Skip to main content

and
  1. No Access

    Protocol

    Machine Learning Models for Predicting Liver Toxicity

    Liver toxicity is a major adverse drug reaction that accounts for drug failure in clinical trials and withdrawal from the market. Therefore, predicting potential liver toxicity at an early stage in drug discov...

    Jie Liu, Wen**g Guo, Sugunadevi Sakkiah in In Silico Methods for Predicting Drug Toxi… (2022)

  2. Article

    Theoretical approaches to identify the potent scaffold for human sirtuin1 activator: Bayesian modeling and density functional theory

    Bayesian and pharmacophore modeling approaches were utilized to identify the fragments and critical chemical features of small molecules that enhance sirtuin1 (SIRT1) activity. Initially, 48 Bayesian models (B...

    Sugunadevi Sakkiah, Mahreen Arooj, Keun Woo Lee in Medicinal Chemistry Research (2014)

  3. No Access

    Article

    Combined chemical feature-based assessment and Bayesian model studies to identify potential inhibitors for Factor Xa

    In our study, we have described chemical feature-based 3D QSAR pharmacophore models with help of known inhibitors of Factor Xa (FXa). The best model, Hypo1, has validated by various techniques to prove its rob...

    Meganathan Chandrasekaran, Sugunadevi Sakkiah, Keun Woo Lee in Medicinal Chemistry Research (2012)

  4. Article

    Pharmacophore-based virtual screening and density functional theory approach to identifying novel butyrylcholinesterase inhibitors

    To identify the critical chemical features, with reliable geometric constraints, that contributes to the inhibition of butyrylcholinesterase (BChE) function.

    Sugunadevi Sakkiah, Keun Woo Lee in Acta Pharmacologica Sinica (2012)