Ligand Structure Research Articles

Clustering Zwitterionic Amino Acids at the Upper Rim of Cone Calix[4]arene Triggers the Selective Recognition of Gram‐Negative Bacterial Envelope

Eleven calix[4]arene ligands, bearing zwitterionic α‐amino acids or charged ammonium or sulfonate/carboxylate groups, are synthesized and screened for the binding to the envelopes of three bacterial strain representatives of Gram‐positive, Gram‐negative, and mycobacteria. The binding is followed by on‐cell Saturation Transfer Difference Nuclear Magnetic Resonance (NMR) experiments directly on alive cells. While the anionic tetrasulfonatocalixarene does not bind to any bacterial strains significantly and the cationic calixarenes strongly bind to both Gram‐positive and Gram‐negative bacteria, the zwitterionic tetraprolino‐ and tetraphenylalaninocalix[4]arene show a remarkable selectivity for Gram‐negatives over Gram‐positives and mycobacteria. The tetraprolinocalixarene binds to the lipopolysaccharides extracted from two Gram‐negative bacteria (Pseudomonas putida or Escherichia coli), suggesting these biomacromolecules as possible targets in the recognition of their cell walls. The ligand binding epitope map demonstrates a deep involvement of the amino acids and calixarene aromatic nuclei in the interaction. In this study, for the first time, the ability of synthetic macrocycles to selectively recognize the envelope of Gram‐negative bacteria is highlighted, and the way to the chemical modifications of the ligand structure is paved to develop devices for the detection or treatment of bacterial infections, thus allowing to add another string to the bow for the fight against antimicrobial resistance.

Selective extraction performance and mechanism of lithium using Lewis base ligands containing phosphoryl/carbonyl groups

With the rapidly increasing demand for lithium resources, lithium extraction from low-grade and secondary resources has received widespread attention. The combination of tributyl phosphate (TBP) and FeCl3 is the most studied and reported separation system. However, the selective extraction mechanism for lithium is not clear. In this study, the extraction systems consisting of different Lewis base ligands (L) with phosphoryl/carbonyl groups and FeCl3 were employed for lithium extraction from the LiCl-MgCl2-H2O system. The extraction efficiency and selectivity of lithium by various Lewis base ligands with different branched structures were investigated. The interactions between Li+ and the ligands were deeply analyzed by spectroscopic characterization and quantum chemistry calculations. Meanwhile, the relationship between the ligand structures and the selective binding ability of Li+ was innovatively established. The results show that the extraction efficiency and selectivity of lithium by various ligands descend in the order: TIBP > TBP > N503 > MIBK > P350 > TBPO > TOA. The extracted complexes [LiLn]+·[FeCl4]− are formed through the non-covalent interaction between Li+ and the O atoms of the ligands as well as the Cl atoms of [FeCl4]−. The ligand with low basicity, strong Mulliken electronegativity, and low average localized ionization energy is preferable for the selective extraction of Li+. On the contrary, the ligand is more likely to be protonated. The study provides a theoretical basis for deeply understanding the relationship between the ligand structures and their selective binding ability towards Li+, which is also conducive to developing more efficient systems for lithium recovery from complex solutions.

Communication—Effect of Ligand Structure on Li-Ion Insertion Kinetics in Ether-Based Solvate Ionic Liquids

The charge-transfer kinetics at the interface between LiMn2O4 thin-film electrodes and ether-based concentrated electrolytes were studied. The [Li(triglyme)1][N(SO2CF3)2] electrolyte exhibited higher charge-transfer resistance and activation energy barrier compared to monoglyme and tetrahydrofuran-based concentrated electrolytes. Li salt concentration and viscosity are the primary factors affecting the electrochemical reaction kinetics.

Learning the language of life with AI.

