The Quixote project: Collaborative and Open Quantum Chemistry data management in the Internet age

Machine Learned Composite Methods for Electronic Structure Theory

Because of the prohibitive scaling of ab initio techniques for modeling chemical species with high accuracy, they are not generally tractable for large systems. It is therefore of considerable interest to develop high-accuracy computational models with low computational cost that can afford predictions of electronic structure and properties of macromolecular species. Composite methods, as first introduced by Pople [Pople, J. A.; Head-Gordon, M.; Fox, D. J.; Raghavachari, K.; Curtiss, L. A. J. Chem. Phys.1989, 90, 5622.], are an intuitive solution to this problem as they seek to systematically increase accuracy in model chemistries by taking advantage of favorable error cancellation among reasonably low-cost models. By linearly combining a series of carefully chosen model chemistries, the result of a prohibitive-scaling correlated model chemistry with a large basis set may be approximated with relatively good fidelity. However, the full extent to which the choice of low-cost models dictates the predictive accuracy of composite methods is not known, and a full exploration of all model chemistries would be advantageous for the design and validation of a generalizable composite method for widespread application. Here, we show that remarkable accuracy can be generally achieved with composite methods that are more judiciously constructed, leading to increased accuracy with significantly reduced computational cost. By designing a systematic procedure for the automated generation and assessment of over 10 billion unique composite methods, we have extensively explored the space of modern model chemistries to elucidate important design principles in the construction of reliable composite procedures. We anticipate our work to be the starting point in the pursuit of creative approaches to modeling large chemical systems with high accuracy by using novel combinatorial modeling.

Nanostructuring and macroscopic behavior of type V deep eutectic solvents based on monoterpenoids

Type V natural deep eutectic solvents based on monoterpenoids (cineole, carvone, menthol, and thymol) are studied using a combined experimental and molecular modeling approach. The reported physicochemical properties showed low viscous fluids whose properties were characterized as a function of temperature. The theoretical study combining quantum chemistry and classical molecular dynamics simulations provided a nanoscopic characterization of the fluids, particularly for the hydrogen bonding network and its relationship with the macroscopic properties. The considered fluids constitute a suitable type of solvents considering their properties, cost, origin, and sustainability in different technological applications and sow the possibility of developing type V NADES from different types of molecules, especially in the terpenoid family of compounds.

Nanoscopic study on carvone-terpene based natural deep eutectic solvents

Terpene-based natural deep eutectic solvents (NADES) formed by using carvone as the hydrogen bond acceptor and a series of organic acids including tartaric, succinic, malic, and lactic acids as hydrogen bond donors are studied using a combination of molecular simulation methods. Density functional theory was used to study small molecular clusters and the topological characterization of the intermolecular forces using the atoms-in-a-molecule approach. Close-range interactions between the optimized carvone bases eutectic solvents between carbon dioxide have been studied for potential utilization of these solvents for gas capture purposes. Furthermore, COSMO-RS calculations have been carried out for the carbon dioxide solubilization performance of NADES compounds and to obtain s-profiles to infer the polarity and H-bond forming ability of the studied solvents. On the other hand, molecular dynamics simulations were carried out to analyze the bulk liquid properties and their relationship with relevant macroscopic properties (e.g., density or thermal expansion). Last but not least, relevant toxicity properties of the studied systems were predicted and reported in this work. The reported results provide the characterization of environmentally friendly NADES and show the suitability of carvone for advanced applications as carbon dioxide solubilizers.

eScience Infrastructures in Physical Chemistry

As the volume of data associated with scientific research has exploded over recent years, the use of digital infrastructures to support this research and the data underpinning it has increased significantly. Physical chemists have been making use of eScience infrastructures since their conception, but in the last five years their usage has increased even more. While these infrastructures have not greatly affected the chemistry itself, they have in some cases had a significant impact on how the research is undertaken. The combination of the human effort of collaboration to create open source software tools and semantic resources, the increased availability of hardware for the laboratories, and the range of data management tools available has made the life of a physical chemist significantly easier. This review considers the different aspects of eScience infrastructures and explores how they have improved the way in which we can conduct physical chemistry research. Expected final online publication date for the Annual Review of Physical Chemistry, Volume 73 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Theoretical insights into the cineole-based deep eutectic solvents

Deep eutectic solvents based on cineole as hydrogen bond acceptors and organic acids (succinic, malic, and lactic) as hydrogen bond donors are studied using a theoretical approach. The nature, strength, and extension of hydrogen bonding are analyzed, thus quantifying this prevailing interaction and its role in the fluid properties. Density functional theory was used to study small molecular clusters, and the topological characterization of the intermolecular forces was carried out using atoms in a molecule theory. Classical molecular dynamics simulations were considered to study nanoscopic bulk liquid properties and their relationship with relevant macroscopic properties such as density or thermal expansion. The reported results provide the characterization of environmentally friendly deep eutectic solvents and show the suitability of cineole for developing these sustainable materials.

