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Thakur S.,Shri Vaishnav Institute of Technology and Science | Thakur M.,Softvision College | Thakur A.,NITTTR
Journal of Physics: Conference Series | Year: 2014

In present study efforts have been made to analyze the role of different structural/topological and non-conventional physicochemical features on the X-ray absorption property wavelength of maximum absorption λm. Efforts are also made to compare the magnitude of various parameters for optimization of the features mainly responsible to characterize the wavelength of maximum absorbance λmin X-ray absorption. For the purpose multiple linear regression method is used and on the basis of regression and correlation value suitable model have been developed. © 2014, Institute of Physics Publishing. All rights reserved.


Yadav M.,Softvision College | Joshi S.,Government Degree College | Nayarisseri A.,Bioinformatics Research Laboratory | Jain A.,Banasthali University | And 2 more authors.
Interdisciplinary Sciences: Computational Life Sciences | Year: 2013

Global QSAR models predict biological response of molecular structures which are generic in particular class. A global QSAR dataset admits structural features derived from larger chemical space, intricate to model but more applicable in medicinal chemistry. The present work is global in either sense of structural diversity in QSAR dataset or large number of descriptor input. Forty phenethylamine structure derivatives were selected from a large pool (904) of similar phenethylamines available in Pubchem database. LogP values of selected candidates were collected from physical properties database (PHYSPROP) determined in identical set of conditions. Attempts to model logP value have produced significant QSAR models. MLR aided linear one-variable and two-variable QSAR models with their respective R2 (0.866, 0.937), R2A (0.862, 0.932), F-stat (181.936, 199.812) and Standard Error (0.365, 0.255) are statistically fit and found predictive after internal validation and external validation. The descriptors chosen after improvisation and optimization reveal mechanistic part of work in terms of Verhaar model of Fish base-line toxicity from MLOGP, i.e. (BLTF96) and 3D-MoRSE -signal 15 /unweighted molecular descriptor calculated by summing atom weights viewed by a different angular scattering function (Mor15u) are crucial in regulation of logP values of phenethylamines. © 2013 International Association of Scientists in the Interdisciplinary Areas and Springer-Verlag Berlin Heidelberg.


Mamta T.,Softvision College | Suprajnya T.,Shree Vaishnav Institute of Technology and Science | Neelu M.,Government Rani Laxmi Bai PG College | Priyadarshini K.,Indore Institute of Science and Technology II | And 2 more authors.
Research Journal of Chemistry and Environment | Year: 2014

Present study aims to understand the application of 3 dimensional parameters in modeling of drug receptor interaction in reference to phenyl acridine derivatives and also efforts have been made to understand the role of volumetric properties in modeling of DNA binding affinity for the set of 21 phenyl acridine derivatives. To perform the same, various structural, topological, physicochemical, quantum, electrostatic and dimensional parameters are tested. Amongst those parameters, it is observed that the parameters responsible for refractive and volumetric properties of the molecule are playing the dominating role over the other parameters in characterizing the DNA binding affinity. Further analysis with quantum, electrostatic and dimensional parameters explore the application of electrostatic and dimensional parameters in modeling of DNA binding affinity with significant regression value.


Ribonucleotide reductase subunit R2 regulates catalytic action of the enzyme to provide DNA synthesis material via reduction. It has been continuously investigated as anticancer drug target for design and discovery of its inhibitors. Present studies aim to design novel heterocyclic/aryl substituted and adamantyl added thiosemicarbazones out fitted with improved cell permeability and effective RNR inhibition. Design strategy renders significant use of virtual screening and molecular docking studies to converge search of selective molecules for synthesis and further experimental studies. Selected candidates were synthesized and evaluated in vitro for their RNR inhibitory activity (IC50, uM) on MCF-7 cells, breast cancer cell lines. Molecular docking results (docking scores) and experimental results (IC50, uM) were found to be correlated and in agreement. Structure-based and ligandbased studies of results substantiate regulative role of water molecules at catalytic site (H2O: 2057) as well as at RNR inhibitor binding site (H2O: 2023, 2047, 2060 and 2070). Admantyl group has testified constant spatial position in docked poses and involved in steric interactions with Cys271, Asp272, Phe237, Gly234 and Val238. Heterocyclic/aryl substitutions equally offered H-bonds with water molecules (H2O: 2028, 2054, 2061 and 2073) along with amino acids Ser264, Asp272, Tyr324 and Asn346. Present efforts to design new inhibitors incur new characteristics in RNR Inhibition. © 2015 Bentham Science Publishers.


Vindya N.G.,Vellore Institute of Technology | Sharma N.,Northeastern University | Yadav M.,Softvision College | Ethiraj K.R.,Vellore Institute of Technology
Current Topics in Medicinal Chemistry | Year: 2015

Tubulin has picked up great focus as a major target in drug discovery and consequently, tubulin inhibitors have pulling in a considerable attention as anticancer agents. Numerable naturally occurring agents have focused on tubulin system act as an imperative target of cancer chemotherapy. Substantial number of tubulin inhibitors has been discovered so far and these agents are classified as indicated by their interaction. They are colchicine site binder, vinca- alkaloid related drugs and those interacting with the Taxol binding site and functioning as stabilising agents. We review the recent advances in the advancement of tubulin interfering agents and will render the current trend in the improvement of tubulin inhibitors as anticancer agents. © 2015 Bentham Science Publishers.


