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27618 Chemoinformatics in drug discovery

Technological specialization course, Bioinformatics and Systems Biology
Technological specialization course, Pharmaceutical Design and Engineering
Technological specialization course, Advanced and Applied Chemistry

Danish title:

Kemoinformatik i lægemiddelforskning


Point( ECTS )


Course type:

Taught under single-course student
Technological specialization course, MSc. Eng., Advanced and Applied Chemistry


E5B (Wed 13-17)


Campus Lyngby

Scope and form:

Lectures, computer exercises, mini-projects

Duration of Course:

13 weeks

Date of examination:


Type of assessment:



Recommended prerequisites:

Participants restrictions:

Minimum 10

General course objectives:

The aim of the course is to introduce the participants to various chemoinformatics methods and the theory behind them, to show examples of the use of chemoinformatics in modern drug research, and to give the participants practical experience through hands-on chemoinformatics exercises.

Learning objectives:

A student who has met the objectives of the course will be able to:
  • Define chemoinformatics and name the main areas of application within drug discovery.
  • Interpret the most important formats used for describing molecular structures
  • Describe the most widely used machine learning tools in chemoinformatics and the algorithms that they are based on.
  • Understand the differences between linear and non-linear models, supervised and unsupervised machine-learning, clustering and classification.
  • Argue on how to choose the appropriate computational tools for a given problem.
  • Plan, carry out and present computer exercises and mini-projects as team work.
  • Interpret the output from and evaluate the performance of a given computational tool.
  • Navigate and extract information from annotated chemical libraries.
  • Construct and interpret drug-protein interaction networks.
  • Create scientific posters and present projects orally.
  • Apply peer-assessment on scientific report writing.


Data sets: Extraction of data from a large database, evaluation of structural diversity.
Molecular structures: Graphical representation, 1D, 2D and 3D molecular structures, pharmacophores.
Molecular descriptors: Generation of descriptors reflecting the physical and chemical properties of the molecules. Molecular fingerprints.
Data analysis: Clustering, classification and regression methods. Multi-linear regression. self-organizing maps, principal component analysis, artificial neural networks, decision trees, support vector machines.
Applications of chemoinformatics in drug research: Chemical libraries, chemogenomics, virtual screening, docking, protein-ligand interactions, network pharmacology, quantitative structure-activity relationships (QSARs), and prediction of ADMET properties (absorption, distribution, metabolism, elimination and toxicity).
Tools: Internet-based programs, databases, in-house and commercial programs.

Green challenge participation:

Please contact the teacher for information on whether this course gives the student the opportunity to prepare a project that may participate in DTU´s Study Conference on sustainability, climate technology, and the environment (GRØN DYST). More infor http://www.groendyst.dtu.dk/english


Ole Lund , Lyngby Campus, Building 208, Ph. (+45) 4525 2425 , lund@cbs.dtu.dk


27 Department of Systems Biology

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Last updated: 11. juli, 2016