AI-Designed Pipeline Identifies Lapatinib as Potential Drug for Monkeypox and LSDV
Scientists at the CSIR-Indian Institute of Chemical Technology (IICT) have developed an artificial intelligence-driven pipeline to identify potential therapies for poxvirus infections, including monkeypox and Lumpy Skin Disease Virus (LSDV). The research, led by Ramars Amanchy, focuses on these zoonotic viruses that pose threats to public health and livestock.
The team created an AI-enabled structural bioinformatics pipeline that combines sequence conservation analysis, phylogenetic mapping, advanced protein structure prediction tools, active-site mapping, molecular docking, and molecular dynamics simulations. This approach identified two conserved kinases as promising drug targets—enzymes used by the viruses to evade immune responses.
Further analysis zeroed in on LSDV and identified the drug lapatinib as a potential competitive inhibitor. Lapatinib, already approved for cancer treatment, showed stable binding and favourable interaction energies during computer simulations. The researchers also found that the kinase inhibitors share physicochemical properties with existing veterinary antivirals, suggesting they could be repurposed for animal health.
Drug repurposing—using approved medicines for new therapeutic purposes—offers a faster and more cost-effective alternative to traditional drug development, the scientists noted. The study highlights the value of leveraging existing drugs to combat emerging viral threats.
The IICT team also developed a combinatorial analog library to support future experimental validation and optimisation. While the findings are promising, the researchers emphasised that laboratory validation, including biochemical assays and antiviral studies, is essential to confirm the therapeutic potential of these compounds.
Viruses like LSDV and monkeypox not only threaten health but also disrupt economies and livelihoods, said Amanchy. The AI-driven approach demonstrates India’s potential to develop rapid, affordable solutions for global health challenges.
The study, titled 'AI-Enabled Structural Bioinformatics Identifies Repositioned Kinase Inhibitor Against Poxviridae Kinases', has been accepted for publication in the journal Computers in Biology and Medicine.
