Data quality as well as library size are crucial issues for force field development. In order to predict molecular properties in a large chemical space, the foundation to build force fields on needs to encompass a large variety of chemical compounds. The tabulated molecular physicochemical properties also need to be accurate. Due to the limited transparency in data used for development of existing force fields it is hard to establish data quality and reusability is low. This paper presents the Alexandria library as an open and freely accessible database of optimized molecular geometries, frequencies, electrostatic moments up to the hexadecupole, electrostatic potential, polarizabilities, and thermochemistry, obtained from quantum chemistry calculations for 2704 compounds. Values are tabulated and where available compared to experimental data. This library can assist systematic development and training of empirical force fields for a broad range of molecules.
Machine-accessible metadata file describing the reported data (ISA-tab format)
Background & Summary
Chemical space is spanned by all possible molecules that are energetically stable1. The to date largest generated database (GDB-17) contains 166.4 billion molecules of up to 17 atoms of H, C, N, O, S, and halogens2 (a more workable representative subset containing 10 million compounds was published recently as well3). Computational chemistry has enabled us to virtually explore and exploit the chemical space by predicting physicochemical properties of its compounds4. This has helped chemical biologists, for example, to identify bioactive regions of the chemical space4,
Compounds in the chemical space may vary in size, they may be organic or inorganic, including synthetic- and bio-polymers7,8. In addition, the chemistry of life9 happens in the liquid phase, which implies that we need to explore the properties of a large range of compounds in at least the gas- and the liquid phases. Hence, the practical tool for navigating chemical space is atomistic molecular simulations based on empirical force fields.
Many areas of materials science and drug discovery have benefited from the application of empirical force fields. High-throughput virtual screening is a promising approach, that has led to the discovery of new materials and drug-like compounds10. However, making accurate prediction of properties of molecules from different parts of the chemical space is yet to be achieved since force fields are not readily transferable from one chemical category to another. In other words, the reliability and the applicability of force fields in practice depends on the chemical composition of the compounds under investigation. The main reason is that empirical force fields are in essence derived using supervised machine learning algorithms that can learn from and make predictions on the available data. The quality of the data and the diversity of the molecules in the database determine the domain of accuracy and reliability of the resulting force fields. Therefore, data quality should be carefully considered when developing force fields. However, the databases used for optimizing force fields are rarely published and when they are made available they are in a format that is difficult to use in data-mining. As a result, it is difficult to assess the underlying data quality for the existing force fields.
Several resources are available providing experimental data for physicochemical properties. For instance, the National Institute of Standard and Technology11,12 and the Design Institute for Physical Properties13 have collected large amounts of experimental molecular properties measured during many decades of research. Due to the size of chemical space there is experimental data only for a small fraction of molecules-most of these databases contain less than ten thousand compounds. In addition, most of the data provided for molecular properties is old and the original sources may not be readily accessible. It would be prohibitively expensive to experimentally determine all the properties of interest for even a small fraction of designed compounds from, e.g., GDB-17. For this reason, the dissemination of quantum chemistry data for a set of assorted molecules is very useful to accelerate progress in empirical force fields. For example, Ramakrishnan et al.14 have provided a quantum-chemistry database of molecular geometries and properties for 134,000 molecules at the B3LYP/6-31G(2df,p) level of theory, for development of machine learning tools. Moreover, the ANI-1 database provides off-equilibrium density functional theory (DFT) calculations for 57,454 organic molecules up to 8 heavy atoms including H, C, N, and O15. Other databases are available as well at both high16,17 and low levels of theory18. These resources containing quantum-chemical molecular properties are of interest for optimization of molecular mechanics potentials for small compounds by facilitating the development of machine learning strategies for predicting molecular properties19,20.
This paper presents the Alexandria library, an open and freely accessible database of quantum-chemically optimized molecular structures and properties of 2704 compounds for empirical force field development. The name “Alexandria” was adopted to highlight that we aim to collect “all” knowledge in the world, old and new, on molecular properties, just like the legendary library of Alexandria, since it has been established that availability of data rapidly declines with time21. The library could also be used for evaluation of density functionals and development of semi-empirical quantum methods. The compounds belong to more than thirty different chemical categories containing functional groups that are common in biomolecules and drug-like compounds. They are predominantly made up of C, H, N, O, Si, P, S, and halogens covering the elements of the GDB-17 chemical space. The library also provides data for some inorganic compounds and metals. The molecular properties provided here are enthalpy of formation, heat capacity, absolute entropy, zero-point vibrational energy, vibrational frequencies, electric moments up to hexadecapole, and polarizability, all in the gas phase. Thermochemistry calculations are in part based on our previous work22. In addition, the electrostatic potential on a grid around the compound and the partial atomic charges (Mulliken charges23, Hirshfeld charges24, ESP charges25, and CM526) are computed for each molecule. Where data is available we compare the quantum chemical calculations to experimental data. For transparency, we make the input files used to perform the quantum chemical calculations as well as all the output files available. This allows for testing the reproducibility of the quantum chemical data provided in the Alexandria library.