In 2021, a year before ChatGPT took the world by storm amid the excitement about generative artificial intelligence (AI), AlphaFold 2 cracked the 50-year-old protein-folding problem, predicting three-dimensional (3D) structures for more than 200 million proteins from their amino acid sequences. This accomplishment was a precursor to an unprecedented burgeoning of large language models (LLMs) in the life sciences. That was just the beginning. In recent months, we have moved into a hyperaccelerated phase of new foundation models, pretrained on massive datasets, with the ability to perform a wide range of tasks that are helping us understand the structure, biology, evolution, and design of proteins, RNA, DNA, and ligands, as well as their biomolecular interactions. Unlike multimodal LLMs such as GPT-4, Gemini, and Claude, which process text, audio, and images, these large language of life models (LLLMs) are multiomic. That is to say, they are not only multimodal but pertain to different layers of molecular biology. For example, Evo, a foundation model trained on 2.7 million diverse phage and prokaryotic genomes (equivalent to about 300 billion DNA nucleotides), predicts the impact of variants in DNA, RNA, or proteins on structure and function, as well as how essential genes are to cell function, and can generate new DNA sequences.

Impact of Ligand Structure on Biological Activity and Photophysical Properties of NHC-Protected Au13 Nanoclusters.

N-heterocyclic carbene (NHC)-protected gold nanoclusters display high stability and high photoluminescence, making them well-suited for fluorescence imaging and photodynamic therapeutic applications. We report herein the synthesis of two bisNHC-protected Au13 nanoclusters with π-extended aromatic systems. Depending on the position of the π-extended aromatic system, changes to the structure of the ligand shell in the cluster are observed, with the ability to correlate increases in rigidity with increases in fluorescence quantum yield. Density functional theory analysis reveals that both synthesized Au13 nanoclusters are 8-electron superatoms but have distinct differences in the characteristics of the lowest unoccupied single-electron states. Qualitatively, this implies different mechanisms for excitations and their decay over the fundamental energy gap. Stability and photophysical studies were carried out to provide the emission lifetime and optical purity of the two clusters. Active intracellular uptake of the nanoclusters was confirmed in vitro using confocal microscopy in human epithelial carcinoma cells. Reactive oxygen species production was measured at 7% efficiency. The high cluster stability, photoluminescence quantum yields, and efficient cellular uptake in cancer cells suggest potential for these nanoclusters as highly efficient and tunable nanomedical platforms.

Carbazolylpyridine (cp)-based tetradentate platinum(II) complexes containing fused 6/5/6 metallocycles.

A series of carbazolylpyridine (cp)-based 6/5/6 Pt(II) complexes featuring tetradentate ligands with nitrogen or oxygen atoms as bridging groups was designed and synthesized, and the bridging nitrogen atoms were derived from acridinyl (Ac), azaaceridine (AAc) and carbazole (Cz). Systematic experimental and theoretical studies reveal that the ligand structures have a significant effect on the electrochemical, photophysical and excited state properties of these complexes. Their oxidation processes mainly occur on the carbazole-Pt moieties, whereas the reduction processes typically occur on the electron-deficient pyridine (Py) moieties. Time-dependent density functional theory (TD-DFT) and natural transition orbital (NTO) calculations reveal that the cp-based Pt(II) complexes have a metal-to-ligand charge transfer (3MLCT) state mixed with ligand-centered (3LC) and intra-ligand charge-transfer (3ILCT) characteristics. Pt(cp-1) shows strong red luminescence with a dominant peak at 611 nm and an excited-state lifetime of 10.7 μs in dichloromethane at room temperature, 602 nm and 10.9 μs in toluene, and 602 nm and 8.2 μs in PMMA films. It also exhibits high photoluminescence quantum efficiencies of 85%, 84% and 60% in dichloromethane, toluene and PMMA, respectively. These studies indicate the potential application of the cp-based Pt(II) complexes as phosphorescent emitters in the field of organic light-emitting diodes (OLEDs).

The Impact of Ligand Structure and Reaction Temperature on Ethenolysis of Fatty Acid Methyl Esters Catalyzed by Spirocyclic Alkyl Amino Carbene Ru Complexes.

