By Blessing Ibegbu

A Nigerian researcher, Dr Gideon Gyebi, says emerging computational technologies can accelerate the discovery of new antibiotics and overcome the global challenge of antimicrobial resistance (AMR).

Gyebi, a scientist in Computational and Systems Biology, stated this while highlighting findings from his recent study to the News Agency of Nigeria (NAN) in Abuja on Tuesday.

The study is titled “Computational profiling of terpenoids for putative dual-target leads against Staphylococcus Aureus Penicillin-Binding Protein 2a and Beta-Lactamase.”

The research, showcased at the Durban University of Technology, South Africa,
demonstrates how Artificial Intelligence (AI), machine learning and molecular modelling could fast-track drug discovery.

According to him, the research focuses on Staphylococcus aureus (S. aureus), a bacteria responsible for many hospital-acquired infections and a major symbol of antimicrobial resistance.

He also stated that the emergence of Methicillin-Resistant Staphylococcus Aureus (MRSA) had made it a global public health challenge, as it significantly limits the effectiveness of commonly used antibiotics.

“By focusing on S. aureus, this study directly addresses an urgent need for innovative strategies to combat antimicrobial resistance.

“Computational biology is transforming the way we think about medicine and by simulating how potential drugs interact with bacterial proteins, we can guide experiments more intelligently and make discoveries faster.

“Computational studies provide speed, cost-efficiency and precision that are not always possible with traditional lab experiments alone.

“While thousands of compounds can be virtually screened in few hours under computational studies, laboratory testing of the same compounds would take months or years,” Gyebi said.

According to him, computational modelling allows researchers to see how drugs interact with bacterial proteins at the molecular level, which is very difficult to observe directly in the lab.

He further explained that under computational studies, promising compounds could be prioritised before expensive and time-consuming experimental validation, hence saving resources.

The scientist, however, added that the tools does not replace experiments but complement them, thereby providing a roadmap that make laboratory studies more focused and efficient.

“Emerging computational approaches enhance the possibility of successfully addressing antibiotic resistance by speeding up discovery and minimising trial-and-error.”

Gyebi said his study used these tools to identify natural compounds, known as terpenoids, that could simultaneously block two major bacterial defence systems which were Penicillin-Binding Protein 2a (PBP2a) and B-lactamase.

“The synthesis of B-lactamase, an enzyme that degrades B-lactam antibiotics before they can take effect, is one of the key resistant mechanisms of S.aureus.

“The methicillin-resistant Staphylococcus aureus carries a modified penicillin-binding protein called PBP2a, which has a very low affinity for most B-lactam antibiotics, making them ineffective.

“This is why a double defense system which includes enzyme destruction of antibiotics and target modification to reduce affinity for antibiotic is needed.

“Even if one mechanism is bypassed, the other still protects the bacterium and the
dual-target approach could restore the effectiveness of common antibiotics that S. aureus has learned to resist,” the researcher said.

According to him, by targeting both B-lactamase and PBP2a simultaneously, antibiotics have a much higher chance of working effectively against S. aureus.

NAN reports that the World Health Organisation (WHO) had listed antimicrobial resistance as one of the top ten global public health threats, with projections indicating it could cause ten million deaths annually by 2050 if not controlled.

With more than 70 publications indexed in Scopus and Web of Science and over a thousand citations, Gyebi is among Africa’s emerging scientists using technology to tackle pressing global health challenges.

He said the integration of computational studies, artificial intelligence and biotechnology could redefine the global antibiotic discovery pipeline and provide faster solutions to the growing threat of drug-resistant infections. (NAN)(www.nannews.ng)

Edited by Magdalene Ukuedojor