Protein Pocket Research Articles

Expansion of pneumococcal serotype 23F and 14 lineages with genotypic changes in capsule polysaccharide locus and virulence gene profiles post introduction of pneumococcal conjugate vaccine in Blantyre, Malawi.

Since the introduction of the 13-valent pneumococcal conjugate vaccine (PCV13) in Malawi in 2011, there has been persistent carriage of vaccine serotype (VT) Streptococcus pneumoniae, despite high vaccine coverage. To determine if there has been a genetic change within the VT capsule polysaccharide (cps) loci since the vaccine's introduction, we compared 1022 whole-genome-sequenced VT isolates from 1998 to 2019. We identified the clonal expansion of a multidrug-resistant, penicillin non-susceptible serotype 23F GPSC14-ST2059 lineage, a serotype 14 GPSC9-ST782 lineage and a novel serotype 14 sequence type GPSC9-ST18728 lineage. Serotype 23F GPSC14-ST2059 had an I253T mutation within the capsule oligosaccharide repeat unit polymerase Wzy protein, which is predicted in silico to alter the protein pocket cavity. Moreover, serotype 23F GPSC14-ST2059 had SNPs in the DNA binding sites for the cps transcriptional repressors CspR and SpxR. Serotype 14 GPSC9-ST782 harbours a non-truncated version of the large repetitive protein (Lrp), containing a Cna protein B-type domain which is also present in proteins associated with infection and colonisation. These emergent lineages also harboured genes associated with antibiotic resistance, and the promotion of colonisation and infection which were absent in other lineages of the same serotype. Together these data suggest that in addition to serotype replacement, modifications of the capsule locus associated with changes in virulence factor expression and antibiotic resistance may promote vaccine escape. In summary, the study highlights that the persistence of vaccine serotype carriage despite high vaccine coverage in Malawi may be partly caused by expansion of VT lineages post-PCV13 rollout.

EMPDTA: An End-to-End Multimodal Representation Learning Framework with Pocket Online Detection for Drug-Target Affinity Prediction.

Accurately predicting drug-target interactions is a critical yet challenging task in drug discovery. Traditionally, pocket detection and drug-target affinity prediction have been treated as separate aspects of drug-target interaction, with few methods combining these tasks within a unified deep learning system to accelerate drug development. In this study, we propose EMPDTA, an end-to-end framework that integrates protein pocket prediction and drug-target affinity prediction to provide a comprehensive understanding of drug-target interactions. The EMPDTA framework consists of three main modules: pocket online detection, multimodal representation learning for affinity prediction, and multi-task joint training. The performance and potential of the proposed framework have been validated across diverse benchmark datasets, achieving robust results in both tasks. Furthermore, the visualization results of the predicted pockets demonstrate accurate pocket detection, confirming the effectiveness of our framework.

Molecular Modeling and simulation-based identification of inhibitors against new Delhi Metallo-Lactamase 1: Implications for bacterial antibiotic resistance

ObjectivesBacterial infections expressing New Delhi metallo-lactamase-1 (NDM-1) pose an escalating global threat to healthcare systems. NDM-1 is an enzyme that renders β-lactam antibiotics ineffective, leading to resistance against numerous antibiotics used in clinical practice. Therefore, there is an urgent need to identify and develop a clinically relevant inhibitor for NDM-1. MethodsVitas-M laboratory database was screened for small molecules with abilities to bind NDM-1, by generating structure-based pharmacophore hypothesis. Thereafter, molecular docking was performed between NDM-1 and the potential small molecule inhibitors. The outcomes of molecular docking were validated by molecular dynamics simulation and MM-GBSA protocols. ResultsBased upon initial NDM-1-binding characteristics, two ligands (STK115225 and STK107343) were nominated for further analyses for stability and affinity of protein–ligand interactions. Assessment of conformational change parameters indicated that these showed tight and stable binding to the active site pocket of NDM-1 protein. Principal component analysis (PCA) further illustrated that the protein ligand complexes were highly stable. Molecular dynamics simulation along with high numbers of static hydrogen bonds signifies the potency of STK115225 and STK107343 in inhibiting NDM-1. Further, MM-GBSA-based binding free energy maps verified favorable energy changes for the binding of the two small molecules, indicating their abilities for high affinity-binding with NDM-1. ConclusionsThis study has significant implications for addressing antibiotic resistance mediated by NDM-1. The identification of STK115225 and STK107343 as high-affinity binding ligands against NDM-1 provides a strong foundation for developing new therapeutic agents. However, to fully ascertain their clinical relevance, these findings must be validated through in vitro and in vivo experiments. If successful, these inhibitors could restore the efficacy of β-lactam antibiotics and offer a new approach to combat NDM-1 mediated antibiotic resistance, ultimately improving patient outcomes and reducing the global burden of resistant bacterial infections.

