Chemometric modeling of pharmaceuticals for partitioning between sludge and aqueous phase during the wastewater treatment process.

Computational techniques, such as quantitative structure-property relationships (QSPRs), can play a significant role in exploring the important chemical features essential for the degree of sorption or sludge/water partition coefficient (Kd) towards sewage sludge of wastewater treatment process to evaluate the environmental consequence and risk of pharmaceuticals. The current research work aims to construct a predictive QSPR model for the sorption of 148 diverse active pharmaceutical ingredients (APIs) in sewage sludge during wastewater treatment. For the development of the model, we employed easily computable 2D descriptors as independent variables. The model has been developed following the Organization for Economic Cooperation and Development's (OECD) guidelines. It has undergone internal and external validation using a variety of methodologies, as well as been tested for its applicability domain. A measure of hydrophobicity, i.e., MLOGP2, showed the most promising contribution in modeling the sorption coefficient of APIs. Among other parameters, the number of tertiary aromatic amines, the presence of electronegative atoms like N, O, and Cl, the size of a molecule, the number of aromatic hydroxyl groups, the presence of substituted aromatic nitrogen atoms and alkyl-substituted tertiary carbon atoms were also found to be influential for the regulation of solid water partition coefficient of APIs during the wastewater treatment process. The statistical validity tests performed on the developed partial least squares (PLS) model showed that it is statistically evident, robust, and predictive (R2Train = 0.750, Q2LOO = 0.683, Q2F1 = 0.655, Q2F2 (or R2Test) = 0.651). In addition, the predictivity of the constructed model was further inspected by using the "prediction reliability indicator" tool for 14 external APIs.

Discovery of newer pyrazole derivatives with potential anti-tubercular activity via 3D-QSAR based pharmacophore modelling, virtual screening, molecular docking and molecular dynamics simulation studies.

Tuberculosis is one of the leading causes of death of at least one million people annually. The deadliest infectious disease has caused more than 120 million deaths in humans since 1882. The cell wall structure of Mycobacterium tuberculosis is important for survival in the host environment. InhA is the foremost target for the development of novel anti-tubercular agents. Therefore, we report pharmacophore-based virtual screening (ZINC and ASINEX databases) and molecular docking study (PDB Code: 4TZK) to identify and design potent inhibitors targeting to InhA. A five-point pharmacophore model AADHR_1 (with R2 = 0.97 and Q2 = 0.77) was developed by using 47 compounds with its reported MIC values. Further, to identify and design potent hit molecules based on lead identification and modification, generated hypothesis employed for virtual screening using ZINC and ASINEX databases. Predicted pyrazole derivatives further gauged for drug likeliness and docked against enoyl acyl carrier protein reductase to categorize the essential amino acid interactions to the active site of the enzyme. Structure elucidation of these synthesized compounds was carried out using IR, MS, 1H-NMR and 13C-NMR spectroscopy. Amongst all the synthesized compounds, some of the compounds 5a, 5c, 5d and 5e were found to be potent with their MIC ranging from 2.23 to 4.61 µM. Based on preliminary anti-tubercular activity synthesized potent molecules were further assessed for MDR-TB, XDR-TB and cytotoxic study.

Exploring quantitative structure-property relationship models for environmental fate assessment of petroleum hydrocarbons.

