Trezza Alfonso, Visibelli Anna, Roncaglia Bianca, Barletta Roberta, Iannielli Stefania, Mahboob Linta, Spiga Ottavia, Santucci Annalisa
ONE-HEALTH Laboratory, Department of Biotechnology Chemistry Pharmacy, University of Siena, Via Aldo Moro, 2, 53100 Siena, Italy.
SienabioACTIVE, University of Siena, Via Aldo Moro, 2, 53100 Siena, Italy.
Int J Mol Sci. 2025 Apr 23;26(9):3971. doi: 10.3390/ijms26093971.
Computational methods have transformed target and drug discovery, significantly accelerating the identification of biological targets and lead compounds. Despite its limitations, in silico molecular docking represents a foundational tool. Molecular Dynamics (MD) simulations, employing accurate force fields, provide near-realistic insights into a compound's behavior within a biological target. However, docking and MD predictions may be unreliable without precise knowledge of the target binding site. Through MD simulations, we investigated 100 co-crystal structures of biological targets complexed with active compounds, identifying key structural and energy dynamic features that govern target-ligand interactions. Our analysis provides a detailed quantitative description of these parameters, offering critical validation for improving the predictive reliability of docking and MD simulations. This work provides a robust framework for refining early-stage drug discovery and target identification.
计算方法已经改变了靶点和药物发现过程，显著加速了生物靶点和先导化合物的识别。尽管存在局限性，但计算机辅助分子对接仍是一项基础工具。分子动力学（MD）模拟利用精确的力场，能够提供关于化合物在生物靶点内行为的近乎真实的见解。然而，如果对靶点结合位点缺乏精确了解，对接和MD预测可能并不可靠。通过MD模拟，我们研究了100个生物靶点与活性化合物复合的共晶体结构，确定了控制靶点-配体相互作用的关键结构和能量动态特征。我们的分析对这些参数进行了详细的定量描述，为提高对接和MD模拟的预测可靠性提供了关键验证。这项工作为优化早期药物发现和靶点识别提供了一个强大的框架。
