Metal–ligand interactions in drug design

Recent advances in Schiff bases and Cu(II) complexes: Applications in fluorescence imaging and anticancer therapy (2020-2024)

Schiff base derivatives have garnered significant attention for their bioimaging and anticancer potentials. In the realm of bioimaging, Schiff base derivatives have shown exceptional capabilities in detecting various metal ions, due to their strong binding affinities and fluorescence properties. Moreover, the potential Schiff bases and their Cu(II) complexes as anticancer agents is being actively explored, with studies demonstrating their ability to induce apoptosis and inhibit cell proliferation in various cancer cell lines. This review article provides a comprehensive overview of recent advancements in the field of cell imaging utilizing Schiff base derivatives for the recognition of Cu2+ in living cells and organisms. From 2022 to 2024, significant progress has been made in understanding the applications of Schiff bases in cell imaging techniques, ranging from fluorescence microscopy to molecular imaging modalities. Additionally, article has focused on leveraging the unique properties of Schiff base Cu(II) complexes to expand the anticancer efficacy. The article offering insights into the mechanisms underlying enhanced anticancer activity and the development of novel anticancer agents.

Rationally designed Pyrazolo[1,5-a]pyrimidines as dual inhibitors of CA IX/XII and CDK6: A novel approach for NSCLC treatment

Developing novel anticancer agents that target critical pathways in non-small cell lung cancer (NSCLC) presents a considerable challenge. This study synthesized 16 pyrazolo[1,5-a]pyrimidine derivatives with zinc-binding groups through molecular hybridization to achieve dual-target inhibition of tumor-associated carbonic anhydrase (CA) isoforms IX/XII and cyclin-dependent kinase 6 (CDK6). In-vitro assays indicated that sulfonamide-bearing compounds displayed enhanced CA inhibition, with compounds 7d, 11b, and 11d presenting Ki values of 11.2, 18.4, and 19.7 nM for CA IX, while compounds 11a and 11c exhibited Ki values of 14.8 and 8.7 nM for CA XII. Cytotoxicity assays conducted on NSCLC cell lines A549 and NCI-H1734 demonstrated that compounds 7c, 7d, 7i, and 11d exhibited superior activity relative to Roscovitine in both cell lines. While these compounds demonstrated limited inhibition of cyclin-dependent kinase 4 (CDK4), 7d and 11d effectively inhibited CDK6, with IC50 values of 0.054 and 0.069 μM, respectively, which are comparable to Palbociclib. Analyses of the cell cycle and apoptosis demonstrated a strong G1 arrest and a notable induction of apoptosis. Molecular docking confirmed essential binding interactions with CA IX/XII and CDK6, while in-silico ADMET predictions suggested favorable pharmacokinetics, despite potential toxicity concerns. Compounds 7d and 11d represent potential dual-target inhibitors for the treatment of NSCLC.

The antibacterial activity and selectivity of bismuth(III) tris(8-hydroxyquinolinates)

The series of bismuth(III) tris(8-hydroxyquinolinates); [Bi(Q")3] (1), [Bi(Q'Cl)3] (2), [Bi(QCl2)3] (3), [Bi(QBr2)3] (4), and [Bi(QI2)3] (5) (where Q"-H = C9H7NO; Q'Cl-H = C9H6NOCl, QCl2-H = C9H5NOCl2; QBr2-H = C9H5NOBr2; and QI2-H = C9H5NOI2) were synthesised, fully characterised, and evaluated for their antibacterial activity towards three Gram-positive bacteria (vancomycin-resistant E. faecalis, S. aureus, methicillin-resistant S. aureus), and four Gram-negative bacteria (A. baumannii, P. aeruginosa, K. pneumoniae, and E. coli) and also their cytotoxicity towards mammalian cells. New crystallographic data on 4 indicates it is dimeric in the solid state through 'Bi2O2' bridging which is consistent with data previously reported for 5. The five complexes (1-5) all exhibited good but variable antibacterial activity and selectivity. Complexes 2 and 5 showed significant activity towards Gram-positive bacteria with MIC (minimum inhibitory concentration) values ranging from 0.78 μM - 3.13 μM and selectivity indices of 6.2 - ≥16.0. For Gram-negative species, complexes 3 and 4 exhibited highly selective activity towards multi-drug resistant strains of A. baumannii with a range of MIC values 0.39-1.56 μM and selectivity indices of 3.14-7.23 respectively. While some of the 8-hydroxyquinolines themselves show reasonable antibacterial activity this is generally enhanced through complexation to bismuth(III).

