Computational Chemical Biology

Common human diseases result from the interplay of many genes and environmental factors. Furthermore, a drug rarely acts only on one target but follows a similarly complex interaction with proteins. Therefore, an integrative chemical biology approach is needed to unravel the genetic background of diseases and to provide the best possible medicinal treatment.
The Computational Chemical Biology group at CBS has evolved from the former group of Chemoinformatics, with interest in exploring via computational methods the interplay between small molecules and biological systems.


Current areas of interest include

• Chemogenomics mapping of natural compounds.
• Mapping of the pharmacological space of small molecules based on bioassays.
• Associating drugs and drug candidates to clinical outcomes via therapeutic targets and protein-protein interaction networks.
• Predicting adverse effects of drugs via tissue-specific gene expression data.
• Predicting the activity profiles of new psychoactive drug candidates by building informative drug-target interaction networks.

The overall aim of the research focus of CCB is to elucidate the biological profile of small molecules regarding their targets, off-targets, phenotypic outcome and side-effects via an in-depth understanding of the biological networks that lead to disease and the perturbations on them that can be caused by small molecules.


Data collection

• ~50.000 natural products
• ~200.000 drugs with protein targets and/or disease annotation
• ~20 million molecules

Expertise: molecular modeling, machine learning methods (QSAR, NN, SVM,...), chemogenomics and chemical-biological networks.


Fields

• Transporters, GPCR
• Nuclear receptors
• Metabolism and cytochrome P450
• Toxicity
• Antimicrobial Peptides