An Updated Structure of Oxybutynin Hydrochloride.

Oxybutynin (Ditropan), a widely distributed muscarinic antagonist for treating the overactive bladder, has been awaiting a definitive crystal structure for nearly 50 years due to the sample and technique limitations. Past reports used powder X-ray diffraction (PCRD) to shed light on the possible packing of the molecule however a 3D structure remained elusive. Here we used Microcrystal Electron Diffraction (MicroED) to successfully unveil the 3D structure of oxybutynin hydrochloride. We identify several inconsistencies between the reported PXRD analyses and the experimental structure. Using the improved model, molecular docking was applied to investigate the binding mechanism between M3 muscarinic receptor (M3R) and (R)-oxybutynin, revealing essential contacts/residues and conformational changes within the protein pocket. A possible universal conformation was proposed for M3R antagonists, which is valuable for future drug development and optimization. This study underscores the immense potential of MicroED as a complementary technique for elucidating the unknown pharmaceutical crystal structures, as well as for the protein-drug interactions.

(-)-Epigallocatechin gallate as an inhibitor of hemoglobin-catalyzed lipid oxidation: molecular mechanism of action and nutritional application

Hemoglobin (Hb) is effective inducer for lipid oxidation and protein–polyphenol interaction is a well-known phenomenon. The effects of the interaction of (-)-epigallocatechin gallate (EGCG) with Hb on lipid oxidation were rarely elucidated. The detailed interaction between bovine Hb and EGCG was systematically explored by experimental and theoretical approaches, to illustrate the molecular mechanisms by which EGCG influenced the redox states and stability of Hb. EGCG would bind to the central pocket of protein with one binding site to form Hb-EGCG complex. The binding constant for Hb-EGCG complex was 0.34 × 104 M−1 at 277 K, and thermodynamic parameters (ΔH > 0, ΔS > 0 and ΔG < 0) revealed the participation of hydrophobic forces in the binding process. The binding of EGCG would increase the compactness of protein molecule and diminish the crevice near the heme cavity, which was responsible for the reduction of met-Hb to oxy-Hb and inhibition of hemin release from met-Hb. Moreover, EGCG efficiently suppressed Hb-caused lipid oxidation in liposomes and cod muscles, which was possibly attributed to the reduction to oxy-Hb state and declined hemin dissociation from met-Hb. Altogether, our results provide significant insights into the binding of EGCG to redox-active Hb, which represents a novel mechanism for the anti-oxidant capacity of EGCG in human health and is favorable to the applications of natural EGCG in the good quality of Hb-containing products.

A Conserved Binding Pocket in HydF is Essential for Biological Assembly and Coordination of the Diiron Site of [FeFe]-Hydrogenases.

The active site cofactor of [FeFe]-hydrogenases consists of a cubane [4Fe-4S]-cluster and a unique [2Fe-2S]-cluster, harboring unusual CO- and CN--ligands. The biosynthesis of the [2Fe-2S]-cluster requires three dedicated maturation enzymes called HydG, HydE and HydF. HydG and HydE are both involved in synthesizing a [2Fe-2S]-precursor, still lacking parts of the azadithiolate (adt) moiety that bridge the two iron atoms. This [2Fe-2S]-precursor is then finalized within the scaffold protein HydF, which binds and transfers the [2Fe-2S]-precursor to the hydrogenase. However, its exact binding mode within HydF is still elusive. Herein, we identified the binding location of the [2Fe-2S]-precursor by altering size and charge of a highly conserved protein pocket via site directed mutagenesis (SDM). Moreover, we identified two serine residues that are essential for binding and assembling the [2Fe-2S]-precursor. By combining SDM and molecular docking simulations, we provide a new model on how the [2Fe-2S]-cluster is bound to HydF and demonstrate the important role of one highly conserved aspartate residue, presumably during the bioassembly of the adt moiety.

