Synthesis, molecular docking and QSAR study of thiazole clubbed pyrazole hybrid as α-amylase inhibitor

Pyrano[2,3-c]pyrazole fused spirooxindole-linked 1,2,3-triazoles as antioxidant agents: Exploring their utility in the development of antidiabetic drugs via inhibition of α-amylase and DPP4 activity

Environment-benign, multicomponent synthetic methodologies are vital in modern pharmaceutical research and facilitates multi-targeted drug development via synergistic approach. Herein, we reported green and efficient synthesis of pyrano[2,3-c]pyrazole fused spirooxindole linked 1,2,3-triazoles using a tea waste supported copper catalyst (TWCu). The synthetic approach involves a one-pot, five-component reaction using N-propargylated isatin, hydrazine hydrate, ethyl acetoacetate, malononitrile/ethyl cyanoacetate and aryl azides as model substrates. Mechanistically, the reaction was found to proceed via in situ pyrazolone formation followed by Knoevenagel condensation, azide alkyne cycloaddition and Michael's addition reactions. The molecules were developed using structure-based drug design. The primary goal is to identifying anti-oxidant molecules with potential ability to modulate α-amylase and DPP4 (dipeptidyl-peptidase 4) activity. The anti-oxidant analysis, as determined via DPPH, suggested that the synthesized compounds, A6 and A10 possessed excellent anti-oxidant potential compared to butylated hydroxytoluene (BHT). In contrast, compounds A3, A5, A8, A9, A13, A15, and A18 were found to possess comparable anti-oxidant potential. Among these, A3 and A13 possessed potential α-amylase inhibitory activity compared to the acarbose, and A3 further emerged as dual inhibitors of both DPP4 and α-amylase with anti-oxidant potential. The relationship of functionalities on their anti-oxidant and enzymatic inhibition was explored in context to their SAR that was further corroborated using in silico techniques and enzyme kinetics.

Exploring the Potential Biological Activities of Pyrazole-Based Schiff Bases as Anti-Diabetic, Anti-Alzheimer's, Anti-Inflammatory, and Cytotoxic Agents: In Vitro Studies with Computational Predictions

In this innovative research, we aim to reveal pyrazole-based Schiff bases as new multi-target agents. In this context, we re-synthesized three sets of pyrazole-based Schiff bases, 5a-f, 6a-f, and 7a-f, to evaluate their biological applications. The data from in vitro biological assays (including antioxidant and scavenging activities, anti-diabetes, anti-Alzheimer's, and anti-inflammatory properties) of the pyrazole-based Schiff bases 5a-f, 6a-f, and 7a-f showed that the six pyrazole-based Schiff bases 5a, 5d, 5e, 5f, 7a, and 7f possess the highest biological properties among the compounds evaluated. The cytotoxicity against lung (A549) and colon (Caco-2) human cancer types, as well as normal lung (WI-38) cell lines, was evaluated. The data from the cytotoxicity investigation demonstrated that the three Schiff bases 5d, 5e, and 7a are active against lung (A549) cells, while the two Schiff bases 5e and 7a exhibited the highest cytotoxicity towards colon (Caco-2) cells. Additionally, the enzymatic activities against caspase-3 and Bcl-2 of the six pyrazole-based Schiff bases 5a, 5d, 5e, 5f, 7a, and 7f were evaluated. Furthermore, we assessed the in silico absorption, distribution, metabolism, and toxicity (ADMT) properties of the more potent pyrazole-based Schiff bases. After modifying the structures of the six pyrazole-based Schiff bases, we plan to further extend the studies in the future.

Correlation intensity index-index of ideality of correlation: A hyphenated target function for furtherance of MAO-B inhibitory activity assessment

Monoamine oxidases are the enzymes involved in the management of brain homeostasis through oxidative deamination of monoamines such as neurotransmitters, tyramine etc. The excessive production of monoamine oxidase-B specifically results in numerous neurodegenerative disorders like Alzheimer's and Parkinson's diseases. Inhibitors of monoamine oxidase-B are applied in the management of these disorders. Here in this article we have developed robust hybrid descriptor based QSAR models related to 123 monoamine oxidase-B inhibitors through CORAL software by means of Monte Carlo optimization method. Three target functions were applied to prepare QSAR models and three splits were made for each target function. The most reliable, robust and better predictive QSAR models were developed with TF3 (correlation intensity index -index of ideality of correlation). Correlation intensity index showed positive effect on QSAR models. The structural features obtained from the QSAR modeling were incorporated in newly designed molecules and exhibited positive effect on their endpoint. Significant binding interactions were represented by these molecules in docking studies. Molecule B5 displayed prominent pIC50 (8.3) and binding affinity (-11.5 kcal mol-1) towards monoamine oxidase-B.

Recent advances in the synthesis and medicinal perspective of pyrazole-based α-amylase inhibitors as antidiabetic agents

Diabetes is a serious health threat across the globe, claiming millions of lives worldwide. Among the various strategies employed, inhibition of α-amylase is a therapeutic protocol for the management of Type 2 diabetes mellitus. α-Amylase is a crucial enzyme involved in the breakdown of dietary starch into simpler units. However, the clinically used α-amylase inhibitors have various drawbacks. Therefore, design and development of novel α-amylase inhibitors have gained significant attention. The pyrazole motif has been identified as a versatile scaffold in medicinal chemistry, and recent studies have led to the identification of various pyrazole-based α-amylase inhibitors. This review compiles therapeutic implications of pyrazole-appended α-amylase inhibitors; their synthesis, biological activities, structure-activity relationships and molecular docking studies are discussed.