The rate and extent of biodegradation of petroleum hydrocarbons in the different aquatic environments is an important element to address. The major avenue for removing petroleum hydrocarbons from the environment is thought to be biodegradation. The present study involves the development of predictive quantitative structure-property relationship (QSPR) models for the primary biodegradation half-life of petroleum hydrocarbons that may be used to forecast the biodegradation half-life of untested petroleum hydrocarbons within the established models' applicability domain. These models use easily computable two-dimensional (2D) descriptors to investigate important structural characteristics needed for the biodegradation of petroleum hydrocarbons in freshwater (dataset 1), temperate seawater (dataset 2), and arctic seawater (dataset 3). All the developed models follow OECD guidelines. We have used double cross-validation, best subset selection, and partial least squares tools for model development. In addition, the small dataset modeler tool has been successfully used for the dataset with very few compounds (dataset 3 with 17 compounds), where dataset division was not possible. The resultant models are robust, predictive, and mechanistically interpretable based on both internal and external validation metrics (R2 range of 0.605-0.959. Q2(Loo) range of 0.509-0.904, and Q2F1 range of 0.526-0.959). The intelligent consensus predictor tool has been used for the improvement of the prediction quality for test set compounds which provided superior outcomes to those from individual partial least squares models based on several metrics (Q2F1 = 0.808 and Q2F2 = 0.805 for dataset 1 in freshwater). Molecular size and hydrophilic factor for freshwater, frequency of two carbon atoms at topological distance 4 for temperate seawater, and electronegative atom count relative to size for arctic seawater were found to be the most significant descriptors responsible for the regulation of biodegradation half-life of petroleum hydrocarbons.

Fragment-based design of SARS-CoV-2 Mpro inhibitors.

The SARS-CoV-2 virus has been identified as a causative agent for COVID-19 pandemic. About more than 6.3 million fatalities have been attributed to COVID-19 worldwide to date. Finding a viable cure for the illness is urgently needed in light of the present pandemic. The prominence of main protease in the life cycle of virus shapes the main protease as a viable target for design and development of antiviral agents to combat COVID-19. The current study presents the fragment linking strategy to design the novel Mpro inhibitors for COVID-19. A total of 293,451 fragments from diversified libraries have been screened for their binding affinity towards Mpro enzyme. The best 1600 fragment hits were subjected to fragment joining to achieve 100 new molecules using Schrödinger software. The resulting molecules were further screened for their Mpro binding affinity, ADMET, and drug-likeness features. The best 13 molecules were selected, and the first 6 compounds were investigated for their ligand-receptor complex stability through a molecular dynamics study using GROMACS software. The resulting molecules have the potential to be further evaluated for COVID-19 drug discovery.

Simultaneous Estimation of Six Nitrosamine Impurities in Valsartan Using Liquid Chromatographic Method.

BACKGROUND: Nitrosamine impurities are potent carcinogens in animals and probable carcinogens in humans. There is a need for effective analytical methods to detect and identify various nitrosamine impurities, and to develop rapid solutions to ensure the safety and quality of the drugs. OBJECTIVE: A liquid chromatographic method was developed for estimation of six nitrosamine impurities in valsartan. METHODS: The developed method employed: a C18 (250 × 4.6 mm, 5 µm) column as a stationary phase; a combination of acetonitrile, water (pH 3.2 adjusted with formic acid), and methanol with gradient elution as mobile phase; and 228 nm as the detection wavelength. The developed method was validated as per International Conference on Harmonization Q2(R1) guidelines. The method was successfully applied to estimate six nitrosamine impurities in valsartan API (active pharmaceutical ingradient) and formulation (tablets). RESULTS: The method was able to separate each impurity and valsartan with resolved and sharp peaks. Results indicated that the developed method is linear in selected ranges (coefficient of regressions >0.9996), precise (RSD <2%), accurate (recovery in a range of 99.02-100.16%), sensitive (low detection and quantitation limits), and specific for estimation of each impurity in valsartan. Assay results were in agreement with the spiked amount of each impurity. CONCLUSION: The developed method can be applied for simultaneous estimation of six nitrosamine impurities in valsartan raw material, tablets, and fixed dose combination at very low levels. HIGHLIGHTS: Development, validation, and application of a HPLC method for the estimation of six nitrosamine impurities in valsartan API and formulation samples.

Advanced Computational Methodologies Used in the Discovery of New Natural Anticancer Compounds.