Mycobacterium susceptibility to ivermectin by inhibition of eccD3, an ESX-3 secretion system component

Drug-resistant tuberculosis is a pressing global health issue that requires the development of new drugs or the identification of new therapeutic targets. The ESX-3 secretion system is essential for the Mycobacterium tuberculosis growth and plays a role in iron/zinc homeostasis and virulence. The aim of this study was to evaluate the quaternary interface of EccD3, a component of the ESX-3 secretion system, and to evaluate the association of an eccD3 mutant with drug resistance. The molecular structures of EccD3 protein and other ESX-3 secretion system proteins of the M. tuberculosis were predicted based in homology with the Mycolicibacterium smegmatis tertiary protein structures. According to the in silico results, selamectin, avermectin, ivermectin, and moxidectin were selected as prospective drugs. Selamectin and moxidectin had favorable ΔG values for the EccB3 and EccD3 dimer interfaces, whereas the ESX-3 Protomer 1 interface had the best ΔG + with avermectin, ivermectin, and moxidectin. Furthermore, ivermectin susceptibility increased when the eccD3 gene was inhibited using CRISPRi in M. smegmatis. Blockage of EccD3 increased the ivermectin action, but the modest changes observed may be explained by the compensatory mechanisms or other ivermectin targets in absence of this Esx3 component. Further in vitro and preclinical studies are required to validate our findings.

Self-Assembled Peptide-Gold Nanoparticle 1D Nanohybrids Functionalized with GHK Tripeptide for Enhanced Wound-Healing and Photothermal Therapy

Glycyl-l-histidyl-l-lysine (GHK) tripeptides are known for their remarkable therapeutic potential, including wound-healing, anti-inflammatory activity, and cellular regeneration. However, their clinical application has been significantly hindered by poor biological stability and limited efficacy in a physiological medium. In this study, we introduce a sophisticated approach to overcome these limitations by developing supramolecular peptide nanofiber-gold (Au) nanoparticle (NP) hybrids functionalized with GHK tripeptides. By strategically manipulating peptide self-assembly and NP integration, we demonstrated a useful platform that enhances both therapeutic efficacy and material stability. Our methodology involves the precise engineering of 9-fluorenylmethoxycarbonyl-diphenylalanine scaffolds with GHK and KHG tripeptides, enabling robust nanofibril formation through π-π stacking and hydrogen bonding. Critically, we discovered that the specific amino acid sequence significantly influences the surface exposure of lysine, directly impacting the nanohybrid's wound-healing capabilities. The resultant nanohybrids exhibit exceptional characteristics: Au NPs are spatially confined within the peptide nanofibers, achieving a remarkably uniform size distribution of approximately 3 nm. These nanohybrids demonstrate superior near-infrared (NIR) light absorption and photothermal conversion efficiency, enabling effective eradication of cancer cells and organoids killing under NIR irradiation. This dual-functional nanohybrid integrates biocompatible and enzymatically degradable peptide scaffolds to achieve synergistic wound-healing and cancer-killing effects. By mitigating the cytotoxicity and biodegradability issues associated with conventional photothermal agents, our system provides a promising strategy to improve postoperative cancer therapy and promote tissue regeneration. This work highlights the potential of peptide-inorganic nanohybrids in advancing multifunctional therapeutic platforms for cancer treatment and tissue repair.

High performance-oriented computer aided drug design approaches in the exascale era

INTRODUCTION

In 2023, the first exascale supercomputer was opened to the public in the US. With a demonstrated 1.1 exaflops of performance, Frontier represents an unprecedented breakthrough in high-performance computing (HPC). Currently, more (and more powerful) machines are being installed worldwide. Computer-aided drug design (CADD) is one of the fields of computational science that can greatly benefit from exascale computing for the benefit of the whole society. However, scaling CADD approaches to exploit exascale machines require new algorithmic and software solutions.

AREAS COVERED

Here, the authors consider physics-based and machine learning (ML)-aided techniques for the design of small molecule binders capable of leveraging modern parallel computer architectures. Specifically, the authors focus on HPC-oriented large-scale applications from the past 3 years that were enabled by (pre)exascale supercomputers by running on up tothousands of accelerated nodes.

EXPERT OPINION

In the area of ML, exascale computers can enable the training of generative models with unprecedented predictive power to design novel ligands, provided large amounts of high-quality data are available. Exascale computers could also unlock the potential of accurate ML-aided physics-based methods to boost the success rate of structure-based drug design campaigns. Currently, however, methodological developments are still required to allow routine large-scale applications of such rigorous approaches.

