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Unlocking the surface chemistry of ionic minerals: a high-throughput pipeline for modeling realistic interfaces.

ABSTRACT: A systematic procedure is introduced for modeling charge-neutral non-polar surfaces of ionic minerals containing polyatomic anions. By integrating distance- and charge-based clustering to identify chemical species within the mineral bulk, our pipeline, PolyCleaver, renders a variety of theoretically viable surface terminations. As a demonstrative example, this approach was applied to forsterite (Mg₂SiO₄), unveiling a rich interface landscape based on interactions with formaldehyde, a relevant multifaceted molecule, and more particularly in prebiotic chemistry. This high-throughput method, going beyond techniques traditionally applied in the modeling of minerals, offers new insights into the potential catalytic properties of diverse surfaces, enabling a broader exploration of synthetic pathways in complex mineral systems.

SUBMITTER: Mates-Torres E

PROVIDER: S-EPMC11001413 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature

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Unlocking the surface chemistry of ionic minerals: a high-throughput pipeline for modeling realistic interfaces.

Mates-Torres Eric E Rimola Albert A

Journal of applied crystallography 20240315 Pt 2

A systematic procedure is introduced for modeling charge-neutral non-polar surfaces of ionic minerals containing polyatomic anions. By integrating distance- and charge-based clustering to identify chemical species within the mineral bulk, our pipeline, PolyCleaver, renders a variety of theoretically viable surface terminations. As a demonstrative example, this approach was applied to forsterite (Mg2SiO4), unveiling a rich interface landscape based on interactions wit ...[more]

PMID: 38596731

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Project description:Americium is a highly radioactive actinide element found in used nuclear fuel. Its adsorption on aluminum (hydr)oxide minerals is important to study for at least two reasons: (i) aluminum (hydr)oxide minerals are ubiquitous in the subsurface environment and (ii) bentonite clays, which are proposed engineered barriers for the geologic disposal of used nuclear fuel, have the same ≡AlOH sites as aluminum (hydr)oxide minerals. Surface complexation modeling is widely used to interpret the adsorption behavior of heavy metals on mineral surfaces. While americium sorption is understudied, multiple adsorption studies for europium, a chemical analog, are available. In this study we compiled data describing Eu(III) adsorption on three aluminum (hydr)oxide minerals-corundum (α-Al2O3), γ-alumina (γ-Al2O3) and gibbsite (γ-Al(OH)3)-and developed surface complexation models for Eu(III) adsorption on these minerals by employing diffuse double layer (DDL) and charge distribution multisite complexation (CD-MUSIC) electrostatic frameworks. We also developed surface complexation models for Am(III) adsorption on corundum (α-Al2O3) and γ-alumina (γ-Al2O3) by employing a limited number of Am(III) adsorption data sourced from literature. For corundum and γ-alumina, two different adsorbed Eu(III) species, one each for strong and weak sites, were found to be important regardless of which electrostatic framework was used. The formation constant of the weak site species was almost 10,000 times weaker than the formation constant for the corresponding strong site species. For gibbsite, two different adsorbed Eu(III) species formed on the single available site type and were important for the DDL model, whereas the best-fit CD-MUSIC model for Eu(III)-gibbsite system required only one Eu(III) surface species. The Am(III)-corundum model based on the CD-MUSIC framework had the same set of surface species as the Eu(III)-corundum model. However, the log K values of the surface reactions were different. The best-fit Am(III)-corundum model based on the DDL framework had only one site type. Both the CD-MUSIC and the DDL model developed for Am(III)-γ-alumina system only comprised of one site type and the formation constant of the corresponding surface species was ~ 500 times stronger and ~ 700 times weaker than the corresponding Eu(III) species on the weak and the strong sites, respectively. The CD-MUSIC model for corundum and both the DDL and the CD-MUSIC models for γ-alumina predicted the Am(III) adsorption data very well, whereas the DDL model for corundum overpredicted the Am(III) adsorption data. The root mean square of errors of the DDL and CD-MUSIC models developed in this study were smaller than those of two previously-published models describing Am(III)-γ-alumina system, indicating the better predictive capacity of our models. Overall, our results suggest that using Eu(III) as an analog for Am(III) is practical approach for predicting Am(III) adsorption onto well-characterized minerals.

Project description:BackgroundIntegration of medicinal chemistry data from numerous public resources is an increasingly important part of academic drug discovery and translational research because it can bring a wealth of important knowledge related to compounds in one place. However, different data sources can report the same or related compounds in various forms (e.g., tautomers, racemates, etc.), thus highlighting the need of organising related compounds in hierarchies that alert the user on important bioactivity data that may be relevant. To generate these compound hierarchies, we have developed and implemented canSARchem, a new compound registration and standardization pipeline as part of the canSAR public knowledgebase. canSARchem builds on previously developed ChEMBL and PubChem pipelines and is developed using KNIME. We describe the pipeline which we make publicly available, and we provide examples on the strengths and limitations of the use of hierarchies for bioactivity data exploration. Finally, we identify canonicalization enrichment in FDA-approved drugs, illustrating the benefits of our approach.ResultsWe created a chemical registration and standardization pipeline in KNIME and made it freely available to the research community. The pipeline consists of five steps to register the compounds and create the compounds' hierarchy: 1. Structure checker, 2. Standardization, 3. Generation of canonical tautomers and representative structures, 4. Salt strip, and 5. Generation of abstract structure to generate the compound hierarchy. Unlike ChEMBL's RDKit pipeline, we carry out compound canonicalization ahead of getting the parent structure, similar to PubChem's OpenEye pipeline. canSARchem has a lower rejection rate compared to both PubChem and ChEMBL. We use our pipeline to assess the impact of grouping the compounds in hierarchies for bioactivity data exploration. We find that FDA-approved drugs show statistically significant sensitivity to canonicalization compared to the majority of bioactive compounds which demonstrates the importance of this step.ConclusionsWe use canSARchem to standardize all the compounds uploaded in canSAR (> 3 million) enabling efficient data integration and the rapid identification of alternative compound forms with useful bioactivity data. Comparison with PubChem and ChEMBL pipelines evidenced comparable performances in compound standardization, but only PubChem and canSAR canonicalize tautomers and canSAR has a slightly lower rejection rate. Our results highlight the importance of compound hierarchies for bioactivity data exploration. We make canSARchem available under a Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0) at https://gitlab.icr.ac.uk/cansar-public/compound-registration-pipeline .

Dataset Information

Unlocking the surface chemistry of ionic minerals: a high-throughput pipeline for modeling realistic interfaces.

Publications

Unlocking the surface chemistry of ionic minerals: a high-throughput pipeline for modeling realistic interfaces.

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