Compound ID Research Articles

Synthesis, Pharmacological Study of 3,5-Di- Substituted Isoxazole Derivatives as Anticancer Drug Against Breast Cancer Cell Line Followed by Computational Study

Objective: Cancer has remained a challenge to the healthcare system due to changes in eating habits and lifestyle, tremendous side effects of chemotherapy, and resistance to existing treatment due to mutations, which creates difficulty in identifying specific targets. Chemistry and Methodology: In this study, equimolecular amounts of reagents were used to synthesize substituted isoxazoles from alpha-beta unsaturated intermediates. Result: Compounds were collected in varying amounts of yield. Spectroscopic data supports the formation of compounds. Compound Id shows GI50 of 46.3 μg/mL against MDA-MB-231. Conclusion: The effective synthesis of novel derivatives has opened up exciting new avenues for medicinal research; one of these compounds has moderate anticancer properties.

Targeting small druggable compounds against 3RZE histamine H1 receptor as potential of anti-allergic drug applying molecular modeling approach

BackgroundAllergic disorders, prevalent global health concerns, afflict a substantial portion of the world’s population. These maladies result from an exaggerated immune system response to ordinarily innocuous substances, such as pollen, dust mites, and specific dietary components. Clinical manifestations of this heightened immune response include itching, swelling, and respiratory impairment, often accompanied by releasing mediators like histamine. The pathophysiological mechanisms of allergy disorders are intricate, arising from a complex interplay between genetic and environmental factors. While clinical presentations may vary, all allergy conditions share a common foundation in the dysregulated immune response to allergens.ResultThe current aim of this study was to identify innovative anti-allergic agents capable of inhibiting histamine and effectively mitigating allergic reactions by utilizing the computer-aided drug design approach by discovery studio (DS) 2022 v 23.1.1 package. The overarching aim was identifying potential drug candidates targeting the active site within the histamine H1 receptor complex; therefore, a collection of 4000 small druggable compounds was curated from ZINC, PubChem, and DRUG BANK databases sources. Four compounds appeared as promising candidates after assessing docking scores and binding energies. Notably, Compound ID 34154, recognized as tymazoline, showed the highest affinity for the H1 receptor of 3RZE, suggesting it may be the most promising choice for more research. Further chemoinformatic and ADMET (absorption, distribution, metabolism, excretion, and toxicity) analyses were conducted to assess the drug-like qualities of this chosen molecule. In addition, bioisosteric substitution techniques were employed to enhance tymazoline’s ADMET characteristics.ConclusionTymazoline shows strong binding affinity with 3RZE and verified all the drug-likeness criteria to inhibit the allergic disorders. Furthermore, molecular dynamics (MD) studies corroborated tymazoline’s potential as an anti-allergic agent, demonstrating contact between the ligand and the receptor that is well defined and stable.

Discovery of Pesticide Candidates from Natural Plant Products: Semisynthesis and Characterization of Andrographolide-Based Esters and Study of Their Pesticidal Properties and Toxicology.

To explore the use of nonfood plant-derived secondary metabolites for plant protection, a series of ester derivatives for controlling the major migratory agricultural pests were obtained by structural modification of andrographolide, a labdane diterpenoid isolated from Andrographis paniculata. Compound Id showed good insecticidal activity against the fall armyworm Spodoptera frugiperda Smith. Compounds IIa (LC50: 0.382 mg/mL) and IIIc (LC50: 0.563 mg/mL), the acaricidal activities of which were, respectively, 13.1 and 8.9 times that of andrographolide (LC50: 4.996 mg/mL), exhibited strong acaricidal and control effects against Tetranychus cinnabarinus Boisduval. Against Aphis citricola Van der Goot, compounds IIIc and IVb displayed 3.9- and 3.7-fold pronounced aphicidal activity of andrographolide. Effects of compound Id on three protective enzymes (superoxide dismutase, peroxidase, and catalase) of S. frugiperda were also observed. The obvious differences of epidermal cuticle structures of mites treated with compound IIa were determined by scanning electron microscopy. Structure-activity relationships indicated that 14-ester derivatives of andrographolide showed potential insecticidal/acaricidal activities and can be further utilized as lead compounds.