Metabolite profiling, antimalarial potentials of Schleichera oleosa using LC-MS and GC-MS: in vitro, molecular docking and molecular dynamics

Purpose

To explore the phytochemical composition of Schleichera oleosa bark and evaluate its potential antimalarial activity through in vitro and in silico analyses.

Methods

The bark of S. oleosa was subjected to Soxhlet extraction using petroleum ether, chloroform, and methanol. The quantitative analysis of the extracts was performed to determine total phenolic, flavonoid, and tannin contents. Advanced analytical techniques such as Gas Chromatography-Mass Spectrometry (GC-MS) and Liquid Chromatography-Mass Spectrometry (LC-MS) were employed to identify 175 phytoconstituents from the methanolic extract In-vitro antimalarial activity was assessed against Plasmodium falciparum using the candle jar method, measuring parasite growth inhibition. The inhibitory concentration (IC50) values were calculated and compared with standard antimalarial drugs, chloroquine and quinine. Furthermore, computational analyses, including molecular docking and molecular dynamics simulations, were conducted to evaluate the interactions of identified phytochemicals with key malarial targets (1CEQ and 4ZL4). The efficacy of these compounds was compared with standard drugs like artesunate and chloroquine. Additionally, ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) profiling and drug-likeness assessments were performed.

Results

The methanolic extract of S. oleosa exhibited promising in-vitro antimalarial activity with an average IC50 value of 0.780 μg/mL, which, while higher than chloroquine (0.020 μg/mL) and quinine (0.268 μg/mL), still demonstrated significant efficacy. GC-MS and LC-MS analyses identified 175 phytoconstituents, among which two novel lead compounds, scillarenin and 4-[(Z)-(6-hydroxy-3-oxo-1-benzofuran-2(3H)-ylidene) methyl] phenyl beta-Dglucopyranoside, exhibited the highest docking scores and favorable ADMET profiles. Molecular docking and dynamics simulations confirmed strong binding affinities to malarial targets, surpassing some standard drugs in efficacy.

Conclusion

This study reports, for the first time, the antimalarial potential of bioactive constituents derived from the bark of S. oleosa. The identified compounds, scillarenin and 4-[(Z)-(6-hydroxy-3-oxo-1-benzofuran-2(3H)-ylidene) methyl] phenyl beta-D-glucopyranoside, demonstrated promising antiplasmodial activity, validating traditional medicinal claims. The findings highlight the potential of S. oleosa as a source of novel antimalarial agents with fewer side effects compared to existing therapies. Further in vivo studies are warranted to confirm these results and support the development of new antimalarial drugs. This groundbreaking discovery contributes to the growing evidence supporting the role of medicinal plants in drug discovery.

Computational approaches for the identification of novel metal-binding pharmacophores: advances and challenges

Metalloenzymes are important therapeutic targets for a variety of human diseases. Computational approaches have recently emerged as effective tools to understand metal-ligand interactions and expand the structural diversity of both metalloenzyme inhibitors (MIs) and metal-binding pharmacophores (MBPs). In this review, we highlight key advances in currently available fine-tuning modeling methods and data-driven cheminformatic approaches. We also discuss major challenges to the recognition of novel MBPs and MIs. The evidence provided herein could expedite future computational efforts to guide metalloenzyme-based drug discovery.

Multiconfigurational short-range on-top pair-density functional theory

We present the theory and implementation of a fully variational wave function-density functional theory (DFT) hybrid model, which is applicable to many cases of strong correlation. We denote this model as the multiconfigurational self-consistent on-top pair-density functional theory (MC-srPDFT) model. We have previously shown how the multiconfigurational short-range DFT (MC-srDFT) hybrid model can describe many multiconfigurational cases of any spin symmetry and also state-specific calculations on excited states [Hedegård et al., J. Chem. Phys. 148(21), 214103 (2018)]. However, the srDFT part of the MC-srDFT has some deficiencies that it shares with Kohn-Sham DFT; in particular, (1) self-interaction errors (albeit reduced because of the range separation), (2) that different MS states incorrectly become non-degenerate, and (3) that singlet and non-singlet states dissociating to the same open-shell fragments incorrectly lead to different electronic energies at dissociation. The model that we present in this paper corrects these deficiencies by introducing the on-top pair density as an auxiliary variable replacing the spin density. Unlike other models in the literature, our model is fully variational and employs a long-range version of the on-top pair density. The implementation is a second-order optimization algorithm ensuring robust convergence to both ground and excited states. We show how MC-srPDFT solves the mentioned challenges by sample calculations on the ground state singlet curve of H2, N2, and Cr2 and the lowest triplet curves for N2 and Cr2. Furthermore, the rotational barrier for ethene is investigated for the S0 and T1 states. The calculations show correct degeneracy between the singlet and triplet curves at dissociation and the results are invariant to the choice of the MS value for the triplet curves.