Thakur A.,Rishiraj institute of Technology | Thakur A.,DJ Laboratory | Thakur M.,Softvision College | Agrawal N.,Mata Jija Bai Government PG College | Bhadoria S.,Central India Institute of Technology
Anti-Infective Agents in Medicinal Chemistry | Year: 2010

The work describes QSAR and SAR studies on the TIBO derivatives as non-nucleotide reverse transcriptase inhibitor of HIV-1 using the 2D-topological, physicochemical and hydrophobic parameters, indicator parameters along with the some 3D or quantum parameters. The set of TIBO derivatives chosen for the modeling is consists of 20 compounds. Application of multiple linear regression analysis indicated that a combination of adhoc molecular descriptors and the indicator parameters yielded a statistically significant model for the prediction of activity, log1/C (50% of Effective concentration for inhibition of reverse transcriptase-1 of HIV.). The final selection of a potential TIBO derivative as nonnucleotide reverse transcriptase inhibitor of HIV-1 is made by the quantum molecular modeling. © 2010 Bentham Science Publishers Ltd.


Prasoona R.K.,Osmania University | Jyoti A.,Osmania University | Mukesh Y.,Softvision College | Nishant S.,Softvision College | And 3 more authors.
Interdisciplinary Sciences: Computational Life Sciences | Year: 2013

The present investigations include utility of latest statistical algorithm Support Vector Machine (SVM) to identify non-linear structure activity relationship between IC50 values and structures of C-aryl glucoside SGLT2 inhibitors. Training dataset consisted of forty molecules and the remaining six molecules were chosen for test set validation. SVM under Gaussian Kernel Function yielded non-linear QSAR models. Forward selection algorithm was applied after pruning and redundancy check on molecular descriptors. Internal validations of QSAR models have been achieved using R CV 2 (LOO), PRESS, SDEP and Y-Scrambling. SVM aided non-linear models are more efficient when optimization of Gaussian Kernel Function was introduced. Non-linear QSAR studies further identified atomic van der Waals volumes, atomic masses, sum of geometrical distances between O..S and degree of unsaturation as molecular descriptors and crucial structural requirements to model IC50 of C-aryl glucoside derivatives. © 2013 International Association of Scientists in the Interdisciplinary Areas and Springer-Verlag Berlin Heidelberg.


Bandaru S.,Osmania University | Cingeetham V.,Osmania University | Akare U.R.,In Silico Research Laboratory | Yadav D.,In Silico Research Laboratory | And 4 more authors.
Current Bioinformatics | Year: 2015

QSAR models supervised by Multiple linear regressions (MLR) and Gaussian kernel support vector machines were developed to predict β2 potency for Sibenadet (Viozan™) and its derivatives along with established LABAs (Formeterol, Salmetrol) and ultra LABA Indacaterol. MLR aided linear QSAR models identified four molecular descriptors MATS6e, GATS5e, Mor17p, R7m+ related to β2 potency while descriptors like R5p+, Lop, Belp4, RDF075m were deduced in prediction of β2 potency in non-linear SVM models. Although, statistical fitness was observed with Gaussian Kernel function SVM models in potency prediction, MLR models proved to be more consistent in predictions. Further MLR and SVM models were statistically validated by internal validation methods like R2CV, RSS and MSS etc. Mechanistic study on linear QSAR models revealed regulative role of atomic autocorrelated electronegativities and polarizabilities in influencing β2 potency. © 2015 Bentham Science Publishers.


Nayarisseri A.,In silico Research Laboratory | Yadav M.,Softvision College | Wishard R.,Softvision College
Interdisciplinary Sciences: Computational Life Sciences | Year: 2013

The Translationally Controlled Tumor Protein (TCTP) has been investigated for tumor reversion and is a target of cancer therapy. Down regulators which suppress the expression of TCTP can trigger the process of tumor reversion leading to the transformation of tumor cells into revertant cells. The present investigation is a novel protein-protein docking approach to target TCTP by a set of proteins similar to the protein: sorting nexin 6 (SNX6) which is an established down regulator of TCTP. The established down regulator along with its set of most similar proteins were modeled using the PYTHON based software - MODELLER v9.9, followed by structure validation using the Procheck Package. Further TCTP was docked with its established and prospective down regulators using the flexible docking protocol suite HADDOCK. The results were evaluated and ranked according to the RMSD values of the complex and the HADDOCK score, which is a weighted sum of van der Waal's energy, electrostatic energy, restraints violation energy and desolvation energy. Results concluded the protein sorting nexin 6 of Mus musculus to be a better down regulator of TCTP, as compared to the suggested down regulator (Homo sapiens snx6). © 2013 International Association of Scientists in the Interdisciplinary Areas and Springer-Verlag Berlin Heidelberg.


PubMed | Softvision College
Type: Journal Article | Journal: Interdisciplinary sciences, computational life sciences | Year: 2013

Global QSAR models predict biological response of molecular structures which are generic in particular class. A global QSAR dataset admits structural features derived from larger chemical space, intricate to model but more applicable in medicinal chemistry. The present work is global in either sense of structural diversity in QSAR dataset or large number of descriptor input. Forty phenethylamine structure derivatives were selected from a large pool (904) of similar phenethylamines available in Pubchem database. LogP values of selected candidates were collected from physical properties database (PHYSPROP) determined in identical set of conditions. Attempts to model logP value have produced significant QSAR models. MLR aided linear one-variable and two-variable QSAR models with their respective R(2) (0.866, 0.937), R(2)A (0.862, 0.932), F-stat (181.936, 199.812) and Standard Error (0.365, 0.255) are statistically fit and found predictive after internal validation and external validation. The descriptors chosen after improvisation and optimization reveal mechanistic part of work in terms of Verhaar model of Fish base-line toxicity from MLOGP, i.e. (BLTF96) and 3D-MoRSE -signal 15 /unweighted molecular descriptor calculated by summing atom weights viewed by a different angular scattering function (Mor15u) are crucial in regulation of logP values of phenethylamines.

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