Mohr Bernadette, van der Mast Diego, Bereau Tristan
Van 't Hoff Institute for Molecular Sciences and Informatics Institute, University of Amsterdam, Amsterdam 1098 XH, The Netherlands.
Max Planck Institute for Polymer Research, Mainz 55128, Germany.
J Chem Theory Comput. 2023 Jul 25;19(14):4770-4779. doi: 10.1021/acs.jctc.3c00201. Epub 2023 Jul 3.
Molecular design requires systematic and broadly applicable methods to extract structure-property relationships. The focus of this study is on learning thermodynamic properties from molecular-liquid simulations. The methodology relies on an atomic representation originally developed for electronic properties: the Spectrum of London and Axilrod-Teller-Muto representation (SLATM). SLATM's expansion in one-, two-, and three-body interactions makes it amenable to probing structural ordering in molecular liquids. We show that such representation encodes enough critical information to permit the learning of thermodynamic properties via linear methods. We demonstrate our approach on the preferential insertion of small solute molecules toward cardiolipin membranes and monitor selectivity against a similar lipid. Our analysis reveals simple, interpretable relationships between two- and three-body interactions and selectivity, identifies key interactions to build optimal prototypical solutes, and charts a two-dimensional projection that displays clearly separated basins. The methodology is generally applicable to a variety of thermodynamic properties.
分子设计需要系统且广泛适用的方法来提取结构-性质关系。本研究的重点是从分子液体模拟中学习热力学性质。该方法依赖于最初为电子性质开发的原子表示:伦敦光谱和阿西洛德-泰勒-武藤表示(SLATM)。SLATM在一、二和三体相互作用中的展开使其适合于探测分子液体中的结构有序性。我们表明,这种表示编码了足够的关键信息,以允许通过线性方法学习热力学性质。我们在小溶质分子向心磷脂膜的优先插入方面展示了我们的方法,并监测了对类似脂质的选择性。我们的分析揭示了二体和三体相互作用与选择性之间简单、可解释的关系,确定了构建最佳原型溶质的关键相互作用,并绘制了一个二维投影,该投影显示了明显分离的区域。该方法通常适用于各种热力学性质。