Importance sampling of chemical compound space: Thermodynamic properties from high-throughput coarse-grained simulations

点击翻译按钮获取中文摘要

The computer-assisted rational design of small molecules to optimize the function of a biomolecular process is a challenging endeavor that holds many promises. In this context, the use of computer simulations is still impinged by computational resources, limiting the typical number of compounds within a single project to 10-100. The underlying concept is the exploration of chemical space, and how molecular structures impact the desired function. A more systematic approach to the problem necessarily requires much larger numbers of molecules. This project aims at developing the realm of high-throughput biomolecular simulations to evaluate free energies of a large number of compounds subject to a certain environment. The goal is made possible by the combination of two complementary techniques. First, coarse-grained modeling alleviates the computational investment of each compound, as well as the size of chemical space. The parallel between coarse-graining's role as the means to reduce both phase space and chemical space is highlighted, suggesting a promising route to more systematically explore the variety of molecular structures. Further, the introduction of an importance-sampling scheme helps the directed evolution of small molecules to optimize a given function. The novel methodology is applied to two biomolecular scenarios: small-molecule insertion in the membrane (i.e., anaesthetics) and protein-ligand binding.