Small-Molecule Disruptors of the Interaction between Calcium- and Integrin-Binding Protein 1 and Integrin αIIbβ3 as Novel Antiplatelet Agents.

Thrombosis, a key factor in most cardiovascular diseases, is a major contributor to human mortality. Existing antithrombotic agents carry a risk of bleeding. Consequently, there is a keen interest in discovering innovative antithrombotic agents that can prevent thrombosis without negatively impacting hemostasis. Platelets play crucial roles in both hemostasis and thrombosis. We have previously characterized calcium- and integrin-binding protein 1 (CIB1) as a key regulatory molecule that regulates platelet function. CIB1 interacts with several platelet proteins including integrin αIIbβ3, the major glycoprotein receptor for fibrinogen on platelets. Given that CIB1 regulates platelet function through its interaction with αIIbβ3, we developed a fluorescence polarization (FP) assay to screen for potential inhibitors. The assay was miniaturized to 1536-well and screened in quantitative high-throughput screening (qHTS) format against a diverse compound library of 14,782 compounds. After validation and selectivity testing using the FP assay, we identified 19 candidate inhibitors and validated them using an in-gel binding assay that monitors the interaction of CIB1 with αIIb cytoplasmic tail peptide, followed by testing of top hits by intrinsic tryptophan fluorescence (ITF) and microscale thermophoresis (MST) to ascertain their interaction with CIB1. Two of the validated hits shared similar chemical structures, suggesting a common mechanism of action. Docking studies further revealed promising interactions within the hydrophobic binding pocket of the target protein, particularly forming key hydrogen bonds with Ser180. The compounds exhibited a potent antiplatelet activity based on their inhibition of thrombin-induced human platelet aggregation, thus indicating that disruptors of the CIB1- αIIbβ3 interaction could carry a translational potential as antithrombotic agents.

Druggability Analysis of Protein Targets for Drug Discovery to Combat Listeria monocytogenes.

Extensive research has been conducted to identify key proteins governing stress responses, virulence, and antimicrobial resistance, as well as to elucidate their interactions within Listeria monocytogenes. While these proteins hold promise as potential targets for novel strategies to control L. monocytogenes, given their critical roles in regulating the pathogen's metabolism, additional analysis is needed to further assess their druggability-the chance of being effectively bound by small-molecule inhibitors. In this work, 535 binding pockets of 46 protein targets for known drugs (mainly antimicrobials) were first analyzed to extract 13 structural features (e.g., hydrophobicity) in a ligand-protein docking platform called Molsoft ICM Pro. The extracted features were used as inputs to develop a logistic regression model to assess the druggability of protein binding pockets, with a value of one if ligands can bind to the protein pocket. The developed druggability model was then used to evaluate 23 key proteins from L. monocytogenes that have been identified in the literature. The following proteins are predicted to be high-potential druggable targets: GroEL, FliH/FliI complex, FliG, FlhB, FlgL, FlgK, InlA, MogR, and PrfA. These findings serve as an initial point for future research to identify specific compounds that can inhibit druggable target proteins and to design experimental work to confirm their effectiveness as drug targets.

An in silico approach for identification of lead compound as FtsZ inhibitor.

