Identification of potential JNK3 inhibitors through virtual screening, molecular docking and molecular dynamics simulation as therapeutics for Alzheimer's disease.

Alzheimer's disease (AD) is a complex neurological disorder and no effective drug is available for its treatment. Numerous pathological conditions are believed to be responsible for the initiation and development of AD including c-Jun N-terminal kinases (JNKs). The JNKs are one of the enzymes from the mitogen-activated protein kinase (MAPK) family that controls the phosphorylation of various transcription factors on serine and threonine residues, and hold significant responsibilities in tasks like gene expression, cell proliferation, differentiation, and apoptosis. Since, JNK3 is primarily expressed in the brain hence its increased levels in the brain are associated with the AD pathology promoting neurofibrillary tangles, senile plaques, neuroinflammation, and nerve cell apoptosis. The current research work is focused on the development of novel JNK inhibitors as therapeutics for AD employing a structure-based virtual screening (SBVS) approach. The ZINC database (14634052 compounds) was investigated after employing pan assay interference (PAINs), drug-likeness, and diversity picking filter to distinguish molecules interacting with JNK3 by following three docking precision criteria: High Throughput Virtual Screening (HTVS), Standard Precision (SP), and Extra Precision (XP) & MMGBSA. Five lead molecules showed a better docking score in the range of -13.091 to -14.051 kcal/mol better than the reference compound (- 11.828 kcal/mol). The lead compounds displayed acceptable pharmacokinetic properties and were subjected to molecular dynamic simulations of 100 ns and binding free energy calculations. All the lead molecules showed stable RMSD and hydrogen bond interactions throughout the trajectory. The ∆GMM/PBSA_total score for the lead compounds ZINC220382956, ZINC147071339, ZINC207081127, ZINC205151456, ZINC1228819126, and CC-930 was calculated and found to be - 31.39, - 42.8, - 37.04, - 39.01, - 36.5, - 34.16 kcal/mol, respectively. Thus, it was concluded that the lead molecules identified in these studies have the potential to be explored as potent JNK3 inhibitors.

Design, synthesis, in silico and biological evaluation of new indole based oxadiazole derivatives targeting estrogen receptor alpha.

A series of new indole-oxadiazole derivatives was designed and synthesized to develop potential anti-breast cancer agents. The compounds exhibited significant inhibitory activity with IC50 values ranging from 1.78 to 19.74 µM against ER-positive human breast cancer (BC) cell lines T-47D and MCF-7. Among them, compounds (5a, 5c, 5e-5h, 5j-5o) displayed superior activity against ER-α dominant (ratio of ER-α/ER-ß is 9/1) T-47D cells compared to the standard drug bazedoxifene (IC50 = 12.78 ± 0.92 µM). Compounds 5c and 5o exhibited remarkable anti-proliferative activity with IC50 values of 3.24 ± 0.46 and 1.72 ± 1.67 µM against T-47D cells, respectively. Further, compound 5o manifested 1589-fold higher ER-α binding affinity (213.4 pM) relative to bazedoxifene (339.2 nM) in a competitive ER-α binding assay, while compound 5c showed a binding affinity of 446.6 nM. The Western blot analysis proved that both compounds influenced the ER-α protein's expression, impeding its subsequent transactivation and signalling pathway within T-47D cells. Additionally, a molecular docking study suggests that compounds 5c and 5o bind in such a fashion that induces conformational changes in the protein, culminating in their antagonistic effect. Also, pharmacokinetic profiles showed that all compounds have drug-like properties. Further, molecular dynamic (MD) simulations and density functional theory (DFT) analysis confirmed the stability, conformational behaviour, reactivity, and biological feasibility of compounds 5c and 5o. In conclusion, based on our findings, compounds 5c and 5o, which exhibit significant ER-α antagonistic activity, can act as potential lead compounds for developing anti-breast cancer agents.

Iodine-PEG as a unique combination for the metal-free synthesis of flavonoids through iodonium-triiodide ion-pair complexation.