Application of temperature-dependent and steered molecular dynamics simulation to screen anti-dengue compounds against Marburg virus

Marburg virus infections are extremely fatal with a fatality range of 23% to 90%, therefore there is an urgent requirement to design and develop efficient therapeutic molecules. Here, a comprehensive temperature-dependent molecular dynamics (MD) simulation method was implemented to identify the potential molecule from the anti-dengue compound library that can inhibit the function of the VP24 protein of Marburg. Virtual high throughput screening identified five effective binders of VP24 after screening 484 anti-dengue compounds. These compounds were treated in MD simulation at four different temperatures: 300, 340, 380, and 420 K. Higher temperatures showed dissociation of hit compounds from the protein. Further, triplicates of 100 ns MD simulation were conducted which showed that compounds ID = 118717693, and ID = 5361 showed strong stability with the protein molecule. These compounds were further validated using Δ G binding free energies and they showed: −30.38 kcal/mol, and −67.83 kcal/mol binding free energies, respectively. Later, these two compounds were used in steered MD simulation to detect its dissociation. Compound ID = 5361 showed the maximum pulling force of 199.02 kcal/mol/nm to dissociate the protein-ligand complex while ID = 118717693 had a pulling force of 101.11 kcal/mol/nm, respectively. This ligand highest number of hydrogen bonds with varying occupancies at 89.93%, 69.80%, 57.93%, 52.33%, and 50.63%. This study showed that ID = 5361 can bind with the VP24 strongly and has the potential to inhibit its function which can be validated in the in-vitro experiment. Communicated by Ramaswamy H. Sarma

Assessing the inhibitory potential of anti-dengue compounds against Japanese encephalitis virus RNA dependent RNA polymerase: an in silico study

Japanese encephalitis (JE), a neurological infection of severe nature, is caused by the Japanese encephalitis virus (JEV) and is transmitted by the mosquito vector. The polymerase domain of Non-structural 5 (NS5), which is also referred to as RdRp (RNA-dependent RNA polymerase), is considered a potential therapeutic target for JEV. The present study employed molecular dynamics modelling and high-throughput virtual screening to evaluate the possible antiviral activity of anti-dengue drugs against JEV RdRp. Furthermore, a ranking was performed utilising the MM/GBSA analysis to identify the three most promising compounds. Compound ID 57409246 exhibited the highest binding affinity with the protein, as evidenced by its minimum binding free energy of −72.96 kcal/mole. In contrast, the other two compounds had minimum binding free energies of −67.57 and −59.19 kcal/mole, respectively. Upon conducting a 100 nanosecond molecular dynamics simulation to confirm the binding of the chemical complexes, it was observed that the three hits, namely 57409246, 70683874, and 44577154, exhibited a consistent and stable RMSD. Subsequently, the binding strength of the trajectory was confirmed through MM/GBSA analysis. The compounds 70683874 and 57409246 exhibited the lowest binding free energies, which were −97.58 kcal/mol and −96.38 kcal/mol, respectively. The binding free energy (ΔG Bind) values for the native ligand ATP and molecule 44577154 were −65.64 kcal/mol and −69.44 kcal/mol, respectively. Overall, compared to the native ligand ATP, all three compounds exhibited higher binding affinity. The study proposes three anti-dengue molecules as a potential remedy for JE, which can be confirmed through in vitro and in vivo investigations. Communicated by Ramaswamy H. Sarma

QHTSWaterfall: 3-dimensional visualization software for quantitative high-throughput screening (qHTS) data

High throughput screening (HTS) is widely used in drug discovery and chemical biology to identify and characterize agents having pharmacologic properties often by evaluation of large chemical libraries. Standard HTS data can be simply plotted as an x–y graph usually represented as % activity of a compound tested at a single concentration vs compound ID, whereas quantitative HTS (qHTS) data incorporates a third axis represented by concentration. By virtue of the additional data points arising from the compound titration and the incorporation of logistic fit parameters that define the concentration–response curve, such as EC50 and Hill slope, qHTS data has been challenging to display on a single graph. Here we provide a flexible solution to the rapid plotting of complete qHTS data sets to produce a 3-axis plot we call qHTS Waterfall Plots. The software described here can be generally applied to any 3-axis dataset and is available as both an R package and an R shiny application.Graphical

