, their long-term effectiveness has often been unsatisfactory. However, recent interest has surged with the introduction of dorzagliatin and TTP399. This study investigates the efficacy of four previously studied compounds (Swertiamarin, Apigenin, Mangiferin, and Tatanan A) in activating GCK using computational methods. Initial molecular docking revealed binding affinities ranging from -6.7 to -8.6 kcal/mol. The compounds were then evaluated for drug-likeness and pharmacokinetic properties. Re-docking studies were performed for validation. Based on their favorable binding affinities and compliance with Lipinski's rule and ADMET criteria, three compounds (Swertiamarin, Apigenin, and Tatanan A) were selected for molecular dynamics (MD) simulations. MD simulations demonstrated that Swertiamarin showed excellent stability, as indicated by analyses of RMSD, RMSF, radius of gyration (Rg), hydrogen bonding, and principal component analysis (PCA). These results suggest that Swertiamarin holds promise for further investigation in in vivo and clinical settings to evaluate its potential in enhancing GCK activity and treating diabetes. This study assessed the potential of four compounds as GCK activators using molecular docking, pharmacokinetic profiling, and MD simulations. Swertiamarin, in particular, showed significant stability and adherence to drug-likeness criteria, making it a promising candidate for further research in combating diabetes.
ABSTRACT
The highly pathogenic Marburg virus (MARV) is a member of the Filoviridae family, a non-segmented negative-strand RNA virus. This article represents the computer-aided drug design (CADD) approach for identifying drug-like compounds that prevent the MARV virus disease by inhibiting nucleoprotein, which is responsible for their replication. This study used a wide range of in silico drug design techniques to identify potential drugs. Out of 368 natural compounds, 202 compounds passed ADMET, and molecular docking identified the top two molecules (CID: 1804018 and 5280520) with a high binding affinity of -6.77 and -6.672 kcal/mol, respectively. Both compounds showed interactions with the common amino acid residues SER_216, ARG_215, TYR_135, CYS_195, and ILE_108, which indicates that lead compounds and control ligands interact in the common active site/catalytic site of the protein. The negative binding free energies of CID: 1804018 and 5280520 were -66.01 and -31.29 kcal/mol, respectively. Two lead compounds were re-evaluated using MD modeling techniques, which confirmed CID: 1804018 as the most stable when complexed with the target protein. PC3 of the (Z)-2-(2,5-dimethoxybenzylidene)-6-(2-(4-methoxyphenyl)-2-oxoethoxy) benzofuran-3(2H)-one (CID: 1804018) was 8.74 %, whereas PC3 of the 2'-Hydroxydaidzein (CID: 5280520) was 11.25 %. In this study, (Z)-2-(2,5-dimethoxybenzylidene)-6-(2-(4-methoxyphenyl)-2-oxoethoxy) benzofuran-3(2H)-one (CID: 1804018) unveiled the significant stability of the proteins' binding site in ADMET, Molecular docking, MM-GBSA and MD simulation analysis studies, which also showed a high negative binding free energy value, confirming as the best drug candidate which is found in Angelica archangelica which may potentially inhibit the replication of MARV nucleoprotein.
ABSTRACT
A series of novel 6-(substituted phenyl piperazine)-8-(4-substituted phenyl)-9-cyclopentyl purines, 10-51, were synthesized by a four-step synthesis, achieving an overall yield of about 43 %. The reaction conditions were effectively optimized, and the final products were obtained with high purity and yield in all synthesis steps. The synthesized nucleobases were evaluated for their in vitro cytotoxic activities on selected human cancer cell lines (HUH7 (liver), HCT116 (colon), and MCF7 (breast)) using the Sulforhodamine B (SRB) assay. Among these analogs, compounds bearing 4-trifluoromethyl phenyl (19, 20 and 21), 4-methoxy phenyl (27) and 4-fluoro phenyl (34) substitutions at C-8 of purine were the most potent, and they were also analyzed in drug-resistance and drug-sensitive hepatocellular cancer cell (HCC) panels. Compound 19 displayed remarkable anticancer activities (IC50 = 2.9-9.3 µM) against Huh7, FOCUS, SNU475, SNU182, HepG2, and Hep3B cells compared to the positive control, Fludarabine. Additionally, the pharmacological properties and toxicity profiles of the molecules were investigated computationally by the Swiss-ADME and Pro-Tox II online tools, respectively. Results showed that our compounds have favorable physicochemical characteristics for oral bioavailability and do not reveal any toxicity endpoints such as carcinogenicity, immunotoxicity, mutagenicity, or cytotoxicity.
