Shilpi Chauhan

Bio: Shilpi Chauhan is an academic researcher from Guru Jambheshwar University of Science and Technology. The author has contributed to research in topics: Quantitative structure–activity relationship & Ionic liquid. The author has an hindex of 8, co-authored 13 publications receiving 210 citations. Previous affiliations of Shilpi Chauhan include University of Delhi.

Development of prediction model for fructose- 1,6- bisphosphatase inhibitors using the Monte Carlo method

Abstract: Fructose-1,6-bisphosphatase (FBPase) is an enzyme important for regulation of gluconeogenesis, which is a major process in the liver responsible for glucose production. Inhibition of FBPase enzyme causing blockage of the gluconeogenesis process represents a newer scheme in the progress of anti-diabetic drugs. The current research describes the development of hybrid optimal descriptors-based quantitative structure-activity relationship (QSAR) models intended for a set of 62 FBPase inhibitors with the Monte Carlo method. The molecular structures were expressed by the simplified molecular input line entry system (SMILES) notation. Three splits were prepared by random division of the molecules into training set, calibration set and validation set. Statistical parameters obtained from QSAR modelling were good for various designed splits. The best QSAR model showed the following parameters: the values of r2 for calibration set and validation set of the best model were 0.6837 and 0.8623 and of Q2 were 0.6114 and 0.8036, respectively. Based on the results obtained for correlation weights, different structural attributes were described as promoter of the endpoint. Further, these structural attributes were used in designing of new FBPase inhibitors and a molecular docking study was completed for the determination of interactions of the designed molecules with the enzyme.

QSAR Differential Model for Prediction of SIRT1 Modulation using Monte Carlo Method.

Abstract: Silent information regulator 2 homologue one (SIRT1) modulators have therapeutic potential for a number of diseases like cardiovascular, metabolic, inflammatory and age related disorders. Here, we have studied both activators and inhibitors of SIRT1 and constructed differential quantitative structure activity relationship (QSAR) models using CORAL software by Monte Carlo optimization method and SMILES notation. 3 splits divided into 3 subsets: sub-training, calibration and test sets, were examined and validated with a prediction set. All the described models were statistically significant models. The values of sensitivity, specificity, accuracy and Matthews’ correlation coefficient for the validation set of best model were 1.0000, 0.8889, 0.9524 and 0.9058, respectively. In mechanistic interpretation, structural features important for SIRT1 activation and inhibition have been defined.

Monte Carlo method based QSAR modelling of natural lipase inhibitors using hybrid optimal descriptors

Abstract: Obesity is one of the most provoking health burdens in the developed countries. One of the strategies to prevent obesity is the inhibition of pancreatic lipase enzyme. The aim of this study was to build QSAR models for natural lipase inhibitors by using the Monte Carlo method. The molecular structures were represented by the simplified molecular input line entry system (SMILES) notation and molecular graphs. Three sets - training, calibration and test set of three splits - were examined and validated. Statistical quality of all the described models was very good. The best QSAR model showed the following statistical parameters: r2 = 0.864 and Q2 = 0.836 for the test set and r2 = 0.824 and Q2 = 0.819 for the validation set. Structural attributes for increasing and decreasing the activity (expressed as pIC50) were also defined. Using defined structural attributes, the design of new potential lipase inhibitors is also presented. Additionally, a molecular docking study was performed for the determination of binding modes of designed molecules.

Catalysis in ionic liquids

Abstract: 2.5. Stabilization of IL Emulsions by Nanoparticles 2623 3. Hydrogenations in ILs 2623 3.1. Hydrogenation on IL-Stabilized Nanoparticles 2623 3.1.1. Hydrogenation of 1,3-Butadiene 2623 3.1.2. Hydrogenation of Alkenes and Arenes 2624 3.1.3. Hydrogenation of Ketones 2624 3.2. Homogeneous Catalytic Hydrogenation in ILs 2624 3.3. Hydrogenation of Functionalized ILs 2625 3.3.1. Selective Hydrogenation of Polymers 2625 3.4. Asymmetric Hydrogenations 2626 3.4.1. Enantioselective Hydrogenation 2626 3.5. Role of the ILs Purity in Hydrogenation Reactions 2628

Direct electrochemical oxidation of alcohols with hydrogen evolution in continuous-flow reactor

Abstract: Alcohol oxidation reactions are widely used for the preparation of aldehydes and ketones. The electrolysis of alcohols to carbonyl compounds have been underutilized owing to low efficiency. Herein, we report an electrochemical oxidation of various alcohols in a continuous-flow reactor without external oxidants, base or mediators. The robust electrochemical oxidation is performed for a variety of alcohols with good functional group tolerance, high efficiency and atom economy, whereas mechanistic studies support the benzylic radical intermediate formation and hydrogen evolution. The electrochemical oxidation proves viable on diols with excellent levels of selectivity for the benzylic position.

The Beneficial Roles of SIRT1 in Neuroinflammation-Related Diseases.

Abstract: Sirtuins are the class III of histone deacetylases whose deacetylate of histones is dependent on nicotinamide adenine dinucleotide (NAD+). Among seven sirtuins, SIRT1 plays a critical role in modulating a wide range of physiological processes, including apoptosis, DNA repair, inflammatory response, metabolism, cancer, and stress. Neuroinflammation is associated with many neurological diseases, including ischemic stroke, bacterial infections, traumatic brain injury, Alzheimer’s disease (AD), and Parkinson’s disease (PD). Recently, numerous studies indicate the protective effects of SIRT1 in neuroinflammation-related diseases. Here, we review the latest progress regarding the anti-inflammatory and neuroprotective effects of SIRT1. First, we introduce the structure, catalytic mechanism, and functions of SIRT1. Next, we discuss the molecular mechanisms of SIRT1 in the regulation of neuroinflammation. Finally, we analyze the mechanisms and effects of SIRT1 in several common neuroinflammation-associated diseases, such as cerebral ischemia, traumatic brain injury, spinal cord injury, AD, and PD. Taken together, this information implies that SIRT1 may serve as a promising therapeutic target for the treatment of neuroinflammation-associated disorders.