Anti Mtb Medicinal Plants Database (AMMPDB): A curated database of Indian anti-tubercular medicinal plants

The utilization of medicinal plants for their therapeutic properties has long been a key component of Indian culture. Unique medicinal characteristics can be found in the phytochemicals that are extracted from these plants. Globally, tuberculosis (TB) burden and management are challenged due to the emergence of new resistant strains of Mycobacterium tuberculosis (Mtb). This highlights the importance of new drug molecules from diverse sources as well as their innovative management options. In this context, the present study formulated an Anti Mtb medicinal plant database (AMMPDB Ver. 1.1), a manually curated database of native Indian medicinal plants that reported anti-tubercular (anti-TB) activities and their potential therapeutic phytochemicals. This is the first-ever freely accessible digital repository. The current version of the database provides users, with information regarding 118 native Indian anti-tubercular medicinal plants and their 3374 phytochemicals. The database provides the following information: Taxonomical ID, botanical description, vernacular names, conservation status, geographical distribution maps, IC-50 value, phytochemical details which include - name, Compound ID, Synonyms, location in plant part, 2D, 3D structures (as per the availability), and their medicinal uses reported in the literature. The tools section of the database is equipped with sequentially catalogued and hyperlinked open-access tools utilized for computational drug designing. A case study has been incorporated under the contributors section to validate the tools section and the phytochemicals of the database. AMMPDB Ver 1.1 will be serviceable to research in computational drug designing and discovery with effectiveness and ease.Database URL: https://www.ammpdb.com/

MLAGO: machine learning-aided global optimization for Michaelis constant estimation of kinetic modeling

BackgroundKinetic modeling is a powerful tool for understanding the dynamic behavior of biochemical systems. For kinetic modeling, determination of a number of kinetic parameters, such as the Michaelis constant (Km), is necessary, and global optimization algorithms have long been used for parameter estimation. However, the conventional global optimization approach has three problems: (i) It is computationally demanding. (ii) It often yields unrealistic parameter values because it simply seeks a better model fitting to experimentally observed behaviors. (iii) It has difficulty in identifying a unique solution because multiple parameter sets can allow a kinetic model to fit experimental data equally well (the non-identifiability problem).ResultsTo solve these problems, we propose the Machine Learning-Aided Global Optimization (MLAGO) method for Km estimation of kinetic modeling. First, we use a machine learning-based Km predictor based only on three factors: EC number, KEGG Compound ID, and Organism ID, then conduct a constrained global optimization-based parameter estimation by using the machine learning-predicted Km values as the reference values. The machine learning model achieved relatively good prediction scores: RMSE = 0.795 and R2 = 0.536, making the subsequent global optimization easy and practical. The MLAGO approach reduced the error between simulation and experimental data while keeping Km values close to the machine learning-predicted values. As a result, the MLAGO approach successfully estimated Km values with less computational cost than the conventional method. Moreover, the MLAGO approach uniquely estimated Km values, which were close to the measured values.ConclusionsMLAGO overcomes the major problems in parameter estimation, accelerates kinetic modeling, and thus ultimately leads to better understanding of complex cellular systems. The web application for our machine learning-based Km predictor is accessible at https://sites.google.com/view/kazuhiro-maeda/software-tools-web-apps, which helps modelers perform MLAGO on their own parameter estimation tasks.