The remarkable conservation of the FtsZ among Gram-positive and Gram-negative bacteria, a crucial GTPase in bacterial cell division, has emerged as a promising antibacterial drug target to combat antibacterial resistance. There have been several coordinated efforts to develop inhibitors against FtsZ which can also serve as potential candidates for future antibiotics. In the present study, a natural product-like library (≈50,000 compounds) was employed to conduct HTVS against Staphylococcus aureus FtsZ protein (PDB Id: 6KVP). Additionally, molecular docking was carried out in two modes, SP and XP docking, using the Schrödinger suite. The glide scores of ligands obtained by XP docking were further summarized and compared with the control ligands (ZI1- co-crystal and PC190723-a compound undergoing clinical trial). Using the Prime-MM-GBSA approach, BFE calculations were performed on the top XP-scored ligands (≈598 compounds). These hits were also evaluated for ADMET parameters using the Qikprop algorithm, SwissADME, and in silico carcinogenicity testing using Carcinopred-El. Based on the results, ligand 4-FtsZ complex was considered for the 300ns MDS analysis to get insights into its binding modes within the catalytic pocket of FtsZ protein. The analysis revealed that the amide linkage sandwiched between the triazole and 1-oxa-8-azaspirodecan-8-ium moiety (Val203) as well as the aminoethyl group present at 1st position on the triazole moiety (Leu209, Leu200, Asp210, and Ala202) were responsible for the FtsZ inhibitory activity, owing to their crucial interactions with key amino acid residues. Further, the complex also displayed good protein-ligand stability, ultimately predicting ligand 4 as a potent lead compound for the inhibition of FtsZ. Thus, our in silico findings will serve as a framework for in-depth in-vitro and in-vivo investigations encouraging the development of FtsZ inhibitors as a new generation of antibacterial agents.

Subpocket-Based Analysis Approach for the Protein Pocket Dynamics.

Structural and dynamic characteristics of protein pockets remarkably influence their biological functions and are also important for enzyme engineering and new drug research and development. To date, several softwares have been developed to analyze the dynamic properties of protein pockets. However, due to the complexity and diversity of the pocket information during the kinetic relaxation, further improvement and capacity expansion of current tools are required. Here, we developed a platform software AlphaTraj in which a computational strategy that divides the whole protein pocket into subpockets and examines various properties of the subpockets such as survival time, stability, and correlation was proposed and implemented. We also proposed a scoring function for the subpockets as well as the whole pocket to visualize the quality of the pocket. Furthermore, we implemented automated conformational search functions for ligand docking and ligand optimization. These functions may help us to gain a deep understanding of the dynamic properties of protein pockets and accelerate the protein engineering and the design of inhibitors and small-molecule drugs. The software is freely available at https://github.com/dooo12332/AlphaTraj.git under the GNU GPL license.

Correlation of protein binding pocket properties with hits’ chemistries used in generation of ultra-large virtual libraries

Although the size of virtual libraries of synthesizable compounds is growing rapidly, we are still enumerating only tiny fractions of the drug-like chemical universe. Our capability to mine these newly generated libraries also lags their growth. That is why fragment-based approaches that utilize on-demand virtual combinatorial libraries are gaining popularity in drug discovery. These à la carte libraries utilize synthetic blocks found to be effective binders in parts of target protein pockets and a variety of reliable chemistries to connect them. There is, however, no data on the potential impact of the chemistries used for making on-demand libraries on the hit rates during virtual screening. There are also no rules to guide in the selection of these synthetic methods for production of custom libraries. We have used the SAVI (Synthetically Accessible Virtual Inventory) library, constructed using 53 reliable reaction types (transforms), to evaluate the impact of these chemistries on docking hit rates for 40 well-characterized protein pockets. The data shows that the virtual hit rates differ significantly for different chemistries with cross coupling reactions such as Sonogashira, Suzuki–Miyaura, Hiyama and Liebeskind–Srogl coupling producing the highest hit rates. Virtual hit rates appear to depend not only on the property of the formed chemical bond but also on the diversity of available building blocks and the scope of the reaction. The data identifies reactions that deserve wider use through increasing the number of corresponding building blocks and suggests the reactions that are more effective for pockets with certain physical and hydrogen bond-forming properties.

Exploring the Interactions between two Ligands, UCB-J and UCB-F, and Synaptic Vesicle Glycoprotein 2 Isoforms.

