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ForceGen 3D structure and conformer generation: from small lead-like molecules to macrocyclic drugs

机译:ForceGen 3D结构和构象异构体生成:从小的铅样分子到大环药物

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摘要

We introduce the ForceGen method for 3D structure generation and conformer elaboration of drug-like small molecules. ForceGen is novel, avoiding use of distance geometry, molecular templates, or simulation-oriented stochastic sampling. The method is primarily driven by the molecular force field, implemented using an extension of MMFF94s and a partial charge estimator based on electronegativity-equalization. The force field is coupled to algorithms for direct sampling of realistic physical movements made by small molecules. Results are presented on a standard benchmark from the Cambridge Crystallographic Database of 480 drug-like small molecules, including full structure generation from SMILES strings. Reproduction of protein-bound crystallographic ligand poses is demonstrated on four carefully curated data sets: the ConfGen Set (667 ligands), the PINC cross-docking benchmark (1062 ligands), a large set of macrocyclic ligands (182 total with typical ring sizes of 12–23 atoms), and a commonly used benchmark for evaluating macrocycle conformer generation (30 ligands total). Results compare favorably to alternative methods, and performance on macrocyclic compounds approaches that observed on non-macrocycles while yielding a roughly 100-fold speed improvement over alternative MD-based methods with comparable performance.
机译:我们介绍了用于3D结构生成和类药物小分子构象异构体构建的ForceGen方法。 ForceGen新颖,避免使用距离几何,分子模板或面向仿真的随机采样。该方法主要由分子力场驱动,该分子力场使用MMFF94s的扩展和基于电负性均衡的部分电荷估算器实现。力场与用于直接采样由小分子进行的实际物理运动的算法耦合。结果以480种药物样小分子的剑桥晶体数据库的标准基准表示,包括从SMILES琴弦生成的完整结构。在四个精心策划的数据集上证明了结合蛋白质的晶体学配体位姿的再现:ConfGen集(667个配体),PINC交叉对接基准(1062个配体),一大套大环配体(总共182个,典型环尺寸为)。 12–23个原子),以及用于评估大环构象异构体生成的常用基准(总共30个配体)。结果优于替代方法,并且在大环化合物上的性能接近在非大环上观察到的性能,同时与具有替代性能的基于MD的替代方法相比,速度提高了约100倍。

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