Metallicious: Automated Force-Field Parameterization of Covalently Bound Metals for Supramolecular Structures

Metal ions play a central, functional, and structural role in many molecular structures, from small catalysts to metal-organic frameworks (MOFs) and proteins. Computational studies of these systems typically employ classical or quantum mechanical approaches or a combination of both. Among classical models, only the covalent metal model reproduces both geometries and charge transfer effects but requires time-consuming parameterization, especially for supramolecular systems containing repetitive units. To streamline this process, we introduce metallicious, a Python tool designed for efficient force-field parameterization of supramolecular structures. Metallicious has been tested on diverse systems including supramolecular cages, knots, and MOFs. Our benchmarks demonstrate that parameters accurately reproduce the reference properties obtained from quantum calculations and crystal structures. Molecular dynamics simulations of the generated structures consistently yield stable simulations in explicit solvent, in contrast to similar simulations performed with nonbonded and cationic dummy models. Overall, metallicious facilitates the atomistic modeling of supramolecular systems, key for understanding their dynamic properties and host-guest interactions. The tool is freely available on GitHub (https://github.com/duartegroup/metallicious).

Design and synthesis of non-hydroxamate lipophilic inhibitors of 1-deoxy-d-xylulose 5-phosphate reductoisomerase (DXR): in silico, in vitro and antibacterial studies

1-Deoxy-d-xylulose 5-phosphate reductoisomerase (DXR) is a key enzyme of the 2-C-methyl-d-erythritol 4-phosphate (MEP) pathway operating in several pathogens, including Mycobacterium and Plasmodium. Since a DXR homologue is not present in humans, it is an important antimicrobial target. Fosmidomycin (FSM) and its analogues inhibit DXR function by chelating the divalent metal (Mn2+ or Mg2+) in its active site via a hydroxamate metal binding group (MBG). The latter, however, enhances the polarity of molecules and is known to display metabolic instability and toxicity issues. While attempts have been made to increase the lipophilicity of FSM by substituting the linker chain and prodrug approach, very few efforts have been made to replace the hydroxamate group with other lipophilic MBGs. We report a systematic in silico and experimental investigation to identify novel MBGs for designing non-hydroxamate lipophilic DXR inhibitors. The SAR studies with selected MBG fragments identified novel inhibitors of E. Coli DXR with IC50 values ranging from 0.29 to 106 μM. The promising inhibitors were also screened against ESKAPE pathogens and M. tuberculosis.

Metal-detection based techniques and their applications in metallobiology

Metals are essential for human health and play a crucial role in numerous biological processes and pathways. Gaining a deeper insight into these biological events will facilitate novel strategies for disease prevention, early detection, and personalized treatment. In recent years, there has been significant progress in the development of metal-detection based techniques from single cell metallome and proteome profiling to multiplex imaging, which greatly enhance our comprehension of the intricate roles played by metals in complex biological systems. This perspective summarizes the recent progress in advanced metal-detection based techniques and highlights successful applications in elucidating the roles of metals in biology and medicine. Technologies including machine learning that couple with single-cell analysis such as mass cytometry and their application in metallobiology, cancer biology and immunology are also emphasized. Finally, we provide insights into future prospects and challenges involved in metal-detection based techniques, with the aim of inspiring further methodological advancements and applications that are accessible to chemists, biologists, and clinicians.

Correct Nucleotide Selection Is Confined at the Binding Site of Polymerase Enzymes