Design, Synthesis, Molecular Modeling and Biological Evaluation of Novel Pyrazole Benzimidazolone Derivatives as Potent Antioxidants

In the present study, we used benzimidazolone as a starting material to efficiently synthesize several hybrid compounds of pyrazole benzimidazolone derivatives by the 1,3-dipolar cycloaddition reaction. These compounds were obtained in average yields and were characterized by NMR (1H and 13C) and HRMS analysis. The antioxidant activity of the synthesized compounds 5(a-c) and 6(a-c) was evaluated using in vitro reduction assays, including ferric reducing antioxidant power (FRAP) and total antioxidant capacity (TAC). The results indicated that products 5c, 6b, and 6c exhibit higher antioxidant activity compared to the reference compounds and showed a remarkable ability to effectively remove the radical at IC50 (14.00 ± 0.14, 12.47± 0.02, and 12.82 ± 0.10 µM, respectively) under the TAC assessment. Conversely, compound 6c showed excellent activity at IC50 (68.97 ± 0.26 µM) in the FRAP assay. We carried out molecular docking and dynamics simulations to investigate the binding mode and stability of 5c, 6b, and 6c in the active site of human Peroxiredoxin 5. An ADMET study was conducted to determine the drug properties of the synthesized compounds.

α-Amylase and mycobacterium-TB H37Rv antagonistic efficacy of novel pyrazole-coumarin hybrids: an in vitro and in silico investigation

The present investigation of minutiae to acquire structural information of the novel pyrazole-coumarin hybrids (PC1-PC10) synthesized using ultrasound methods and characterized using different spectroscopic techniques: mass, 1H-NMR, 13 C-NMR and IR spectroscopy, and theoretically explored using the DFT approach with a B3LYP/6-311G (d, p) basis set, and there in vitro, antagonistic efficacy against α-amylase and mycobacterium-TB H37Rv are described in this article. Pyrazole-coumarin hybrids (PC1-PC10) showed α-amylase inhibition ranging from IC50 (0.32-0.58 mM) when compared with acarbose (IC50 = 0.34 mM). Similarly, Mycobacterium-TB H37Rv strain inhibition screening showed MIC values ranging from 62.5 to 1000 µg/mL when compared with rifampicin and isoniazid MIC = 0.25 and 0.20 µg/mL, respectively. Molecular docking and MD simulation studies were performed to determine the active sites and rationalize the activities of the active compounds. To investigate the binding conformation and dynamics responsible for their activity, the three most active compounds (PC1, PC3 and PC6) were docked into the porcine pancreatic α-amylase active site (PDB ID:1OSE), and mycobacterium-TB H37Rv active site (PDB ID: 4TZK). The binding interactions between PC1, PC3, and PC6 with α-amylase were like those responsible for inhibiting α-amylase by acarbose. Also, the mycobacterium-TB H37Rv inhibiting responsible residues were compared with standard isoniazid and rifampicin.Communicated by Ramaswamy H. Sarma.

In silico computational drug discovery: a Monte Carlo approach for developing a novel JAK3 inhibitors

Inhibition of Janus kinase 3 (JAK3), a member of the JAK family of tyrosine kinases, remains an essential area of research for developing treatments for autoimmune diseases, particularly cancer and rheumatoid arthritis. The recent discovery of a new JAK3 protein, PDB ID: 4Z16, offers exciting possibilities for developing inhibitors capable of forming a covalent bond with the Cys909 residue, thereby contributing to JAK3 inhibition. A powerful prediction model was constructed and validated using Monte Carlo methods, employing various internal and external techniques. This approach resulted in the prediction of eleven new molecules, which were subsequently filtered to identify six compounds exhibiting potent pIC50 values. These candidates were then subjected to ADMET analysis, molecular docking (including reversible-reversible docking with tofacitinib, an FDA-approved drug, and reversible-irreversible docking for the newly designed compounds), molecular dynamics (MD) analysis for 300 ns, and calculation of free binding energy. The results suggested that these compounds hold promise as JAK3 inhibitors. In summary, the new compounds have exhibited favorable outcomes compared to other compounds across various modeling approaches. The collective findings from these investigations provide valuable insights into the potential therapeutic applications of covalent JAK3 inhibitors, offering a promising direction for the development of novel treatments for autoimmune disorders.Communicated by Ramaswamy H. Sarma.

α-amylase inhibition and in silico studies of novel naphtho[2,3-d]imidazole-4,9-dione linked N-acyl hydrazones

Aim: To enrich the pool of α-amylase inhibitors to manage Type 2 diabetes. Methods: Synthesis, conformational study, α-amylase inhibitory action and various in silico studies of novel N'-(arylbenzylidene)-2-(4,9-dioxo-4,9-dihydro-1H-naphtho[2,3-d]imidazol-1-yl)acetohydrazides carried out. Results: Compound H6 demonstrated the highest activity (IC50 = 0.0437 μmol mL-1) among the tested compounds. Structure-activity relationship study suggested that variable substitution at the aryl ring has a pivotal role in determining the inhibitory action of tested compounds. Docking simulations of the most active compound (H6) confirmed its interaction potential with active site residues of A. oryzae α-amylase. The root-mean-square deviation fluctuations substantiated the stability of protein-ligand complex. Absorption, distribution, metabolism and excretion prediction revealed optimal values for absorption, distribution, metabolism and excretion parameters. Conclusion: The developed molecules could be beneficial for the development of novel α-amylase inhibitors to treat Type 2 diabetes.

