BIOINFOQSAR - A SPECIALIZED SOFTWARE DEVELOPED FOR QSAR MODELS. PREDICTABLE CAPACITY TESTING FOR CONVENTIONAL ANTITUMOR DRUGS

被引：0

作者：

Popa, Lacramioara ^{[1
]}

Draganescu, Doina ^{[1
]}

Albu, Madalina Georgiana ^{[2
]}

Ortan, Alina ^{[3
]}

Ghica, Mihaela Violeta ^{[1
]}

机构：

[1] Carol Davila Univ Med & Pharm, Fac Pharm, Phys & Colloidal Chem Dept, Bucharest 020956, Romania

[2] INCDTP Div Leather & Footwear Res Inst, Collagen Dept, Bucharest 031215, Romania

[3] Univ Agron Sci & Vet Med, Fac Land Reclamat & Environm Engn, Bucharest, Romania

来源：

FARMACIA | 2013年 / 61卷 / 03期

关键词：

BIOINFOQSAR; capacity testing; predictive models; antitumor drugs; ALIPHATIC ESTERS; LOG-P; TOXICITY; DESCRIPTORS;

D O I：

暂无

中图分类号：

R9 [药学];

学科分类号：

1007 ;

摘要：

A new software for QSAR design and analysis was developed and is presented in this work. BIOINFOQSAR was designed for developing high predictable and robust models of correlation between molecular structure descriptors and biological properties. This study includes the presentation of the application interface, its modules and functionality. An algorithm for QSAR model generation and QSAR analysis as a structured program are disclosed. The test of BIOINFOQSAR boosting capacity in high level prediction was conducted in a group of conventional antitumor agents. A model of correlation as a linear function between the biological property - IC50 inhibitory concentration, and a sum of molecular descriptors was chosen, and various statistical tests were conducted. The highest level of predictability was obtained, even the number of terms in the equation was quite elevated. The objective of predictability level test for the BIOINFOQSAR was fulfill.

引用

页码：427 / 438

页数：12

共 19 条

[1] B Kier L., 1990, Computational Chemical Graph Theory
[2] Predicting log P of pesticides using different software
Benfenati, E
Gini, G
Piclin, N
Roncaglioni, A
Varì, MR
[J]. CHEMOSPHERE, 2003, 53 (09) : 1155 - 1164
[3] Structure-activity relationship studies of chemical mutagens and carcinogens: Mechanistic investigations and prediction approaches
Benigni, R
[J]. CHEMICAL REVIEWS, 2005, 105 (05) : 1767 - 1800
[4] Devillers J, 2000, TOPOLOGICAL INDICES
[5] Beware of q2!
Golbraikh, A
Tropsha, A
[J]. JOURNAL OF MOLECULAR GRAPHICS & MODELLING, 2002, 20 (04) : 269 - 276
[6] Principles of QSAR models validation: internal and external
Gramatica, Paola
[J]. QSAR & COMBINATORIAL SCIENCE, 2007, 26 (05): : 694 - 701
[7] Karelson M., 2000, Molecular Descriptors in QSAR/QSPR
[8] Katritzky A.R, 1994, CODESSA VERSION 5 3
[9] The characterization of chemical structures using molecular properties. A survey
Livingstone, DJ
[J]. JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES, 2000, 40 (02): : 195 - 209
[10] Substructure versus whole-molecule approaches for calculating log P
Mannhold, R
Petrauskas, A
[J]. QSAR & COMBINATORIAL SCIENCE, 2003, 22 (04): : 466 - 475

← 1 2 →