Divya Yadav

Pharmacophore based virtual screening, molecular docking and biological evaluation to identify novel PDE5 inhibitors with vasodilatory activity

Prompted by the role of PDE5 and its closely associated cAMP and cGMP in hypertension, we have attempted to discover novel PDE5 inhibitors through ligand based virtual screening. Rigorously validated model comprising of one HBA, one HY and one RA was used as a query to search the NCI database leading to retrieval of many compounds which were screened on the basis of estimated activity, fit value and Lipinskis violation. Selected compounds were subjected to docking studies which resulted into visualization of potential interaction capabilities of NCI compounds in line to pharmacophoric features. Finally three compounds were subjected to in vitro evaluation using the isolated rat aortic model. The results showed that all three compounds are potent and novel PDE5 inhibitors with vasodilatory activity range from 10(-2) to 10(-5) M.

Development of a robust QSAR model to predict the affinity of pyrrolidine analogs for dipeptidyl peptidase IV (DPP- IV)

QSAR analysis using multiple linear regression and partial least squares methods were conducted on a data set of 47 pyrrolidine analogs acting as DPP IV inhibitors. The QSAR models generated (both MLR and PLS) were robust with statistically significant s, F, r, r2 and r2 (CV) values. The analysis helped to ascertain the role of shape flexibility index, Ipso atom E-state index and electrostatic parameters like dipole moment, in determining the activity of DPP IV inhibitors. In addition to QSAR modeling, Lipinski’s rule of five was also employed to check the pharmacokinetic profile of DPP IV inhibitors. Since none of the compounds violated the Lipinski’s rule of five indicating that the DPP IV inhibitors reported herein have sound pharmacokinetic profile and can be considered as potential drug candidates for diabetes mellitus Type II.

Identification of Novel HIV 1- Protease Inhibitors: Application of Ligand and Structure Based Pharmacophore Mapping and Virtual Screening

A combined ligand and structure-based drug design approach provides a synergistic advantage over either methods performed individually. Present work bestows a good assembly of ligand and structure-based pharmacophore generation concept. Ligand-oriented study was accomplished by employing the HypoGen module of Catalyst in which we have translated the experimental findings into 3-D pharmacophore models by identifying key features (four point pharmacophore) necessary for interaction of the inhibitors with the active site of HIV-1 protease enzyme using a training set of 33 compounds belonging to the cyclic cyanoguanidines and cyclic urea derivatives. The most predictive pharmacophore model (hypothesis 1), consisting of four features, namely, two hydrogen bond acceptors and two hydrophobic, showed a correlation (r) of 0.90 and a root mean square of 0.71 and cost difference of 56.59 bits between null cost and fixed cost. The model was validated using CatScramble technique, internal and external test set prediction. In the second phase of our study, a structure-based five feature pharmacophore hypothesis was generated which signifies the importance of hydrogen bond donor, hydrogen bond acceptors and hydrophobic interaction between the HIV-1 protease enzyme and its inhibitors. This work has taken a significant step towards the full integration of ligand and structure-based drug design methodologies as pharmacophoric features retrieved from structure-based strategy complemented the features from ligand-based study hence proving the accuracy of the developed models. The ligand-based pharmacophore model was used in virtual screening of Maybridge and NCI compound database resulting in the identification of four structurally diverse druggable compounds with nM activities.

Ligand-based drug design studies using predictive pharmacophore model generation on 4H-1,2,4-triazoles as AT1 receptor antagonists

Angiotensin II subtype I receptor constitutes a successful target for the treatment of hypertension and cardiovascular diseases. In this study, the pharmacophore search was used to identify structural features that are common in the set of 4H-1,2,4-triazoles. The HypoGen algorithms implemented in the Catalyst software package was employed to create quantitative models. The common feature model for AT1 included two ring aromatic features and two hydrophobic features with statistical values of 0.88 as correlation coefficient for training set. The best model Hypo 1 was validated using a test set of 38 compounds and cat-scramble validation method.

In silico structure-based drug design approach to develop novel pharmacophore model of human peroxisome proliferator-activated receptor γ agonists

A structure-based pharmacophore generation approach was employed to identify novel structural characteristics and scaffolds for peroxisome proliferator-activated receptor γ (PPARγ). The structure-based six feature pharmacophore hypothesis generated in the present study signifies the importance of hydrogen bond donors, hydrogen bond acceptors and hydrophobic interaction between the PPARγ structure and its agonists. The interaction shown by the compounds provides an important insight into the mechanism involved in the ligand receptor interaction. The model will aid in the development of oral hypoglycemic agents with improved efficacy and reduced side effects and can be used to search comparatively larger compound libraries/databases to retrieve more potent and structurally diverse group of compounds.

