RT Journal Article
T1 Extending PROXIMAL to predict degradation pathways of phenolic compounds in the human gut microbiota.
A1 Balzerani, Francesco
A1 Blasco, Telmo
A1 Pérez-Burillo, Sergio
A1 Valcárcel, Luis V
A1 Hassoun, Soha
A1 Planes, Francisco Javier
K1 Biología computacional
K1 Bioinformática
K1 Fenoles
K1 Enzimas
K1 Degradación biológica
AB Despite significant advances in reconstructing genome-scale metabolic networks, the understanding of cellular metabolism remains incomplete for many organisms. A promising approach for elucidating cellular metabolism is analysing the full scope of enzyme promiscuity, which exploits the capacity of enzymes to bind to non-annotated substrates and generate novel reactions. To guide time-consuming costly experimentation, different computational methods have been proposed for exploring enzyme promiscuity. One relevant algorithm is PROXIMAL, which strongly relies on KEGG to define generic reaction rules and link specific molecular substructures with associated chemical transformations. Here, we present a completely new pipeline, PROXIMAL2, which overcomes the dependency on KEGG data. In addition, PROXIMAL2 introduces two relevant improvements with respect to the former version: i) correct treatment of multi-step reactions and ii) tracking of electric charges in the transformations. We compare PROXIMAL and PROXIMAL2 in recovering annotated products from substrates in KEGG reactions, finding a highly significant improvement in the level of accuracy. We then applied PROXIMAL2 to predict degradation reactions of phenolic compounds in the human gut microbiota. The results were compared to RetroPath RL, a different and relevant enzyme promiscuity method. We found a significant overlap between these two methods but also complementary results, which open new research directions into this relevant question in nutrition.
PB Springer Nature
YR 2024
FD 2024-05-27
LK https://hdl.handle.net/10630/38630
UL https://hdl.handle.net/10630/38630
LA eng
NO Balzerani F, Blasco T, Pérez-Burillo S, Valcarcel L V., Hassoun S, Planes FJ. Extending PROXIMAL to predict degradation pathways of phenolic compounds in the human gut microbiota. npj Systems Biology and Applications 2024 10:1. 2024;10:1–11.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 21 ene 2026