Softvision College

Indore, India

Softvision College

Indore, India
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Sharma N.,Vellore Institute of Technology | Ethiraj K.R.,Vellore Institute of Technology | Yadav M.,Softvision College | Anuraj Nayarisseri S.,Bioinformatics Research Laboratory | And 3 more authors.
Current Topics in Medicinal Chemistry | Year: 2012

Linear and non-linear QSAR studies have been performed in present investigation with multiple linear regressions (MLR) analysis and Support vector machine (SVM) using different kernels. Three relevant descriptors out of fifteen descriptors calculated are identified as LOGP values, G3e and Rte+. Their relationship with biological activity IC50 have provided structural insights in interpretation and serializing the results into a pragmatic approachable technique. QSAR models obtained show statistical fitness and good predictability. SVM using Gaussian kernel function was found more efficient in prediction of IC50 of training set of thirty small molecules HIV-1 capsid inhibitors. Y-scrambling, PRESS and test set were used as validation parameters. SVM was found superior to training set prediction and internal validations and found inferior to external test set (11 molecules) predictions. Wherein MLR analysis it was vice-versa. Mechanistic interpretation of selected descriptors from both the models actuates further research. © 2012 Bentham Science Publishers.


Bandaru S.,Osmania University | Hema Prasad M.,Osmania University | Jyothy A.,Osmania University | Nayarisseri A.,In silico Research Laboratory | Yadav M.,Softvision College
Current Topics in Medicinal Chemistry | Year: 2013

β2 agonists and anticholinergics are two major classes of bronchodilators which form first line of drugs recommended in symptomatic treatment of asthma and COPD. Combinational therapy involving β agonists and anticholinergics prove more effective in treating airway disease than use of either agent alone. In present investigation, binding modes of Muscarinic Antagonism and β 2 Agonism (MABA) conjugates designed by Lyn et al. were revealed on structural grounds adopting molecular docking techniques. The conjugates tether β 2 motif onto M3 motif which makes it a single molecule that acts as both β 2 agonist and antimuscarinic agent. Series of conjugates were docked against β 2 adrenergic receptor and modeled M3 muscarinic acetylcholine receptor and pharmacophoric features were identified. Upon screening the conjugates on the basis of receptor ligand free energy, hydrogen bonding and internal electrostatic interaction, conjugate 11 demonstrated superior interactions with the receptors compared to remaining conjugates in the series. While, in vitro results and in silico outcomes are in agreement to reveal that conjugate 11 to possess best pharmacological profile, binding modes obtained in docking can be utilized to design new conjugates with improved biological activity. A close study of receptor residues in binding site and atoms, groups and substructures of conjugates may be used to develop favourable secondary valence forces towards receptor-ligand interactions. © 2013 Bentham Science Publishers.


Yadav M.,Softvision College | Nayarisseri A.,Bioinformatics Research Laboratory | Chatterjee P.,Bioinformatics Research Laboratory
Journal of Pharmacy Research | Year: 2013

Multiple linear regressions (MLR) and support vector machine (SVM) supervised linear and non-linear quantitative structureeactivity relationship (QSAR) models were developed for a dataset of (81) NeN-disubstituted trifluoro-3-amino-2-propanol derivatives. QSAR dataset was divided into training set (64) and tests (17) to facilitate external validation. QSAR models derived from MLR and SVM yielded appreciable internal and external predictability. Though SVM models were found statistically fit, MLR models attained more effective and consistent predictability of training and test set. It is important to mention that molecular descriptors (structural information) selected in linear and non-linear QSAR models belong to same categories and code for same structural properties. These different descriptors coding for same structural properties are identified and discussed as overlapping structure features in linear and non-linear QSAR models. Molecular descriptors deduced in relation with biological responses are EEig09d, R3uP, P1P1C6, EPS0 and nCb- in MLR aided linear QSAR models and EEig07d, R6uP, P2C6, G1p and Mor12m in SVM aided non-linear. QSAR models are found reliable for further optimization of NeN-disubstituted trifluoro-3-amino- 2-propanol CETP inhibitory activity. Concluding remarks include selection of overlapping structure features in linear (MLR) and non-linear (SVM) models and utility of statistical approaches in QSAR. These overlapping features may reveal underlying structural properties which convert a linear relationship to non-linear and better understandings of bio-chemical aspects of QSAR models to medicinal chemists. © 2012, JPR Solutions.


Nayarisseri A.,In silico Research Laboratory | Moghni S.M.,National Institute of Technology Rourkela | Yadav M.,In silico Research Laboratory | Yadav M.,Softvision College | And 5 more authors.
Journal of Pharmacy Research | Year: 2013

Molecular chaperones are proteins that are responsible for an appropriate folding, function and stability of client proteins. Out of these, heat shock protein 90 (Hsp90) has recently emerged as a focus of interest for its role in regulating proteins such as ERBB2, C-RAF, CDK2, AKT steroid hormone receptors, mutant p53, HIF-1α which are associated with malignant transformation. Aim: Present investigations cover trials to identify more effective HSP90 inhibitors after obtaining multichaperone complex of HSP90 as an outcome of proteineprotein docking. We have included biological events taking place sequentially in computational frame to evaluate binding of proposed inhibitors. Method: We have extensively used homology modeling using MODELLER, structure preparation and validation to obtain HSP90 with full sequence length. Hydrophobic patches recognition, proteineprotein docking and proteineligand docking were then used to investigate better HSP90 inhibition. Results: Results include generation of multichaperone complex by docking Hsp90 to its partner chaperone Hsp70 and co chaperones like Aha1 and Hsp40 which gave a favorable complex with docking energy of = -711 kcal/mol. The result suggests that Hsp90 in association with its partner chaperone (Hsp70) and co chaperones (Hsp40 and Aha1) forms stable multichaperone complex which favors strong interactions with mutant p53 (Docking energy = -1103.9 kcal/mol) as compared to wild type p53 (Docking energy = -894.6 kcal/ mol). Proteineligand docking revealed EGCG as the most potent inhibitor with formation of 14 Hydrogen-bonds with the key residues of Hsp90 and RMSD value 0.09. Conclusion: Based on the proteineligand docking results and drug-likeness of various molecules (Lipinski's filter criteria) selected for studying their inhibitory action over Hsp90, we found that 17-DMAG can be used into further investigations as a therapeutic molecule for breast cancer. © 2013, JPR Solutions.


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.


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.


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.


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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