Identification of hydantoin based Decaprenylphosphoryl-β-D-Ribose Oxidase (DprE1) inhibitors as antimycobacterial agents using computational tools

Design, synthesis, QSAR modelling and molecular dynamic simulations of N-tosyl-indole hybrid thiosemicarbazones as competitive tyrosinase inhibitors

Tyrosinase is an enzyme crucial for the progression of melanogenesis. Immoderate production of melanin may be the cause of hyperpigmentation and darkening leading to skin diseases. Tyrosinase is the most researched target for suppressing melanogenesis since it catalyzes the rate-limiting stage of melanin production. Thiosemicarbazones have been reported to possess strong inhibition capability against tyrosinase. We have designed and synthesized eighteen N-tosyl substituted indole-based thiosemicarbazones as competitive tyrosinase inhibitors in the current work. All the compounds exhibited outstanding to good potency with half maximal inhibitory concentration in the range of 6.40 ± 0.21 µM to 61.84 ± 1.47 µM. The compound 5r displayed the top-tier inhibition amongst the entire series with IC50 = 6.40 ± 0.21 µM. Compounds, 5q and 5r exhibited competitive inhibitions in concentration dependent manner with Ki = 3.42 ± 0.03 and 10.25 ± 0.08 µM respectively. The binding mode of 5r was evaluated through in silico molecular dynamics simulations and molecular docking, while ADME assessment studies predicted the drug-like characteristics of the derivatives. The newly synthesized derivatives may serve as a structural guide for designing and developing novel tyrosinase inhibitors.

Synthesis of the chromone-thiosemicarbazone scaffold as promising α-glucosidase inhibitors: An in vitro and in silico approach toward antidiabetic drug design

Diabetes is a serious metabolic disorder affecting individuals of all age groups and prevails globally due to the failure of previous treatments. This study aims to address the most prevalent form of type 2 diabetes mellitus (T2DM) by reporting on the design, synthesis, and in vitro as well as in silico evaluation of chromone-based thiosemicarbazones as potential α-glucosidase inhibitors. In vitro experiments showed that the tested compounds were significantly more potent than the standard acarbose, with the lead compound 3n exhibiting an IC50 value of 0.40 ± 0.02 μM, ~2183-fold higher than acarbose having an IC50 of 873.34 ± 1.67 μM. A kinetic mechanism analysis demonstrated that compound 3n exhibited reversible inhibition of α-glucosidase. To gain deeper insights, in silico molecular docking, pharmacokinetics, and molecular dynamics simulations were conducted for the investigation of the interactions, orientation, stability, and conformation of the synthesized compounds within the active pocket of α-glucosidase.

Synthesis, biological evaluation, and molecular modelling of substituted thiazolyl thiourea derivatives: A new class of prolyl oligopeptidase inhibitors

Prolyl oligopeptidase (POP) is a compelling therapeutic target associated with aging and neurodegenerative disorders due to its pivotal role in neuropeptide processing. Despite initial promise demonstrated by early-stage POP inhibitors, their progress in clinical trials has been halted at Phase I or II. This impediment has prompted the pursuit of novel inhibitors. The current study seeks to contribute to the identification of efficacious POP inhibitors through the design, synthesis, and comprehensive evaluation (both in vitro and in silico) of thiazolyl thiourea derivatives (5a-r). In vitro experimentation exhibited that the compounds displayed significant higher potency as POP inhibitors. Compound 5e demonstrated an IC50 value of 16.47 ± 0.54 μM, representing a remarkable potency. A meticulous examination of the structure-activity relationship indicated that halogen and methoxy substituents were the most efficacious. In silico investigations delved into induced fit docking, pharmacokinetics, and molecular dynamics simulations to elucidate the intricate interactions, orientation, and conformational changes of these compounds within the active site of the enzyme. Moreover, our pharmacokinetic assessments confirmed that the majority of the synthesized compounds possess attributes conducive to potential drug development.