An efficient metal-free single-step protocol has been developed for the direct synthesis of flavones from 2-hydroxyacetophenone and substituted benzaldehydes. This chemical transformation is exclusively promoted by the iodonium-triiodide ion couple formed through iodine and PEG-400 complexation. The triiodide anion not only helps in the abstraction of a proton from the acetophenone but also promotes the cyclization of intermediate chalcone to the corresponding flavones. The flavones were obtained in very high yields without using any toxic metal catalysts or harsh reaction conditions. The reaction mechanism was established through a series of test reactions and entrapping of reaction intermediates. The developed protocol provides direct access to flavones in high yields under milder reaction conditions with great substrate compatibility, including hydroxylated derivatives.

3D-QSAR-based pharmacophore modelling of quinazoline derivatives for the identification of acetylcholinesterase inhibitors through virtual screening, molecular docking, molecular dynamics and DFT studies.

Alzheimer's disease (AD) is a progressive neurological disorder responsible for the cognitive dysfunction and cognitive impairment in the patients. Acetylcholinesterase inhibitors (AChEIs) are used to treat AD however, these only provided symptomatic relief and more efficient drug molecules are desired for the effective treatment of the disease. In this article, ligand-based drug-designing strategy was used to develop and validate a field-based 3D-QSAR pharmacophore model on quinazoline-based AChEIs reported in the literature. The validated pharmacophore model (AAAHR_1) was used as a prefilter to screen an ASINEX database via virtual screening workflow (VSW). The hits generated were subjected to MM-GBSA to identify potential AChEIs and top three scoring molecules (BAS 05264565, LEG 12727144 and SYN 22339886) were evaluated for thermodynamic stability at the target site using molecular dynamic simulations. Additionally, DFT study was performed to predict the reactivity of lead molecules towards acetylcholinesterase (AChE). Thus, by utilising various computational tools, three molecules were identified as potent AChEIs that can be developed as potential drug candidates for the treatment of AD.Communicated by Ramaswamy H. Sarma.

Identification of coumarin derivatives targeting acetylcholinesterase for Alzheimer's disease by field-based 3D-QSAR, pharmacophore model-based virtual screening, molecular docking, MM/GBSA, ADME and MD Simulation study.

Alzheimer's disease (AD) leads to gradual memory loss including other compromised cognitive abilities. Acetylcholinesterase (AChE), an important biochemical enzyme from the cholinesterase (ChE) family, is recognized as primary pharmacological target for treating AD. Currently marketed drugs for AD treatment are primarily AChE inhibitors and coumarin derivatives comprising a wide variety of pharmacological activities have proved their efficacy towards AChE inhibition. Ensaculin (KA-672 HCl), a compound that belong to the coumarin family, is a clinical trial candidate for AD treatment. Therefore, a ligand library was prepared with 60 reported coumarin derivatives for field-based 3D-QSAR and pharmacophore modelling. The field-based 3D-QSAR model obtained at partial least square (PLS) factor 7, was the best validated model that predicted activity closer to original activity for each ligand introduced. The contour maps demonstrated spatial distribution of favourable and unfavorable steric, hydrophobic, electrostatic and H-bond donor and acceptor contours around coumarin nucleus. The best pharmacophore model, ADHRR_1 exhibited five essential pharmacophoric features of four different traits for optimum AChE inhibition. Virtual screening through ADHRR_1 accompanied with molecular docking and MM/GBSA identified 10 HITs from a 4,00,000 coumarin derivatives from PubChem database. HITs comprised docking scores ranging from -12.096 kcal/mol to -8.271 kcal/mol and compared with the reference drug Donepezil (-8.271 kcal/mol). ADME properties analysis led into detecting two leads (HIT 1 and HIT 2) among these 10 HITs. Molecular Dynamics Simulation indicated thermodynamic stability of the complex of lead compounds with AChE protein. Finally, thorough survey of the experimental results from 3D-QSAR modelling, pharmacophore modelling and molecular docking interactions led us to develop the lead formula I for future advancements in treating AD through AChE inhibitors.

Virtual screening and molecular dynamics simulation approach for the identification of potential multi-target directed ligands for the treatment of Alzheimer's disease.