Initial structures were downloaded from the PubChem27 and the ChemSpider28 databases for most of the molecules. The downloaded structures were checked for missing hydrogens and the presence of 3D coordinates. The rest of molecules were generated by Avogadro29 or Molden30 softwares and their structures were minimized before performing quantum calculations. Quantum chemistry calculations were performed using the Gaussian 0931 and Gaussian 16 (ref. 32) set of programs. The B3LYP level of density functional theory33,
The OpenBabel program (version 2.4.1)55 was used to determine the number of rotatable bonds based on the optimized geometry for each molecule. The results, wherever possible, were compared to the PubChem database27 to check for consistency and manually curated in case of discrepancies. We here count bonds as rotatable if they increase the number of unique conformations. In our previous work22 we introduced an OpenBabel tool obthermo to extract thermochemistry data from Gaussian31 output files (with the aid of library of atomization energies, provided in OpenBabel (version 2.4.1). This open source tool contributes to our aim to make the data provided here accessible to other workers in the field.
The Alexandria library contains the input (.com) and the output (.log) files in GNU-zip compressed format (.gz) of quantum chemical calculations performed using Gaussian 09 (ref. 31) or Gaussian 16 (ref. 32) (Data Citation 1: Zenodo https://doi.org/10.5281/zenodo.1004711). All compounds are provided in a single Chemical Markup Language (CML) and in a single Tripos Mol2 (.mol2) file as well. The .mol2 file contains the optimized geometries at the B3LYP/aug-cc-pVTZ level of theory, the atomic partial charges computed by the ESP fitting algorithm, and the bond information. The molecular electrostatic potential surface used to fit the atomic partial charges is also provided in (compressed) XML files for each compound. This must be used in conjunction with the corresponding coordinates of the compound, that can be extracted from the Gaussian log files using OpenBabel. SMILES fingerprints were also generated for all molecules using the OpenBabel software (version 2.4.1)55 and stored in a .smiles file.
For each quantum chemical method, a table is provided in a .csv file (comma-separated value, however since both compound names and InChI identifiers contain comma's, we use the pipe symbol '|' as a separator). The files include the compound information (Table 2), the calculated and the experimental values of the molecular dipole moment, polarizability and thermochemistry results. These tables can be read using either commercial or open source spreadsheet software but they can also be processed by scripting languages. Further molecular properties are available in the Gaussian log files that can be extracted by OpenBabel software (version 2.4.1)55 or other software.
The experimental results used for the validation of quantum chemistry calculations are taken from several sources13,56,
Quantum Chemical Calculations
We have previously benchmarked and validated a number of standard quantum thermochemistry methods used to build the Alexandria library and shown that the G4 theory is a good compromise for thermochemistry calculations in comparison to the other methods22. Therefore, we here focus on the validation of optimized geometries, molecular polarizability, and dipole moments.
The optimized geometries were validated by comparing the StdInChI generated from each optimized geometry to the StdInChI obtained from PubChem database27. Moreover, the StdInChI obtained from the initial structure is compared to the StdInChI generated from the optimized structure confirming that both the initial and the optimized geometries correspond to the same compound14,61. 40 compounds out of 2704 did not pass this test, because StdInChI representations are not unique and thus the generation of StdInChI from Cartesian coordinates is error prone. This problem has been discussed in detail elsewhere14. Here, these 40 compounds were validated manually.
DFT calculations of molecular dipole moment and isotropic polarizability were validated by comparing to experiments. The B3LYP/aug-cc-pVTZ level of theory34,37,
The experimental and quantum chemical data provided in this paper also allow performing systematic analyses of molecular properties. Such analyses aid in understanding the relation between the chemical composition and the physicochemical properties of molecules. The variation of the experimental isotropic polarizability between different chemical formulae is small (Table 4). The mean signed errors (MSE) show that the B3LYP/aug-cc-pVTZ level of theory slightly underestimates the isotropic polarizability for most of the chemical formulas listed in Table 4. The standard deviation obtained from the experimental thermochemistry data show that the standard entropy (Table 5) and the heat capacity at constant volume (Table 6) can be predicted quite accurately by the chemical formula, while this does not hold for the enthalpy of formation (Table 7). The MSE values show that the G4 theory underestimates the entropy and heat capacity at constant volume (Tables 5 and 6), however, it overestimates the enthalpy of formation for most of the chemical formulas (Table 7).
Programs like Molden30, Avogadro29 and GaussView can be used to visualize and analyze quantum chemical calculations. Moreover, the obthermo22 program implemented in the OpenBabel program package (version 2.4.1)55 extracts enthalpy of formation, heat capacity at constant volume, and absolute entropy from the Gaussian 09 (ref. 31) and Gaussian 16 (ref. 32) log files. It can also be used to estimate the heat capacity at constant pressure from the calculated heat capacity at constant volume and the temperature derivative of the second virial coefficient, which must then be specified by the user as the input to the program22.
How to cite this article: Ghahremanpour, M. M. et al. The Alexandria library, a quantum-chemical database of molecular properties for force field development. Sci. Data 5:180062 doi: 10.1038/sdata.2018.62 (2018).
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Ghahremanpour, M. M., van Maaren, P. J., & van der Spoel, D. Zenodo https://doi.org/10.5281/zenodo.1004711 (2017)
The Swedish research council is acknowledged for financial support to DvdS (grant 2013-5947) and for grants of computer time (SNIC2015-16-33, SNIC2016-34-44) through the High Performance Computing Center North in Umeå, Sweden.