Evaluation of diethyl 4-(5-bromo-1H-indol-3-yl)-2,6-dimethyl-1,4-dihydropyridine-3,5-dicarboxylate: synthesis, anti-corrosion potential, and biomedical applications

The pursuit of advanced multifunctional compounds has gained significant momentum in recent scientific endeavours. This study is dedicated to elucidating the synthesis, rigorous characterization, and multifaceted applications-encompassing anti-corrosion, antimicrobial, and antioxidant properties-of Diethyl 4-(5-bromo-1H-indol-3-yl)-2,6-dimethyl-1,4-dihydropyridine-3,5-dicarboxylate. The 1,4-dihydropyridine derivative was meticulously synthesized through a strategic reaction of ethyl acetoacetate, ammonium acetate, and 5-bromoindole-3-carboxaldehydein the ethanol medium at 60  C. Subsequent spectral validations were conducted using sophisticated techniques, namely FTIR, NMR, and Mass spectrometry, resulting in data that perfectly resonated with the hypothesized chemical structure of the compound. Its anti-corrosive potential was assessed on mild steel subjected to an aggressive acidic environment, employing comprehensive methodologies like gravimetric analysis, Tafel polarization, and EIS. Concurrently, its antimicrobial prowess was ascertained against a spectrum of bacterial and fungal pathogens viz., Staphylococcus aureus, Bacillus subtilis, Escherichia coli, Pseudomonas, Candida albicansandAspergillusniger, leveraging the disc diffusion method and using Gentamicin as a reference standard.The empirical results illustrated a substantial decrement in corrosion rates with ascending concentrations of the organic compound, achieving an apex of anti-corrosive efficacy at 81.89% for a concentration of 2 × 103 M. Furthermore, the compound outperformed Gentamicin in antimicrobial screenings, manifesting superior efficacy against all tested pathogens. The antioxidant potential, quantified using the DPPH free radical scavenging assay against ascorbic acid as a benchmark, was found to have an IC50 value of 113.964 ± 0.076 µg/ml.This comprehensive investigation accentuates the paramount potential of the synthesized dihydropyridine derivative in diverse domains-from industrial applications as a corrosion inhibitor to therapeutic avenues given its pronounced antimicrobial and antioxidant capabilities. The compelling results obtained pave the way for expansive research and development initiatives cantered around this multifaceted compound.

Design, synthesis, and evaluation of purine and pyrimidine-based KRAS G12D inhibitors: Towards potential anticancer therapy

Oncogenic RAS mutations, commonly observed in human tumors, affect approximately 30% of cancer cases and pose a significant challenge for effective cancer treatment. Current strategies to inhibit the KRAS G12D mutation have shown limited success, emphasizing the urgent need for new therapeutic approaches. In this study, we designed and synthesized several purine and pyrimidine analogs as inhibitors for the KRAS G12D mutation. Our synthesized compounds demonstrated potent anticancer activity against cell lines with the KRAS G12D mutation, effectively impeding their growth. They also exhibited low toxicity in normal cells, indicating their selective action against cancer cells harboring the KRAS G12D mutation. Notably, the lead compound, PU1-1 induced the programmed cell death of KRAS G12D-mutated cells and reduced the levels of active KRAS and its downstream signaling proteins. Moreover, PU1-1 significantly shrunk the tumor size in a pancreatic xenograft model induced by the KRAS G12D mutation, further validating its potential as a therapeutic agent. These findings highlight the potential of purine-based KRAS G12D inhibitors as candidates for targeted cancer therapy. However, further exploration and optimization of these compounds are essential to meet the unmet clinical needs of patients with KRAS-mutant cancers.

Revealing innovative JAK1 and JAK3 inhibitors: a comprehensive study utilizing QSAR, 3D-Pharmacophore screening, molecular docking, molecular dynamics, and MM/GBSA analyses

