A recent experimental research study, led by University professor Pablo de Olavide Younes Smaniprincipal investigator of the ‘Bacterial Infections’ group at the Andalusian Center for Developmental Biology (CABD), and carried out in collaboration with the National School of Applied Sciences of Tangier of the Abdelmalek Essaadi University (Morocco), discovers new antibiotics through use of artificial intelligence for the treatment of infections caused by multidrug-resistant bacteria Acinetobacter baumannii.
The collaborative work has been published in the international magazine mSystems of the American Society for Microbiology.
infections due to Acinetobacter baumannii represent a serious threat to global health, with alarming levels of antimicrobial resistance resulting in significant morbidity and mortality in the United States, according to data provided by the United States Centers for Disease Control and Prevention (CDC). Centers for Disease Control and Prevention).
“To address this threat, novel strategies beyond traditional antibiotics are imperative. Computational approaches, such as QSAR models (of English, Quantitative Structure-Activity Relationship), take advantage of molecular structures to predict biological effects, accelerating drug discovery,” argues Dr. Younes Smani, professor in the UPO Microbiology Area.
Taking the conclusions of a previous investigation, in which Younes Smani’s team identified the outer membrane protein W (OmpW) as a therapeutic target in Acinetobacter baumanniithe authors have analyzed a total of 11,648 natural compounds, identifying the active compound of curcumin called demethoxycurcumin as a blocking substance for OmpW.
“We used QSAR models of a bioactivity data set from ChEMBL (database of bioactive molecules with pharmaceutical-like properties) and performed virtual structure-based screening against OmpW,” says Dr. Younes Smani, who explains how identified demethoxycurcumin as a compound capable of exhibiting promising antibacterial activity against Acinetobacter baumanniiincluding multiresistant strains.
The results obtained thus highlight the potential of artificial intelligence in the discovery of curcuminoids as effective antimicrobial agents against infections Acinetobacter baumannii, offering a promising strategy to address antibiotic resistance.
Scientific synergy
The collaboration between Younes Smani’s team and the National School of Applied Sciences of Tangier arose thanks to the visit of professors from the Abdelmalek Essaadi University, within the framework of the Erasmus+ KA171 program, to the Andalusian Center for Developmental Biology (center mixed of the Pablo de Olavide University, CSIC and Junta de Andalucía), where they had the opportunity to learn up close about the infrastructure that the CABD has and the research that is carried out.
Dr. Younes Smani highlights the importance of creating synergies “which lies in generating significant advances in the fields of microbiology and computational biology, taking advantage of the strengths and resources of each research group. “This allows exploring new frontiers at the intersection of microbiology and computational biology, leading to disruptive innovations.”
Reference:
Boulaamane Y, Molina Panadero I, Hmadcha A, Atalaya Rey C, Baammi S, El Allali A, Maurady A, Smani Y. Antibiotic discovery with artificial intelligence for the treatment of Acinetobacter baumannii infections. mSystems. 2024 May 3:e0032524. doi:10.1128/msystems.00325-24