Validation of the Crystallography Open Database using the Crystallographic Information Framework

Data curation practices of the Crystallography Open Database are described with greater focus being placed on the cif_validate program, capable of validating crystallographic information files against both DDL1 and DDLm dictionaries.

Data curation practices of the Crystallography Open Database (COD) are described with additional focus being placed on the formal validation using the Crystallographic Information Framework (CIF). The cif_validate program, capable of validating CIF files against both the DDL1 and the DDLm dictionaries, is presented and used to process the entirety of the COD. Validation results collected from over 450 000 CIF files are demonstrated to be a useful resource in the data maintenance process as well as the development of the underlying ontologies. A set of programs intended to aid in the dictionary migration from DDL1 to DDLm is also presented.

Effect of Hydrogen Bond Donors and Acceptors on CO2 Absorption by Deep Eutectic Solvents

The effects of a hydrogen bond acceptor and hydrogen bond donor on carbon dioxide absorption via natural deep eutectic solvents were studied in this work. Naturally occurring non-toxic deep eutectic solvent constituents were considered; choline chloride, b-alanine, and betaine were selected as hydrogen bond acceptors; lactic acid, malic acid, and fructose were selected as hydrogen bond donors. Experimental gas absorption data were collected via experimental methods that uses gravimetric principles. Carbon dioxide capture data for an isolated hydrogen bond donor and hydrogen bond acceptor, as well as natural deep eutectic solvents, were collected. In addition to experimental data, a theoretical study using Density Functional Theory was carried out to analyze the properties of these fluids from the nanoscopic viewpoint and their relationship with the macroscopic behavior of the system, and its ability for carbon dioxide absorption. The combined experimental and theoretical reported approach work leads to valuable discussions on what is the effect of each hydrogen bond donor or acceptor, as well as how they influence the strength and stability of the carbon dioxide absorption in deep eutectic solvents. Theoretical calculations explained the experimental findings, and combined results showed the superiority of the hydrogen bond acceptor role in the gas absorption process, with deep eutectic solvents. Specifically, the cases in which choline chloride was used as hydrogen bond acceptor showed the highest absorption performance. Furthermore, it was observed that when malic acid was used as a hydrogen bond donor, it led to low carbon dioxide solubility performance in comparison to other studied deep eutectic solvents. The cases in which lactic acid was used as a hydrogen bond donor showed great absorption performance. In light of this work, more targeted, specific, deep eutectic solvents can be designed for effective and alternative carbon dioxide capture and management.

Quantum Chemistry Insight into the Interactions Between Deep Eutectic Solvents and SO2

A systematic research work on the rational design of task specific Deep Eutectic Solvents (DES) has been carried out via density functional theory (DFT) in order to increase knowledge on the key interaction parameters related to efficient SO₂ capture by DES at a molecular level. A total of 11 different DES structures, for which high SO₂ affinity and solubility is expected, have been selected in this work. SO₂ interactions in selected DES were investigated in detail through DFT simulations and this work has generated a valuable set of information about required factors at the molecular level to provide high SO₂ solubility in DES, which is crucial for enhancing the current efficiency of the SO₂ capture process and replacing the current state of the art with environmentally friendly solvents and eventually implementing these materials in the chemical industry. Results that were obtained from DFT calculations were used to deduce the details of the type and the intensity of the interaction between DES and SO₂ molecules at various interaction sites as well as to quantify short-range interactions by using various methods such as quantum theory of atoms in a molecule (QTAIM), electrostatic potentials (ESP) and reduced density gradients (RDG). Systematic research on the molecular interaction characterization between DES structures and SO₂ molecule increases our knowledge on the rational design of task-specific DES.

Design of arginine-based therapeutic deep eutectic solvents as drug solubilization vehicles for active pharmaceutical ingredients

The solvation of lidocaine in three newly designed deep eutectic solvents is studied using combined experimental and theoretical methods that include density functional theory and molecular dynamics methods. The intermolecular forces between lidocaine and the hydrogen bond acceptors and hydrogen bond donors of the deep eutectic solvents were analysed regarding the type and the strength of inter- and intra-molecular bonding. The structure, composition and properties of the lidocaine solvation shells are analysed together with the possible lidocaine-clustering around the studied deep eutectic solvents and their constituent molecules. Furthermore, the changes in the solvent structures upon lidocaine solubilization are also studied. Natural product-based eutectic solvents showed considerably high solvation of lidocaine in all three deep eutectics based on the strong solute-solvent intermolecular interactions accompanied by a slight volume expansion and minor solvent structural changes. These non-toxic and almost null-volatile therapeutic deep eutectic solvents can be considered as suitable solubilization media for developing pharmaceutical applications and they can be considered as effective drug delivery vehicles for active pharmaceutical ingredients.