The heterocycle compounds, with their diverse functionalities, are particularly effective in inhibiting Janus kinases (JAKs). Therefore, it is crucial to identify the correlation between their complex structures and biological activities for the development of new drugs for the treatment of rheumatoid arthritis (RA) and cancer. In this study, a diverse set of 28 heterocyclic compounds selective for JAK1 and JAK3 was employed to construct quantitative structure-activity relationship (QSAR) models using multiple linear regression (MLR). Artificial neural network (ANN) models were employed in the development of QSAR models. The robustness and stability of the models were assessed through internal and external methodologies, including the domain of applicability (DoA). The molecular descriptors incorporated into the model exhibited a satisfactory correlation with the receptor-ligand complex structures of JAKs observed in X-ray crystallography, making the model interpretable and predictive. Furthermore, pharmacophore models ADRRR and ADHRR were designed for each JAK1 and JAK3, proving effective in discriminating between active compounds and decoys. Both models demonstrated good performance in identifying new compounds, with an ROC of 0.83 for the ADRRR model and an ROC of 0.75 for the ADHRR model. Using a pharmacophore model, the most promising compounds were selected based on their strong affinity compared to the most active compounds in the studied series each JAK1 and JAK3. Notably, the pharmacokinetic, physicochemical properties, and biological activities of the selected compounds (As compounds ZINC79189223 and ZINC66252348) were found to be consistent with their therapeutic effects in RA, owing to their non-toxic, cholinergic nature, absence of P-glycoprotein, high gastrointestinal absorption, and ability to penetrate the blood-brain barrier. Furthermore, ADMET properties were assessed, and molecular dynamics and MM/GBSA analysis revealed stability in these molecules.

Discerning of isatin-based monoamine oxidase (MAO) inhibitors for neurodegenerative disorders by exploiting 2D, 3D-QSAR modelling and molecular dynamics simulation

Almost a billion people worldwide suffer from neurological disorders, which pose public health challenges. An important enzyme that is well-known for many neurodegenerative illnesses is monoamine oxidase (MAO). Although several promising drugs for the treatment of MAO inhibition have recently been examined, it is still necessary to identify the precise structural requirements for robust efficacy. Atom-based, field-based, and GA-MLR (genetic algorithm multiple linear regression) models were created for this investigation. All of the models have strong statistical (R2 and Q2) foundations because of both internal and external validation. Our dataset's molecule has a higher docking score than safinamide, a well-known and co-crystallized MAO-B inhibitor, as we also noticed. Using the SwissSimilarity platform, we further inquired which of our docked molecules would be the best for screening. We chose ZINC000016952895 as the screen molecule with the best binding docking score (XP score = -13.3613). Finally, the 100 ns for the ZINC000016952895-MAO-B complex in our MD investigations is stable. For compounds that we hit, also anticipate ADME properties. Our research revealed that the successful compound ZINC000016952895 might pave the way for the future development of MAO inhibitors for the treatment of neurological disease.Communicated by Ramaswamy H. Sarma.

Carbonylbis(hydrazine-1-carbothioamide) derivatives as a new class of α-glucosidase inhibitors and their mechanistic insights via molecular docking and dynamic simulations

In the past, efforts have been made to find a cure for diabetes, mainly evaluating new classes of compounds to explore their potency. In this study, we present the synthesis and evaluation of carbonylbis(hydrazine-1-carbothioamide) derivatives as potential α-glucosidase inhibitors, employing both in vivo and in silico investigations. The in vitro experiments revealed that all tested compounds were significantly potent for α-glucosidase inhibition, with the lead compound 3a displaying approximately 80 times higher activity than acarbose. To delve deeper, in silico induced fit docking, pharmacokinetics, and molecular dynamics studies were conducted. Significantly, compound 3a exhibited a docking score of -7.87 kcal/mol, surpassing acarbose, which had a docking score of -6.59 kcal/mol. The in silico ADMET indicated that most of the synthesized compounds have properties conducive to drug development. Molecular dynamics analysis demonstrated that, when the ligand 3a was coupled with the target 3TOP, Cα-RMSD backbone RMSD values below 2.4 Å and "Lig_fit_Prot" values below 2.7 Å were observed. QSAR analysis demonstrates that the "fOC8A" descriptor positively correlates with α-glucosidase inhibition activity, while "lipoplus_AbSA" positively contributes and "notringC_notringO_8B" negatively contributes to this activity.

A Novel Nucleic Acid Sensing-related Genes Signature for Predicting Immunotherapy Efficacy and Prognosis of Lung Adenocarcinoma

BACKGROUND

As a novel pillar for lung adenocarcinoma (LUAD) treatment, immunotherapy has limited efficiency in LUAD patients. The nucleic acid sensing (NAS) pathways are critical in the anti-tumor immune response, but their role in LUAD remains controversial.

