Faculty of Chemistry and Chemical Engineering, University of Maribor, Smetanova ulica 17, Maribor SI-2000, Slovenia.
The Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Glagoljaška 8, Koper SI-6000, Slovenia.
J Chem Inf Model. 2023 Aug 28;63(16):5204-5219. doi: 10.1021/acs.jcim.3c00558. Epub 2023 Aug 9.
In order to identify the locations of metal ions in the binding sites of proteins, we have developed a method named the MADE (MAcromolecular DEnsity and Structure Analysis) approach. The MADE approach represents an evolution of our previous toolset, the ProBiS HO (MD) methodology, for the identification of conserved water molecules. Our method uses experimental structures of proteins homologous to a query, which are subsequently superimposed upon it. Areas with a particular species present in a similar location among many homologous protein structures are identified using a clustering algorithm. Dense clusters likely represent positions containing species important to the query protein structure or function. We analyze well-characterized protein structures and show that the MADE approach can identify clusters corresponding to the expected positions of metal ions in their binding sites. The greatest advantage of our method lies in its generality. It can in principle be applied to any species found in protein records; it is not only limited to metal ions. We additionally demonstrate that the MADE approach can be successfully applied to predict the location of cofactors in computer-modeled structures, e.g., via AlphaFold. We also conduct a careful protein superposition method comparison and find our methodology robust and the results largely independent of the selected protein superposition algorithm. We postulate that with increasing structural data availability, additional applications of the MADE approach will be possible such as non-protein systems, water network identification, protein binding site elaboration, and analysis of binding events, all in a dynamic manner. We have implemented the MADE approach as a plugin for the PyMOL molecular visualization tool. The MADE plugin is available free of charge at https://gitlab.com/Jukic/made_software.
为了确定蛋白质结合位点中金属离子的位置,我们开发了一种名为 MADE(大分子密度和结构分析)的方法。MADE 方法是我们之前的 ProBiS HO(MD)方法的改进,用于鉴定保守水分子。我们的方法使用与查询相关的蛋白质实验结构,随后将其叠加在查询结构上。使用聚类算法识别在许多同源蛋白质结构中具有相似位置的特定物种的区域。密集的聚类可能代表包含对查询蛋白质结构或功能重要的物种的位置。我们分析了具有良好特征的蛋白质结构,并表明 MADE 方法可以识别与金属离子在其结合位点中的预期位置相对应的聚类。我们方法的最大优势在于其通用性。它原则上可以应用于蛋白质记录中发现的任何物种;它不仅限于金属离子。我们还证明,MADE 方法可以成功地应用于预测计算机建模结构中辅助因子的位置,例如通过 AlphaFold。我们还进行了仔细的蛋白质叠加方法比较,发现我们的方法稳健,结果在很大程度上独立于所选的蛋白质叠加算法。我们假设,随着结构数据可用性的增加,MADE 方法将有更多的应用,例如非蛋白质系统、水网络识别、蛋白质结合位点阐述以及结合事件分析,所有这些都以动态的方式进行。我们已经将 MADE 方法实现为 PyMOL 分子可视化工具的插件。MADE 插件可在 https://gitlab.com/Jukic/made_software 免费获得。