Spirocyclic alkyl amino carbene (SCAAC) Ru complexes demonstrate outstanding activity and selectivity in ethenolysis of methyl oleate (MO) or fatty acid methyl esters (FAMEs), and 5,6-dimethoxyindane derivative was the most active catalyst to date. For the further catalyst design, we proposed modifying the spirocyclic fragment by fusion of saturated carbo- or heterocycle, linked to the 5,6-positions of indane or 6,7- positions of tetralin. Another suggested way of the modification of SCAAC complex was the insertion of chromane fragment to the carbene ligand. Using an alternative approach to SCAAC ligand precursors, based on hydroformylation of indenes, dihydronaphthalenes and their analogs, new SCAAC complexes were synthesized, their cis-configuration was confirmed by XRD. Comparative study of new and known selected complexes in ethenolysis of FAMEs (84 wt% MO) revealed that each of SCAAC catalysts has a temperature optimum of activity. At 60 °C 0.5 ppm of the complex containing 1,2,3,4,5,6,7,8-octahydroanthracene spirocyclic fragment provided 56% conversion of FAMEs with TON = 1.1∙106; 0.25 ppm of this complex in ethenolysis of high-purity MO demonstrated the TON ~2∙106, leading among the catalysts under study. In ethenolysis of FAMEs chromane derivative showed TON of 4-6∙105 and unprecedented temperature-independent 99.7-99.9% selectivity at 15-60 °C.

Fragmenstein: predicting protein–ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding–based methodology

Current strategies centred on either merging or linking initial hits from fragment-based drug design (FBDD) crystallographic screens generally do not fully leaverage 3D structural information. We show that an algorithmic approach (Fragmenstein) that ‘stitches’ the ligand atoms from this structural information together can provide more accurate and reliable predictions for protein–ligand complex conformation than general methods such as pharmacophore-constrained docking. This approach works under the assumption of conserved binding: when a larger molecule is designed containing the initial fragment hit, the common substructure between the two will adopt the same binding mode. Fragmenstein either takes the atomic coordinates of ligands from a experimental fragment screen and combines the atoms together to produce a novel merged virtual compound, or uses them to predict the bound complex for a provided molecule. The molecule is then energy minimised under strong constraints to obtain a structurally plausible conformer. The code is available at https://github.com/oxpig/Fragmenstein.Scientific contributionThis work shows the importance of using the coordinates of known binders when predicting the conformation of derivative molecules through a retrospective analysis of the COVID Moonshot data. This method has had a prior real-world application in hit-to-lead screening, yielding a sub-micromolar merger from parent hits in a single round. It is therefore likely to further benefit future drug design campaigns and be integrated in future pipelines.Graphical

Probing Pregnane‐3,20‐Dione, 17,21‐[(Methylborylene)Bis(Oxy)]‐, (5. Beta)‐ as an Antiviral Candidate Against White Spot Syndrome Virus (WSSV): Molecular Docking and Simulation Approach

White spot syndrome virus (WSSV) is a highly infectious virus that poses an imminent threat to global shrimp aquaculture and is responsible for significant mortality in shrimp farms. There is a lack of targeted drug therapy options for preventing or treating WSSV. Consequently, these envelope proteins have garnered attention as an alternative focus for drug development at the molecular level. In the current study, the binding efficiency of pregnane‐3,20‐dione, 17,21‐[(methylborylene)bis(oxy)]‐, (5. beta)‐, a compound identified from Turbianria ornata, was predicted. The target proteins were major envelope proteins VP28, VP24, and VP110 of WSSV. The ligand structure was generated using PubChem and the SMILES platform. Docking was performed using AutoDock 4.2, employing blind docking to identify the preferred binding sites autonomously. A 100‐nanosecond molecular dynamics (MD) simulation was conducted for each protein–ligand complex using Desmond software to evaluate the stability and dynamics of these interactions. The complexes exhibited minimum values for both docking scores and binding energies. The additional data on root mean square deviation (RMSD) and root mean square fluctuation (RMSF) further supported the stability of proteins and ligands. The compound’s strong and stable binding with multiple WSSV envelope proteins suggests its potential as a broad‐spectrum antiviral agent against WSSV. The study found that the compound pregnane‐3,20‐dione, 17,21‐[(methylborylene)bis(oxy)]‐, (5. beta)‐ demonstrated high binding affinity Turbinaria ornata and stability with the viral envelope proteins VP28, VP24, and VP110, indicating strong antiviral potential against WSSV.

