Advanced modeling of salt-inducible kinase (SIK) inhibitors incorporating protein flexibility through molecular dynamics and cross-docking.

IF 3.8 2区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES

Scientific Reports Pub Date : 2025-05-29 DOI:10.1038/s41598-025-03699-w

Jorge Luis Valdés-Albuernes, Erbio Díaz-Pico, Sergio Alfaro, Julio Caballero

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Abstract

Salt-inducible kinases (SIK1, SIK2, and SIK3) regulate metabolism and immune responses, making them promising targets for inflammatory and autoimmune diseases. Understanding inhibitor selectivity among isoforms is crucial for therapeutic development. In this study, 44 compounds were investigated as SIK inhibitors using molecular modeling. A flexible treatment of the kinases via molecular dynamics (MD) simulations captured binding site conformational changes, followed by molecular docking to generate protein kinase (PK)-ligand complex models. Ligand orientations were validated against crystallographic data using LigRMSD and interaction fingerprints (IFPs). A genetic algorithm was applied to select conformations that maximize correlation between docking energies and biological activities, yielding R² values of 0.821, 0.646, and 0.620 for SIK1, SIK2, and SIK3, respectively. Our results highlight the importance of protein flexibility in achieving accurate correlations between docking energies and experimental pIC₅₀ values, enhancing inhibitor selectivity predictions.

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盐诱导激酶（SIK）抑制剂通过分子动力学和交叉对接的先进建模，结合蛋白质的灵活性。

盐诱导激酶（SIK1， SIK2和SIK3）调节代谢和免疫反应，使其成为炎症和自身免疫性疾病的有希望的靶点。了解同种异构体之间抑制剂的选择性对治疗发展至关重要。本研究利用分子模型研究了44个化合物作为SIK抑制剂。通过分子动力学（MD）模拟对激酶进行灵活处理，捕获结合位点构象变化，随后进行分子对接，生成蛋白激酶(PK)-配体复合物模型。利用LigRMSD和相互作用指纹图谱（IFPs）对晶体学数据验证配体取向。采用遗传算法选择对接能与生物活性相关性最大的构象，得到SIK1、SIK2和SIK3的R²值分别为0.821、0.646和0.620。我们的研究结果强调了蛋白质灵活性在实现对接能量和实验pIC50值之间的准确相关性方面的重要性，增强了抑制剂选择性预测。

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来源期刊

Scientific Reports Natural Science Disciplines-

CiteScore

7.50

自引率

4.30%

发文量

19567

审稿时长

3.9 months

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