Prediction methods and databases within chemoinformatics: emphasis on drugs and drug candidates

Svava Osk Jónsdóttir; Flemming Steen Jørgensen; Søren Brunak

doi:10.1093/bioinformatics/bti314

Prediction methods and databases within chemoinformatics: emphasis on drugs and drug candidates

Svava Osk Jónsdóttir, Flemming Steen Jørgensen, Søren Brunak

78 Citations (Scopus)

Abstract

MOTIVATION: To gather information about available databases and chemoinformatics methods for prediction of properties relevant to the drug discovery and optimization process. RESULTS: We present an overview of the most important databases with 2-dimensional and 3-dimensional structural information about drugs and drug candidates, and of databases with relevant properties. Access to experimental data and numerical methods for selecting and utilizing these data is crucial for developing accurate predictive in silico models. Many interesting predictive methods for classifying the suitability of chemical compounds as potential drugs, as well as for predicting their physico-chemical and ADMET properties have been proposed in recent years. These methods are discussed, and some possible future directions in this rapidly developing field are described.

Original language	English
Journal	Bioinformatics
Volume	21
Issue number	10
Pages (from-to)	2145-60
Number of pages	16
ISSN	1367-4803
DOIs	https://doi.org/10.1093/bioinformatics/bti314
Publication status	Published - 2005

Keywords

Chemistry, Pharmaceutical
Computational Biology
Databases, Factual
Drug Design
Models, Chemical
Models, Molecular
Pharmaceutical Preparations
Structure-Activity Relationship

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10.1093/bioinformatics/bti314

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abstract = "MOTIVATION: To gather information about available databases and chemoinformatics methods for prediction of properties relevant to the drug discovery and optimization process. RESULTS: We present an overview of the most important databases with 2-dimensional and 3-dimensional structural information about drugs and drug candidates, and of databases with relevant properties. Access to experimental data and numerical methods for selecting and utilizing these data is crucial for developing accurate predictive in silico models. Many interesting predictive methods for classifying the suitability of chemical compounds as potential drugs, as well as for predicting their physico-chemical and ADMET properties have been proposed in recent years. These methods are discussed, and some possible future directions in this rapidly developing field are described.",

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doi = "10.1093/bioinformatics/bti314",

language = "English",

volume = "21",

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T1 - Prediction methods and databases within chemoinformatics

T2 - emphasis on drugs and drug candidates

AU - Jónsdóttir, Svava Osk

AU - Jørgensen, Flemming Steen

AU - Brunak, Søren

PY - 2005

Y1 - 2005

N2 - MOTIVATION: To gather information about available databases and chemoinformatics methods for prediction of properties relevant to the drug discovery and optimization process. RESULTS: We present an overview of the most important databases with 2-dimensional and 3-dimensional structural information about drugs and drug candidates, and of databases with relevant properties. Access to experimental data and numerical methods for selecting and utilizing these data is crucial for developing accurate predictive in silico models. Many interesting predictive methods for classifying the suitability of chemical compounds as potential drugs, as well as for predicting their physico-chemical and ADMET properties have been proposed in recent years. These methods are discussed, and some possible future directions in this rapidly developing field are described.

AB - MOTIVATION: To gather information about available databases and chemoinformatics methods for prediction of properties relevant to the drug discovery and optimization process. RESULTS: We present an overview of the most important databases with 2-dimensional and 3-dimensional structural information about drugs and drug candidates, and of databases with relevant properties. Access to experimental data and numerical methods for selecting and utilizing these data is crucial for developing accurate predictive in silico models. Many interesting predictive methods for classifying the suitability of chemical compounds as potential drugs, as well as for predicting their physico-chemical and ADMET properties have been proposed in recent years. These methods are discussed, and some possible future directions in this rapidly developing field are described.

KW - Chemistry, Pharmaceutical

KW - Computational Biology

KW - Databases, Factual

KW - Drug Design

KW - Models, Chemical

KW - Models, Molecular

KW - Pharmaceutical Preparations

KW - Structure-Activity Relationship

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DO - 10.1093/bioinformatics/bti314

M3 - Journal article

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SN - 1367-4803

VL - 21

SP - 2145

EP - 2160

JO - Bioinformatics

JF - Bioinformatics

IS - 10

ER -

Prediction methods and databases within chemoinformatics: emphasis on drugs and drug candidates

Abstract

Keywords

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