In silico modeling was applied to study the efficiency of two ligands, namely, UCB-J and UCB-F, to bind to isoforms of the synaptic vesicle glycoprotein 2 (SV2) that are involved in the regulation of synaptic function in the nerve terminals, with the ultimate goal to understand the selectivity of the interaction between UCB-J and UCB-F to different isoforms of SV2. Docking and large-scale molecular dynamics simulations were carried out to unravel various binding patterns, types of interactions, and binding free energies, covering hydrogen bonding and nonspecific hydrophobic interactions, water bridge, π-π, and cation-π interactions. The overall preference for bonding types of UCB-J and UCB-F with particular residues in the protein pockets can be disclosed in detail. A unique interaction fingerprint, namely, hydrogen bonding with additional cation-π interaction with the pyridine moiety of UCB-J, could be established as an explanation for its high selectivity over the SV2 isoform A (SV2A). Other molecular details, primarily referring to the presence of π-π interactions and hydrogen bonding, could also be analyzed as sources of selectivity of the UCB-F tracer for the three isoforms. The simulations provide atomic details to support future development of new selective tracers targeting synaptic vesicle glycoproteins and their associated diseases.

Predicting Solvatochromism of Chromophores in Proteins through QM/MM and Machine Learning.

Solvatochromism occurs in both homogeneous solvents and more complex biological environments, such as proteins. While in both cases the solvatochromic effects report on the surroundings of the chromophore, their interpretation in proteins becomes more complicated not only because of structural effects induced by the protein pocket but also because the protein environment is highly anisotropic. This is particularly evident for highly conjugated and flexible molecules such as carotenoids, whose excitation energy is strongly dependent on both the geometry and the electrostatics of the environment. Here, we introduce a machine learning (ML) strategy trained on quantum mechanics/molecular mechanics calculations of geometrical and electrochromic contributions to carotenoids' excitation energies. We employ this strategy to compare solvatochromism in protein and solvent environments. Despite the important specifities of the protein, ML models trained on solvents can faithfully predict excitation energies in the protein environment, demonstrating the robustness of the chosen descriptors.

Anti-inflammatory and anti-diabetic properties of indanone derivative isolated from Fernandoa adenophylla in vitro and in silico studies

Fernandoa adenophylla, due to the presence of phytochemicals, has various beneficial properties and is used in folk medicine to treat many conditions. This study aimed to isolate indanone derivative from F. adenophylla root heartwood and assess in-vitro anti-inflammatory and anti-diabetic characteristics at varying concentrations. Heat-induced hemolysis and glucose uptake by yeast cells assays were conducted to evaluate these properties. Besides, docking analyses were performed on four molecular targets. These studies were combined with molecular dynamics simulations to elucidate the time-evolving inhibitory effect of selected inhibitors within the active pockets of the target proteins (COX-1 and COX-2). Indanone derivative (10–100 µM) inhibited the lysis of human red blood cells from 9.12 ± 0.75 to 72.82 ± 4.36% and, at 5–100 µM concentrations, it significantly increased the yeast cells’ glucose uptake (5.16 ± 1.28% to 76.59 ± 1.62%). Concluding, the isolated indanone might act as an anti-diabetic agent by interacting with critical amino acid residues of 5′ adenosine monophosphate-activated protein kinase (AMPK), and it showed a binding affinity with anti-inflammatory targets COX-1, COX-2, and TNF-α. Besides, the obtained results may help to consider the indanone derivative isolated from F. adenophylla as a promising candidate for drug delivery, subject to outcomes of further in vivo and clinical studies.

An Atomic and Molecular Insight into How PFOA Reduces α-Helicity, Compromises Substrate Binding, and Creates Binding Pockets in a Model Globular Protein.

Per- and polyfluoroalkyl substances (PFAS) pose significant health risks due to their widespread presence in various environmental and biological matrices. However, the molecular-level mechanisms underlying the interactions between PFAS and biological constituents, including proteins, carbohydrates, lipids, and DNA, remain poorly understood. Here, we investigate the interactions between a legacy PFAS, viz. perfluorooctanoic acid (PFOA), and the milk protein β-lactoglobulin (BLG) obtained using a combination of experimental and computational techniques. Circular dichroism studies reveal that PFOA perturbs the secondary structure of BLG, by driving a dose-dependent loss of α-helicity and alterations in its β-sheet content. Furthermore, exposure of the protein to PFOA attenuates the on-rate constant for the binding of the hydrophobic probe 8-anilino-1-naphthalene sulfonic acid (ANS), suggesting potential functional impairment of BLG by PFOA. Steered molecular dynamics and umbrella sampling calculations reveal that PFOA binding leads to the formation of an energetically favorable novel binding pocket within the protein, when residues 129-142 are steered to unfold from their initial α-helical structure, wherein a host of intermolecular interactions between PFOA and BLG's residues serve to insert the PFOA into the region between the unfolded helix and beta-sheets. Together, the data provide a novel understanding of the atomic and molecular mechanism(s) by which PFAS modulates structure and function in a globular protein, leading to a beginning of our understanding of altered biological outcomes.