The structure-property relationship of metallocene-based ethylene oligomerization catalysts using DFT and graph neural networks.

Ethylene oligomerization catalysts have been extensively studied in both experimental and simulation contexts, yet a molecular-level understanding of structure-property relationship remains far from full understanding. Herein, an applicable strategy for the design of ligands of ethylene oligomerization catalysts is proposed. Density functional theory (DFT) and 3D graph neural networks (3D GNNs) have been combined to establish the relationship between the catalyst structure and its property. A series of titanium-based metallocene catalysts with different ligands were designed and calculated using DFT to establish a dataset. The catalyst prediction model was constructed using 3D GNNs, and a weighted removal approach was used to compare output results and study the impact of different ligand structures on the oligomerization selectivity represented by the energy barrier difference between β-hydrogen transfer and the fourth ethylene insertion. The R2 values of the energy barrier difference predictions by four 3D GNNs were 0.93-0.96, indicating good predictive accuracy of the graph network models. Using the graph neural network explanation algorithms, we investigated the influence of different substructures within the ligands on trimerization selectivity. Based on the training and explanation results of the model, an external validation set is designed, and the R2 is 0.92, suggesting the generalization ability of the model. This enabled a molecular-level study of the relationship between the structure of the titanocene catalyst and its properties, providing guidance for the design of new catalyst structures.

A novel platinum(II) complex with a berberine derivative as a potential antitumor agent targeting G-quadruplex DNA.

G-quadruplexes are considered attractive targets for various human diseases, including cancer therapy, owing to their potential therapeutic applications. Understanding the interaction between ligands and G-quadruplexes is crucial for the development of novel anticancer agents. In this study, we designed a novel platinum(II) complex (Pt1), with a berberine derivative (L) serving as a bioactive ligand. The structures of both ligand L and Pt1 were fully characterized using NMR, ESI-MS, and IR. UV-visible spectroscopy, fluorescence spectroscopy, circular dichroism spectroscopy, electrostatic surface potential, frontier molecular orbital and molecular docking experiments were employed to investigate the interaction between Pt1 and G-quadruplexes. The results suggested that Pt1 interacted favorably with G-quadruplex DNA over double-stranded DNA (DS26). Among them, Pt1 interacts with the bcl-2 G-quadruplex with a binding affinity of 17.9 μM and did not induce conformational changes in the topology of the bcl-2 G-quadruplex. Moreover, we evaluated its antiproliferative activities on tumor cells (HeLa, A549 and T24), which demonstrated that Pt1 inhibited tumor cell proliferation and induced HeLa cell apoptosis. Overall, this study offers novel insights for the development of promising platinum(II) antitumor agents based on G-quadruplex structures.

Palladium Bisphosphine Monoxide Complexes: Synthesis, Scope, Mechanism, and Catalytic Relevance.

Recent studies in transition metal catalysis employing chelating phosphines have suggested a role for partial ligand oxidation in formation of the catalytically active species, with potentially widespread relevance in a number of catalytic systems. We examine the internal redox reaction of PdII(bisphosphine)X2 (X = Cl, OAc, etc.) complexes to reveal previously underexplored aspects of bisphosphine monoxides (BPMOs), including evaluation of ligand structure and development of general reaction conditions to access a collection of structurally diverse BPMO precatalysts based on organopalladium oxidative addition complexes. In particular, a series of PdII(BPMO)(R)(X) (R = aryl, alkyl; X = I, Br) oxidative addition complexes bearing 24 different BPMO ligands were characterized by NMR and X-ray crystallography. Comparison of the catalytic performance of the oxidative addition complexes of bisphosphine versus bisphosphine monoxides as precatalysts is demonstrated to be an enabling diagnostic tool in Pd catalytic reaction development. Finally, the differences in catalytic behavior between bisphosphine and bisphosphine monoxide complexes were rationalized through solid-state parametrization and stoichiometric experiments.