QPoweredCompound2DeNovoDrugPropMax – a novel programmatic tool incorporating deep learning and in silico methods for automated in silico bio-activity discovery for any compound of interest

Network data is composed of nodes and edges. Successful application of machine learning/deep learning algorithms on network data to make node classification and link prediction have been shown in the area of social networks through which highly customized suggestions are offered to social network users. Similarly one can attempt the use of machine learning/deep learning algorithms on biological network data to generate predictions of scientific usefulness. In the presented work, compound-drug target interaction network data set from bindingDB has been used to train deep learning neural network and a multi class classification has been implemented to classify PubChem compound queried by the user into class labels of PBD IDs. This way target interaction prediction for PubChem compounds is carried out using deep learning. The user is required to input the PubChem Compound ID (CID) of the compound the user wishes to gain information about its predicted biological activity and the tool outputs the RCSB PDB IDs of the predicted drug target interaction for the input CID. Further the tool also optimizes the compound of interest of the user toward drug likeness properties through a deep learning based structure optimization protocol. The tool also incorporates a feature to perform automated In Silico modelling to find the interaction between the compounds and the predicted drug targets to uncover their protein-ligand interaction profiles. The program is hosted, supported and maintained at the following GitHub repository. https://github.com/bengeof/Compound2DeNovoDrugPropMax. Anticipating the use of quantum computing and quantum machine learning in drug discovery we use the Penny-lane interface to quantum hardware to turn classical Keras layers used in our machine/deep learning models into a quantum layer and introduce quantum layers into classical models to produce a quantum-classical machine/deep learning hybrid model of our tool and the code corresponding to the same is provided below. https://github.com/bengeof/QPoweredCompound2DeNovoDrugPropMax. HIGHLIGHTS Deep learning based network pharmacology approach to predict the bio-activity of compounds. Further optimization of the compound toward drug like properties using deep learning techniques. Automated in silico modeling and interaction profiling of deep learning predicted target protein-ligand interaction. Communicated by Ramaswamy H. Sarma

Identification of novel anti‐Alzheimer’s drugs through inhibition of LRP‐DKK interaction: A computational approach using high throughput virtual screening and molecular dynamics studies

AbstractBackgroundActivation of WNT signalling pathway was involved in a neuroprotective mechanism against amyloid beta toxicity (1). Inhibition of this pathway is associated with GSK‐3 beta activation, tau hyperphosphorylation, neuronal apoptosis (1), (2) and is implicated in Alzheimer’s disease (1). DKK‐1 competes with Wnt for the binding to LRP5/6 receptor (3) and disrupts the Wnt‐induced Fzd‐Wnt‐LRP6 complex (4) and thus antagonizes the neuro‐protective effect of WNT. In this study, we have targeted the DKK‐LRP interaction through virtual screening the first time to develop novel anti‐Alzheimer’s agent.MethodBased upon crystal structure information and protein validation using Ramachandran Plots, a crystal structure (PDB: 3S8V) was selected for further works. In this study, we have targeted the surface of LRP 5/6, which is interacting with DKK and grid was generated on LRP. The virtual screening of Asinex database library (N=19642) was done against this grid. Molecules were selected on the basis of good dock score and binding free energy calculation using MMGBSA in Schrodinger GLIDE (5)(6). The protein ligand complex structure stability were also evaluated by molecular dynamic simulation study (7). ADMET profile of the screened ligands were evaluated using Quick prop module of Schrodinger.ResultAfter running the virtual screening protocol (HTVS: SP: XP), 14 compounds were screened out, which showed significant binding top the DKK1 binding interface of LRP. These compounds were further evaluated on basis of docking score and MMGBSA. On the basis of After then on the basis of ADME profile selected 2 compound id ZINC000100138828 and ZINC000247940500 for further molecular dynamic simulation study which were shown the compound ZINC000100138828 had an avg. RMSD of ∼4.0Å, also the RMSF is 2.4 Å for overall protein side chain residue was reduced with reference to the apo form. It is displays rich interaction profile and strength with core binding residues (A: Pro833, B: Tyr706, B: Glu708, B: Arg751 and B: Ile681).ConclusionZINC000100138828 is a potent binder to the DKK1 binding surface on LRP5/6. It needs further in‐vitro and preclinical validation as a potential anti‐Alzheimer’s agent.

Molecular docking analysis of selected pyrimidine derivatives with human cyclin-dependent kinase 2.