Thiazolidinedione-triazole conjugates: design, synthesis and probing of the α-amylase inhibitory potential

Aim: The primary objective of this investigation was the synthesis, spectral interpretation and evaluation of the α-amylase inhibition of rationally designed thiazolidinedione-triazole conjugates (7a-7aa). Materials & methods: The designed compounds were synthesized by stirring a mixture of thiazolidine-2,4-dione, propargyl bromide, cinnamaldehyde and azide derivatives in polyethylene glycol-400. The α-amylase inhibitory activity of the synthesized conjugates was examined by integrating in vitro and in silico studies. Results: The investigated derivatives exhibited promising α-amylase inhibitory activity, with IC50 values ranging between 0.028 and 0.088 μmol ml-1. Various computational approaches were employed to get detailed information about the inhibition mechanism. Conclusion: The thiazolidinedione-triazole conjugate 7p, with IC50 = 0.028 μmol ml-1, was identified as the best hit for inhibiting α-amylase.

Development of thiazole-appended novel hydrazones as a new class of α-amylase inhibitors with anticancer assets: an in silico and in vitro approach

Hyperamylasemia is reported to be associated with numerous chronic diseases, including diabetes and cancer. Considering this fact, we developed a series of thiazole-clubbed hydrazones. The derivatives were explored for their in vitro α-amylase inhibitory activity, which was further corroborated with their anticancer assets using a panel of cancer cells, including colon cancer (HCT-116), lung cancer (A549), and breast cancer (MDA-MB-231). To better understand pharmacokinetics, the synthetic derivatives were subjected to in silico ADMET prediction. The in vitro based biological investigation revealed that compared to the reference drug acarbose (IC50 = 0.21 ± 0.008 μM), all the synthesized compounds (5a-5aa) exhibited in vitro α-amylase inhibitory response in the range of IC50 values from 0.23 ± 0.003 to 0.5 ± 0.0 μM. Along with this, the proliferations of the HCT-116, A549 and MDA-MB-231 cells were inhibited when treated with the synthesized compounds. Notable cancer cell growth inhibition was observed for compounds 5e, 5f and 5y, which correlated with their α-amylase inhibition. Additionally, the kinetics investigation revealed that 5b, 5e, 5f and 5y exhibit uncompetitive inhibition. 5b was found to be the least cytotoxic and most potent α-amylase inhibitor and was further validated by absorption and fluorescence quenching technique.

Quantitative structure activity relationship studies of androgen receptor binding affinity of endocrine disruptor chemicals with index of ideality of correlation, their molecular docking, molecular dynamics and ADME studies

Endocrine disrupter chemicals (EDCs) are both natural and man-made chemicals that mimic, block or interfere with human hormonal system. In the present manuscript, QSAR modeling was performed for the androgen disruptors that interfere with biosynthesis, metabolism or action of androgens that causes adverse effects on male reproductive system. A set of 96 EDCs that exhibited affinity towards androgen receptors (Log RBA) in rats were employed for carrying out QSAR studies using Hybrid descriptors (combination of HFG and SMILES) through Monte Carlo Optimization. Using index of ideality of correlation (TF2), five splits were formed and predictability of five models resulting from these splits was assessed by various validation parameters. Models resulted from first split was the top most one with R2validation = 0.7878. Structural attributes responsible for change in endpoint were studied by employing correlation weights of structural attributes. In order to further validate the model, new EDCs were designed using these attributes. In silico molecular modelling studies were performed to assess the detailed interactions with the receptor. The binding energies of all the designed compounds were observed to be better than lead and are in the range of -10.46 to -14.80. Molecular dynamics simulation of 100 ns was performed for ED01 and NED05. The results revealed that the protein-ligand complex bearing NED05 was more stable than lead ED01 exhibiting better interactions with the receptor. Further, in an attempt to assess their metabolism, ADME studies were evaluated using SwissADME. The developed model enables to predict the characteristics of designed compounds in an authentic way.Communicated by Ramaswamy H. Sarma.

Parsing structural fragments of thiazolidin-4-one based α-amylase inhibitors: A combined approach employing in vitro colorimetric screening and GA-MLR based QSAR modelling supported by molecular docking, molecular dynamics simulation and ADMET studies

α-Amylase (EC.3.2.1.1) is a ubiquitous digestive endoamylase. The abrupt rise in blood glucose levels due to the hydrolysis of carbohydrates by α-amylase at a faster rate is one of the main reasons for type 2 diabetes. The inhibitors prevent the action of digestive enzymes, slowing the digestion of carbs and eventually assisting in the management of postprandial hyperglycemia. In the course of developing α-amylase inhibitors, we have screened 2-aryliminothiazolidin-4-one based analogs for their in vitro α-amylase inhibitory potential and employed various in silico approaches for the detailed exploration of the bioactivity. The DNSA bioassay revealed that compounds 5c, 5e, 5h, 5j, 5m, 5o and 5t were more potent than the reference drug (IC₆₀ value = 22.94 ± 0.24 μg mL^-1). The derivative 5o with -NO₂ group at both the rings was the most potent analog with an IC₆₀ value of 19.67 ± 0.20 μg mL^-1 whereas derivative 5a with unsubstituted aromatic rings showed poor inhibitory potential with an IC₆₀ value of 33.40 ± 0.15 μg mL^-1. The reliable QSAR models were developed using the QSARINS software. The high value of R²_ext = 0.9632 for model IM-9 showed that the built model can be applied to predict the α-amylase inhibitory activity of the untested molecules. A consensus modelling approach was also employed to test the reliability and robustness of the developed QSAR models. Molecular docking and molecular dynamics were employed to validate the bioassay results by studying the conformational changes and interaction mechanisms. A step further, these compounds also exhibited good ADMET characteristics and bioavailability when tested for in silico pharmacokinetics prediction parameters.

