Theoretical and Computational Biosciences

Theoretical and Computational Biochemistry
TCB Research Labs

The TCB Group develops research in computational sciences applied to human health. The group uses in silico approaches to decode multi-omics profiles and simulate biomolecular interactions, with the final goal of discovering new biomarkers and drugs.


The TCB group aims to improve our knowledge about the molecular mechanisms underlying gene expression regulation. Hence, we are combining genome-wide profiles of genome, epigenome, and transcriptome to unveil how molecular alterations can disrupt cell homeostasis. In such line, we have contributed for the development of computational pipelines to identify transcription noise and to process high-throughput sequencing profiles of nascent transcripts. Moreover, we are exploring the crosstalk between cancer cells and respective microenvironment to identify future prognostic biomarkers or therapeutic targets. This work has been developed within multidisciplinary networks, including hospitals, to foster precision medicine approaches into the biomedical research and healthcare.


In parallel, through biomolecular simulations we aim to understand how enzymes catalyze their reactions and to use this knowledge to rationally develop new, more effective, and “greener” biocatalysts for the pharmaceutical, chemical and food industries. We are also involved in the development of computational drug development methodologies and have established strategic collaboration networks with several experimental research groups, bridging fundamental and applied research. In particular, we have designed target-specific protocols for the identification of promising drug candidates for experimental testing and have been involved in the rationalization of experimental results, and in drug optimization. In addition, we currently maintain open scientific databases of reference on Biofilm research ( and on Legionella outbreaks (

Recent publications
Sabino, JC; de Almeida, MR; Abreu, PL; Ferreira, AM; Caldas, P; Domingues, MM; Santos, NC; Azzalin, CM; Grosso, AR; de Almeida, SF. 2022. Epigenetic reprogramming by TET enzymes impacts co-transcriptional R-loops. eLife, 11, DOI: 10.7554/eLife.69476
Sobral, D; Francisco, R; Duro, L; Videira, PA; Grosso, AR. 2022. Concerted Regulation of Glycosylation Factors Sustains Tissue Identity and Function. BIOMEDICINES, 10, DOI: 10.3390/biomedicines10081805
Sobral, Daniel; Martins, Marta; Kaplan, Shannon; Golkaram, Mahdi; Salmans, Michael; Khan, Nafeesa; Vijayaraghavan, Raakhee; et al. 2022. Genetic and microenvironmental intra-tumor heterogeneity impacts colorectal cancer evolution and metastatic development. Communications Biology, 5, DOI: 10.1038/s42003-022-03884-x
Yu Ting Ong, Jorge Andrade and Max Armbruster, Chenyue Shi, Marco Castro, Ana S. H. Costa, Toshiya Sugino, Guy Eelen, Barbara Zimmermann, Kerstin Wilhelm, Joseph Lim, Shuichi Watanabe, Stefan Guenther, Andre Schneider, Francesca Zanconato, Manuel Kaulich, Duojia Pan and Thomas Braun, Holger Gerhardt, Alejo Efeyan, Peter Carmeliet, Stefano Piccolo, Ana Rita Grosso, Michael Potente. 2022. A YAP/TAZ-TEAD signalling module links endothelial nutrient acquisition to angiogenic growth. Nature Metabolism, 4, DOI: 10.1038/s42255-022-00584-y
Juliana FRocha; Sérgio FSousa; Nuno MFSousa ACerqueira. 2022. Computational Studies Devoted to the Catalytic Mechanism of Threonine Aldolase, a Critical Enzyme in the Pharmaceutical Industry to Synthesize β-Hydroxy-α-amino Acids. ACS Catalysis, DOI: 10.1021/acscatal.1c05567