QSAR Modeling: Where Have You Been? Where Are You Going To?

被引：1314

作者：

Cherkasov, Artem ^{[1
]}

Muratov, Eugene N. ^{[2
,3
]}

Fourches, Denis ^{[2
]}

Varnek, Alexandre ^{[4
]}

Baskin, Igor I. ^{[5
]}

Cronin, Mark ^{[6
]}

Dearden, John ^{[6
]}

Gramatica, Paola ^{[7
]}

Martin, Yvonne C. ^{[8
]}

Todeschini, Roberto ^{[9
]}

Consonni, Viviana ^{[9
]}

Kuz'min, Victor E. ^{[3
]}

Cramer, Richard ^{[10
]}

Benigni, Romualdo ^{[11
]}

Yang, Chihae ^{[12
]}

Rathman, James ^{[12
,13
]}

Terfloth, Lothar ^{[14
]}

Gasteiger, Johann ^{[14
]}

Richard, Ann ^{[15
]}

Tropsha, Alexander ^{[2
]}

机构：

[1] Univ British Columbia, Vancouver Prostate Ctr, Vancouver, BC V6H 3Z6, Canada

[2] Univ N Carolina, UNC Eshelman Sch Pharm, Lab Mol Modeling, Chapel Hill, NC 27599 USA

[3] Natl Acad Sci Ukraine, AV Bogatsky Phys Chem Inst, Dept Mol Struct & Cheminformat, UA-65080 Odessa, Ukraine

[4] L Pasteur Univ Strasbourg, Dept Chem, F-67000 Strasbourg, France

[5] Moscow MV Lomonosov State Univ, Dept Phys, Moscow 119991, Russia

[6] Liverpool John Moores Univ, Sch Pharm & Biomol Sci, Liverpool L3 3AF, Merseyside, England

[7] Univ Insubria, Dept Struct & Funct Biol, I-21100 Varese, Italy

[8] Martin Consulting, Waukegan, IL 60079 USA

[9] Univ Milano Bicocca, Milano Chemometr & QSAR Res Grp, I-20126 Milan, Italy

[10] Tripos Inc, St Louis, MO 63144 USA

[11] Ist Super Sanita, Environm & Hlth Dept, I-00161 Rome, Italy

[12] Altamira LLC, Columbus, OH 43235 USA

[13] Ohio State Univ, Dept Chem & Biomol Engn, Columbus, OH 43215 USA

[14] Mol Networks GmbH, D-91052 Erlangen, Germany

[15] US EPA, Natl Ctr Computat Toxicol, Res Triangle Pk, NC 27519 USA

来源：

JOURNAL OF MEDICINAL CHEMISTRY | 2014年 / 57卷 / 12期

基金：

加拿大自然科学与工程研究理事会;

关键词：

QUANTITATIVE STRUCTURE-ACTIVITY; AUTOMATED STRUCTURE EVALUATION; NANO-COMBINATORIAL CHEMISTRY; SUPPORT VECTOR MACHINE; COMPUTER-AIDED-DESIGN; IN-SILICO TOOLS; BIOLOGICAL-ACTIVITY; ANTIMICROBIAL PEPTIDES; MIXTURE TOXICITY; SIMPLEX REPRESENTATION;

D O I：

10.1021/jm4004285

中图分类号：

R914 [药物化学];

学科分类号：

100701 ;

摘要：

Quantitative structure-activity relationship modeling is one of the major computational tools employed in medicinal chemistry. However, throughout its entire history it has drawn both praise and criticism concerning its reliability, limitations, successes, and failures. In this paper, we discuss (i) the development and evolution of QSAR; (ii) the current trends, unsolved problems, and pressing challenges; and (iii) several novel and emerging applications of QSAR modeling. Throughout this discussion, we provide guidelines for QSAR development, validation, and application, which are summarized in best practices for building rigorously validated and externally predictive QSAR models. We hope that this Perspective will help communications between computational and experimental chemists toward collaborative development and use of QSAR models. We also believe that the guidelines presented here will help journal editors and reviewers apply more stringent scientific standards to manuscripts reporting new QSAR studies, as well as encourage the use of high quality, validated QSARs for regulatory decision making.

引用

页码：4977 / 5010

页数：34

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