Literature DB >> 27339433

Common SAR Derived from Multiple QSAR Models on Vorinostat Derivatives Targeting HDACs in Tumor Treatment.

Sugathan Praseetha, Srinivas Bandaru, Mukesh Yadav, Anuraj Nayarisseri, Sivanpillai Sureshkumar1.   

Abstract

BACKGROUND: Dysregulation of HDACs has been associated with tumour development and therefore inhibiting HDAC's have surfaced as promising therapeutic strategy in malignancy.
METHODS: Vorinostat analogues with different biological activities were investigated for underlying structure-activity relationship.
RESULTS: Out of six activities and their multiple QSAR models, HDAC1 and HDAC8 produced statistically fit, stable and predictive linear (MLR) and non-linear (SVM) QSAR models. In case of HDAC1 activity as end point, linear (R2=0.8089, R2 CV=0.7343) and non-linear (R2=0.9801, R2 CV=0.8952) QSAR models turned reliable to investigate SAR. Similarly, HDAC8 activity based linear (R2=0.9454, R2 CV=0.9049) and non-linear (R2=0.9899, R2 CV=0.9232) QSAR models produced statistically improved and stable models.
CONCLUSION: Molecular descriptors derived from 3-D Morse and Radial Distribution Function indices were found to be selective in all the models. These molecular descriptors which encode common SAR among Vorinostat derivatives were evaluated for their potent HDAC inhibition activity.

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Year:  2016        PMID: 27339433     DOI: 10.2174/1381612822666160621094009

Source DB:  PubMed          Journal:  Curr Pharm Des        ISSN: 1381-6128            Impact factor:   3.116


  1 in total

1.  Identification of Potent VEGF Inhibitors for the Clinical Treatment of Glioblastoma, A Virtual Screening Approach.

Authors:  Mohini Yadav; Ravina Khandelwal; Urvy Mudgal; Sivaraj Srinitha; Natasha Khandekar; Anuraj Nayarisseri; Sugunakar Vuree; Sanjeev Kumar Singh
Journal:  Asian Pac J Cancer Prev       Date:  2019-09-01
  1 in total

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