DFT calculations reveal interesting structure–property relationships of the redox potentials of phenazines in non-aqueous media.

are limited by high cost, safety issues, poor recycling infrastructure, and growing concerns of resource scarcity. [4,5] Therefore, in the quest of finding alternative sustainable energy storage solutions, systems based on multivalent chemistries, such as Ca 2+ , Mg 2+ , Zn 2+ , Al 3+ , etc., should provide ample opportunities owing to their greater abundance, lower costs, superior safety features, in addition to their significantly higher volumetric energy densities. [6][7][8][9][10][11] In particular, zinc metal batteries (ZMBs) are highly intriguing because Zn anode shows high specific capacity (820 mAh g −1 ), high volumetric capacity of 5851 mAh cm −3 , nontoxicity, nonflammability, cost-effectiveness, large production, and easy processing. [12][13][14][15][16][17] Moreover, differently from other multivalent chemistries (Ca 2+ , Mg 2+ , Al 3+ ), the relatively higher redox potential of Zn (−0.76 V vs standard hydrogen electrode) makes it the only feasible choice as reversible anode for aqueous electrolytes. Certainly, taking advantage of the potentially large voltage window (>2 V) and high ionic conductivity of aqueous electrolytes, aqueous zinc metal batteries (AZMBs) might present an excellent high energy/power trade-off which is triggering the growing interest of this technology in the last years. [18,19] To date, AZMBs are mainly based on inorganic intercalation/ conversion cathode materials such as metal oxides (manganese, vanadium, etc.), transition metal dichalcogenides, polyanionic olivine-based phosphates, and Prussian blue analogs. [12,13,18,19] However, these cathode materials resulted in poor cell performances, exhibiting slow kinetics, low round-trip efficiency, and unstable cycling. This is due to the large cation size which hinders interfacial charge transfer and provokes strong electrostatic interactions between the highly charged Zn 2+ and the host inorganic framework causing destabilization of the crystal lattice and significant volume changes upon intercalation/deintercalation. [6][7][8][9][10][11] It is also important to highlight that most of these multivalent cathodes still involve toxic and/or environmentally unfriendly elements (except widely used MnO 2 ), which make further steps critical toward accomplishment of large-scale, sustainable energy storage systems. Therefore, the main challenge Aqueous zinc-metal batteries (AZMBs) are predicted to be an attractive solutions for viable, high-performance, and large-scale energy storage applications, but their advancement is greatly hindered by the lack of adequate aqueous electrolytes and sustainable cathodes. Herein, an ultra-robust Zn-polymer AZMB is demonstrated using poly(catechol) redox copolymer (P(4VC 86 -stat-SS 14 )) as the cathode and concentrated Zn(TFSI) 2 aqueous solution as stable electrolyte. The Zn(TFSI) 2 electrolyte shows enhanced iontransport properties and confers improved (electro)chemical compatibility with superior cell performance compared to traditional ZnSO 4 . The assembled Zn||P(4VC 86 -stat-SS 14 ) (2.5 mg cm ...

Aiming at a deep understanding of fragment binding to ligandable targets, we performed a large scale analysis of the Protein Data Bank. Binding modes of 1832 drug-like ligands and 1079 fragments to 235 proteins were compared. We observed that the binding modes of fragments and their drug-like superstructures binding to the same protein are mostly conserved, thereby providing experimental evidence for the preservation of fragment binding modes during molecular growing. Furthermore, small chemical changes in the fragment are tolerated without alteration of the fragment binding mode. The exceptions to this observation generally involve conformational variability of the molecules. Our data analysis also suggests that, provided enough fragments have been crystallized within a protein, good interaction coverage of the binding pocket is achieved. Last, we extended our study to 126 crystallization additives and discuss in which cases they provide information relevant to structure-based drug design.

The success of fragment-based drug design (FBDD) hinges upon the optimization of low-molecular-weight compounds (MW < 300 Da) with weak binding affinities to lead compounds with high affinity and selectivity. Usually, structural information from fragment-protein complexes is used to develop ideas about the binding mode of similar but drug-like molecules. In this regard, crystallization additives such as cryoprotectants or buffer components, which are highly abundant in crystal structures, are frequently ignored. Thus, the aim of this study was to investigate the information present in protein complexes with fragments as well as those with additives and how they relate to the binding modes of their drug-like counterparts. We present a thorough analysis of the binding modes of crystallographic additives, fragments, and drug-like ligands bound to four diverse targets of wide interest in drug discovery and highly represented in the Protein Data Bank: cyclin-dependent kinase 2, β-secretase 1, carbonic anhydrase 2, and trypsin. We identified a total of 630 unique molecules bound to the catalytic binding sites, among them 31 additives, 222 fragments, and 377 drug-like ligands. In general, we observed that, independent of the target, protein-fragment interaction patterns are highly similar to those of drug-like ligands and mostly cover the residues crucial for binding. Crystallographic additives are also able to show conserved binding modes and recover the residues important for binding in some of the cases. Moreover, we show evidence that the information from fragments and drug-like ligands can be applied to rescore docking poses in order to improve the prediction of binding modes.

Alzheimer’s disease is one of the most common neurodegenerative disorders in elder population. The β -site amyloid cleavage enzyme 1 (BACE1) is the major constituent of amyloid plaques and plays a central role in this brain pathogenesis, thus it constitutes an auspicious pharmacological target for its treatment. In this paper, a QSAR model for identification of potential inhibitors of BACE1 protein is designed by using classification methods. For building this model, a database with 215 molecules collected from different sources has been assembled. This dataset contains diverse compounds with different scaffolds and physical-chemical properties, covering a wide chemical space in the drug-like range. The most distinctive aspect of the applied QSAR strategy is the combination of hybridization with backward elimination of models, which contributes to improve the quality of the final QSAR model. Another relevant step is the visual analysis of the molecular descriptors that allows guaranteeing the absence of information redundancy in the model. The QSAR model performances have been assessed by traditional metrics, and the final proposed model has low cardinality, and reaches a high percentage of chemical compounds correctly classified.

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