Subject(s)
Antineoplastic Agents , Drug Screening Assays, Antitumor , Liver Neoplasms , Purines , Humans , Antineoplastic Agents/pharmacology , Antineoplastic Agents/chemical synthesis , Antineoplastic Agents/chemistry , Purines/pharmacology , Purines/chemical synthesis , Purines/chemistry , Structure-Activity Relationship , Liver Neoplasms/drug therapy , Liver Neoplasms/pathology , Cell Line, Tumor , Molecular Structure , Cell Proliferation/drug effects , Dose-Response Relationship, DrugABSTRACT
The direct-linked coumarin-benzimidazole hybrids, featuring aryl and n-butyl substituents at the N1-position of benzimidazole were synthesized through a Knoevenagel condensation reaction. This reaction involved the condensation of 1,2-diaminobenzene derivatives with coumarin-3-carboxylic acids in the presence of polyphosphoric acid (PPA) at 154 °C. The in vitro antibacterial potency of the hybrid molecules against different gram-positive and gram-negative bacterial strains led to the identification of the hybrids 6m and 6p with a MIC value of 6.25 µg/mL against a gram-negative bacterium, Klebsiella pneumonia ATCC 27736. Cell viability studies on THP-1 cells demonstrated that the compounds 6m and 6p were non-toxic at a concentration of 50 µM. Furthermore, in vivo efficacy studies using a murine neutropenic thigh infection model revealed that both compounds significantly reduced bacterial (Klebsiella pneumonia ATCC 27736) counts (more than 2 log) compared to the control group. Additionally, both compounds exhibited favorable physicochemical properties and drug-likeness characteristics. Consequently, these compounds hold promise as lead candidates for further development of effective antibacterial drugs.
Subject(s)
Anti-Bacterial Agents , Benzimidazoles , Coumarins , Microbial Sensitivity Tests , Animals , Humans , Mice , Anti-Bacterial Agents/pharmacology , Anti-Bacterial Agents/chemistry , Anti-Bacterial Agents/chemical synthesis , Benzimidazoles/chemistry , Benzimidazoles/pharmacology , Benzimidazoles/chemical synthesis , Cell Survival/drug effects , Coumarins/chemistry , Coumarins/pharmacology , Coumarins/chemical synthesis , Dose-Response Relationship, Drug , Gram-Negative Bacteria/drug effects , Gram-Positive Bacteria/drug effects , Klebsiella pneumoniae/drug effects , Molecular Structure , Structure-Activity RelationshipABSTRACT
A novel metal complex was synthesized using freshly prepared 2-Amino-5-nitro-N-[(E)-thiophen-2-yl-methylidene]aniline ligand with Zn (II) sulphate heptahydrate in a 1:1 molar ratio. The ligand and the complex were characterized using different spectroscopic techniques, and the complex was assigned a distorted square pyramidal geometry. Additionally, DNA binding assays and antibacterial activity were used to assess the biological perspectives for the synthesized complex, including the ligand and complex which was further confirmed by molecular docking. Fluorescence Spectroscopy, viscosity measurement, and adsorption measurement were used to investigate the interaction of the Zn (II) complex with CT-DNA. A comparative in vitro antibacterial activity study against Escherichia coli, Klebsiella pneumoniae, Bacillus subtilis, and Staphylococcus aureus strains were studied with free ligand and Zn (II) metal complex. The stable geometry of the complex was additionally established through computational simulation utilizing density functional theory, which was followed by the calculation of several electronic properties. The ADMET characteristics of the complex and ligand were also assessed using ADMET analysis. The in-silico ADMET properties pointed to a significant drug-likeness feature in the synthesized compounds, based on the Lipinski criteria.
ABSTRACT
Condensing 2-phenoxyaniline with 5-chlorosalicyldehyde under reflux conditions, a 4-chloro-2-(((2-phenoxyphenyl)imino)methyl)phenol Schiff base has been Synthesized. A zinc complex was synthesized by combining the ligand in a 1:1 molar ratio with zinc sulphateheptahydrate. Mass spectroscopy, NMR, infrared, and elemental analysis were used to characterize the ligand and zinc complex. By measuring the molar conductance, the non-electrolytic character of the complex was confirmed. The zinc ion is coordinated in a pentadentate manner, according to an IR and NMR investigation. Viscosity measurements, absorption and fluorescence spectroscopy were utilized to examine the complex's interaction with CT (calf thymus) DNA. Furthermore, the ligand and complex's ADMET characteristics were ascertained through the use of ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) study. Calculation of the different electronic parameters of the optimized structure through Density Functional Theory (DFT) indicated the stability of the Zn(II) complex. Molecular docking study reflected the future opportunity for the consideration of Zn(II) complex to fight against Alzheimer and Glaucoma diseases.