Use of Intramolecular Quinol Redox Couples to Facilitate the Catalytic Transformation of O2 and O2-Derived Species.

ConspectusThe redox reactivity of transition metal centers can be augmented by nearby redox-active inorganic or organic moieties. In some cases, these functional groups can even allow a metal center to participate in reactions that were previously inaccessible to both the metal center and the functional group by themselves. Our research groups have been synthesizing and characterizing coordination complexes with polydentate quinol-containing ligands. Quinol is capable of being reversibly oxidized by either one or two electrons to semiquinone or para-quinone, respectively. Functionally, quinol behaves much differently than phenol, even though the pKa values of the first O-H bonds are nearly identical.The redox activity of the quinol in the polydentate ligand can augment the abilities of bound redox-active metals to catalyze the dismutation of O2-• and H2O2. These complexes can thereby act as high-performing functional mimics of superoxide dismutase (SOD) and catalase (CAT) enzymes, which exclusively use redox-active metals to transfer electrons to and from these reactive oxygen species (ROS). The quinols augment the activity of redox-active metals by stabilizing higher-valent metal species, providing alternative redox partners for the oxidation and reduction of reactive oxygen species, and protecting the catalyst from destructive side reactions. The covalently attached quinols can even enable redox-inactive Zn(II) to catalyze the degradation of ROS. With the Zn(II)-containing SOD and CAT mimics, the organic redox couple entirely substitutes for the inorganic redox couples used by the enzymes. The ligand structure modulates the antioxidant activity, and thus far, we have found that compounds that have poor or negligible SOD activity can nonetheless behave as efficient CAT mimics.Quinol-containing ligands have also been used to prepare electrocatalysts for dioxygen reduction, functionally mimicking the enzyme cytochrome c oxidase. The installation of quinols can boost electrocatalytic activity and even enable otherwise inactive ligand frameworks to support electrocatalysis. The quinols can also shift the product selectivity of O2 reduction from H2O2 to H2O without markedly increasing the effective overpotential. Distinct control of the coordination environment around the metal center allows the most successful of these catalysts to use economic and naturally abundant first-row transition metals such as iron and cobalt to selectively reduce O2 to H2O at low effective overpotentials. With iron, we have found that the electrocatalysts can enter the catalytic cycle as either an Fe(II) or Fe(III) species with no difference in turnover frequency. The entry point to the cycle, however, has a marked impact on the effective overpotential, with the Fe(III) species thus far being more efficient.

Current Status and Perspectives of Novel Radiopharmaceuticals with Heterologous Dual-targeted Functions: 2013-2023.

Radiotracers provide molecular- and cellular-level information in a noninvasive manner and have become important tools for precision medicine. In particular, the successful clinical application of radioligand therapeutic (RLT) has further strengthened the role of nuclear medicine in clinical treatment. The complicated microenvironment of the lesion has rendered traditional single-targeted radiopharmaceuticals incapable of fully meeting the requirements. The design and development of dual-targeted and multitargeted radiopharmaceuticals have rapidly emerged. In recent years, significant progress has been made in the development of heterologous dual-targeted radiopharmaceuticals. This perspective aims to provide a comprehensive overview of the recent progress in these heterologous dual-targeted radiopharmaceuticals, with a special focus on the design of ligand structures, pharmacological properties, and preclinical and clinical evaluation. Furthermore, future directions are discussed from this perspective.

Materials Nanoarchitectonics for Advanced Devices.