DNA polymerases (Pols) add incoming nucleotides (deoxyribonucleoside triphosphate (dNTPs)) to growing DNA strands, a crucial step for DNA synthesis. The insertion of correct (vs incorrect) nucleotides relates to Pols' fidelity, which defines Pols' ability to faithfully replicate DNA strands in a template-dependent manner. We and others have demonstrated that reactant alignment and correct base pairing at the Pols catalytic site are crucial structural features to fidelity. Here, we first used equilibrium molecular simulations to demonstrate that the local dynamics at the protein-DNA interface in the proximity of the catalytic site is different when correct vs incorrect dNTPs are bound to polymerase β (Pol β). Formation and dynamic stability of specific interatomic interactions around the incoming nucleotide influence the overall binding site architecture. This explains why certain Pols' mutants can affect the local catalytic environment and influence the selection of correct vs incorrect nucleotides. In particular, this is here demonstrated by analyzing the interaction network formed by the residue R283, whose mutant R283A has an experimentally measured lower capacity of differentiating correct (G:dCTP) vs incorrect (G:dATP) base pairing in Pol β. We also used alchemical free-energy calculations to quantify the G:dCTP →G:dATP transformation in Pol β wild-type and mutant R283A. These results correlate well with the experimental trend, thus corroborating our mechanistic insights. Sequence and structural comparisons with other Pols from the same family suggest that these findings may also be valid in similar enzymes.

Perspective: multi-configurational methods in bio-inorganic chemistry

Transition metal ions play crucial roles in the structure and function of numerous proteins, contributing to essential biological processes such as catalysis, electron transfer, and oxygen binding. However, accurately modeling the electronic structure and properties of metalloproteins poses significant challenges due to the complex nature of their electronic configurations and strong correlation effects. Multiconfigurational quantum chemistry methods are, in principle, the most appropriate tools for addressing these challenges, offering the capability to capture the inherent multi-reference character and strong electron correlation present in bio-inorganic systems. Yet their computational cost has long hindered wider adoption, making methods such as density functional theory (DFT) the method of choice. However, advancements over the past decade have substantially alleviated this limitation, rendering multiconfigurational quantum chemistry methods more accessible and applicable to a wider range of bio-inorganic systems. In this perspective, we discuss some of these developments and how they have already been used to answer some of the most important questions in bio-inorganic chemistry. We also comment on ongoing developments in the field and how the future of the field may evolve.

How exascale computing can shape drug design: A perspective from multiscale QM/MM molecular dynamics simulations and machine learning-aided enhanced sampling algorithms

Molecular simulations are an essential asset in the first steps of drug design campaigns. However, the requirement of high-throughput limits applications mainly to qualitative approaches with low computational cost, but also low accuracy. Unlocking the potential of more rigorous quantum mechanical/molecular mechanics (QM/MM) models combined with molecular dynamics-based free energy techniques could have a tremendous impact. Indeed, these two relatively old techniques are emerging as promising methods in the field. This has been favored by the exponential growth of computer power and the proliferation of powerful data-driven methods. Here, we briefly review recent advances and applications, and give our perspective on the impact that QM/MM and free-energy methods combined with machine learning-aided algorithms can have on drug design.

Diruthenium Paddlewheel Complexes Attacking Proteins: Axial versus Equatorial Coordination

Metallodrugs are an important group of medicinal agents used for the treatment of various diseases ranging from cancers to viral, bacterial, and parasitic diseases. Their distinctive features include the availability of a metal centre, redox activity, as well as the ability to multitarget. Diruthenium paddlewheel complexes are an intensely developing group of metal scaffolds, which can securely coordinate bidentate xenobiotics and transport them to target tissues, releasing them by means of substitution reactions with biomolecular nucleophiles. It is of the utmost importance to gain a complete comprehension of which chemical reactions happen with them in physiological milieu to design novel drugs based on these bimetallic scaffolds. This review presents the data obtained in experiments and calculations, which clarify the chemistry these complexes undergo once administered in the proteic environment. This study demonstrates how diruthenium paddlewheel complexes may indeed embody a new paradigm in the design of metal-based drugs of dual-action by presenting and discussing the protein metalation by these complexes.

Peptide composition analysis, structural characterization, and prediction of iron binding modes of small molecular weight peptides from mung bean

Iron supplementation is a proactive approach to limit instances of iron deficiency anemia. This study is based on the enzymatic hydrolysis and fractionation of mung bean proteins (MBPs) followed by the determination of the Fe2+ chelating activities of these peptide-containing fractions. MBP-Fe complex was generated using a chemical chelation method and subsequently characterized. Following Sephadex G15 separation of MBPs, one of the fractions containing 10 different peptides, demonstrated maximum Fe2+ chelating activity of 39.97 ± 0.07 μg/mg. The sequences of these peptides were determined using liquid chromatography-tandem mass spectrometry. The Fe2+ ion content of the MBP-Fe complex was determined using X-ray photoelectron spectroscopy and 80% of the iron was found to be in Fe2+ oxidation state. After iron chelation, there was an increase in the peptide's particle size, with an average value of 550.67 ± 0.70 nm. This increase in size was attributed to the contributions of the amino proline and glycine, which extended the peptides to form the MBP-Fe complex. Finally, molecular docking studies revealed that Fe2+ mainly bound to carboxy-oxygen of glutamate and aspartate residues of mung bean peptides to form MBP-Fe complex. This research could serve as a scientific foundation for the development of dietary iron supplements using plant-derived peptides.