A series of pyrimidine were synthesized, characterized and evaluated for their antioxidant properties using the human cyclin-dependent kinase-2 protein model. Data shows that the pyrimidine derivatives (compound ID 4G) with para fluoro groups substitution at phenyl ring attached to the 4th position (IC50: 98.5µg/ml), compound 4B bearing hydroxy group at para position of phenyl ring (IC50: 117.8 µg/ml) have significant antioxidant activity. Docking data infer that compounds 4c, 4a, 4h and 4b possess binding energy (-7.9, -7.7, -7.5 and -7.4 kcal.mol-1) with 1HCK (PDB ID) receptor.

Binding profile of protein–ligand inhibitor complex and structure based design of new potent compounds via computer-aided virtual screening

BackgroundMycobacterium tuberculosis protein target (DNA gyrase) is a type II topoisomerase target present in all bacteria. The enzyme comprises of two subunits A and B. DNA binding domain is located in the subunits A while the catalysis and cleavage of two DNA strands occur in the subunits B using ATP hydrolysis. This enzyme has been reported to emerge in extensively drug resistant tuberculosis. Therefore this research aimed to design new potent compounds against the target and establish the analysis of protein–ligand binding interaction between the target and novel quinoline analogues via the application of in silicovirtual screening to predict the inhibition binding affinities of the analogues. ResultThe docking results revealed that compound ID 17 with efficient inhibition activity has a noticeable binding affinity of −18.8 kcal/mol. Hence compound 17 was designated as the reference template to design novel fourteen compounds with higher binding affinities as a promising compounds. ConclusionDesigned compound 17i, 17j and 17n with lead binding affinities among the designed compounds were observed with the most perceptible binding affinity which ranges from (−21.2 to −26.8) kcal/mol compared to low binding affinity (-5.8 kcal/mol) computed for ethambutol.

MedFused: A framework to discover the relationships between drug chemical functional group impacts and side effects

It is a well-known fact that there are often side effects to the long-term use of certain medications. These side effects can vary from mild dizziness to, at its most serious, death. The main factors that cause these side effects are the chemical composition, the mode of treatment, and the dose. The dynamics that govern the reaction of a drug heavily depend on its structural composition. The structural composition of a drug is defined by the structural arrangement of the corresponding basic chemical functional groups. Hence, it is essential to investigate the effect of chemical functional groups on the side effects to synthesize drugs with minimal side effects. To support this process, we developed a framework named MedFused (Medical Functional Group Side Effects Database), which is composed of drugs (International Union of Pure and Applied Chemistry: IUPAC nomenclature), functional groups, and the side effects along with other valuable information such as STITCH (search tool for interactions of chemicals) compound ID, and the Unified Medical Language System (UMLS) concept ID. We develop a web framework that functions on the MedFused system database on top of the Django web framework. Our web server supports functionalities such as exploring the database and descriptive graph tools, which provide additional exploration capabilities to the framework. These descriptive tools include histograms, pie charts, and association charts, which further explore the system. Above these basic tools, MedFused includes functionality to discover the drug's “chemical functional group” impact on “side effects”. The method conducts an association rule analysis on the relationships by considering the MedFused database as a collection of transactions. A specific transaction has a list of the functional groups of a drug and one side effect. Hence, a drug that has more than one side effect forms multiple transactions. Next, we generate a binary feature matrix based on the transactions and introduce a pruning mechanism to consider only the potential functional groups and side effects based on their support (frequencies), subjected to a predefined threshold (which can be changed accordingly). As the current version of the MedFused database has a limited number of side effects (hence low support), we restricted the analysis to identify the functional groups which have the most potential of causing a particular side effect, based on a confidence value of 1. Our framework can be further extended with more functions and tools as it supports the model view controller (MVC) architecture, which is inherited from the Django Python web framework.