Design, synthesis, spectroscopic characterization, single crystal X-ray analysis, in vitro α-amylase inhibition assay, DPPH free radical evaluation and computational studies of naphtho[2,3-d]imidazole-4,9-dione appended 1,2,3-triazoles

In our quest to design and develop N/O-containing inhibitors of α-amylase, we have tried to synergize the inhibitory action of 1,4-naphthoquinone, imidazole and 1,2,3-triazole motifs by incorporating these structures into a single matrix. For this, a series of novel naphtho[2,3-d]imidazole-4,9-dione appended 1,2,3-triazoles is synthesized by a sequential approach involving [3 + 2] cycloaddition of 2-aryl-1-(prop-2-yn-1-yl)-1H-naphtho[2,3-d]imidazole-4,9-diones with substituted azides. The chemical structures of all the compounds are established with the help of 1D-NMR, 2D-NMR, IR, mass and X-ray studies. The developed molecular hybrids are screened for their inhibitory action on the α-amylase enzyme using the reference drug, acarbose. Different substituents present on the attached aryl part of the target compounds show amazing variations in inhibitory action against the α-amylase enzyme. Based on the type of substituents and their respective positions, it is observed that compounds containing -OCH₃ and -NO₂ groups show more inhibition potential than others. All the tested derivatives display α-amylase inhibitory activity with IC₅₀ values in the range of 17.83 ± 0.14 to 26.00 ± 0.17 μg/mL. Compound 2-(2,3,4-trimethoxyphenyl)-1-{[1-(4-methoxyphenyl)-1H-1,2,3-triazol-4-yl]methyl}-1H-naphtho[2,3-d]imidazole-4,9-dione (10y) show maximum inhibition of amylase activity with IC₅₀ value 17.83 ± 0.14 μg/mL as compared to reference drug acarbose (18.81 ± 0.05 μg/mL). A molecular docking study of the most active derivative (10y) is performed with A. oryzae α-amylase (PDB ID: 7TAA) and it unveils favourable binding interactions within the active site of the receptor molecule. The dynamic studies reveal that the receptor-ligand complex is stable as the RMSD of less than 2 is observed in 100 ns molecular dynamic simulation. Also, the designed derivatives are assayed for their DPPH free radical scavenging ability and all of them exhibit comparable radical scavenging activity with the standard, BHT. Further, to assess their drug-likeness properties, ADME properties are also evaluated and all of them demonstrate worthy in silico ADME results.

Design, synthesis, and molecular modeling of heterodimer and inhibitors of α-amylase as hypoglycemic agents

A series of rosiglitazone-based heterodimers were designed and synthesized, and their α-amylase and antioxidant activity was evaluated. The binding mode of the compounds at the active site of PPARγ and α-amylase enzyme was explored using MolDock docking method. In molecular docking studies against crystal structure of PPARγ (PDB code: 1FM6), compounds 10 and 13 showed interaction with amino acids Arg379, Asp379, Asn385, Ala387, Glu388, Val389, Glu390, and Lys438. Docking results of α-amylase enzyme (PDB code: 5EOF) with compounds 10 and 13 showed excellent interaction with amino acids Ala169, Lys172, Asp173, Tyr174, Val175, Arg176, and Lys178. Depending on the docking score, the designed compounds were selectively prioritized for synthesis. All synthesized compounds were subjected to in vitro α-amylase activity and antioxidant activity. Compounds 10 and 13 were to possess higher potency than acarbose, and most of the compounds showed antioxidant activity. Additionally, the most active compound 10 was evaluated for in vivo anti-diabetic activity.

Recent Applications of the Multicomponent Synthesis for Bioactive Pyrazole Derivatives

Pyrazole and its derivatives are considered a privileged N-heterocycle with immense therapeutic potential. Over the last few decades, the pot, atom, and step economy (PASE) synthesis of pyrazole derivatives by multicomponent reactions (MCRs) has gained increasing popularity in pharmaceutical and medicinal chemistry. The present review summarizes the recent developments of multicomponent reactions for the synthesis of biologically active molecules containing the pyrazole moiety. Particularly, it covers the articles published from 2015 to date related to antibacterial, anticancer, antifungal, antioxidant, α-glucosidase and α-amylase inhibitory, anti-inflammatory, antimycobacterial, antimalarial, and miscellaneous activities of pyrazole derivatives obtained exclusively via an MCR. The reported analytical and activity data, plausible synthetic mechanisms, and molecular docking simulations are organized in concise tables, schemes, and figures to facilitate comparison and underscore the key points of this review. We hope that this review will be helpful in the quest for developing more biologically active molecules and marketed drugs containing the pyrazole moiety.

CORAL: Development of a hybrid descriptor based QSTR model to predict the toxicity of dioxins and dioxin-like compounds with correlation intensity index and consensus modelling

In the present study, ninety-five halogenated dioxins and related chemicals (dibenzo-p-dioxins, dibenzofurans, biphenyls, and naphthalene) with endpoint pEC₅₀ were used to develop twelve quantitative structure toxicity relationship (QSTR) models using inbuilt Monte Carlo algorithm of CORAL software. The hybrid optimal descriptor of correlation weights (DCW) using a combination of SMILES and HSG (hydrogen suppressed graph) was employed to generate QSTR models. Three target functions i.e. TF₁ (W_IIC=W_CII=0), TF₂ (W_IIC= 0.3 & W_CII=0) and TF₃ (W_IIC= 0.0 &W_CII=0.3) were employed to develop robust QSTR models and the statistical outcomes of each target function were compared with each other. The correlation intensity index (CII) was found a reliable benchmark of the predictive potential for QSTR models. The numerical value of the determination coefficient of the validation set of split 1 computed by TF₃ was found highest (R_Valid²=0.8438). The fragments responsible for the toxicity of dioxins and related chemicals were also identified in terms of the promoter of increase/decrease for pEC₅₀. Three random splits (Split 1, Split 2 and Split 4) were selected for the extraction of the promoter of increase/decrease for pEC₅₀. In the last, consensus modelling was performed using the intelligent consensus tool of DTC lab (https://dtclab.webs.com/software-tools). The original consensus model, which was created by combining four distinct models employing the split 4 arrangement, was more predictive for the validation set and the numerical value of the determination coefficient of the test set (validation set) was increased from 0.8133 to 0.9725. For the validation set of split 4, the mean absolute error (MAE 100%) was also lowered from 0.513 to 0.2739.