Natural chemical compounds have been widely investigated for their programmed necrosis causing characteristics. One of the conventional methods for screening such compounds is the use of concentrated plant extracts without isolation of active moieties for understanding pharmacological activity. For the last two decades, modern medicine has relied mainly on the isolation and purification of one or two complicated active and isomeric compounds. The idea of multi-target drugs has advanced rapidly and impressively from an innovative model when first proposed in the early 2000s to one of the popular trends for drug development in 2021. Alternatively, fragment-based drug discovery is also explored in identifying target-based drug discovery for potent natural anticancer agents which is based on well-defined fragments opposite to use of naturally occurring mixtures. This review summarizes the current key advancements in natural anticancer compounds; computer-assisted/fragment-based structural elucidation and a multi-target approach for the exploration of natural compounds.

The analog of cGAMP, c-di-AMP, activates STING mediated cell death pathway in estrogen-receptor negative breast cancer cells.

Immune adaptor protein like STING/MITA regulate innate immune response and plays a critical role in inflammation in the tumor microenvironment and regulation of metastasis including breast cancer. Chromosomal instability in highly metastatic cells releases fragmented chromosomal parts in the cytoplasm, hence the activation of STING via an increased level of cyclic dinucleotides (cDNs) synthesized by cGMP-AMP synthase (cGAS). Cyclic dinucleotides 2' 3'-cGAMP and it's analog can potentially activate STING mediated pathways leading to nuclear translocation of p65 and IRF-3 and transcription of inflammatory genes. The differential modulation of STING pathway via 2' 3'-cGAMP and its analog and its implication in breast tumorigenesis is still not well explored. In the current study, we demonstrated that c-di-AMP can activate type-1 IFN response in ER negative breast cancer cell lines which correlate with STING expression. c-di-AMP binds to STING and activates downstream IFN pathways in STING positive metastatic MDA-MB-231/MX-1 cells. Prolonged treatment of c-di-AMP induces cell death in STING positive metastatic MDA-MB-231/MX-1 cells mediated by IRF-3. c-di-AMP induces IRF-3 translocation to mitochondria and initiates Caspase-9 mediated cell death and inhibits clonogenicity of triple-negative breast cancer cells. This study suggests that c-di-AMP can activate and modulates STING pathway to induce mitochondrial mediated apoptosis in estrogen-receptor negative breast cancer cells.

Identification of potential Mpro inhibitors for the treatment of COVID-19 by using systematic virtual screening approach.

The Corona virus Disease (COVID-19) is caused because of novel coronavirus (SARS-CoV-2) pathogen detected in China for the first time, and from there it spread across the globe creating a worldwide pandemic of severe respiratory complications. The virus requires structural and non-structural proteins for its multiplication that are produced from polyproteins obtained by translation of its genomic RNA. These polyproteins are converted into structural and non-structural proteins mainly by the main protease (Mpro). A systematic screening of a drug library (having drugs and diagnostic agents which are approved by FDA or other world authorities) and the Asinex BioDesign library was carried out using pharmacophore and sequential conformational precision level filters using the Schrodinger Suite. From the screening of approved drug library, three antiviral agents ritonavir, nelfinavir and saquinavir were predicted to be the most potent Mpro inhibitors. Apart from these pralmorelin, iodixanol and iotrolan were also identified from the systematic screening. As iodixanol and iotrolan carry some limitations, structural modifications in them could lead to stable and safer antiviral agents. Screenings of Asinex BioDesign library resulted in 20 molecules exhibiting promising interactions with the target protein Mpro. They can broadly be categorized into four classes based on the nature of the scaffold, viz. disubstituted pyrazoles, cyclic amides, pyrrolidine-based compounds and miscellaneous derivatives. These could be used as potential molecules or hits for further drug development to obtain clinically useful therapeutic agents for the treatment of COVID-19.

Pharmacophore modeling, molecular docking and molecular dynamics simulation for screening and identifying anti-dengue phytocompounds.

