In silico ADME/T Prediction of Steroidal Chalcone derivatives using Swiss ADME and OSIRIS explorer

Author:

M. Mukadam Marwa1,M. Jagdale Deepali1

Affiliation:

1. Department of Pharmaceutical Chemistry, Bharati Vidyapeeth’s College of Pharmacy, Navi Mumbai, 400614, Maharashtra, India.

Abstract

Cancer is the most devastating and widespread disease all over the globe. To overcome drug resistance, new drugs need to be developed that are target specific. Previously designed ten steroidal chalcone derivatives were assessed for their pharmacokinetic profile and toxicity. The present study describes the evaluation of these derivatives for their ADME profile and toxicity using Swiss ADME and OSIRIS web tools. Structures of designed steroidal chalcone derivatives and progesterone (standard) were converted into canonical SMILES format by using Swiss ADME web tool. These structures were submitted to the Swiss ADME web tool that provided physicochemical and pharmacokinetic properties of the compounds. The OSIRIS web server was mainly used for predicting toxicity properties of all derivatives. OSIRIS results on toxicity showed that all compounds were slightly toxic. Based on Swiss ADME analysis, compounds 4, 9 and 10 have an acceptable bioavailability and comply with Lipinski's rule of five. By evaluating their drug score and ADMET properties, it was concluded that compounds 4, 9 and 10 could potentially have favourable characteristics of oral drugs, and further research could be carried out to evaluate them as anticancer agents by performing in-vitro and in-vivo cytotoxic studies.

Publisher

A and V Publications

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3