In vitro and in silico evaluation of N-(alkyl/aryl)-2-chloro-4-nitro-5- [(4-nitrophenyl)sulfamoyl]benzamide derivatives for antidiabetic potential using docking and molecular dynamic simulations

A series of N-(alkyl/aryl)-2-chloro-4-nitro-5-[(4-nitrophenyl)sulfamoyl]benzamide derivatives were synthesized and evaluated for its in vitro antidiabetic potential against α-glucosidase and α-amylase enzymes and also for its antimicrobial potential. Compounds N-(2-methyl-4-nitrophenyl)-2-chloro-4-nitro-5-[(4-nitrophenyl)sulfamoyl]benzamide and N-(2-methyl-5-nitrophenyl)-2-chloro-4-nitro-5-[(4-nitrophenyl)sulfamoyl]benzamide were found to be the most potent α-glucosidase and α-amylase inhibitors with IC₅₀ values of 10.13 and 1.52 µM, respectively. The docking results depicted reasonable dock score -10.2 to -8.0 kcal/mol (α-glucosidase), -11.1 to -8.3 kcal/mol (α-amylase) and binding interactions of synthesized molecules with respective targets with enzymes. During molecular dynamic simulations, analysis of RMSD of ligand protein complex suggested stability of the most active compound at binding site of target proteins. Compound N-(2-chloro-4-nitrophenyl)-2-chloro-4-nitro-5-[(4-nitrophenyl)sulfamoyl] benzamide showed antibacterial potential against Gram positive and Gram negative bacteria and compound N-(2-methyl-5-nitrophenyl)-2-chloro-4-nitro-5-[(4-nitrophenyl)sulfamoyl] benzamide showed excellent antifungal potential against Candida albicans and Aspergillus niger. The computational studies were also executed to predict the drug-likeness and ADMET properties of the title compounds. The N-(alkyl/aryl)-2-chloro-4-nitro-5-[(4-nitrophenyl)sulfamoyl]benzamide derivatives showed significant antidiabetic and antimicrobial potential which is equally supported by the molecular dynamic and docking studies. This study will prove useful in revealing the molecular structure and receptor target site details which can be further utilized for the development of newer active antidiabetic and antimicrobial agents.

Monte Carlo Method and GA-MLR-Based QSAR Modeling of NS5A Inhibitors against the Hepatitis C Virus

Hepatitis C virus (HCV) is a serious disease that threatens human health. Despite consistent efforts to inhibit the virus, it has infected more than 58 million people, with 300,000 deaths per year. The HCV nonstructural protein NS5A plays a critical role in the viral life cycle, as it is a major contributor to the viral replication and assembly processes. Therefore, its importance is evident in all currently approved HCV combination treatments. The present study identifies new potential compounds for possible medical use against HCV using the quantitative structure–activity relationship (QSAR). In this context, a set of 36 NS5A inhibitors was used to build QSAR models using genetic algorithm multiple linear regression (GA-MLR) and Monte Carlo optimization and were implemented in the software CORAL. The Monte Carlo method was used to build QSAR models using SMILES-based optimal descriptors. Four splits were performed and 24 QSAR models were developed and verified through internal and external validation. The model created for split 3 produced a higher value of the determination coefficients using the validation set (R2 = 0.991 and Q2 = 0.943). In addition, this model provides interesting information about the structural features responsible for the increase and decrease of inhibitory activity, which were used to develop eight novel NS5A inhibitors. The constructed GA-MLR model with satisfactory statistical parameters (R2 = 0.915 and Q2 = 0.941) confirmed the predicted inhibitory activity for these compounds. The Absorption, Distribution, Metabolism, Elimination, and Toxicity (ADMET) predictions showed that the newly designed compounds were nontoxic and exhibited acceptable pharmacological properties. These results could accelerate the process of discovering new drugs against HCV.

Identification of Cyclic Sulfonamides with an N-Arylacetamide Group as α-Glucosidase and α-Amylase Inhibitors: Biological Evaluation and Molecular Modeling

Diabetes mellitus (DM), a complicated metabolic disorder, is due to insensitivity to insulin function or reduction in insulin secretion, which results in postprandial hyperglycemia. α-Glucosidase inhibitors (AGIs) and α-amylase inhibitors (AAIs) block the function of digestive enzymes, which delays the carbohydrate hydrolysis process and ultimately helps to control the postprandial hyperglycemia. Diversified 2-(3-(3-methoxybenzoyl)-4-hydroxy-1,1-dioxido-2H-benzo[e][1,2]thiazin-2-yl)-N-arylacetamides were synthesized and evaluated for their in vitro inhibitory potential against α-glucosidase and α-amylase enzymes. The compounds with chloro, bromo and methyl substituents demonstrated good inhibition of α-glucosidase enzymes having IC50 values in the range of 25.88-46.25 μM, which are less than the standard drug, acarbose (IC50 = 58.8 μM). Similarly, some derivatives having chloro, bromo and nitro substituents were observed potent inhibitors of α-amylase enzyme, with IC50 values of 7.52 to 15.06 μM, lower than acarbose (IC50 = 17.0 μM). In addition, the most potent compound, N-(4-bromophenyl)-2-(4-hydroxy-3-(3-methoxybenzoyl)-1,1-dioxido-2H-benzo[e][1,2]thiazin-2-yl)acetamide (12i), was found to be a non-competitive and competitive inhibitor of α-glucosidase and α-amylase enzymes, respectively, during kinetic studies. The molecular docking studies provided the binding modes of active compounds and the molecular dynamics simulation studies of compound 12i in complex with α-amylase also showed that the compound is binding in a fashion similar to that predicted by molecular docking studies.