OBJECTIVE

The study aims to develop a classification system to identify immune subtypes of LUAD based on nucleic acid sensing-related genes so that it can help screen patients who may respond to immunotherapy.

METHODS

We performed a comprehensive bioinformatics analysis of the NAS molecule expression profiles across multiple public datasets. Using qRT-PCR to verify the NAS genes in multiple lung cancer cell lines. Molecular docking was performed to screen drug candidates.

RESULTS

The NAS-activated subgroup and NAS-suppressed subgroup were validated based on the different patterns of gene expression and pathways enrichment. The NAS-activated subgroup displayed a stronger immune infiltration and better prognosis of patients. Moreover, we constructed a seven nucleic acid sensing-related risk score (NASRS) model for the convenience of clinical application. The predictive values of NASRS in prognosis and immunotherapy were subsequently fully validated in the lung adenocarcinoma dataset and the uroepithelial carcinoma dataset. Additionally, five potential drugs binding to the core target of the NAS signature were predicted through molecular docking.

CONCLUSION

We found a significant correlation between nucleic acid sensing function and the immune treatment efficiency in LUAD. The NASRS can be used as a robust biomarker for the predicting of prognosis and immunotherapy efficiency and may help in clinical decisions for LUAD patients.

MeltSerts technology (brinzolamide ocular inserts via hot-melt extrusion): QbD-steered development, molecular dynamics, in vitro, ex vivo and in vivo studies

The research work aimed to develop a robust sustained release biocompatible brinzolamide (BRZ)-loaded ocular inserts (MeltSerts) using hot-melt extrusion technology with enhanced solubility for glaucoma management. A 32 rotatable central composite design was employed for the optimization of the MeltSerts to achieve sustained release. The effect of two independent factors was examined: Metolose® SR 90SH-100000SR (HPMC, hydroxypropyl methyl cellulose) and Kolliphor® P 407 (Poloxamer 407, P407). The drug release (DR) of BRZ at 0.5 h and 8 h were adopted as dependent responses. The factorial analysis resulted in an optimum composition of 50.00 % w/w of HPMC and 15.00 % w/w of P407 which gave % DR of 9.11 at 0.5 h and 69.10 at 8 h. Furthermore, molecular dynamic simulations were performed to elucidate various interactions between BRZ, and other formulation components and it was observed that BRZ showed maximum interactions with HPC and HPMC with an occupancy of 92.82 and 52.87 %, respectively. Additionally, molecular docking studies were performed to understand the interactions between BRZ and mucoadhesive polymers with ocular mucin (MUC-1). The results indicated a docking score of only -5.368 for BRZ alone, whereas a significantly higher docking score was observed for the optimized Meltserts -6.977, suggesting enhanced retention time of the optimized MeltSerts. SEM images displayed irregular surfaces, while EDS analysis validated uniform BRZ distribution in the optimized formulation. The results of the ocular irritancy studies both ex vivo and in vivo demonstrated that MeltSerts are safe for ocular use. The results indicate that the developed MeltSerts Technology has the potential to manufacture ocular inserts with cost-effectiveness, one-step processability, and enhanced product quality. Nonetheless, it also offers a once-daily regimen, consequently decreasing the dosing frequency, preservative exposure, and ultimately better glaucoma management.

Synthesis, Characterization, DFT, and In Silico Investigation of Two Newly Synthesized β-Diketone Derivatives as Potent COX-2 Inhibitors

Despite extensive genetic and biochemical characterization, the molecular genetic basis underlying the biosynthesis of β-diketones remains largely unexplored. β-Diketones and their complexes find broad applications as biologically active compounds. In this study, in silico molecular docking results revealed that two β-diketone derivatives, namely 2-(2-(4-fluorophenyl)hydrazono)-5,5-dimethylcyclohexane-1,3-dione and 5,5-dimethyl-2-(2-(2-(trifluoromethyl)phenyl)hydrazono)cyclohexane-1,3-dione, exhibit anti-COX-2 activities. However, recent docking results indicated that the relative anti-COX-2 activity of these two studied β-diketones was influenced by the employed docking programs. For improved design of COX-2 inhibitors from β-diketones, we conducted molecular dynamics simulations, density functional theory (DFT) calculations, Hirshfeld surface analysis, energy framework, and ADMET studies. The goal was to understand the interaction mechanisms and evaluate the inhibitory characteristics. The results indicate that 5,5-dimethyl-2-(2-(2-(trifluoromethyl)phenyl)hydrazono)cyclohexane-1,3-dione shows greater anti-COX-2 activity compared to 2-(2-(4-fluorophenyl)hydrazono)-5,5-dimethylcyclohexane-1,3-dione.