Dengue is a fast spreading mosquito borne viral disease that poses a serious threat to human health. Lack of therapeutic drugs and vaccines signify that more resources need to be explored. Accumulated evidence has suggested that plants offer a vast reservoir for antiviral drug discovery which are safe for human consumption. Plant-based drug discovery is a complex and time-consuming process as plants possess rich repository of chemically diverse compounds. Various in silico methods can make this process simple and economic. We, therefore, performed pharmacophore mapping, molecular docking, molecular dynamics (MD) simulations and ADME (absorption, distribution, metabolism, excretion) prediction to screen potential candidates against dengue. In particular, combined pharmacophore mapping and molecular docking were used to prioritize the potentially active ligands from a ligand library. Biological activities of plant based ligands were predicted using 3D-QSAR pharmacophore modeling. Interaction between proteins, namely, envelope G protein, NS2B/NS3 protease, NS5 methyltransferase, NS1, NS5 polymerase and active plant-based ligands (pIC50 > 5.1) were analyzed using molecular docking. Best docked complex, namely, envelope G protein-mulberroside C, NS2B-NS3 protease-curcumin, NS5 methyltransferase-chebulic acid, NS1-mulberroside A, NS5 methyltransferase-punigluconin and NS5 methyltransferase-chebulic acid were further subjected to MD simulations study to assess the fluctuation and conformational changes during protein-ligand interaction. ADME studies were performed to assess their drug-likeness properties. Collectively, these in silico results helped to identify the potential plant-based hits against the various receptors of dengue virus which can be further validated by bioactivity-based experiments.Communicated by Ramaswamy H. Sarma.

In silico Screening of Natural Compounds as Potential Inhibitors of SARS-CoV-2 Main Protease and Spike RBD: Targets for COVID-19.

Historically, plants have been sought after as bio-factories for the production of diverse chemical compounds that offer a multitude of possibilities to cure diseases. To combat the current pandemic coronavirus disease 2019 (COVID-19), plant-based natural compounds are explored for their potential to inhibit the SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2), the cause of COVID-19. The present study is aimed at the investigation of antiviral action of several groups of phytoconstituents against SARS-CoV-2 using a molecular docking approach to inhibit Main Protease (Mpro) (PDB code: 6LU7) and spike (S) glycoprotein receptor binding domain (RBD) to ACE2 (PDB code: 6M0J) of SARS-CoV-2. For binding affinity evaluation, the docking scores were calculated using the Extra Precision (XP) protocol of the Glide docking module of Maestro. CovDock was also used to investigate covalent docking. The OPLS3e force field was used in simulations. The docking score was calculated by preferring the conformation of the ligand that has the lowest binding free energy (best pose). The results are indicative of better potential of solanine, acetoside, and rutin, as Mpro and spike glycoprotein RBD dual inhibitors. Acetoside and curcumin were found to inhibit Mpro covalently. Curcumin also possessed all the physicochemical and pharmacokinetic parameters in the range. Thus, phytochemicals like solanine, acetoside, rutin, and curcumin hold potential to be developed as treatment options against COVID-19.

A decennary update on applications of metal nanoparticles (MNPs) in the synthesis of nitrogen- and oxygen-containing heterocyclic scaffolds.

Heterocycles have been found to be of much importance as several nitrogen- and oxygen-containing heterocycle compounds exist amongst the various USFDA-approved drugs. Because of the advancement of nanotechnology, nanocatalysis has found abundant applications in the synthesis of heterocyclic compounds. Numerous nanoparticles (NPs) have been utilized for several organic transformations, which led us to make dedicated efforts for the complete coverage of applications of metal nanoparticles (MNPs) in the synthesis of heterocyclic scaffolds reported from 2010 to 2019. Our emphasize during the coverage of catalyzed reactions of the various MNPs such as Ag, Au, Co, Cu, Fe, Ni, Pd, Pt, Rh, Ru, Si, Ti, and Zn has not only been on nanoparticles catalyzed synthetic transformations for the synthesis of heterocyclic scaffolds, but also provide an inherent framework for the reader to select a suitable catalytic system of interest for the synthesis of desired heterocyclic scaffold.

Structure-based identification of novel sirtuin inhibitors against triple negative breast cancer: An in silico and in vitro study.

