Dataset for quantum-mechanical exploration of conformers and solvent effects in large drug-like molecules

被引:7
|
作者
Medrano Sandonas, Leonardo [1 ,2 ,3 ]
Van Rompaey, Dries [4 ]
Fallani, Alessio [1 ,4 ]
Hilfiker, Mathias [1 ]
Hahn, David [5 ]
Perez-Benito, Laura [5 ]
Verhoeven, Jonas [4 ]
Tresadern, Gary [5 ]
Kurt Wegner, Joerg [4 ,6 ]
Ceulemans, Hugo [4 ]
Tkatchenko, Alexandre [1 ]
机构
[1] Univ Luxembourg, Dept Phys & Mat Sci, L-1511 Luxembourg, Luxembourg
[2] Tech Univ Dresden, Inst Mat Sci, D-01062 Dresden, Germany
[3] Tech Univ Dresden, Max Bergmann Ctr Biomat, D-01062 Dresden, Germany
[4] Janssen Pharmaceut NV, Drug Discovery Data Sci D3S, Turnhoutseweg 30, B-2340 Beerse, Belgium
[5] Janssen Pharmaceut NV, Computat Chem, Turnhoutseweg 30, B-2340 Beerse, Belgium
[6] Johnson & Johnson Innovat Med, Drug Discovery Data Sci D3S, 301 Binney St, Cambridge, MA 02142 USA
关键词
DENSITY-FUNCTIONAL THEORY; FORCE-FIELD; SOLVATION; PARAMETERS; EFFICIENT; MODEL; GEOMETRIES; ENERGIES; EXCHANGE; ROBUST;
D O I
10.1038/s41597-024-03521-8
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
We here introduce the Aquamarine (AQM) dataset, an extensive quantum-mechanical (QM) dataset that contains the structural and electronic information of 59,783 low-and high-energy conformers of 1,653 molecules with a total number of atoms ranging from 2 to 92 (mean: 50.9), and containing up to 54 (mean: 28.2) non-hydrogen atoms. To gain insights into the solvent effects as well as collective dispersion interactions for drug-like molecules, we have performed QM calculations supplemented with a treatment of many-body dispersion (MBD) interactions of structures and properties in the gas phase and implicit water. Thus, AQM contains over 40 global and local physicochemical properties (including ground-state and response properties) per conformer computed at the tightly converged PBE0+MBD level of theory for gas-phase molecules, whereas PBE0+MBD with the modified Poisson-Boltzmann (MPB) model of water was used for solvated molecules. By addressing both molecule-solvent and dispersion interactions, AQM dataset can serve as a challenging benchmark for state-of-the-art machine learning methods for property modeling and de novo generation of large (solvated) molecules with pharmaceutical and biological relevance.
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页数:14
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