Identification of new potent NLRP3 inhibitors by multi-level in-silico approaches

Nod-like receptor protein 3 (NLRP-3), is an intracellular sensor that is involved in inflammasome activation, and the aberrant expression of NLRP3 is responsible for diabetes mellitus, its complications, and many other inflammatory diseases. NLRP3 is considered a promising drug target for novel drug design. Here, a pharmacophore model was generated from the most potent inhibitor, and its validation was performed by the Gunner-Henry scoring method. The validated pharmacophore was used to screen selected compounds databases. As a result, 646 compounds were mapped on the pharmacophore model. After applying Lipinski's rule of five, 391 hits were obtained. All the hits were docked into the binding pocket of target protein. Based on docking scores and interactions with binding site residues, six compounds were selected potential hits. To check the stability of these compounds, 100 ns molecular dynamic (MD) simulations were performed. The RMSD, RMSF, DCCM and hydrogen bond analysis showed that all the six compounds formed stable complex with NLRP3. The binding free energy with the MM-PBSA approach suggested that electrostatic force, and van der Waals interactions, played a significant role in the binding pattern of these compounds. Thus, the outcomes of the current study could provide insights into the identification of new potential NLRP3 inflammasome inhibitors against diabetes and its related disorders.

In silico identification of phytochemical inhibitors for multidrug-resistant tuberculosis based on novel pharmacophore generation and molecular dynamics simulation studies

BackgroundMultidrug-resistant tuberculosis (particularly resistant to pyrazinoic acid) is a life-threatening chronic pulmonary disease. Running a marketed regime specifically targets the ribosomal protein subunit-1 (RpsA) and stops trans-translation in the non-mutant bacterium, responsible for the lysis of bacterial cells. However, in the strains of mutant bacteria, this regime has failed in curing TB and killing pathogens, which may only because of the ala438 deletion, which inhibit the binding of pyrazinoic acid to the RpsA active site. Therefore, such cases of tuberculosis need an immediate and effective regime.ObjectiveThis study has tried to determine and design such chemotypes that are able to bind to the mutant RpsA protein.MethodsFor these purposes, two phytochemical databases, i.e., NPASS and SANCDB, were virtually screened by a pharmacophore model using an online virtual screening server Pharmit.ResultsThe model of pharmacophore was developed using the potential inhibitor (zr115) for the mutant of RpsA. Pharmacophore-based virtual screening results into 154 hits from the NPASS database, and 22 hits from the SANCDB database. All the predicted hits were docked in the binding pocket of the mutant RpsA protein. Top-ranked five and two compounds were selected from the NPASS and SANCDB databases respectively. On the basis of binding energies and binding affinities of the compounds, three compounds were selected from the NPASS database and one from the SANCDB database. All compounds were found to be non-toxic and highly active against the mutant pathogen. To further validate the docking results and check the stability of hits, molecular dynamic simulation of three compounds were performed. The MD simulation results showed that all these finally selected compounds have stronger binding interactions, lesser deviation or fluctuations, with greater compactness compared to the reference compound.ConclusionThese findings indicate that these compounds could be effective inhibitors for mutant RpsA.

