Applied Computational Chemistry


Students shall be able to model complex organic systems and to understand their reactivity, with particular emphasis on asymmetric systems. Integration of knowledge with the subjects of organic chemistry and structural analysis. Training on common strategies for the establishment of structure-property relationships (QSAR). Acquisition of theoretical and practical skills on the use of computational tools for drug discovery and drug development.

General characterization





Responsible teacher

António Gil de Oliveira Santos, João Montargil Aires de Sousa


Weekly - 4

Total - 50

Teaching language



Good knowledge of Organic and Physical Chemistry. Basic knowledge of Mathematics.


1. A Guide to Molecular Mechanisms and Quantum Chemical Calculations, Warren. J. Hehre, Wavefunction, Inc., 2003.

2. Molecular Modelling, Principles and Applications, Andrew R. Leach, 2nd Ed., Pearson, Prentice Hall, 2001.

3. Introduction to Computational Chemistry, Frank Jensen, John Wiley and Sons, 1999.

4. Chemoinformatics - A Textbook, eds. Johann Gasteiger and Thomas Engel, Wiley-VCH, 2003.

5. Handbook of Chemoinformatics, ed. Johann Gasteiger, Wiley-VCH, 2003.

6. Chemoinformatics: Basic Concepts and Methods, eds. Thomas Engel and Johann Gasteiger, Wiley-VCH, 2018.

7. Applied Chemoinformatics: Achievements and Future Opportunities, eds. Thomas Engel and Johann Gasteiger, Wiley-VCH, 2018.

Teaching method

Classes use modern multimedia techniques. Students have access to desktop computers with software for 3D modelling and visualization as well as to the computer clusters working in our Department.

Evaluation method

Evaluation of the first part (Chemoinformatics, 50%) consists of a multiple choice test covering any aspect of the contents, both theoretical and practical, including the tutorials. The second part (50%) is evaluated with two tests (25% each, one theoretical and the other practical). Approval requires an average mark >= 9.5/20.

Subject matter

1. Computational molecular modelling as a tool in organic chemistry.

2. Structure-activity and structure-property relationships (QSAR and QSPR).

3. Computer-assisted synthesis design.

4. Software for molecular edition. Molecular mechanics. Docking.

5. The role of Computational Chemistry in drug discovery.

6. Software for quantum calculation.

7. Most common theoretical approaches in the rationalization of chemical reactivity.

8. Calculation of structures in solvent, excited states and transition states. Frequency calculations and thermodynamic corrections.

9. Modelling of asymmetric systems.


Programs where the course is taught: