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The Open Databases Integration for Materials Design (OPTIMADE) application programming interface (API) empowers users with holistic access to a growing federation of databases, enhancing the accessibility and discoverability of materials and chemical data. Since the first release of the OPTIMADE specification (v1.0), the API has undergone significant development, leading to the v1.2 release, and has underpinned multiple scientific studies. In this work, we highlight the latest features of the API format, accompanying software tools, and provide an update on the implementation of OPTIMADE in contributing materials databases. We end by providing several use cases that demonstrate the utility of the OPTIMADE API in materials research that continue to drive its ongoing development., Competing Interests: G. J. C. is a shareholder and Director of Intellegens Ltd. G.-M. R. is a shareholder and Chief Innovation Officer of Matgenix SRL. E. B. is a shareholder and Director of Materials Platform for Data Science OÜ., (This journal is © The Royal Society of Chemistry.)

Artificial intelligence (AI) and machine learning (ML) are expanding in popularity for broad applications to challenging tasks in chemistry and materials science. Examples include the prediction of properties, the discovery of new reaction pathways, or the design of new molecules. The machine needs to read and write fluently in a chemical language for each of these tasks. Strings are a common tool to represent molecular graphs, and the most popular molecular string representation, Smiles, has powered cheminformatics since the late 1980s. However, in the context of AI and ML in chemistry, Smiles has several shortcomings-most pertinently, most combinations of symbols lead to invalid results with no valid chemical interpretation. To overcome this issue, a new language for molecules was introduced in 2020 that guarantees 100% robustness: SELF-referencing embedded string (Selfies). Selfies has since simplified and enabled numerous new applications in chemistry. In this perspective, we look to the future and discuss molecular string representations, along with their respective opportunities and challenges. We propose 16 concrete future projects for robust molecular representations. These involve the extension toward new chemical domains, exciting questions at the interface of AI and robust languages, and interpretability for both humans and machines. We hope that these proposals will inspire several follow-up works exploiting the full potential of molecular string representations for the future of AI in chemistry and materials science., (© 2022 The Author(s).)

Streamlit is an open-source Python coding framework for building web-applications or "web-apps" and is now being used by researchers to share large data sets from published studies and other resources. Here we present Stmol, an easy-to-use component for rendering interactive 3D molecular visualizations of protein and ligand structures within Streamlit web-apps. Stmol can render protein and ligand structures with just a few lines of Python code by utilizing popular visualization libraries, currently Py3DMol and Speck. On the user-end, Stmol does not require expertise to interactively navigate. On the developer-end, Stmol can be easily integrated within structural bioinformatic and cheminformatic pipelines to provide a simple means for user-end researchers to advance biological studies and drug discovery efforts. In this paper, we highlight a few examples of how Stmol has already been utilized by scientific communities to share interactive molecular visualizations of protein and ligand structures from known open databases. We hope Stmol will be used by researchers to build additional open-sourced web-apps to benefit current and future generations of scientists., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Nápoles-Duarte, Biswas, Parker, Palomares-Baez, Chávez-Rojo and Rodríguez-Valdez.)

Novel chalcone derivatives with different substituents attached to A and B-rings: hydroxyl, methoxyl, geranyl, and prenyl groups were synthesized. The obtained compounds were characterized by NMR, HRMS, UV-Vis, IR, and MS. The theoretical analysis was carried out in all the compounds using density functional theory (DFT) with the B3LYP, PBE0, and M06-2X functionals in combination with the 6-311G(d,p) Pople-type basis set. The excited state properties were calculated by time dependent density functional theory (TD-DFT) using the same methodology applied for the ground state properties. The calculated vertical absorption wavelengths (λ max ) in gas phase and in ethanol as a solvent are consistent with the experimental ones, being the TD-DFT:B3LYP/6-311G(d,p) and PCM-TD-DFT:PBE0/6-311G(d,p) the best methodologies for these calculations with good approximation to the experimental values. The calculated reorganization energies indicated that, the four chalcone derivatives present an electron transfer character due to the smaller registered values. From these parameters it is proposed that these show an n-type semiconductor character. The localization of the frontier orbitals (HOMO and LUMO) shows that only the compound containing a hydroxyl group on the A-ring displays a marked delocalization favoring the charge-transfer process in this system. The HOMO-LUMO gap energies indicate that the inclusion of different donor groups in the rings does not improve the obtained values for this property. Graphical Abstract Relationship between spectroscopic and geometrical properties of chalcones were carried out using quantum-chemical calculations and compared with experimental values.