Lütge Sebastian, Krebs Maximilian, Risselada Herre Jelger
Department of Physics, Technische Universität Dortmund, 44227 Dortmund, Germany.
J Phys Chem B. 2025 Mar 6;129(9):2482-2492. doi: 10.1021/acs.jpcb.4c08200. Epub 2025 Feb 21.
Exploring the vast chemical space of small molecules poses a significant challenge. We develop a new strategy to efficiently explore this space using coarse-grained toy-like molecules utilizing the Martini3 force field and graph representations. This yields initial proof-of-concept results for the approach enabling the identification of optimal molecules with specific properties targeting lipid bilayers. By leveraging genetic algorithms and coarse-grained molecular dynamics simulations, we demonstrate the potential of our method in designing simple, linear molecules. Our findings show a good convergence toward molecules with weak amphiphilic properties, resembling known (general anesthetic) molecules. While this study demonstrates the feasibility of our method, further refinement is needed to fully realize its potential and explore more complex molecular topologies. Nevertheless, these encouraging results suggest a new path for future research in small molecule discovery and design without relying on extensive data sets.
探索小分子的广阔化学空间是一项重大挑战。我们开发了一种新策略,利用基于Martini3力场的粗粒度类玩具分子和图形表示来有效探索这一空间。这为该方法产生了初步的概念验证结果,能够识别针对脂质双层具有特定性质的最佳分子。通过利用遗传算法和粗粒度分子动力学模拟,我们证明了我们的方法在设计简单线性分子方面的潜力。我们的研究结果表明,该方法能很好地收敛到具有弱两亲性的分子,类似于已知的(全身麻醉)分子。虽然这项研究证明了我们方法的可行性,但仍需要进一步优化以充分发挥其潜力并探索更复杂的分子拓扑结构。尽管如此,这些令人鼓舞的结果为未来不依赖大量数据集的小分子发现和设计研究开辟了一条新途径。