In vitro and in silico studies of fluorinated 2,3-disubstituted thiazolidinone-pyrazoles as potential α-amylase inhibitors and antioxidant agents

As part of our effort to identify potent α-amylase inhibitors, in the present study, a novel series of fluorinated thiazolidinone-pyrazole hybrid molecules were prepared by the condensation of 3-(aryl/benzyloxyaryl)-pyrazole-4-carbaldehydes with fluorinated 2,3-disubstituted thiazolidin-4-ones. The structures of the newly synthesized compounds were confirmed by infrared, ¹ H nuclear magnetic resonance (NMR), ¹³ C NMR, and liquid chromatography-mass spectrometry data. All the compounds were screened for their α-amylase inhibitory and free radical scavenging activities by DPPH (1,1-diphenyl-2-picrylhydrazyl) and ABTS methods. Among the tested compounds, compound 8g emerged as a promising α-amylase inhibitor with IC₅₀  = 0.76 ± 1.23 µM, and it was found to be more potent than the standard drug acarbose (IC₅₀  = 0.86 ± 0.81 μM). Compounds 8b and 8g showed strong free radical scavenging activity compared to the standard butylated hydroxyl anisole. The kinetic study of compound 8g revealed the reversible, classical competitive inhibition mode on the α-amylase enzyme. Molecular docking and dynamic simulations studies were performed for the most potent compound 8g, which displayed remarkable hydrogen bonding with the α-amylase protein (PDB ID: 1DHK).

The Monte Carlo approach to model and predict the melting point of imidazolium ionic liquids using hybrid optimal descriptors

Ionic liquids (ILs) have captured intensive attention owing to their unique properties such as high thermal stability, negligible vapour pressure, high dissolution capacity and high ionic conductivity as well as their wide applications in various scientific fields including organic synthesis, catalysis, and industrial extraction processes. Many applications of ionic liquids (ILs) rely on the melting point (T_m). Therefore, in the present manuscript, the melting points of imidazolium ILs are studied employing a quantitative structure–property relationship (QSPR) approach to develop a model for predicting the melting points of a data set of imidazolium ILs. The Monte Carlo algorithm of CORAL software is applied to build up a robust QSPR model to calculate the values T_m of 353 imidazolium ILs. Using a combination of SMILES and hydrogen-suppressed molecular graphs (HSGs), the hybrid optimal descriptor is computed and used to generate the QSPR models. Internal and external validation parameters are also employed to evaluate the predictability and reliability of the QSPR model. Four splits are prepared from the dataset and each split is randomly distributed into four sets i.e. training set (≈33%), invisible training set (≈31%), calibration set (≈16%) and validation set (≈20%). In QSPR modelling, the numerical values of various statistical features of the validation sets such as R_Validation², Q_Validation², and IIC_Validation are found to be in the range of 0.7846–0.8535, 0.7687–0.8423 and 0.7424–0.8982, respectively. For mechanistic interpretation, the structural attributes which are responsible for the increase/decrease of T_m are also extracted.

The melting points of imidazolium ILs are studied employing a quantitative structure–property relationship (QSPR) approach to develop a model for predicting the melting points of a data set of imidazolium ILs.

Exploring biological efficacy of novel benzothiazole linked 2,5-disubstituted-1,3,4-oxadiazole hybrids as efficient α-amylase inhibitors: Synthesis, characterization, inhibition, molecular docking, molecular dynamics and Monte Carlo based QSAR studies

In an effort to explore a class of novel antidiabetic agents, we have made an effort to synergize the α-amylase inhibitory potential of 1,3-benzothiazole and 1,3,4-oxadiazole scaffolds by combining the two into a single structure via an ether linkage. The structure of synthesized benzothiazole clubbed oxadiazole derivatives are established by different spectral techniques. The synthesized hybrids are evaluated for their in vitro inhibitory potential against α-amylase. Compound 8f is found to be the most potent with a significant inhibition (87.5 ± 0.74% at 50 μg/mL, 82.27 ± 1.85% at 25 μg/mL and 79.94 ± 1.88% at 12.5 μg/mL) when compared to positive control acarbose (77.96 ± 2.06%, 71.17 ± 0.60%, 67.24 ± 1.16% at 50 μg/mL, 25 μg/mL and 12.5 μg/mL concentration). Molecular docking of the most potent enzyme inhibitor, 8f, shows promising interaction with the binding site of biological macromolecule Aspergillus oryzae α-amylase (PDB ID: 7TAA) and human pancreatic α-amylase (PDB ID: 3BAJ). To a step further, in-depth QSAR studies show a significant correlation between the experimental and the predicted inhibitory activities with the best R_validation²= 0.8701. The developed QSAR model can provide ample information about the structural features responsible for the increase and decrease of inhibitory activity. The mechanistic interpretation of the structure-activity relationship (SAR) is done with the help of combined computational calculations i.e. molecular docking and QSAR. Finally, molecular dynamic simulations are performed to get an insight into the binding mode of the most potent derivative with α-amylase from A. oryzae (PDB ID: 7TAA) and human pancreas (PDB ID: 3BAJ).