Alzheimer's disease (AD) is a multifactorial neurological disorder characterized by memory loss and cognitive impairment. The currently available single-targeting drugs have miserably failed in the treatment of AD, and multi-target directed ligands (MTDLs) are being explored as an alternative treatment strategy. Cholinesterase and monoamine oxidase enzymes are reported to play a crucial role in the pathology of AD, and multipotent ligands targeting these two enzymes simultaneously are under various phases of design and development. Recent studies have revealed that computational approaches are robust and trusted tools for identifying novel therapeutics. The current research work is focused on the development of potential multi-target directed ligands that simultaneously inhibit acetylcholinesterase (AChE) and monoamine oxidase B (MAO-B) enzymes employing a structure-based virtual screening (SBVS) approach. The ASINEX database was screened after applying pan assay interference and drug-likeness filter to identify novel molecules using three docking precision criteria; High Throughput Virtual Screening (HTVS), Standard Precision (SP), and Extra Precision (XP). Additionally, binding free energy calculations, ADME, and molecular dynamic simulations were employed to get structural insights into the mechanism of protein-ligand binding and pharmacokinetic properties. Three lead molecules viz. AOP19078710, BAS00314308 and BDD26909696 were successfully identified with binding scores of -10.565, -10.543 & -8.066 kcal/mol against AChE and -11.019, -12.357 & -10.068 kcal/mol against MAO-B, better score as compared to the standard inhibitors. In the near future, these molecules will be synthesized and evaluated through in vitro and in vivo assays for their inhibition potential against AChE and MAO-B enzymes.

Identification of terpenoids as dihydropteroate synthase and dihydrofolate reductase inhibitors through structure-based virtual screening and molecular dynamic simulations.

Bacterial infections are rising, and antimicrobial resistance (AMR) in bacteria has worsened the scenario, requiring extensive research to find alternative therapeutic agents. Terpenoids play an essential role in protecting plants from herbivores and pathogens. The present study was designed to focus on in silico evaluation of terpenoids for their affinity towards two necessary enzymes, i.e. DHFR and DHPS, which are involved in forming 5, 6, 7, 8-tetrahydrofolate, a key component in bacterial DNA synthesis proteins. Additionally, to account for activity against resistant bacteria, their affinity towards the L28R mutant of DHFR was also assessed in the study. The structure-based drug design approach was used to screen the compound library of terpenes for their interaction with active sites of DHFR and DHPS. Further, compounds were screened based on their dock score, pharmacokinetic properties, and binding affinities. A total of five compounds for each target protein were screened, having dock scores better than their respective standard drug molecules. CNP0169378 (-8.4 kcal/mol) and CNP0309455 (-6.5 kcal/mol) have been identified as molecules with a higher affinity toward the targets of DHFR and DHPS, respectively. At the same time, one molecule CNP0298407 (-5.8 kcal/mol for DHPS, -7.6 kcal/mol for DHFR, -6.1 kcal/mol for the L28R variant), has affinity for both proteins (6XG5 and 6XG4). All the molecules have good pharmacokinetic properties. We further validated the docking study by binding free energy calculations using the MM/GBSA approach and molecular dynamics simulations.Communicated by Ramaswamy H. Sarma.

An amalgamated molecular dynamic and Gaussian based 3D-QSAR study for the design of 2,4-thiazolidinediones as potential PTP1B inhibitors.

Overexpression of protein tyrosine phosphatase 1B (PTP1B) is the major cause of various diseases such as diabetes, obesity, and cancer. PTP1B has been identified as a negative regulator of the insulin signaling cascade, thereby causing diabetes. Numerous anti-diabetic medications based on thiazolidinedione have been successfully developed; however, 2,4-thiazolidinedione (2,4-TZD) scaffolds have been reported as potential PTP1B inhibitors for the manifestation of type 2 diabetes mellitus involving insulin resistance. In the present study, we have employed amalgamated approach involving MD-simulation studies (100 ns) as well as Gaussian field-based 3D-QSAR to develop a pharmacophoric model of 2,4-TZD as potent PTP1B inhibitors. MD simulation studies of the most potent compound in the PTP1B (PDB Id: 2QBS) binding pocket revealed that compound 43 was stable in the binding pocket and demonstrated excellent binding efficacy within the active site pocket. MM/GBSA results revealed that compound 43, bearing C-5 arylidine substitution, strongly bound to the target as compared to rosiglitazone with ΔGMM/GBSA difference of -11.13 kcal/mol. PCA, Rg, RMSF, RMSD, and SASA were analyzed from the complex's trajectories to anticipate the simulation outcome. We have suggested a series of 2,4-TZD as possible PTP1B inhibitors based on the results of MD simulation and 3D-QSAR studies.