Screening of Prospective Plant Compounds as H1R and CL1R Inhibitors and Its Antiallergic Efficacy through Molecular Docking Approach

Allergens have the ability to enter the body and cause illness. Leukotriene is the widespread allergen which could stimulate mast cells to discharge histamine which causes allergy symptoms. An effective strategy for treating leukotriene-induced allergy is to find the inhibitors of leukotriene or histamine activity from phytochemicals. For this purpose, a library of 8,500 phytochemicals was generated using MOE software. The structures of histamine-1 receptor and cysteinyl leukotriene receptor-1 were predicted by the homology modeling method through the SWISS model. The phytochemicals were docked with predicted structures of histamine-1 and cysteinyl leukotriene receptor-1 in MOE software to determine the binding affinity of the phytochemicals against the targets. Moreover, chemoinformatics properties and ADMET of phytochemicals were assessed to find the drug likeness behavior of compounds. Compound ID 10054216 has the lowest S -score value for H-1 receptor that is -18.9186 kcal/mol which is lower than the value of standard -15.167 kcal/mol. The other compounds 393471, 71448939, 10722577, and 442614 also showed good S -score values than the standard. Moreover, compound ID 11843082 has the lowest S -score value for CL1R that is -15.481 kcal/mol which is lower than the value of standard -12.453 kcal/mol. The other compounds 72284, 5282102, 66559251, and 102506430 also showed good S -score values than the standard. In this research article, we performed molecular docking to find the best inhibitors against H1R and CL1R and their antiallergic efficacy. This in silico knowledge will be helpful in near future for the design of novel, safe, and less costing H-1 receptor and CL1R inhibitors with the aim to improve human life quality.

Identification of potential drug target in malarial disease using molecular docking analysis.

Malaria caused by genus Plasmodium, is a parasite which is the main health issue for humans and about half of the population were suffered. An every year, approximately 1.2–2.7 million people died due to malaria globally. Therefore to prevent the spreading of malaria from the glob novel active drugs with specific activities are necessary. The present study aimed to identify novel drug molecule together with the bioinformatic tools for the development of active malarial drugs. As the search for latest anti malarial compound was developed, this work determined six active blends from various drug databases which possess drug-like characteristics and presents a significant anti malarial actions in in-silico level. Compound ID 300238, 889, 76569, 87324, 45678, and Z185397112are a few of the ligands were got from the Toss lab, Maybridge, Cambridge, Life chem, Bitter, and Examine drug databases and docked against hexokinase 1 protein (PDB: 1CZA) with high throughput practical screening (HTVS) using Glide v6.6. Amid the 6 compounds, compound no: 300238 from Toss lab has the greatest docking score of −9.889 kcal/mol targeting 1CZA protein. The active sites of Hexokinase I of protein were determine by using superimposition of the destination and template structure showed similar structural folds and active sites which were decidedly conserved. The quality of hexokinase I protein was considered to be sterically stable where the protein was prepared by utilizing the software protein preparation execute in the Schrodinger suite. Prepared proteins were evaluated using SAVES and the studies of molecular dynamics of the hexokinase, and the GROMACS were performed for protein–ligand complex. The low HOMO-LUMO energy gaps of the compound verified the greater stability of the molecule. Here, the tested drug candidates have good absorption, distribution, metabolism, and excretion (ADME) properties which were established by using QikProp, version 3.4 of Schrodinger.

Pharmacology, Pharmacognosy, Natural Medicine, and Medical Science

First of all, I found lots of medicine for lots of diseases like phlegm and sore throat and headache etc. I stated a Therapy for scrupulous and other kind of disease like this. Except disease and medical science and medicine and astronomy, I have some other research into/on other fields of study. I found how stars moves at constellation, they have two general movements, and in conclusion, I say some of my studies here. You drink water at stand up stance it can because you sweat a lot. My findings support my hypothesis. My hypothesis is can we have natural medicine instead of chemicals one? Does any disease have medicine? Can we success at our life? And other hypothesis that I explain it in manuscript. Most scrutinized literature was collected from different sources including PubMed. This database has been curetted using published methods for all most all pharmaceuticals. Required information for regular method development/validation such as IUPAC name, structure, solubility, chromatographic conditions, instrumentation information like HPLC, LCMS detection parameters, sample preparations, recovery details, limit of detection and limit of quantification, Tmax, Cmax etc., for routine application in BA/BE studies of pharmaceuticals was incorporated including official pharmacopeias information such as European Pharmacopeia, Japan Pharmacopeia and US Pharmacopeia. Database includes drug based bioanalytical methods covering most required fields and external database links of important drug portals such as drug bank, Rxlist, MEDLINE plus, KEGG Drug ID, KEGG Compound ID, Merck manual, PubChem compound ID, PubChem substance ID and USFDA. I use many studies and conducted my studies with lots of references that I said it at the end of my manuscript.