2-Amino Thiazole Derivatives as Prospective Aurora Kinase Inhibitors against Breast Cancer: QSAR, ADMET Prediction, Molecular Docking, and Molecular Dynamic Simulation Studies

The aurora kinase is a key enzyme that is implicated in tumor growth. Research revealed that small molecules that target aurora kinase have beneficial effects as anticancer agents. In the present study, in order to identify potential antibreast cancer agents with aurora kinase inhibitory activity, we employed QSARINS software to perform the quantitative structure-activity relationship (QSAR). The statistical values resulted from the study include R2 = 0.8902, CCCtr = 0.7580, Q2 LOO = 0.7875, Q2LMO = 0.7624, CCCcv = 0.7535, R2ext = 0.8735, and CCCext = 0.8783. Among the four generated models, the two best models encompass five important variables, including PSA, EstateVSA5, MoRSEP3, MATSp5, and RDFC24. The parameters including the atomic volume, atomic charges, and Sanderson's electronegativity played an important role in designing newer lead compounds. Based on the above data, we have designed six series of compounds including 1a-e, 2a-e, 3a-e, 4a-e, 5a-e, and 6a-e. All these compounds were subjected to molecular docking studies by using AutoDock v4.2.6 against the aurora kinase protein (1MQ4). Among the above 30 compounds, the 2-amino thiazole derivatives 1a, 2a, 3e, 4d, 5d, and 6d have excellent binding interactions with the active site of 1MQ4. Compound 1a had the highest docking score (-9.67) and hence was additionally subjected to molecular dynamic simulation investigations for 100 ns. The stable binding of compound 1a with 1MQ4 was verified by RMSD, RMSF, RoG, H-bond, molecular mechanics-generalized Born surface area (MM-GBSA), free binding energy calculations, and solvent-accessible surface area (SASA) analyses. Furthermore, newly designed compound 1a exhibited excellent ADMET properties. Based on the above findings, we propose that the designed compound 1a may be utilized as the best theoretical lead for future experimental research of selective inhibition of aurora kinase, therefore assisting in the creation of new antibreast cancer drugs.

Synthesis, biological evaluation and molecular modelling of 3-Formyl-6-isopropylchromone derived thiosemicarbazones as α-glucosidase inhibitors

Type-2 Diabetes Mellitus (T2DM) is one of the most common metabolic disorders in the world and over the past three decades its incidence has increased drastically. α-Glucosidase inhibitors are used to control the hyperglycemic affect of T2DM. Herein, we report the synthesis, α-glucosidase inhibition, structure activity relationship, pharmacokinetics and docking analysis of various novel chromone based thiosemicarbazones 3(a-r). The derivatives displayed potent activity against α-glucosidase with IC50 in range of 0.11 ± 0.01-79.37 ± 0.71 µM. Among all the synthesized compounds, 3a (IC50 = 0.17 ± 0.026 µM), 3 g (IC50 = 0.11 ± 0.01 µM), 3n (IC50 = 0.55 ± 0.02 µM), and 3p (IC50 = 0.43 ± 0.025 µM) displayed higher inhibitory activity as compared to the standard, acarbose. Moreover, we have developed a statistically significant 2D-QSAR model (R2tr:0.9693; F: 50.4647 and Q2LOO:0.9190), which can be used in future to further design potent thiosemicarbazones as inhibitors of α-glucosidase.