ABSTRACT
This study aims to assess the potential bioactivity of newly designed benzodiazepine-1,2,3-triazole derivatives using in-silico methodologies, with a primary focus on elucidating their inhibitory interactions with the butyrylcholinesterase (BuChE) enzyme, which is implicated in Alzheimer's disease. We employed multiple linear regression (MLR) methods to conduct a quantitative structure-activity relationship (QSAR) analysis on a collection of 31 benzodiazepine-1,2,3-triazole derivatives, with the goal of investigating, assessing, and predicting their activities, as well as designing novel compounds. This approach yielded highly accurate results, with coefficients of determination (R²) of 0.77 and 0.81 for the training and test datasets, respectively. Additionally, the optimized compounds were subjected to an Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) analysis, demonstrating their potential as non-hepatotoxic agents with enhanced absorption and blood-brain barrier permeability. To further validate these findings, the most favorable docking conformations were analyzed using molecular dynamics (MD) simulations with GROMACS software, predicting the stability of the formed complexes. These simulations underscored the critical role of hydrogen bonds in stabilizing the compounds at the BuChE receptor binding site. The results hold great promise for the development of innovative benzodiazepine-1,2,3-triazole derivatives as effective BuChE inhibitors, potentially leading to therapeutic interventions for Alzheimer's disease.
ABSTRACT
Herein, we report the synthesis of a series of new fourteen iodoquinazoline derivatives 7a-c to 13a-e and their evaluation as potential anticancer agents via dual targeting of EGFRT790M and VEGFR-2. The new derivatives were designed according to the target receptors structural requirements. The compounds were evaluated for their cytotoxicity against HepG2, MCF-7, HCT116 and A549 cancer cell lines using MTT assay. Compound 13e showed the highest anticancer activities with IC50 = 5.70, 7.15, 5.76 and 6.50 µM against HepG2, MCF-7, HCT116 and A549 cell lines correspondingly. Compounds 7c, 9b and 13a-d exhibited very good anticancer effects against the tested cancer cell lines. The highly effective six derivatives 7c, 10, 13b, 13c, 13d and 13e were examined against VERO normal cell lines to estimate their cytotoxic capabilities. Our conclusion revealed that compounds 7c, 10, 13b, 13c, 13d and 13e possessed low toxicity against VERO normal cells with IC50 prolonging from 41.66 to 53.99 µM. Also compounds 7a-c to 13a-e were further evaluated for their inhibitory activity against EGFRT790M and VEGFR-2. Also, their ability to bind with both EGFR and VEGFR-2 receptors was examined by molecular modeling. Compounds 13e, 13d, 7c and 13c excellently inhibited VEGFR-2 activity with IC50 = 0.90, 1.00, 1.25 and 1.50 µM respectively. Moreover, Compounds 13e, 7c, 10 and 13d excellently inhibited EGFRT790M activity with IC50 = 0.30, 0.35, 0.45 and 0.47 µM respectively. Finally, our derivatives 7b, 13d and 13e showed good in silico calculated ADMET profile.
Subject(s)
Antineoplastic Agents , Lung Neoplasms , Quinazolines , Humans , Antineoplastic Agents/chemistry , Cell Proliferation , Drug Design , Drug Screening Assays, Antitumor , ErbB Receptors/antagonists & inhibitors , Lung Neoplasms/drug therapy , Molecular Docking Simulation , Molecular Structure , Mutation , Protein Kinase Inhibitors , Structure-Activity Relationship , Vascular Endothelial Growth Factor Receptor-2/antagonists & inhibitors , Quinazolines/chemistry , Quinazolines/pharmacologyABSTRACT
Investigation into the interactions between photoprotective agents and skin can offer a precise understanding of their biological behaviors in vitro and in vivo, providing crucial insights for generating new substances. For this purpose, we designed and synthesized a series of naphthoxazine derivatives and examined their photoprotective properties. 1,3-naphthoxazine derivatives were synthesized through the multi-component reaction of 2-naphthol, arylamines and aromatic aldehydes in the presence of copper(II) trifluoromethanesulfonate (Cu(OTf)2) and (±)-Camphor-10-sulfonic acid ((±)-CSA) catalyst system under sonication. The potential of these synthesized 1,3-naphthoxazine derivatives as antioxidants and viable organic structural-based sunscreen ingredients has been investigated. Sun protection factor (SPF) assay results showed that especially compounds 4i, 4c, 4k, 4d, 4r, and 4h had remarkably high activity (23.65, 23.57, 23.04, 21.94, 20.80, and 20.26, respectively at 900 µg/mL concentration). Additionally, antioxidant activity of the synthesized compounds was evaluated and compounds 4h, 4e, 4b, and 4j exhibited the highest activities in DPPH scavenging activity assay (86.46 %, 82.83 %, 80.78 %, and 80.65 % respectively at 400 µg/mL concentration). The synthesized compounds exhibit promising characteristics for effective UV radiation absorption, suggesting their suitability for inclusion in sunscreen formulations. Cytotoxic activity of compound 4k against normal human fibroblast cell line (MRC-5) was determined by CVDK-8 method. The results revealed that the compound provided remarkable viability (87.55 %) of MRC-5 cells at concentration of 100 µM. The study explores their efficacy in providing broad-spectrum protection against UVA and UVB rays, degradation and photostability, ADMET profile, and other pharmacokinetic properties.