Triple-negative breast cancer (TNBC) is an aggressive disease exemplified by a poor prognosis, greater degrees of relapse, the absence of hormonal receptors for coherent utilization of targeted therapy, poor response to currently available therapeutics and development of chemoresistance. Aberrant activity of sirtuins (SIRTs) has strong implications in the metastatic and oncogenic progression of TNBC. Synthetic SIRT inhibitors are effective, however, they have shown adverse side effects emphasizing the need for plant-derived inhibitors (PDIs). In the current study, we identified potential plant-derived sirtuin inhibitors using in silico approach i.e. molecular docking, ADMET and molecular dynamics simulations (MD). Docking studies revealed that Sulforaphane, Kaempferol and Apigenin exhibits the highest docking scores against SIRT1 & 5, 3 and 6 respectively. ADMET analysis of above hits demonstrated drug-like profile. MD of prioritized SIRTs-PDIs complexes displayed stability with insignificant deviations throughout the trajectory. Furthermore, we determined the effect of our prioritized molecules on cellular viability, global activity as well as protein expression of sirtuins and stemness of TNBC cells utilizing in vitro techniques. Our in vitro findings complements our in silico results. Collectively, these findings provide a better insight into the structural basis of sirtuin inhibition and can facilitate drug design process for TNBC management.

Structure-based design, synthesis and biological evaluation of a newer series of pyrazolo[1,5-a]pyrimidine analogues as potential anti-tubercular agents.

In-depth study of structure-based drug designing can provide vital leads for the development of novel, clinically active molecules. In this present study, twenty six novel pyrazolo[1,5-a]pyrimidine analogues (6a-6z) were designed using molecular docking studies. The designed molecules were synthesized in good yields. Structural elucidation of the synthesized molecules was carried out using IR, MS, 1H NMR and 13C NMR spectroscopy. All the synthesized compounds were evaluated for their in-vitro anti-tubercular activity against H37Rv strain by Alamar Blue assay method. Most of the synthesized compounds displayed potent anti-tubercular activities. Amongst all the tested compounds 6p, 6g, 6n and 6h exhibited promising anti-tubercular activity. Further, these potent compounds were gauged for MDR-TB, XDR-TB and cytotoxic study. None of these compounds exhibited potent cytotoxicity. Stability of protein ligand complex was further evaluated by molecular dynamics simulation for 10 ns. All these results indicate that the synthesized compounds could be potential leads for further development of new potent anti-tubercular agents.

Structure based virtual screening, 3D-QSAR, molecular dynamics and ADMET studies for selection of natural inhibitors against structural and non-structural targets of Chikungunya.

The transmission of mosquito-borne Chikungunya virus (CHIKV) has large epidemics worldwide. Till date, there are neither anti-viral drugs nor vaccines available for the treatment of Chikungunya. Accumulated evidences suggest that some natural compounds i.e., Epigallocatechin gallate, Harringtonine, Apigenin, Chrysin, Silybin, etc. have the capability to inhibit CHIKV replication in vitro. Natural compounds are known to possess less or no side effects. Therefore, natural compound in its purified or crude extracts form could be the preeminent and safe mode of therapies for Chikungunya. Wet lab screening and identification of natural compounds against Chikungunya targets is a time consuming and expensive exercise. In the present study, we used in silico techniques like receptor-ligand docking, Molecular dynamic (MD), Three Dimensional Quantitative Structure Activity Relation (3D-QSAR) and ADME properties to screen out potential compounds. Aim of the study is to identify potential lead/s from natural sources using in silico techniques that can be developed as a drug like molecule against Chikungunya infection and replication. Three softwares were used for molecular docking studies. Potential ligands selected by docking studies were subsequently subjected 3D-QSAR studies to predict biological activity. Based on docking scores and pIC50 value, potential anti-Chikungunya compounds were identified. Best docked receptor-ligands were also subjected to MD for more accurate estimation. Lipinski's rule and ADME studies of the identified compounds were also studied to assess their drug likeness properties. Results of in silico findings, led to identification of few best fit compounds of natural origin against targets of Chikungunya virus which may lead to discovery of new drugs for Chikungunya. Communicated by Ramaswamy H. Sarma.