Advances in nanotechnology have made it possible to observe and evaluate structures down to the atomic and molecular level. The next step in the development of functional materials is to apply the knowledge of nanotechnology to materials sciences. This is the role of nanoarchitectonics, which is a concept of post-nanotechnology. Nanoarchitectonics is defined as a methodology to create functional materials using nanounits such as atoms, molecules, and nanomaterials as building blocks. Nanoarchitectonics is very general and is not limited to materials or applications, and thus nanoarchitecture is applied in many fields. In particular, in the evolution from nanotechnology to nanoarchitecture, it is useful to consider the contribution of nanoarchitecture in device applications. There may be a solution to the widely recognized problem of integrating top-down and bottom-up approaches in the design of functional systems. With this in mind, this review discusses examples of nanoarchitectonics in developments of advanced devices. Some recent examples are introduced through broadly dividing them into organic molecular nanoarchitectonics and inorganic materials nanoarchitectonics. Examples of organic molecular nanoarchitecture include a variety of control structural elements, such as π-conjugated structures, chemical structures of complex ligands, steric hindrance effects, molecular stacking, isomerization and color changes due to external stimuli, selective control of redox reactions, and doping control of organic semiconductors by electron transfer reactions. Supramolecular chemical processes such as association and intercalation of organic molecules are also important in controlling device properties. The nanoarchitectonics of inorganic materials often allows for control of size, dimension, and shape, and their associated physical properties can also be controlled. In addition, there are specific groups of materials that are suitable for practical use, such as nanoparticles and graphene. Therefore, nanoarchitecture of inorganic materials also has a more practical aspect. Based on these aspects, this review finally considers the future of materials nanoarchitectonics for further advanced devices.

Constructing a Metal-Organic Frameworks-Based Long-Acting Sequential Release System for the Treatment of Alzheimer's Disease.

Due to the unclear pathogenesis of Alzheimer's disease (AD) and the lack of a completely cured medication, AD patients need to take medication in order and on time every day all one's life, which is difficult for severe memory impairment patients to strictly follow on time. Traditional AD drug carriers, such as sugar coating and capsules, rely on dissolution or fragmentation to achieve drug release, which lacks the interaction between drug molecules and carriers, thus they cannot achieve sufficient long-acting and sequential drug release. Herein, Mn-MOF-74, which ligand structure is similar to two antioxidants dihydroquercetin (DHQ) and resveratrol (Res) is chosen as the carrier. Due to the differences in adsorption energy between DHQ/MOF and Res/MOF, the release speed of DHQ is much faster than Res. Therefore, Mn-MOF-74 loaded with DHQ and Res (DR@MOF) showed sequential drug release and a long-term antioxidant effect for ≈72h, with an efficacy time six times longer than that of vitamin E. In 5×FAD transgenic mice, DR@MOF exhibited excellent capacity in maintaining oxidative balance in the brain, ameliorating spatial learning and memory deficits, and showed the potential of an AD agent for long-acting and sequential treatment.

Efficient electrochemical water oxidation catalyzed by a novel nickel complex: Critical effect of the flexibility of pyridine-amine based pentadentate ligand on catalytic property

Efficient electrochemical water oxidation can be realized by reasonable modulation of the ligand structure of metal complex-based molecular water oxidation catalysts (WOCs). Herein, the synthesis and prowess in electrocatalytic water oxidation of a mononuclear water-soluble nickel complex, [Ni(tmbptu)(OH2)](ClO4)2 (1, tmbptu = 2,6,10-trimethyl-1,11-bis(2-pyridyl)-2,6,10-triazaundecanone), is reported for the first time. Complex 1 is found to be an efficient homogeneous WOCs under near neutral condition with long-term catalytic stability by a series of characterizations, including dynamic light scattering (DLS) measurement, scanning electron microscope (SEM), X-ray photoelectron spectroscopy (XPS), energy dispersive X-ray (EDX) analysis, chelation experiment, and Fe3+ test. Electrochemical tests reveal that water oxidation is accomplished via the generation of NiIV species generated by two successive e−/H+ proton coupled electron transfer (PCET) processes. Astonishingly, compared to the homologous complex [Ni(tmbptn)(OH2)](ClO4)2 (2, tmbptn = 2,5,8-trimethyl-1,9-bis(2-pyridyl)-2,5,8-triazanonane), which is a well-defined molecular WOC with high catalytic onset overpotential, 1 displays lower onset overpotential and much higher catalytic activity. This work suggesting that though the tertiary amine coordination environment have gain effect on the redox potential of metal center due to its poor sigma-donor effect, resulting in high onset overpotential of metal complex for water oxidation, this negative impact of the pyridine-amine ligand on the catalytic properties of complex can be weaken by adjusting the flexibility of backbone of those ligands.

