Amino acid ionic liquids have garnered significant attention for their potential in electrochemical energy storage due to their wide electrochemical stability windows and inherent safety. The performance of ChGly as an electrolyte for supercapacitors has been compared to that of highly efficient conventional ionic liquids. However, a thorough understanding of the microstructural characteristics responsible for the enhanced properties of ChGly aqueous solutions remains largely unexplored. In this study, ab initio molecular dynamics simulations were employed to investigate the energetic, structural, transport and spectroscopic properties of ChGly-based pure and aqueous electrolytes. A comprehensive analysis of the cation-anion and water-ion hydrogen bonding was conducted for both electrolyte systems. Structural features were examined using radial and spatial distribution functions, while the vibrational power spectra were analyzed to identify significant differences in intermolecular interactions between pure and aqueous electrolytes, stemming from modified solvation shell structures. The findings presented in this work shed light on crucial structural and spectroscopic distinctions between pure and aqueous ChGly electrolytes, providing valuable insights for further advancements in the field.

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The binding mechanisms between a mixture of catanionic surfactants, hexadecyltrimethylammonium bromide (CTAB) and dicloxacillin (Diclox), interacting with the lysozyme protein was investigated by combining computational structure-based and spectrofluorometric approaches. The ezPocket method efficiently predicted lysozyme binding sites, which improved the accuracy of molecular docking simulations for the mixture. The estimated IC50 values indicated the potency and effectiveness of both ligands in the lysozyme binding pockets. Dicloxacillin showed stronger binding affinity than CTAB, as evidenced by lower IC50 values and higher interaction affinity based on Delta G results. Additionally, CTAB induced conformational changes in the lysozyme binding sites, that decreased the binding affinity of dicloxacillin, and vice versa. The outcomes on the synergistic or antagonistic binding in the catanionic system revealed negative cooperativity based on the obtained negative Hill coefficients. Besides, theoretical 2D-isobolograms illustrated the interaction between the ligands, indicating synergistic and antagonistic effects on the lysozyme binding pockets. Experimental validation unveiled that the presence of the catanionic mixture altered the absorption spectrum of lysozyme, decreasing its hydrophobicity and increasing polarity. The interaction between dicloxacillin and lysozyme resulted in fluorescence quenching and a red shift in the emission wavelength, demonstrating a change towards a more polar environment, while in the case of CTAB, the interaction resulted in shifts in the maximum wavelength and tertiary structure unfolding. These findings support the idea that dicloxacillin is a more potent ligand for lysozyme than CTAB, further unravelling their binding interplay, and laying the groundwork for future investigations aimed at rational drug design for potential biomedical applications.

The catalytic epoxidation of small alkenes and allylic alcohols includes a wide range of valuable chemical applications, with many works describing vanadium complexes as suitable catalysts towards sustainable process chemistry. But, given the complexity of these mechanisms, it is not always easy to sort out efficient examples for streamlining sustainable processes and tuning product optimization. In this review, we provide an update on major works of tunable vanadium-catalyzed epoxidations, with a focus on sustainable optimization routes. After presenting the current mechanistic view on vanadium catalysts for small alkenes and allylic alcohols' epoxidation, we argue the key challenges in green process development by highlighting the value of updated kinetic and mechanistic studies, along with essential computational studies.

Explanation is a foundational goal in the exact sciences. Besides the contemporary considerations on 'description', 'classification', and 'prediction', we often see these terms in thriving applications of artificial intelligence (AI) in chemistry hypothesis generation. Going beyond describing 'things in the world', these applications can make accurate numerical property calculations from theoretical or topological descriptors. This association makes an interesting case for a logic of discovery in chemistry: are these induction-led ventures showing a shift in how chemists can problematize research questions? In this article, I present a fresh perspective on the current context of discovery in chemistry. I argue how data-driven statistical predictions in chemistry can be explained as a quasi-logical process for generating chemical theories, beyond the classic examples of organic and theoretical chemistry. Through my position on formal models of scientific explanation, I demonstrate how the dawn of AI can provide novel insights into the explanatory power of scientific endeavors.

The partitioning of the molecular mechanics (MM) energy in calculations involving biomolecular systems is important to identify the source of major stabilizing interactions, e.g., in ligand-protein interactions, or to identify residues with considerable contributions in hybrid multiscale calculations, i.e., quantum mechanics/molecular mechanics (QM/MM). Here, we describe Energy Split, a software program to calculate MM energy partitioning considering the AMBER Hamiltonian and parameters. Energy Split includes a graphical interface plugin for VMD to facilitate the selection of atoms and molecules belonging to each part of the system. Energy Split is freely available at or can be easily installed through the VMD Store.

Carbon nanotubes (CNTs) display exceptional properties that predispose them to wide use in technological or biomedical applications. To remove the toxicity of CNTs and to protect them against undesired protein adsorption, coverage of the CNT sidewall with poly(ethylene oxide) (PEO) is often considered. However, controversial results on the antifouling effectiveness of PEO layers have been reported so far. In this work, the interactions of pristine CNT and CNT covered with the PEO chains at different grafting densities with polyglycine, polyserine, and polyvaline are studied using molecular dynamics simulations in vacuum, water, and saline environments. The peptides are adsorbed on CNT in all investigated systems; however, the adsorption strength is reduced in aqueous environments. Save for one case, addition of NaCl at a physiological concentration to water does not appreciably influence the adsorption and structure of the peptides or the grafted PEO layer. It turns out that the flexibility of the peptide backbone allows the peptide to adopt more asymmetric conformations which may be inserted deeper into the grafted PEO layer. Water molecules disrupt the internal hydrogen bonds in the peptides, as well as the hydrogen bonds formed between the peptides and the PEO chains.