S
Shalini Singh
Researcher at Bareilly College
Publications - 35
Citations - 364
Shalini Singh is an academic researcher from Bareilly College. The author has contributed to research in topics: Quantitative structure–activity relationship & Topological index. The author has an hindex of 11, co-authored 34 publications receiving 343 citations.
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Journal ArticleDOI
3D-QSAR CoMFA studies on sulfonamide inhibitors of the Rv3588c β-carbonic anhydrase from Mycobacterium tuberculosis and design of not yet synthesized new molecules
Shalini Singh,Claudiu T. Supuran +1 more
TL;DR: Results indicate that the steric and electrostatic factors play a significant role in mtCA 2 inhibition for the investigated compounds and proposed nine new not yet synthesizedmtCA 2 inhibitors, all of them probably with significantly improved anti-Rv3588c inhibitory activity.
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Comparative QSAR Study on Para-substituted Aromatic Sulphonamides as CAII Inhibitors: Information versus Topological (Distance-Based and Connectivity) Indices
Jyoti Singh,Basheerulla Shaik,Shalini Singh,Vijay K. Agrawal,Padmakar V. Khadikar,Omar Deeb,Claudiu T. Supuran +6 more
TL;DR: The study has shown that distance‐based and connectivity type indices are superior for modelling, monitoring and estimating CAII inhibition.
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Novel estimation of lipophilic behaviour of polychlorinated biphenyls
TL;DR: The statistical analyses showed that the proposed method based on the PI index is quite useful and compared with the earlier reported Abraham method.
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QSAR study on bioconcentration factor (BCF) of polyhalogented biphenyls using the PI index.
TL;DR: Attempt has been made to estimate the accuracy, predictive power, and domain of application of the PI (Padmakar-Ivan) index for modeling bioconcentration factor (BCF) of polyhalogenated biphenyls and it was observed that these distance-based topological indices gave better results for modeling log BCF than logP.
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Use of the PI index in predicting toxicity of nitrobenzene derivatives.
TL;DR: The results have shown that the PI Index alone is not an appropriate index for modelling toxicity of nitrobenzene derivatives, and combined with other distance-based topological indices resulted into statistically significant models and excellent results are obtained in pentaparametric models.