ABSTRACT
Based on the crucial role of histone deacetylase (HDAC) and receptor tyrosine kinase in angiogenesis, in situ assembly, skeletal transition, molecular hybridization, and pharmacophore fusion were employed to yield seventy-six multi-target angiogenesis inhibitors. Biological evaluation indicated that most of the compounds exhibited potent proliferation inhibitory activity on MCF-7 cells, with the TH series having the highest inhibitory activity on MCF-7 cells. In addition, the IC50 values of TA11 and TH3 against HT-29 cellswere 0.078 µmol/L and 0.068 µmol/L, respectively. The cytotoxicity evaluation indicated that TC9, TA11, TM4, and TH3 displayed good safety against HEK293T cells. TH2 and TH3 could induce apoptosis of MCF-7 cells. Molecular modeling and ADMET prediction results indicated that most of target compounds showed promising medicinal properties, which was consistent with the experimental results. Our findings provided new lead compounds for the structural optimization of multi-target angiogenesis inhibitors.
Subject(s)
Angiogenesis Inhibitors , Antineoplastic Agents , Humans , Structure-Activity Relationship , Cell Line, Tumor , Angiogenesis Inhibitors/pharmacology , Angiogenesis , HEK293 Cells , Histone Deacetylase Inhibitors/chemistry , Drug Screening Assays, Antitumor , Drug Design , Molecular Docking Simulation , Antineoplastic Agents/chemistry , Cell ProliferationABSTRACT
Prostate cancer is one of the most prevalent cancers in men leading to second most death causing cancer in men. Despite the availability of multiple treatment still the prevalence is high for prostate cancer. Steroidal antagonists associated with poor bioavailability, side effects while non-steroidal antagonists show serious side effects like gynecomastia. Therefore, there is a need of potential candidate for the treatment of prostate cancer with better bioavailability, good therapeutic effect and minimal side effects. In the same context, we have designed the series, SP1-SP25 based 3-phenyl-5-styryl-1,2,4-oxadiazole as the core structure. We successfully synthesized all 25 molecules in this series and characterized them using 1H, 13C NMR, and mass spectroscopy. Subsequently, we conducted MTT assays using PC-3 cells and observed that all the compounds exhibited a dose-dependent decrease in cell viability. Notably, compounds SP04, SP16, and SP19 demonstrated a significant decrease in cell viability and exhibited potent activity compared to the other synthesized molecules and standard drug bicalutamide. Among them, SP04 emerged as the one of the most potent compounds with an IC50 value of 238.13 nM and an 89.99 % inhibition of PC-3 cells, compared to synthesized molecules and standard drug bicalutamide. Furthermore, we conducted ROS assays and androgen receptor inhibition assays using the potent compound SP04 and bicalutamide. The results indicated that SP04 increased ROS production and decreased androgen receptor expression dose-dependent manner. Additionally, we conducted a docking study to analyse the interaction patterns within the active site of the androgen receptor. ADMET analysis revealed that all the compounds exhibited favorable physicochemical properties and manageable toxicity profiles.
Subject(s)
Anilides , Antineoplastic Agents , Nitriles , Prostatic Neoplasms , Tosyl Compounds , Male , Humans , Molecular Docking Simulation , Receptors, Androgen/chemistry , Antineoplastic Agents/chemistry , Reactive Oxygen Species , Steroids/chemistry , Prostatic Neoplasms/drug therapy , Molecular Structure , Cell Proliferation , Structure-Activity Relationship , Drug Screening Assays, Antitumor , Cell Line, TumorABSTRACT
Inhibition of α-glucosidase and α-amylase is an important target for treatment of type 2 diabetes. In this work, a novel series of pyrano[2,3-b]chromene derivatives 5a-m was designed based on potent α-glucosidase and α-amylase inhibitors and synthesized by simple chemical reactions. These compounds were evaluated against the latter enzymes. Most of the title compounds exhibited high inhibitory activity against α-glucosidase and α-amylase in comparison to standard inhibitor (acarbose). Representatively, the most potent compound, 4-methoxy derivative 5d, was 30.4 fold more potent than acarbose against α-glucosidase and 6.1 fold more potent than this drug against α-amylase. In silico molecular modeling demonstrated that compound 5d attached to the active sites of α-glucosidase and α-amylase with a favorable binding energies and established interactions with important amino acids. Dynamics of compound 5d also showed that this compound formed a stable complex with the α-glucosidase active site. In silicodrug-likeness as well as ADMET prediction of this compound was also performed and satisfactory results were obtained.