Computer-Aided Drug Design of Novel Derivatives of 2-Amino-7,9-dihydro-8H-purin-8-one as Potent Pan-Janus JAK3 Inhibitors

Rheumatoid arthritis (RA) remains one of the most prevalent autoimmune diseases worldwide. Janus kinase 3 (JAK3) is an essential enzyme for treating autoimmune diseases, including RA. Molecular modeling techniques play a crucial role in the search for new drugs by reducing time delays. In this study, the 3D-QSAR approach is employed to predict new JAK3 inhibitors. Two robust models, both field-based with R2 = 0.93, R = 0.96, and Q2 = 87, and atom-based with R2 = 0.94, R = 0.97, and Q2 = 86, yielded good results by identifying groups that may readily direct their interaction. A reliable pharmacophore model, DHRRR1, was provided in this work to enable the clear characterization of chemical features, leading to the design of 13 inhibitors with their pIC50 values. The DHRRR1 model yielded a validation result with a ROC value of 0.87. Five promising inhibitors were selected for further study based on an ADMET analysis of their pharmacokinetic properties and covalent docking (CovDock). Compared to the FDA-approved drug tofacitinib, the pharmaceutical features, binding affinity and stability of the inhibitors were analyzed through CovDock, 300 ns molecular dynamics simulations, free energy binding calculations and ADMET predictions. The results show that the inhibitors have strong binding affinity, stability and favorable pharmaceutical properties. The newly predicted molecules, as JAK3 inhibitors for the treatment of RA, are promising candidates for use as drugs.

Advances in computational frameworks in the fight against TB: The way forward

Around 1.6 million people lost their life to Tuberculosis in 2021 according to WHO estimates. Although an intensive treatment plan exists against the causal agent, Mycobacterium Tuberculosis, evolution of multi-drug resistant strains of the pathogen puts a large number of global populations at risk. Vaccine which can induce long-term protection is still in the making with many candidates currently in different phases of clinical trials. The COVID-19 pandemic has further aggravated the adversities by affecting early TB diagnosis and treatment. Yet, WHO remains adamant on its "End TB" strategy and aims to substantially reduce TB incidence and deaths by the year 2035. Such an ambitious goal would require a multi-sectoral approach which would greatly benefit from the latest computational advancements. To highlight the progress of these tools against TB, through this review, we summarize recent studies which have used advanced computational tools and algorithms for-early TB diagnosis, anti-mycobacterium drug discovery and in the designing of the next-generation of TB vaccines. At the end, we give an insight on other computational tools and Machine Learning approaches which have successfully been applied in biomedical research and discuss their prospects and applications against TB.

Molecular docking, QSAR, pharmacophore modeling, and dynamics studies of some chromone derivatives for the discovery of anti-breast cancer agents against hormone-dependent breast cancer

In search of new anti-breast cancer agents, the present study envisaged the design and synthesis of a series of benzopyran-chalcones. All the synthesized compounds were assayed for their in-vitro anticancer activity against ER + MCF-7 and triple-negative MDA-MB-231 breast cancer cell lines using SRB assay. The synthesized compounds were found active against ER + MCF-7 cell lines. Based on the in-vitro data, in-silico analysis was performed using hormone-dependent breast cancer targets such as hER-α and aromatase because the compounds showed activity against MCF-7 cells and none was active against MDA-MB-231. The in-silico results supported the in-vitro anticancer activity suggesting the affinity of compounds toward hormone-dependant breast cancer. Compounds 4A1 to 4A3 were found to be most cytotoxic to MCF-7 cells with IC50 values of 31.87, 22.95, and 20.34 μg/ml, respectively (Doxorubicin IC50: <10 μg/ml). In addition, they showed the interactions with the amino acid residues of a binding cavity of an hER-α. Furthermore, quantitative structure-activity relationship (QSAR) studies were performed to reveal the vital structural features required for anticancer activity against breast cancer. Molecular dynamic simulation studies of hER-α and 4A3 in comparison with the raloxifene complex ensure the appropriate refinement of compounds in the dynamic system. Additionally, a generated pharmacophore model explored the essential pharmacophoric features of the synthesized scaffolds with respect to clinically used drug molecules for optimal hormone-dependant anti-breast cancer activity.Communicated by Ramaswamy H. Sarma.