Luscus: molecular viewer and editor for MOLCAS

The novel program for graphical display and editing of molecular systems, luscus, is described. The program allows fast and easy building and/or editing different molecular structures, up to several thousands of atoms large. Luscus is able to visualise dipole moments, normal modes, molecular orbitals, electron densities and electrostatic potentials. In addition, simple geometrical objects can be rendered in order to reveal a geometrical feature or a physical quantity. The program is developed as a graphical interface for the MOLCAS program package, however its adaptive nature makes possible to use luscus with other computational program packages and chemical formats. All data files are opened via simple plug-ins which makes easy to implement a new file format in luscus. The easiness of editing molecular geometries makes luscus suitable for teaching students chemical concepts and molecular modelling. Graphical AbstractScreenshot of luscus program showing molecular orbital.

Managing the computational chemistry big data problem: the ioChem-BD platform

We present the ioChem-BD platform ( www.iochem-bd.org ) as a multiheaded tool aimed to manage large volumes of quantum chemistry results from a diverse group of already common simulation packages. The platform has an extensible structure. The key modules managing the main tasks are to (i) upload of output files from common computational chemistry packages, (ii) extract meaningful data from the results, and (iii) generate output summaries in user-friendly formats. A heavy use of the Chemical Mark-up Language (CML) is made in the intermediate files used by ioChem-BD. From them and using XSL techniques, we manipulate and transform such chemical data sets to fulfill researchers' needs in the form of HTML5 reports, supporting information, and other research media.

Data model, dictionaries, and desiderata for biomolecular simulation data indexing and sharing

Background

Few environments have been developed or deployed to widely share biomolecular simulation data or to enable collaborative networks to facilitate data exploration and reuse. As the amount and complexity of data generated by these simulations is dramatically increasing and the methods are being more widely applied, the need for new tools to manage and share this data has become obvious. In this paper we present the results of a process aimed at assessing the needs of the community for data representation standards to guide the implementation of future repositories for biomolecular simulations.

Results

We introduce a list of common data elements, inspired by previous work, and updated according to feedback from the community collected through a survey and personal interviews. These data elements integrate the concepts for multiple types of computational methods, including quantum chemistry and molecular dynamics. The identified core data elements were organized into a logical model to guide the design of new databases and application programming interfaces. Finally a set of dictionaries was implemented to be used via SQL queries or locally via a Java API built upon the Apache Lucene text-search engine.

Conclusions

The model and its associated dictionaries provide a simple yet rich representation of the concepts related to biomolecular simulations, which should guide future developments of repositories and more complex terminologies and ontologies. The model still remains extensible through the decomposition of virtual experiments into tasks and parameter sets, and via the use of extended attributes. The benefits of a common logical model for biomolecular simulations was illustrated through various use cases, including data storage, indexing, and presentation. All the models and dictionaries introduced in this paper are available for download at http://ibiomes.chpc.utah.edu/mediawiki/index.php/Downloads.

From data to analysis: linking NWChem and Avogadro with the syntax and semantics of Chemical Markup Language

BACKGROUND

Multidisciplinary integrated research requires the ability to couple the diverse sets of data obtained from a range of complex experiments and computer simulations. Integrating data requires semantically rich information. In this paper an end-to-end use of semantically rich data in computational chemistry is demonstrated utilizing the Chemical Markup Language (CML) framework. Semantically rich data is generated by the NWChem computational chemistry software with the FoX library and utilized by the Avogadro molecular editor for analysis and visualization.

RESULTS

The NWChem computational chemistry software has been modified and coupled to the FoX library to write CML compliant XML data files. The FoX library was expanded to represent the lexical input files and molecular orbitals used by the computational chemistry software. Draft dictionary entries and a format for molecular orbitals within CML CompChem were developed. The Avogadro application was extended to read in CML data, and display molecular geometry and electronic structure in the GUI allowing for an end-to-end solution where Avogadro can create input structures, generate input files, NWChem can run the calculation and Avogadro can then read in and analyse the CML output produced. The developments outlined in this paper will be made available in future releases of NWChem, FoX, and Avogadro.

CONCLUSIONS

The production of CML compliant XML files for computational chemistry software such as NWChem can be accomplished relatively easily using the FoX library. The CML data can be read in by a newly developed reader in Avogadro and analysed or visualized in various ways. A community-based effort is needed to further develop the CML CompChem convention and dictionary. This will enable the long-term goal of allowing a researcher to run simple "Google-style" searches of chemistry and physics and have the results of computational calculations returned in a comprehensible form alongside articles from the published literature.