Design, synthesis, and unraveling the antibacterial and antibiofilm potential of 2-azidobenzothiazoles: insights from a comprehensive in vitro study.

The present study reports the synthesis of 2-azidobenzothiazoles from substituted 2-aminobenzothiazoles using sodium nitrite and sodium azide under mild conditions. All the synthesized compounds were examined for their antibacterial activity against Gram (+) bacteria, Staphylococcus aureus (ATCC 25923), Enterococcus faecalis (ATCC 51299), Bacillus cereus (ATCC 10876) and Gram (-) bacteria, Escherichia coli (ATCC 10536), Pseudomonas aeruginosa (ATCC 10145), Klebsiella pneumonia (ATCC BAA-2146)and clinical isolates of Gram (+) Methicillin Resistant S. aureus (MRSA) and Multi Drug Resistant E. coli. The Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC) values by broth dilution method revealed that compound 2d exhibited significant antibacterial potential against E. faecalis and S. aureus with MIC of 8 µg/mL, while other synthesized compounds had only moderate effects against all the tested species. The compound significantly inhibited the biofilm formation of the bacterial strains below its MIC. The selective cytotoxicity of Compound 2d towards bacterial cells was evidenced on extended exposure of Human Embryonic Kidney-293 cell line to higher concentrations of the compound. Hence, the present study confirmed that compound 2d can be a potential drug candidate for future development as an antibacterial drug.

Identification of 1,3,4-oxadiazoles as tubulin-targeted anticancer agents: a combined field-based 3D-QSAR, pharmacophore model-based virtual screening, molecular docking, molecular dynamics simulation, and density functional theory calculation approach.

Cancer is one of the most prominent causes of death worldwide and tubulin is a crucial protein of cytoskeleton that maintains essential cellular functions including cell division as well as cell signalling, that makes an attractive drug target for cancer drug development. 1,3,4-oxadiazoles disrupt microtubule causing G2-M phase cell cycle arrest and provide anti-proliferative effect. In this study, field-based 3D-QSAR models were developed using 62 bioactive anti-tubulin 1,3,4-oxadiazoles. The best model characterized by PLS factor 7 was rigorously validated using various statistical parameters. Generated 3D-QSAR model having high degree of confidence showed favourable and unfavourable contours around 1,3,4-oxadiazole core that assisted in defining proper spatial positioning of desired functional groups for better bioactivity. A five featured pharmacophore model (AAHHR_1) was developed using same ligand library and validated through enrichment analysis (BEDROC160.9 value = 0.59, Average EF 1% = 27.05, and AUC = 0.74). Total 30,212 derivatives of 1,3,4-oxadiazole obtained from PubChem database was prefiltered through validated pharmacophore model and docked in XP mode on binding cavity of tubulin protein (PDB code: 1SA0) which led into the identification of 11 HITs having docking scores between -7.530 and -9.719 kcal/mol while the reference compound Colchicine exerted docking score of -7.046 kcal/mol. Following the analysis of MM-GBSA and ADME studies, HIT1 and HIT4 emerged as the two promising hits. To verify their thermodynamic stability at the target site, molecular dynamic simulations were carried out. Both HITs were further subjected to DFT analysis to determine their HOMO-LUMO energy gap for ensuring their biological feasibility. Finally, molecular docking based structural exploration for 1,3,4-oxadiazoles to set up a lead of Formula I for further advancements of tubulin polymerization inhibitors as anti-cancer agents.Communicated by Ramaswamy H. Sarma.

Probing the molecular mechanisms of α-synuclein inhibitors unveils promising natural candidates through machine-learning QSAR, pharmacophore modeling, and molecular dynamics simulations.