Equivariant 3D-conditional diffusion model for molecular linker design

AbstractFragment-based drug discovery has been an effective paradigm in early-stage drug development. An open challenge in this area is designing linkers between disconnected molecular fragments of interest to obtain chemically relevant candidate drug molecules. In this work, we propose DiffLinker, an E(3)-equivariant three-dimensional conditional diffusion model for molecular linker design. Given a set of disconnected fragments, our model places missing atoms in between and designs a molecule incorporating all the initial fragments. Unlike previous approaches that are only able to connect pairs of molecular fragments, our method can link an arbitrary number of fragments. Additionally, the model automatically determines the number of atoms in the linker and its attachment points to the input fragments. We demonstrate that DiffLinker outperforms other methods on the standard datasets, generating more diverse and synthetically accessible molecules. We experimentally test our method in real-world applications, showing that it can successfully generate valid linkers conditioned on target protein pockets.

Design, synthesize, physicochemical characterization, nonlinear optical properties structural elucidation, biomedical studies, and DNA interaction of some new mixed ligand complexes incorporating 4,6‐dimethylpyrimidine derivative and imidazole ligand

This study was planned to prepare new mixed ligand chelates derived from N‐(4,6‐dimethylpyrimidin‐2‐yl)‐3a,4,5,6,7,7a‐hexahydro‐1H‐benzimidazol‐2‐amine (BIP), and imidazole (I). They identified through CHN study, spectroscopic (NMR, FT‐IR, and UV–Vis), conductivity, magnetic susceptibility, mass analysis, and thermal analysis. Correlation between all results exposed that the BIP ligand performed as a bi‐dentate ligand through NN donation locations, where the co‐ligand shows as N–H monodentate. The optimization for the studied chelates led to the formation of distorted octahedral geometry for BIPICu and BIPIVO chelates, distorted (tetrahedral and square planar) geometry for BIPIAg and BIPIPd chelates, respectively, around the metal salt. The B3LYP level, B3LYP/6‐311G** level for the free ligand, and B3LYP/6–311G**‐LANL2DZ functional level for the solid chelates were used in density functional theory (DFT) calculations. The findings showed that DFT calculations produce conclusions that are consistent with those of the experiments. The resulting compounds' nonlinear optical properties were examined by calculating the hyperpolarizability (β) and molecular polarizability (α) parameters, which gave rise to several unexpected optical properties for the synthesized compounds. Using the agar well diffusion method, the antimicrobial activity of the produced compounds was experimentally confirmed against a subset of G+ and G− bacteria. To ascertain how these substances attach to the targeted protein binding sites, a molecular docking mechanism between the microbially resistant chelates and their suppressed microbial protein pocket receptors was investigated. Also, DNA binding estimated for studied structures was tested by electronic absorption spectrum, viscosity estimation, and gel electrophoresis. Data proposed that all tested compounds link with DNA using an intercalation, electrostatic, and covalent binding mechanism. Moreover, antioxidant performance for studied compounds was governed by radical scavenging techniques in vitro. In addition, an MTT assay has been worked out to explore in vitro cytotoxic impending. All the tested chelates assumed antimicrobial, antitumor, and antioxidant performances that cause them to suggest drugs.

Advances in exploration of photoinduced electron transfer reactions involving small molecules probed by magnetic field effect

The review focuses on photoinduced electron transfer (PET) reactions between small molecules and various kinds of chemical and biological systems using a weak external magnetic field (MF). Laser flash photolysis is a competent tool to characterize the intermediates which are formed due to PET. A weak MF, very close to the hyperfine interaction of the system, has the potential to inhibit or enhance reaction channels for singlet and triplet states, which eventually effects the product distribution. At first, well-documented examples of PET involving small molecules like derivatives of phenazines, carbazoles and acridines with classical electron donors in varying homogeneous and heterogeneous media have been discussed and the influence of a weak MF on the dynamics of PET is highlighted. Secondly, utilization of magnetic field effect (MFE) to probe PET in protein pockets has been described. Thirdly, an extensive discussion on PET involving nucleobases, nucleosides, nucleotides and nucleic acids and subsequent MFE on such reactions has been reported. Next, MFE has been exploited to study PET involving nanomaterials. Finally, some very recent studies of MFE have been discussed. Thus, this review is an attempt to unravel various aspects of PET in a large number of systems of varying dimensions by means of several facets of MFE like B1/2 parameter, its capability to authenticate the initial spin state and distance dependence property.