Synthesis of new diphenyl urea-clubbed imine analogs and its Implications in diabetic management through in vitro and in silico approaches

Type II diabetes mellitus (T2DM) is a global health issue with high rate of prevalence. The inhibition of α-glucosidase enzyme has prime importance in the management of T2DM. This study was established to synthesize Schiff bases of 1,3-dipheny urea (3a-y) and to investigate their in vitro anti-diabetic capability via inhibiting α-glucosidase, a key player in the catabolism of carbohydrates. The structures of all compounds were confirmed through various techniques including, Fourier-transform infrared spectroscopy (FTIR) and nuclear magnetic resonance (NMR) and mass-spectrometry (MS) methods. Interestingly all these compounds displayed potent inhibition IC₅₀ values in range of 2.14-115 µM as compared to acarbose used as control. Additionally, all the compounds were docked at the active site of α-glucosidase to predict their mode of binding. The docking results indicates that Glu277 and Asn350 play important role in the stabilization of these compounds in the active site of enzyme. These molecules showed excellent predicted pharmacokinetics, physicochemical and drug-likeness profile. The anti-diabetic potential of these molecules signifies their medical importance and provide insights into prospective therapeutic options for the treatment of T2DM.

Exploiting butyrylcholinesterase inhibitors through a combined 3-D pharmacophore modeling, QSAR, molecular docking, and molecular dynamics investigation†

Alzheimer's disease (AD), a neurodegenerative condition associated with ageing, can occur. AD gradually impairs memory and cognitive function, which leads to abnormal behavior, incapacity, and reliance. By 2050, there will likely be 100 million cases of AD in the world's population. Acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) inhibition are significant components of AD treatment. This work developed models using the genetic method multiple linear regression, atom-based, field-based, and 3-D pharmacophore modelling. Due to internal and external validation, all of the models have solid statistical (R² > 0.81 and Q² > 0.77) underpinnings. From a pre-plated CNS library (6055), we discovered a hit compound using virtual screening on a QSAR model. Through molecular docking, additional hit compounds were investigated (XP mode). Finally, a molecular dynamics simulation revealed that the Molecule5093-4BDS complex was stable (100 ns). Finally, the expected ADME properties for the hit compounds (Molecule5093, Molecule1076, Molecule4412, Molecule1053, and Molecule3344) were found. According to the results of our investigation and the prospective hit compounds, BuChE inhibitors may be used as a treatment for AD.

Alzheimer's disease (AD), a neurodegenerative condition associated with ageing, can occur.

Facing Antitubercular Resistance: Identification of Potential Direct Inhibitors Targeting InhA Enzyme and Generation of 3D-pharmacophore Model by in silico Approach

Purpose

The enoyl-acyl carrier protein reductase (InhA) is one of the important key enzymes employed in mycolic acids biosynthesis pathway and an important component of mycobacterial cell walls. This enzyme has also been identified as major target of isoniazid drug, except that isoniazid needs to be activated first by the catalase peroxidase (KatG) protein to form the isonicotinoyl-NAD (INH-NAD) adduct that inhibits the action of InhA enzyme. However, this activation becomes more difficult and unreachable with the problem of mutation-related resistance caused mainly by acquired mutations in KatG and InhA protein. Our main interest in this study is to identify direct InhA inhibitors using computer-aided drug design.

Methods

Computer-aided drug design was used to solve this problem by applying three different approaches including mutation impact modelling, virtual screening and 3D-pharmacophore search.

Results

A total of 15 mutations were collected from the literature, then a 3D model was generated for each of them and their impact was predicted. Of the 15 mutations, 10 were found to be deleterious and have a direct effect on flexibility, stability and SASA of the protein. In virtual screening, from 1,000 similar INH-NAD analogues obtained by the similarity search method, 823 compounds passed toxicity filter and drug likeness rules, which were then docked to the wild-type of InhA protein. Subsequently, 34 compounds with binding energy score better than that of INH-NAD were selected and docked against the 10 generated mutated models of InhA. Only three leads showed a lower binding affinity better than the reference. The 3D-pharmacophore model approach was used to identify the common features between those three compounds by generating a pharmacophoric map.

Conclusion

The result of this study may pave the way to develop more potent mutant-specific inhibitors to overcome this resistance.