Molecular docking, QSAR and ADMET based mining of natural compounds against prime targets of HIV.

AIDS is one of the multifaceted diseases and this underlying complexity hampers its complete cure. The toxicity of existing drugs and emergence of multidrug-resistant virus makes the treatment worse. Development of effective, safe and low-cost anti-HIV drugs is among the top global priority. Exploration of natural resources may give ray of hope to develop new anti-HIV leads. Among the various therapeutic targets for HIV treatment, reverse transcriptase, protease, integrase, GP120, and ribonuclease are the prime focus. In the present study, we predicted potential plant-derived natural molecules for HIV treatment using computational approach, i.e. molecular docking, quantitative structure activity relationship (QSAR), and ADMET studies. Receptor-ligand binding studies were performed using three different software for precise prediction - Discovery studio 4.0, Schrodinger and Molegrow virtual docker. Docking scores revealed that Mulberrosides, Anolignans, Curcumin and Chebulic acid are promising candidates that bind with multi targets of HIV, while Neo-andrographolide, Nimbolide and Punigluconin were target-specific candidates. Subsequently, QSAR was performed using biologically proved compounds which predicted the biological activity of compounds. We identified Anolignans, Curcumin, Mulberrosides, Chebulic acid and Neo-andrographolide as potential natural molecules for HIV treatment from results of molecular docking and 3D-QSAR. In silico ADMET studies showed drug-likeness of these lead molecules. Structure similarities of identified lead molecules were compared with identified marketed drugs by superimposing both the molecules. Using in silico studies, we have identified few best fit molecules of natural origin against identified targets which may give new drugs to combat HIV infection after wet lab validation.

Identification of some novel pyrazolo[1,5-a]pyrimidine derivatives as InhA inhibitors through pharmacophore-based virtual screening and molecular docking.

The InhA inhibitors play key role in mycolic acid synthesis by preventing the fatty acid biosynthesis pathway. In this present article, Pharmacophore modelling and molecular docking study followed by in silico virtual screening could be considered as effective strategy to identify newer enoyl-ACP reductase inhibitors. Pyrrolidine carboxamide derivatives were opted to generate pharmacophore models using HypoGen algorithm in Discovery studio 2.1. Further it was employed to screen Zinc and Minimaybridge databases to identify and design newer potent hit molecules. The retrieved newer hits were further evaluated for their drug likeliness and docked against enoyl acyl carrier protein reductase. Here, novel pyrazolo[1,5-a]pyrimidine analogues were designed and synthesized with good yields. Structural elucidation of synthesized final molecules was perform through IR, MASS, 1H-NMR, 13C-NMR spectroscopy and further tested for its in vitro anti-tubercular activity against H37Rv strain using Microplate Alamar blue assay (MABA) method. Most of the synthesized compounds displayed strong anti-tubercular activities. Further, these potent compounds were gauged for MDR-TB, XDR-TB and cytotoxic study.

Rational Discovery of Novel Squalene Synthase Inhibitors through Pharmacophore Modelling.

INTRODUCTION: In the present research work, a pharmacophore based virtual screening was performed using Discovery Studio 2.1 for the discovery of some novel molecules as inhibitors of Squalene Synthase Enzyme, a key enzyme in cholesterol biosynthetic pathway. METHODS: A quantitative pharmacophore HypoGen was generated and the best HypoGen had two ring aromatic and one hydrogen bond acceptor lipid features. The best HypoGen showed a very good correlation coefficient (r = 0.901) with satisfactory cost analysis. Furthermore, the HypoGen was validated externally by predicting the activity of test set. The developed model was found to be predictive as it showed low error of prediction for test set molecules. The developed model was used as a search query for virtually screening two chemical databases: sample database from catalyst and minimaybridge. RESULTS AND DISCUSSION: The best hit with good fit value and low predicted activity was further modified to design novel drug-like molecules, which were able to bind to Squalene synthase enzyme active site. CONCLUSION: The best scoring molecule, compound 67 showed 53% inhibition of the human Squalene synthase enzyme, isolated from the cell lysates of Human Hepatoma Cell Line, at a dose of 10 mcg with an IC50 value of 9.43 µm.