Parkinson's disease is characterized by a multifactorial nature that is linked to different pathways. Among them, the abnormal deposition and accumulation of α-synuclein fibrils is considered a neuropathological hallmark of Parkinson's disease. Several synthetic and natural compounds have been tested for their potency to inhibit the aggregation of α-synuclein. However, the molecular mechanisms responsible for the potency of these drugs to further rationalize their development and optimization are yet to be determined. To enhance our understanding of the structural requirements necessary for modulating the aggregation of α-synuclein fibrils, we retrieved a large dataset of α-synuclein inhibitors with their reported potency from the ChEMBL database to explore their chemical space and to generate QSAR models for predicting new bioactive compounds. The best performing QSAR model was applied to the LOTUS natural products database to screen for potential α-synuclein inhibitors followed by a pharmacophore design using the representative compounds sampled from each cluster in the ChEMBL dataset. Five natural products were retained after molecular docking studies displaying a binding affinity of - 6.0 kcal/mol or lower. ADMET analysis revealed satisfactory properties and predicted that all the compounds can cross the blood-brain barrier and reach their target. Finally, molecular dynamics simulations demonstrated the superior stability of LTS0078917 compared to the clinical candidate, Anle138b. We found that LTS0078917 shows promise in stabilizing the α-synuclein monomer by specifically binding to its hairpin-like coil within the N-terminal region. Our dynamic analysis of the inhibitor-monomer complex revealed a tendency towards a more compact conformation, potentially reducing the likelihood of adopting an elongated structure that favors the formation and aggregation of pathological oligomers. These findings offer valuable insights for the development of novel α-synuclein inhibitors derived from natural sources.

Flavonoids as promising anticancer agents: an in silico investigation of ADMET, binding affinity by molecular docking and molecular dynamics simulations.

Cancer is one of the most concerning diseases to humankind. Various treatment strategies are being employed for its treatment, out of which use of natural products is an essential one. Flavonoids have proven to be promising anticancer targets since decades. Also, tubulin is a significant biological target for the development of anticancer agents due to its crucial role in mitosis and abundance throughout the body. In the current study, in silico ADMET parameters of 104 flavonoids were examined, followed by molecular docking with the colchicine binding site of Tubulin protein (PDB; Id 4O2B). The best conformation from each flavonoid subcategory with the best docking score (MolDock score) was further subjected to 100 ns of molecular dynamics to investigate the protein-ligand complex's stability. Different parameters such as RMSD, RMSF, rGy and SASA were calculated for the six flavonoids using molecular dynamic studies. The top most compound from all the six subcategories of flavonoids elicited best behavior in the colchicine binding site of Tubulin protein. This in silico study employing molecular docking and molecular dynamics simulation provides strong evidence for flavonoids to be excellent anti-tubulin agents for the treatment of cancer.Communicated by Ramaswamy H. Sarma.

Flavonoids as P-glycoprotein inhibitors for multidrug resistance in cancer: an in-silico approach.

Cancer has become a leading cause of mortality due to non-communicable diseases after cardiovascular disease worldwide and is increasing day by day at a daunting pace. According to an estimate by 2040 there will be 28.4 million cancer cases. Occurrence of multidrug resistance has further worsened the scenario of available cancer treatment. Among different mechanisms of multidrug resistance efflux of xenobiotics by ABC transporter is of prime importance. P-glycoprotein (P-gp) is the major factor behind occurrence of multidrug resistance due to its wide distribution and invariably big binding cavity. Various generations of chemical inhibitors for P-gp have been designed and tested are not devoid of major side effects. Thus, in present study flavonoids a major class of natural compounds was virtually screened in order to find molecules which can be used as selective P-gp inhibitors to be used along with chemotherapeutics. After screening 4275 molecules from different classes of flavonoids i.e. flavan, flavanol, flavonone, flavone, anthocyanins, and isoflavone, through Glide docking top ten hit molecules were selected based on their binding affinity, binding energy calculation and pharmacokinetic properties. All the hit molecules were found to have docking score within the range of -11.202 to -9.699 kcal/mol showing very strong interaction with the amino acid residues of binding pocket. Whereas, dock score of standard P-gp inhibitor verapamil was -4.984 kcal/mol. The ligand and protein complex were found to be quite stable while run through molecular dynamics simulations.Communicated by Ramaswamy H. Sarma.