Crystal structures, syntheses, and spectroscopic and electrochemical measurements of two push-pull chromophores: 2-[4-(di-methyl-amino)-benzyl-idene]-1H-indene-1,3(2H)-dione and (E)-2-{3-[4-(di-meth-ylamino)-phen-yl]allyl-idene}-1H-indene-1,3(2H)-dione.

The title pull-push chromophores, 2-[4-(di-methyl-amino)-benzyl-idene]-1H-indene-1,3(2H)-dione, C18H15NO2 (ID[1]) and (E)-2-{3-[4-(di-methyl-amino)-phen-yl]allyl-idene}-1H-indene-1,3(2H)-dione, C20H17NO2 (ID[2]), have donor-π-bridge-acceptor structures. The mol-ecule with the short π-bridge, ID[1], is almost planar while for the mol-ecule with a longer bridge, ID[2], is less planar. The benzene ring is inclined to the mean plane of the 2,3-di-hydro-1H-indene unit by 3.19 (4)° in ID[1] and 13.06 (8)° in ID[2]. The structures of three polymorphs of compound ID[1] have been reported: the α-polymorph [space group P21/c; Magomedova & Zvonkova (1978 ▸). Kristallografiya, 23, 281-288], the β-polymorph [space group P21/c; Magomedova & Zvonkova (1980 ▸). Kristallografiya, 25 1183-1187] and the γ-polymorph [space group Pna21; Magomedova, Neigauz, Zvonkova & Novakovskaya (1980 ▸). Kristallografiya, 25, 400-402]. The mol-ecular packing in ID[1] studied here is centrosymmetric (space group P21/c) and corresponds to the β-polymorph structure. The mol-ecular packing in ID[2] is non-centrosymmetric (space group P21), which suggests potential NLO properties for this crystalline material. In both compounds, there is short intra-molecular C-H⋯O contact present, enclosing an S(7) ring motif. In the crystal of ID[1], mol-ecules are linked by C-H⋯O hydrogen bonds and C-H⋯π inter-actions, forming layers parallel to the bc plane. In the crystal of ID[2], mol-ecules are liked by C-H⋯O hydrogen bonds to form 21 helices propagating along the b-axis direction. The mol-ecules in the helix are linked by offset π-π inter-actions with, for example, a centroid-centroid distance of 3.9664 (13) Å (= b axis) separating the indene rings, and an offset of 1.869 Å. Spectroscopic and electrochemical measurements show the ability of these compounds to easily transfer electrons through the π-conjugated chain.

Small-molecule-mediated chemical knock-down of MuRF1/MuRF2 and attenuation of diaphragm dysfunction in chronic heart failure.

BackgroundChronic heart failure (CHF) leads to diaphragm myopathy that significantly impairs quality of life and worsens prognosis. In this study, we aimed to assess the efficacy of a recently discovered small‐molecule inhibitor of MuRF1 in treating CHF‐induced diaphragm myopathy and loss of contractile function.MethodsMyocardial infarction was induced in mice by ligation of the left anterior descending coronary artery. Sham‐operated animals (sham) served as controls. One week post‐left anterior descending coronary artery ligation animals were randomized into two groups—one group was fed control rodent chow, whereas the other group was fed a diet containing 0.1% of the compound ID#704946—a recently described MuRF1‐interfering small molecule. Echocardiography confirmed development of CHF after 10 weeks. Functional and molecular analysis of the diaphragm was subsequently performed.ResultsChronic heart failure induced diaphragm fibre atrophy and contractile dysfunction by ~20%, as well as decreased activity of enzymes involved in mitochondrial energy production (P < 0.05). Treatment with compound ID#704946 in CHF mice had beneficial effects on the diaphragm: contractile function was protected, while mitochondrial enzyme activity and up‐regulation of the MuRF1 and MuRF2 was attenuated after infarct.ConclusionsOur murine CHF model presented with diaphragm fibre atrophy, impaired contractile function, and reduced mitochondrial enzyme activities. Compound ID#704946 rescued from this partially, possibly by targeting MuRF1/MuRF2. However, at this stage of our study, we refrain to claim specific mechanism(s) and targets of compound ID#704946, because the nature of changes after 12 weeks of feeding is likely to be complex and is not necessarily caused by direct mechanistic effects.

