At BioLab we perform the biological evaluation of synthetic and natural compounds against a panel of representative human solid tumor cell lines. From this test, we determine if compounds are active and/or interesting to go into depth. We try to shed light on the mechanism of action by studying the effects of the products at a molecular level. Our ultimate goal is to identify the biological target(s) at which the active compound is directed. While the core activities of BioLab remain in this specific topic, in the past recent years we have expanded our capacities.

At present, three divisions comprise BioLab, namely Bioevaluation, Synthesis and Computation.

Bioevaluation

We perform the biological evaluation of synthetic and natural compounds against a panel of representative human solid tumour cell lines. From this test, we determine if compounds are active and/or interesting to go into depth. We try to shed light on the mechanism of action by studying the phenotypic effects of the products at a molecular level. Our ultimate goal is to identify the biological target(s) at which the active compound is directed.

Synthesis

Although compounds are provided from long-term establish collaborations with national and international chemistry groups, we implemented our own synthesis programme devoted to obtain new analogues with an enhanced biological activity profile. The design of analogues is based on the previous results from our own research. With all the information we elaborate a list of chemical structures selected on the basis of stucture-activity relationship studies or rational design in silico. Then, we design the most appropriate chemical routes to prepare the analogues.

Computation

In an effort to enhance our PDD strategy, we have envisioned the use of computational methods in combination with the data obtained from the phenotypic screen. Noteworthy, computational methods have played a major role in the development of therapeutically important small-molecules in the last decades. We have started the development of artificial neural networks modelling to correlate the chemical structure with the experimental data of the phenotypic assays in order to allow the prediction of activity, to run virtual screenings, or to anticipate pharmacokinetic and pharmacodynamics. We also use docking experiments to gain a better understanding on how small-molecules might bind to the cellular target.