Advancing Bioactivity Prediction through Molecular Docking and Self-Attention.

Bioactivity refers to the ability of a substance to induce biological effects within living systems, often describing the influence of molecules, drugs, or chemicals on organisms. In drug discovery, predicting bioactivity streamlines early-stage candidate screening by swiftly identifying potential active molecules. The popular deep learning methods in bioactivity prediction primarily model the ligand structure-bioactivity relationship under the premise of Quantitative Structure-Activity Relationship (QSAR). However, bioactivity is determined by multiple factors, including not only the ligand structure but also drug-target interactions, signaling pathways, reaction environments, pharmacokinetic properties, and species differences. Our study first integrates drug-target interactions into bioactivity prediction using protein-ligand complex data from molecular docking. We devise a Drug-Target Interaction Graph Neural Network (DTIGN), infusing interatomic forces into intermolecular graphs. DTIGN employs multi-head self-attention to identify native-like binding pockets and poses within molecular docking results. To validate the fidelity of the self-attention mechanism, we gather ground truth data from crystal structure databases. Subsequently, we employ these limited native structures to refine bioactivity prediction via semi-supervised learning. For this study, we establish a unique benchmark dataset for evaluating bioactivity prediction models in the context of protein-ligand complexes, showcasing the superior performance of our method (with an average improvement of 27.03%) through comparison with 9 leading deep learning-based bioactivity prediction methods.

Utility of Immobilized Metal Salens as Electrocatalysts: Fuel Cells and Organic Electrosynthesis

AbstractThere have been significant advancements in the electrosynthesis of fuels and organic molecules, making it an increasingly sustainable and cost‐effective alternative to traditional chemical redox reagents. Early versions of these systems faced challenges in chemoselectivity due to high applied overpotentials, which have been mitigated with the introduction of molecular electrocatalysts, like metal salens (MSalens). These MSalens reduce the required overpotentials, increase turnover numbers (TON), and have simple modularity within their ligand structure allowing for tunable selectivity. While these MSalen electrocatalysts are typically used homogeneously for engineering simplicity, downstream separations are often costly and time‐consuming. Immobilization of MSalens addresses these issues by enabling synthesis at lower potentials, achieving high selectivity, and facilitating straightforward separations. This review explores the application of MSalens in electrosynthesis and immobilized molecular electrocatalysts in organic electrosynthesis.

Synthesis, Spectroscopic Studies, Thermal Stability and Crystal Structure of New Bidentate Schiff Base and Its Cadmium Complex

A new asymmetric bidentate Schiff base ligand was synthesized from a condensation reaction between 2,4-dichlorobenzaldehyde (C7H4Cl2O) and 1,3-pentanediamine (C5H14N2). A cadmium complex was prepared by adding Cd(II) iodide dissolved in methanol to a methanolic solution of the Schiff base ligand, in a ratio of 1:1. The ligand was characterized by elemental, spectroscopic (IR, <sup>1</sup>H NMR), and thermogravimetric analyses. The ligand structure, thermally very stable, is revealed to be bidentate with two potential N-donor sites. The crystal structure of the Schiff base was elucidated by X-ray diffraction analysis. Compound crystallizes in a monoclinic system with a space group P21/n and a number of units per unit cell Z = 4. The unit cell parameters are: a =7.3885(2), b =16.9332 (4), c = 15.5624(4), and β = 90.4306(10). In the asymmetric unit of the ligand, the benzene rings C08/C10/C09/C11/C21/C17 and C20/C15/C13/C18/C22/C24 are in trans position with the aliphatic group with respect to the bonds (C07-N05) and (C19-N06), respectively. In addition, these two aromatic rings are located in two different planes, forming an angle of 3.60º between them, given that the dihedral angle between the ring C08/C10/C09/C11/C21/C17 and the aliphatic group N05-N06 is 67.49º. The spectroscopic data of the complex reveals a mononuclear complex where the Cd(II) ion is housed in a N2I2 coordination site with a slightly distorted tetrahedral geometry. The conductance data indicate that the complex is a neutral electrolyte.