Prediction of power conversion efficiency of phenothiazine-based dye-sensitized solar cells using Monte Carlo method with index of ideality of correlation

Simplified molecular-input line-entry system (SMILES) notation and inbuilt Monte Carlo algorithm of CORAL software were employed to construct generative and prediction QSPR models for the analysis of the power conversion efficiency (PCE) of 215 phenothiazine derivatives. The dataset was divided into four splits and each split was further divided into four sets. A hybrid descriptor, a combination of SMILES and hydrogen suppressed graph (HSG), was employed to build reliable and robust QSPR models. The role of the index of ideality of correlation (IIC) was also studied in depth. We performed a comparative study to predict PCE using two target functions (TF₁ without IIC and TF₂ with IIC). Eight QSPR models were developed and the models developed with TF₂ was shown robust and reliable. The QSPR model generated from split 4 was considered a leading model. The different statistical benchmarks were computed for the lead model and these were rtraining set2=0.7784; rinvisible training set2=0.7955; rcalibration set2=0.7738; rvalidation set2=0.7506; Qtraining set2=0.7691; Qinvisible training set2=0.7850; Qcalibration set2=0.7501;  Qvalidation set2=0.7085; IIC_{training set} = 0.8590; IIC_{invisible training set} = 0.8297; IIC_{calibration set} = 0.8796; IIC_{validation set} = 0.8293, etc. The promoters of increase and decrease of endpoint PCE were also extracted.

Trifluoromethylated Flavonoid-Based Isoxazoles as Antidiabetic and Anti-Obesity Agents: Synthesis, In Vitro α-Amylase Inhibitory Activity, Molecular Docking and Structure-Activity Relationship Analysis

Diabetes mellitus is a major health problem globally. The management of carbohydrate digestion provides an alternative treatment. Flavonoids constitute the largest group of polyphenolic compounds, produced by plants widely consumed as food and/or used for therapeutic purposes. As such, isoxazoles have attracted the attention of medicinal chemists by dint of their considerable bioactivity. Thus, the main goal of this work was to discover new hybrid molecules with properties of both flavonoids and isoxazoles in order to control carbohydrate digestion. Moreover, the trifluoromethyl group is a key entity in drug development, due to its strong lipophilicity and metabolic stability. Therefore, the present work describes the condensation of a previously synthesized trifluoromethylated flavonol with different aryl nitrile oxides, affording 13 hybrid molecules indicated as trifluoromethylated flavonoid-based isoxazoles. The structures of the obtained compounds were deduced from by ¹H NMR, ¹³C NMR, and HRMS analysis. The 15 newly synthesized compounds inhibited the activity of α-amylase with an efficacy ranging from 64.5 ± 0.7% to 94.7 ± 1.2% at a concentration of 50 μM, and with IC₅₀ values of 12.6 ± 0.2 μM-27.6 ± 1.1 μM. The most effective compounds in terms of efficacy and potency were 3b, 3h, 3j, and 3m. Among the new trifluoromethylated flavonoid-based isoxazoles, the compound 3b was the most effective inhibitor of α-amylase activity (PI = 94.7 ± 1.2% at 50 μM), with a potency (IC₅₀ = 12.6 ± 0.2 μM) similar to that of the positive control acarbose (IC₅₀ = 12.4 ± 0.1 μM). The study of the structure-activity relationship based on the molecular docking analysis showed a low binding energy, a correct mode of interaction in the active pocket of the target enzyme, and an ability to interact with the key residues of glycosidic cleavage (GLU-230 and ASP-206), explaining the inhibitory effects of α-amylase established by several derivatives.

Alpha-amylase as molecular target for treatment of diabetes mellitus: A comprehensive review

The alpha (α)-amylase is a calcium metalloenzyme that aids digestion by breaking down polysaccharide molecules into smaller ones such as glucose and maltose. In addition, the enzyme causes postprandial hyperglycaemia and blood glucose levels to rise. α-Amylase is a well-known therapeutic target for the treatment and maintenance of postprandial blood glucose elevations. Various enzymatic inhibitors, such as acarbose, miglitol and voglibose, have been found to be effective in targeting this enzyme, prompting researchers to express an interest in developing potent alpha-amylase inhibitor molecules. The review mainly focused on designing different derivatives of drug molecules such as benzofuran hydrazone, indole hydrazone, spiroindolone, benzotriazoles, 1,3-diaryl-3-(arylamino) propan-1-one, oxadiazole and flavonoids along with their target-receptor interactions, IC₅₀ values and other biological activities.

The index of ideality of correlation: QSAR studies of hepatitis C virus NS3/4A protease inhibitors using SMILES descriptors

Robust and reliable QSAR models were developed to predict half-maximal inhibitory concentration (IC₅₀) values of hepatitis C virus NS3/4A protease inhibitors from the Monte Carlo technique. 524 HCV NS3/4A protease inhibitors were extracted from the scientific literature to create a reasonably large set. The models were developed using CORAL software by using two target functions namely target function 1 (TF1) without applying the index of ideality of correlation (IIC) and target function 2 (TF2) that uses IIC. The constructed models based on TF2 were statistically more significant and robust than the models based on TF1. The determination coefficients (r²) of training and test sets were 0.86 and 0.88 for the best split based on TF2. The promoters of the increase/decrease of activity were also extracted and interpreted in detail. The model interpretation results explain the role of different structural attributes in predicting the pIC₅₀ values of hepatitis C virus NS3/4A protease inhibitors. Based on the mechanistic model interpretation results, eight new compounds were designed and their pIC₅₀ values were predicted based on the average prediction of ten models.

