Departamento de Ciencia y Tecnología, Universidad Nacional de Quilmes, Bernal B1876BXD, Argentina.
Departamento de Ciencia y Tecnología, Universidad Nacional de Quilmes, Bernal B1876BXD, Argentina; Departamento de Ciencias Básicas, Facultad de Agronomía, Universidad Nacional del Centro de la Provincia de Buenos Aires, Azul, Buenos Aires B7300, Argentina.
J Mol Biol. 2024 Dec 1;436(23):168852. doi: 10.1016/j.jmb.2024.168852. Epub 2024 Nov 6.
Protein-ligand interactions represent an essential step to understand the bases of molecular recognition, an intense field of research in many scientific areas. Structural biology has played a central role in unveiling protein-ligand interactions, but current techniques are still not able to reliably describe the interactions of ligands with highly flexible regions. In this work, we explored the capacity of AlphaFold2 (AF2) to estimate the presence of interactions between ligands and residues belonging to disordered regions. As these interactions are missing in the crystallographic-derived structures, we called them "ghost interactions". Using a set of protein structures experimentally obtained after AF2 was trained, we found that the obtained models are good predictors of regions associated with order-disorder transitions. Additionally, we found that AF2 predicts residues making ghost interactions with ligands, which are mostly buried and show differential evolutionary conservation with the rest of the residues located in the flexible region. Our findings could fuel current areas of research that consider, given their biological relevance and their involvement in diseases, intrinsically disordered proteins as potentially valuable targets for drug development.
蛋白质-配体相互作用是理解分子识别基础的关键步骤,这是许多科学领域的一个研究热点。结构生物学在揭示蛋白质-配体相互作用方面发挥了核心作用,但目前的技术仍然无法可靠地描述配体与高度灵活区域的相互作用。在这项工作中,我们探索了 AlphaFold2 (AF2) 估计配体与无序区域残基之间相互作用存在的能力。由于这些相互作用在晶体学衍生结构中不存在,我们称之为“幽灵相互作用”。使用一组在训练完 AF2 后通过实验获得的蛋白质结构,我们发现所得到的模型是与构象转变相关区域的良好预测因子。此外,我们发现 AF2 预测与配体发生幽灵相互作用的残基,这些残基主要是埋藏的,并且与位于柔性区域的其余残基的进化保守性不同。我们的发现可以为当前的研究领域提供动力,这些领域考虑到内在无序蛋白质的生物学相关性及其在疾病中的参与,将其作为药物开发的潜在有价值的靶点。