Avogadro: an advanced semantic chemical editor, visualization, and analysis platform

Background

The Avogadro project has developed an advanced molecule editor and visualizer designed for cross-platform use in computational chemistry, molecular modeling, bioinformatics, materials science, and related areas. It offers flexible, high quality rendering, and a powerful plugin architecture. Typical uses include building molecular structures, formatting input files, and analyzing output of a wide variety of computational chemistry packages. By using the CML file format as its native document type, Avogadro seeks to enhance the semantic accessibility of chemical data types.

Results

The work presented here details the Avogadro library, which is a framework providing a code library and application programming interface (API) with three-dimensional visualization capabilities; and has direct applications to research and education in the fields of chemistry, physics, materials science, and biology. The Avogadro application provides a rich graphical interface using dynamically loaded plugins through the library itself. The application and library can each be extended by implementing a plugin module in C++ or Python to explore different visualization techniques, build/manipulate molecular structures, and interact with other programs. We describe some example extensions, one which uses a genetic algorithm to find stable crystal structures, and one which interfaces with the PackMol program to create packed, solvated structures for molecular dynamics simulations. The 1.0 release series of Avogadro is the main focus of the results discussed here.

Conclusions

Avogadro offers a semantic chemical builder and platform for visualization and analysis. For users, it offers an easy-to-use builder, integrated support for downloading from common databases such as PubChem and the Protein Data Bank, extracting chemical data from a wide variety of formats, including computational chemistry output, and native, semantic support for the CML file format. For developers, it can be easily extended via a powerful plugin mechanism to support new features in organic chemistry, inorganic complexes, drug design, materials, biomolecules, and simulations. Avogadro is freely available under an open-source license from http://avogadro.openmolecules.net.

Semantic physical science

The articles in this special issue arise from a workshop and symposium held in January 2012 (Semantic Physical Science'). We invited people who shared our vision for the potential of the web to support chemical and related subjects. Other than the initial invitations, we have not exercised any control over the content of the contributed articles.

Web tools for predictive toxicology model building

INTRODUCTION

The development and use of web tools in chemistry has accumulated more than 15 years of history already. Powered by the advances in the Internet technologies, the current generation of web systems are starting to expand into areas, traditional for desktop applications. The web platforms integrate data storage, cheminformatics and data analysis tools. The ease of use and the collaborative potential of the web is compelling, despite the challenges.

AREAS COVERED

The topic of this review is a set of recently published web tools that facilitate predictive toxicology model building. The focus is on software platforms, offering web access to chemical structure-based methods, although some of the frameworks could also provide bioinformatics or hybrid data analysis functionalities. A number of historical and current developments are cited. In order to provide comparable assessment, the following characteristics are considered: support for workflows, descriptor calculations, visualization, modeling algorithms, data management and data sharing capabilities, availability of GUI or programmatic access and implementation details.

EXPERT OPINION

The success of the Web is largely due to its highly decentralized, yet sufficiently interoperable model for information access. The expected future convergence between cheminformatics and bioinformatics databases provides new challenges toward management and analysis of large data sets. The web tools in predictive toxicology will likely continue to evolve toward the right mix of flexibility, performance, scalability, interoperability, sets of unique features offered, friendly user interfaces, programmatic access for advanced users, platform independence, results reproducibility, curation and crowdsourcing utilities, collaborative sharing and secure access.

CMLLite: a design philosophy for CML

CMLLite is a collection of definitions and processes which provide strong and flexible validation for a document in Chemical Markup Language (CML). It consists of an updated CML schema (schema3), conventions specifying rules in both human and machine-understandable forms and a validator available both online and offline to check conformance. This article explores the rationale behind the changes which have been made to the schema, explains how conventions interact and how they are designed, formulated, implemented and tested, and gives an overview of the validation service.

The semantics of Chemical Markup Language (CML): dictionaries and conventions

The semantic architecture of CML consists of conventions, dictionaries and units. The conventions conform to a top-level specification and each convention can constrain compliant documents through machine-processing (validation). Dictionaries conform to a dictionary specification which also imposes machine validation on the dictionaries. Each dictionary can also be used to validate data in a CML document, and provide human-readable descriptions. An additional set of conventions and dictionaries are used to support scientific units. All conventions, dictionaries and dictionary elements are identifiable and addressable through unique URIs.

Semantic science and its communication - a personal view

The articles in this special issue represent the culmination of about 15 years working with the potential of the web to support chemical and related subjects. The selection of papers arises from a symposium held in January 2011 ('Visions of a Semantic Molecular Future') which gave me an opportunity to invite many people who shared the same vision. I have asked them to contribute their papers and most have been able to do so. They cover a wide range of content, approaches and styles and apart from the selection of the speakers (and hence the authors) I have not exercised any control over the content.