Quantitative structure activity relationship studies of novel hydrazone derivatives as α-amylase inhibitors with index of ideality of correlation

The present manuscript describes the synthesis, α-amylase inhibition, in silico studies and in-depth quantitative structure-activity relationship (QSAR) of a library of aroyl hydrazones based on benzothiazole skeleton. All the compounds of the developed library are characterized by various spectral techniques. α-Amylase inhibitory potential of all compounds has been explored, where compound 7n exhibits remarkable α-amylase inhibition of 87.5% at 50 µg/mL. Robust QSAR models are made by using the balance of correlation method in CORAL software. The chemical structures at different concentration with optimal descriptors are represented by SMILES. A data set of 66 SMILES of 22 hydrazones at three distinct concentrations are prepared. The significance of the index of ideality of correlation (IIC) with applicability domain (AD) is also studied at depth. A QSAR model with best Rvalidation2 = 0.8587 for split 1 is considered as a leading model. The outliers and promoters of increase and decrease of endpoint are also extracted. The binding modes of the most active compound, that is, 7n in the active site of Aspergillus oryzae α-amylase (PDB ID: 7TAA) are also explored by in silico molecular docking studies. Compound 7n displays high resemblance in binding mode and pose with the standard drug acarbose. Molecular dynamics simulations performed on protein-ligand complex for 100 ns, the protein gets stabilised after 20 ns and remained below 2 Å for the remaining simulation. Moreover, the deviation observed in RMSF during simulation for each amino acid residue with respect to Cα carbon atom is insignificant.

SARS-CoV Mpro inhibitory activity of aromatic disulfide compounds: QSAR model

The main protease (M^pro) of SARS-associated coronavirus (SARS-CoV) had caused a high rate of mortality in 2003. Current events (2019-2020) substantiate important challenges for society due to coronaviruses. Consequently, advancing models for the antiviral activity of therapeutic agents is a necessary component of the fast development of treatment for the virus. An analogy between anti-SARS agents suggested in 2017 and anti-coronavirus COVID-19 agents are quite probable. Quantitative structure-activity relationships for SARS-CoV are developed and proposed in this study. The statistical quality of these models is quite good. Mechanistic interpretation of developed models is based on the statistical and probability quality of molecular alerts extracted from SMILES. The novel, designed structures of molecules able to possess anti-SARS activities are suggested. For the final assessment of the designed molecules inhibitory potential, developed from the obtained QSAR model, molecular docking studies were applied. Results obtained from molecular docking studies were in a good correlation with the results obtained from QSAR modeling.

In silico enhancement of azo dye adsorption affinity for cellulose fibre through mechanistic interpretation under guidance of QSPR models using Monte Carlo method with index of ideality correlation

Azo dyes are a group of chemical moieties joined by azo (-N=N-) group with potential usefulness in different industrial applications. But these dyes are not devoid of hazardous consequence because of poor affinity for the fibre and discharge into the water stream. The chemical aspects of 72 azo dyes towards cellulose fibre in terms of their affinity by QSPR have been explored in the present work. We have employed two approaches, namely balance of correlation without IIC (TF₁) and balance of correlation with IIC (TF₂), to generate 16 QSAR models from 8 splits. The determination coefficient of calibration and validation set was found higher when the QSPR models were developed using the index of ideality correlation (IIC) parameter (TF₂). The model developed with TF₂ for split 3 was considered as a prominent model because the determination coefficient of the validation set was maximum (r ² = 0.9468). The applicability domain (AD) was also analysed based on 'statistical defect', d(A) for a SMILES attribute. The mechanistic interpretation was done by identifying the SMILES attributes responsible for the promoter of endpoint increase and promoter of endpoint decrease. These SMILES attributes were applied to design 15 new dyes with higher affinity for cellulose fibre.

In silico exploration of the fingerprints triggering modulation of glutaminyl cyclase inhibition for the treatment of Alzheimer's disease using SMILES based attributes in Monte Carlo optimization

Alzheimer's disease is the most common neurodegenerative disorder and being a social burden Alzheimer's has become an economic liability on developing countries. With limited understanding regarding the cause of disease, it is commonly identified by extracellular deposit of amyloid β (Aβ) peptides as senile plaques. Pyroglutamated Aβ is identified from the brain of AD patients and constituted the majority of total Aβ present. The formation of Pyroglutamated Aβ could be hindered by the use of Glutaminyl cyclase inhibitors and could efficiently improve the symptoms of Alzheimer's. The literature revealed the competence of quantitative structure activity/property relationship studies in drug discovery. The present work explores the efficiency of Monte Carlo based QSAR modelling studies on a dataset of 125 Glutaminyl cyclase inhibitors with pKi taken as the endpoint for QSAR analysis. The dataset is divided into training, subtraining, calibration and validation sets resulting in the generation of five random splits. The validation is performed in accordance with the Organization of Economic Corporation and Development principles. The values of R², Q², index of ideality of correlation, concordance correlation coefficient, av. rm2 and delta rm2 of calibration set of the best split are found to be 0.9012, 0.8775, 0.9479, 0.9435, 0.8347 and 0.0847, respectively. The structural features responsible for increasing the inhibitory activity are identified. These structural features are added to a base compound from the dataset to design six novel molecules. These new molecules possess improved inhibitory activity as compare to the base compound. The results are further supported by docking studies.Communicated by Vsevolod Makeev.