Literature DB >> 21470180

Recent developments of in silico predictions of oral bioavailability.

Jingyu Zhu1, Junmei Wang, Huidong Yu, Youyong Li, Tingjun Hou.   

Abstract

Unfavorable oral bioavailability is an important reason accounting for the failure of the drug candidates. Considering the lack of in vitro high-throughput screening assay for oral bioavailability, it is critical to develop in silico models for early predictions of oral bioavailability. In this review, we summarize present knowledge and recent progress related to the in silico prediction of oral bioavailability, including the current available datasets of oral bioavailability in human, the roles of physiochemical properties contributing to oral bioavailability, and the available theoretical models to predict oral bioavailability. Particularly, the regression model recently developed by us was demonstrated, which is based on the largest dataset of oral bioavailability in human. Although promising progress has been made recently, it is still indispensable to improve the accuracy of the models to predict oral bioavailability.

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Year:  2011        PMID: 21470180     DOI: 10.2174/138620711795508368

Source DB:  PubMed          Journal:  Comb Chem High Throughput Screen        ISSN: 1386-2073            Impact factor:   1.339


  9 in total

Review 1.  Simulation Models for Prediction of Bioavailability of Medicinal Drugs-the Interface Between Experiment and Computation.

Authors:  Mahmoud E Soliman; Adeniyi T Adewumi; Oluwole B Akawa; Temitayo I Subair; Felix O Okunlola; Oluwayimika E Akinsuku; Shahzeb Khan
Journal:  AAPS PharmSciTech       Date:  2022-03-15       Impact factor: 3.246

2.  Drug-Induced Immune Thrombocytopenia Toxicity Prediction Based on Machine Learning.

Authors:  Binyou Wang; Xiaoqiu Tan; Jianmin Guo; Ting Xiao; Yan Jiao; Junlin Zhao; Jianming Wu; Yiwei Wang
Journal:  Pharmaceutics       Date:  2022-04-26       Impact factor: 6.525

3.  Critical evaluation of human oral bioavailability for pharmaceutical drugs by using various cheminformatics approaches.

Authors:  Marlene T Kim; Alexander Sedykh; Suman K Chakravarti; Roustem D Saiakhov; Hao Zhu
Journal:  Pharm Res       Date:  2013-12-03       Impact factor: 4.200

4.  ADMET evaluation in drug discovery: 15. Accurate prediction of rat oral acute toxicity using relevance vector machine and consensus modeling.

Authors:  Tailong Lei; Youyong Li; Yunlong Song; Dan Li; Huiyong Sun; Tingjun Hou
Journal:  J Cheminform       Date:  2016-02-01       Impact factor: 5.514

5.  Systems biological approach of molecular descriptors connectivity: optimal descriptors for oral bioavailability prediction.

Authors:  Shiek S S J Ahmed; V Ramakrishnan
Journal:  PLoS One       Date:  2012-07-16       Impact factor: 3.240

6.  In silico docking analysis revealed the potential of phytochemicals present in Phyllanthus amarus and Andrographis paniculata, used in Ayurveda medicine in inhibiting SARS-CoV-2.

Authors:  Shridhar Hiremath; H D Vinay Kumar; M Nandan; M Mantesh; K S Shankarappa; V Venkataravanappa; C R Jahir Basha; C N Lakshminarayana Reddy
Journal:  3 Biotech       Date:  2021-01-11       Impact factor: 2.406

7.  HobPre: accurate prediction of human oral bioavailability for small molecules.

Authors:  Min Wei; Xudong Zhang; Xiaolin Pan; Bo Wang; Changge Ji; Yifei Qi; John Z H Zhang
Journal:  J Cheminform       Date:  2022-01-06       Impact factor: 5.514

8.  Random Forest Model Prediction of Compound Oral Exposure in the Mouse.

Authors:  Haseeb Mughal; Han Wang; Matthew Zimmerman; Marc D Paradis; Joel S Freundlich
Journal:  ACS Pharmacol Transl Sci       Date:  2021-01-26

9.  Design and Synthesis of Novel 1,3-Thiazole and 2-Hydrazinyl-1,3-Thiazole Derivatives as Anti-Candida Agents: In Vitro Antifungal Screening, Molecular Docking Study, and Spectroscopic Investigation of their Binding Interaction with Bovine Serum Albumin.

Authors:  Andreea-Iulia Pricopie; Ioana Ionuț; Gabriel Marc; Anca-Maria Arseniu; Laurian Vlase; Adriana Grozav; Luiza Ioana Găină; Dan C Vodnar; Adrian Pîrnău; Brîndușa Tiperciuc; Ovidiu Oniga
Journal:  Molecules       Date:  2019-09-21       Impact factor: 4.411

  9 in total

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