Structure-based design, synthesis and evaluation of 2,4-diaminopyrimidine derivatives as novel caspase-1 inhibitors.

Interleukin-1ß converting enzyme contributes in various inflammatory and autoimmune diseases by maturing pro-inflammatory cytokines IL-1ß, IL-18 and IL-33. Therefore, inhibition caspase-1 may provide a potential therapeutic strategy for the treatment of chronic inflammatory diseases. Here we have reported structure-based design, synthesis and biological evaluation of 2,4-diaminopyrimidine derivatives (6a-6w) as potential caspase-1 inhibitors. Six compounds 6m, 6n, 6o, 6p, 6q and 6r showed significant enzymatic inhibition with IC50 ranging from 0.022 to 0.078 µM. These compounds also displayed excellent cellular potency at sub-micromolar concentration. Moreover, molecular docking studies provided the useful binding insights specific for caspase-1 inhibition. All these results indicated that compounds 6m, 6n and 6o could be potential leads for the development of newer caspase-1 inhibitors as anti-inflammatory agents.

Rational approach to identify newer caspase-1 inhibitors using pharmacophore based virtual screening, docking and molecular dynamic simulation studies.

Caspase-1 is a key endoprotease responsible for the post-translational processing of pro-inflammatory cytokines IL-1ß, 18 & 33. Excessive secretion of IL-1ß leads to numerous inflammatory and autoimmune diseases. Thus caspase-1 inhibition would be considered as an important therapeutic strategy for development of newer anti-inflammatory agents. Here we have employed an integrated virtual screening by combining pharmacophore mapping and docking to identify small molecules as caspase-1 inhibitors. The ligand based 3D pharmacophore model was generated having the essential structural features of (HBA, HY & RA) using a data set of 27 compounds. A validated pharmacophore hypothesis (Hypo 1) was used to screen ZINC and Minimaybridge chemical databases. The retrieved virtual hits were filtered by ADMET properties and molecular docking analysis. Subsequently, the cross-docking study was also carried out using crystal structure of caspase-1, 3, 7 and 8 to identify the key residual interaction for specific caspase-1 inhibition. Finally, the best mapped and top scored (ZINC00885612, ZINC72003647, BTB04175 and BTB04410) molecules were subjected to molecular dynamics simulation for accessing the dynamic structure of protein after ligand binding. This study identifies the most promising hits, which can be leads for the development of novel caspase-1 inhibitors as anti-inflammatory agents.

Thiazole: A Review on Chemistry, Synthesis and Therapeutic Importance of its Derivatives.

Thiazole, a unique heterocycle containing sulphur and nitrogen atoms, occupies an important place in medicinal chemistry. It is an essential core scaffold present in many natural (Vitamin B1- Thiamine) and synthetic medicinally important compounds. The versatility of thiazole nucleus demonstrated by the fact that it is an essential part of penicillin nucleus and some of its derivatives which have shown antimicrobial (sulfazole), antiretroviral (ritonavir), antifungal (abafungin), antihistaminic and antithyroid activities. The synthetic importance of thiazole derivatives, its reduced forms and condensed derivatives have been increased much by their recent applications as anticancer (tiazofurin), anthelmintic, vulcanising accelerators (mercaptobenzothiazole) and photographic sensitizers. Thiazole chemistry has developed steadily after the pioneering work of Hofmann and Hantsch. Bogert and co-workers made significant contribution to expand this field. Mills established the importance of thiazole ring in cyanine dyes which is used as photographic sensitizer. Benzothiazole, a fused derivative of thiazole have also proved its commercial value. Present review describes chemical and biological importance of thiazole and its condensed derivatives with an emphasis on recent developments.