Heyram K, Manikandan J, Prabhu D, Jeyakanthan J
Structural Biology and Biocomputing Lab, Department of Bioinformatics, Alagappa University, Karaikudi, India.
Centre for Drug Discovery, Department of Biotechnology, Karpagam Academy of Higher Education, Coimbatore, India.
SAR QSAR Environ Res. 2024 Dec;35(12):1129-1154. doi: 10.1080/1062936X.2024.2443844. Epub 2025 Jan 8.
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.
糖尿病（DM）在印度影响着超过7700万成年人，预计到2045年病例数将达到1.34亿。目前的治疗方法，包括磺脲类和噻唑烷二酮类，并不充分，这凸显了对新型治疗策略的需求。本研究调查海洋天然产物（MNPs）作为针对SIK2的替代治疗剂，SIK2是一种参与糖尿病的关键酶。使用计算方法验证了预测的SIK2模型的结构稳定性，随后将其用于对超过38000种MNPs进行基于结构的虚拟筛选（SBVS）。该方法确定了五个有前景的候选物：来自综合海洋天然产物数据库的CMNPD21753和CMNPD13370、来自海洋天然产物数据库的MNPD10685以及来自海藻代谢物数据库的SWMDRR053和SWMDRR052。所鉴定的化合物对接分数范围为-7.64至-11.95 kcal/mol，MMGBSA结合分数在-33.29至-68.29 kcal/mol之间，具有良好的预测药代动力学和毒性特征。分子动力学模拟（MDS）显示，与已知的SIK2抑制剂ARN-3236相比，这些化合物具有更强的预测结合亲和力。基于主成分（PC）的自由能景观（FEL）分析进一步支持了这些化合物与SIK2的稳定结合。这些计算结果突出了这些先导化合物作为新型SIK2抑制剂的潜力，值得未来进行体外和体内验证。
