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Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
Published on: February 23, 2024
Computational insights into marine natural products as potential antidiabetic agents targeting the SIK2 protein
K Heyram1, J Manikandan1, D Prabhu2
1Structural Biology and Biocomputing Lab, Department of Bioinformatics, Alagappa University, Karaikudi, India.
Abstract:
Diabetes mellitus (DM) affects over 77 million adults in India, with cases expected to reach 134 million by 2045. Current treatments, including sulfonylureas and thiazolidinediones, are inadequate, underscoring the need for novel therapeutic strategies. This study investigates marine natural products (MNPs) as alternative therapeutic agents targeting SIK2, a key enzyme involved in DM. The structural stability of the predicted SIK2 model was validated using computational methods and subsequently employed for structure-based virtual screening (SBVS) of over 38,000 MNPs. This approach identified five promising candidates: CMNPD21753 and CMNPD13370 from the Comprehensive Marine Natural Product Database, MNPD10685 from the Marine Natural Products Database, and SWMDRR053 and SWMDRR052 from the Seaweed Metabolite Database. The identified compounds demonstrated docking scores ranging from -7.64 to -11.95 kcal/mol and MMGBSA binding scores between -33.29 and -68.29 kcal/mol, with favourable predicted pharmacokinetic and toxicity profiles. Molecular dynamics simulations (MDS) revealed stronger predicted binding affinity for these compounds compared to ARN-3236, a known SIK2 inhibitor. Principal component (PC)-based free energy landscape (FEL) analysis further supported the stable binding of these compounds to SIK2. These computational findings highlight the potential of these leads as novel SIK2 inhibitors, warranting future in vitro and in vivo validation.
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