Pharmacophore-based virtual screening approach for identification of potent natural modulatory compounds of human Toll-like receptor 7

Toll-like receptor 7 (TLR7) is a transmembrane glycoprotein playing very crucial role in the signaling pathways involved in innate immunity and has been demonstrated to be useful in fighting against infectious disease by recognizing viral ssRNA & specific small molecule agonists. In order to find novel human TLR7 (hTLR7) modulators, computational ligand-based pharmacophore modeling approach was used to identify the molecular chemical features required for the modulation of hTLR7 protein. A training set of 20 TLR7 agonists with their known experimental activity was used to create pharmacophore model using 3D-QSAR pharmacophore generation (HypoGen algorithm) module in Discovery Studio. The best developed hypothesis consists of four pharmacophoric features namely, one hydrogen bond donor (HBD), one ring aromatic (RA), and two hydrophobic (HY) character. The developed hypothesis was then validated by different methods such as cost analysis, test set method, and Fischer’s test method for consistency. Hence, this validated model was further employed for screening of natural hit compounds from InterBioScreen Natural product database, consisting of more than 60,000 natural compounds and derivatives. The screened hit compounds were subsequently filtered by Lipinski’s rule of 5, ADME and toxicity parameters and molecular docking studies to remove the false positive rates. Finally, molecular docking analysis led to identification of the (3a′S,6a′R)-3′-(3,4-dihydroxybenzyl)-5′-(3,4-dimethoxyphenethyl)-5-ethyl-3′,3a′-dihydro-2′H-spiro[indoline-3,1′-pyrrolo[3,4-c]pyrrole]-2,4′,6′(5′H,6a′H)-trione (Compound ID: STOCK1N-65837) as potent hTLR7 modulator due to its better docking score and molecular interactions compared to other compounds. The result of virtual screening was further validated using molecular dynamics (MD) simulation analysis. Thus, a 30 ns MD simulation analysis revealed high stability and effective binding of STOCK1N-65837 within the binding site of hTLR7. Therefore, the present study provides confidence for the utility of the selected chemical feature based pharmacophore model to design novel TLR7 modulators with desired biological activity.

Research into/on pharmacology and pharmacognosy and natrual medicine and medical science

First of all I found lots of medicine for lots of diseases like phlegm and sore throat and headache and etc. I stated a Therapy for scrupulous and other kind of disease like this. Except disease and medical science and medicine and astronomy I have some other research into/on other fields of study. I found how stars moves at constellation and they have two general movements and in conclusion I say some of my studies here. you drink water at stand-up stance it can cause you sweat a lot. My findings support my hypothesis. My hypothesis is can we have natural medicine instead of chemicals one? Does any disease have medicine? Can we success at our life? And other hypothesis that I explain it in manuscript. Most scrutinized literature was collected from different sources including PubMed. This database has been curetted using published methods for all most all pharmaceuticals. Required information for regular method development/validation such as IUPAC name, structure, solubility, chromatographic conditions, instrumentation information like HPLC, LCMS detection parameters, sample preparations, recovery details, limit of detection and limit of quantification, Tmax, Cmax etc., for routine application in BA/BE studies of pharmaceuticals was incorporated including official pharmacopeias information such as European Pharmacopeia, Japan Pharmacopeia and US Pharmacopeia. Database includes drug based bioanalytical methods covering most required fields and external database links of important drug portals such as drug bank, Rx list, MEDLINE plus, KEGG Drug ID, KEGG Compound ID, Merck manual, PubChem compound ID, PubChem substance ID and USFDA.I use lots of studies and conducted my studies with lots of references that I said it at the end of my manuscript