Discovery of novel DPP IV inhibitors: application of pharmacophore-based virtual screening

Dipeptidyl peptidase IV (DPP-IV) is a potential drug target for type-2 diabetes and DPP-IV inhibitors are known to efficiently improve glucose tolerance. In the present study, pharmacophore model for a set of 29 DPP-IV inhibitors was generated by ligand-based pharmacophore generation process. The best hypothesis, hypo 1, consisting of four chemical features, namely, one hydrogen bond donor, one hydrogen bond acceptor, one hydrophobe and one ring aromatic was validated by cost function analysis, test set prediction and Fischer test. The validated pharmacophore model was then used for searching new lead compounds from Maybridge and NCI database. Four compounds (CD01797, CD06202, CD02493, and AW01077) from Maybridge database and three compounds (NSC997, NSC2450, and NSC5815) from NCI database were identified as structurally diverse druggable novel leads with nM activity against DPP-IV.

Common binding requirements of PPAR-α/δ/γ pan agonists: quantitative structure–activity relationship analysis of indanylacetic acid derivatives carrying 4-thiazolyl-phenoxy tail group

A QSAR study on a series of indanylacetic acid derivatives with activity against PPAR-α, δ, and γ was made using combination of various physiochemical descriptors. Several statistical regression expressions were obtained using stepwise multiple linear regression (MLR) analysis and partial least square (PLS) method. The highly predictive and validated models generated through classical 2D molecular descriptors provided deeper insights about the binding of these small molecules to the human nuclear receptor PPAR-α, δ, and γ. The results reveal that dipole moment and number of hydrogen bond donors are important descriptors in determining effective binding of PPAR agonists to all three subtypes.

Quantitative structure activity relationship (QSAR) of N6-substituted adenosine receptor agonists as potential antihypertensive agents

Quantitative structure activity relationship studies are indubitably of great importance in modern chemistry. In pursuit of better antihypertensive agents, QSAR studies were performed on a series of 48 N6-substituted adenosines analogs. The models were developed using multiple linear regression (MLR) and partial least square (PLS) with many descriptors like electronic, topological, and lipophilic. QSAR models were evaluated for statistical significance and predictive power. The MLR and PLS generated comparable results with good predictive ability and all the other statistical values such as r, r2, rcv2, F, and s values were 0.92, 0.84, 0.83, 61.74, 0.24, respectively, for MLR and rcv2 and statistical significance values of 0.82 and 0.80, respectively, for PLS were satisfactory. The model indicates that the Verloop L, total lipole, VAMP nuclear energy, plays an important role in determining the antihypertensive activity of N6-substituted adenosine receptor agonists. The model developed in the present study will be useful in the design of more potent N6-substituted adenosine receptor agonists as antihypertensive agent.

Synthesis and evaluation of vanillin derivatives as antimicrobial agents

Objectives: The present work involves the synthesis of novel acetyl vanillin derivatives and evaluation for their anti-microbial potential against Escherichia coli. Materials and Methods: The titled compounds were prepared by reacting acetyl nitro vanillin with different substituted amines (Schiff base). The starting material acetyl nitro vanillin was synthesized by reacting acetyl vanillin with fuming nitric acid which in turn was prepared from 4-hydroxy-3-methoxybenzaldehyde (vanillin). Results: The chemical structures of the synthesized compounds were confirmed on the basis of their spectral data (FT-IR, UV/Visible, 1H-NMR, Mass spectra). Conclusion: All the synthesized compounds were tested in vitro for antimicrobial activity and compound F & I showed significant activity as compared to the standard drug.

Histone Deacetylase Inhibitors: A Prospective In Drug Discovery

Cancer is a provocative issue across the globe and treatment of uncontrolled cell growth follows a deep investigation in the field of drug discovery. Therefore, there is a crucial requirement for discovering an ingenious medicinally active agent that can amend idle drug targets. Increasing pragmatic evidence implies that histone deacetylases (HDACs) are trapped during cancer progression, which increases deacetylation and triggers changes in malignancy. They provide a ground-breaking scaffold and an attainable key for investigating chemical entity pertinent to HDAC biology as a therapeutic target in the drug discovery context. Due to gene expression, an impending requirement to prudently transfer cytotoxicity to cancerous cells, HDAC inhibitors may be developed as anticancer agents. The present review focuses on the basics of HDAC enzymes, their inhibitors, and therapeutic outcomes.