Modern Alchemical Free Energy Methods for Drug Discovery Explained

This Perspective provides a contextual explanation of the current state-of-the-art alchemical free energy methods and their role in drug discovery as well as highlights select emerging technologies. The narrative attempts to answer basic questions about what goes on "under the hood" in free energy simulations and provide general guidelines for how to run simulations and analyze the results. It is the hope that this work will provide a valuable introduction to students and scientists in the field.

α-Aminophosphonate inhibitors of metallo-β-lactamases NDM-1 and VIM-2

The upswing of antibiotic resistance is an escalating threat to human health. Resistance mediated by bacterial metallo-β-lactamases is of particular concern as these enzymes degrade β-lactams, our most frequently prescribed class of antibiotics. Inhibition of metallo-β-lactamases could allow the continued use of existing β-lactam antibiotics, such as penicillins, cephalosporins and carbapenems, whose applicability is becoming ever more limited. The design, synthesis, and NDM-1, VIM-2, and GIM-1 inhibitory activities (IC50 4.1-506 μM) of a series of novel non-cytotoxic α-aminophosphonate-based inhibitor candidates are presented herein. We disclose the solution NMR spectroscopic and computational investigation of their NDM-1 and VIM-2 binding sites and binding modes. Whereas the binding modes of the inhibitors are similar, VIM-2 showed a somewhat higher conformational flexibility, and complexed a larger number of inhibitor candidates in more varying binding modes than NDM-1. Phosphonate-type inhibitors may be potential candidates for development into therapeutics to combat metallo-β-lactamase resistant bacteria.

Free energies at QM accuracy from force fields via multimap targeted estimation

Accurate predictions of ligand binding affinities would greatly accelerate the first stages of drug discovery campaigns. However, using highly accurate interatomic potentials based on quantum mechanics (QM) in free energy methods has been so far largely unfeasible due to their prohibitive computational cost. Here, we present an efficient method to compute QM free energies from simulations using cheap reference potentials, such as force fields (FFs). This task has traditionally been out of reach due to the slow convergence of computing the correction from the FF to the QM potential. To overcome this bottleneck, we generalize targeted free energy methods to employ multiple maps-implemented with normalizing flow neural networks (NNs)-that maximize the overlap between the distributions. Critically, the method requires neither a separate expensive training phase for the NNs nor samples from the QM potential. We further propose a one-epoch learning policy to efficiently avoid overfitting, and we combine our approach with enhanced sampling strategies to overcome the pervasive problem of poor convergence due to slow degrees of freedom. On the drug-like molecules in the HiPen dataset, the method accelerates the calculation of the free energy difference of switching from an FF to a DFTB3 potential by three orders of magnitude compared to standard free energy perturbation and by a factor of eight compared to previously published nonequilibrium calculations. Our results suggest that our method, in combination with efficient QM/MM calculations, may be used in lead optimization campaigns in drug discovery and to study protein-ligand molecular recognition processes.

Regioselective and Enantioselective Copper-Catalyzed Hydroaminocarbonylation of Unactivated Alkenes and Alkynes

Given the prevalence of amide backbones in marketed pharmaceuticals and their ubiquity as critical binding units in natural peptides and proteins, it remains important to develop novel methods to construct amide bonds. We report here a general method for the anti-Markovnikov hydroaminocarbonylation of unactivated alkenes under mild conditions, using copper catalysis in combination with hydroxylamine electrophile reagents and poly(methylhydrosiloxane) (PMHS) as a cheap and environmentally friendly hydride source. The reaction tolerates a variety of functional groups and efficiently converts unactivated terminal alkenes, 1,1-disubstituted alkenes, and cyclic alkenes to the corresponding amides with exclusive anti-Markovnikov selectivity (and high enantioselectivities/diastereoselectivities). Additionally, with minimal modification of the reaction conditions, alkynes can also undergo tandem hydrogenation-hydroaminocarbonylation to alkyl amides.

The multifaceted roles of mass spectrometric analysis in nucleic acids drug discovery and development

The deceptively simple concepts of mass determination and fragment analysis are the basis for the application of mass spectrometry (MS) to a boundless range of analytes, including fundamental components and polymeric forms of nucleic acids (NAs). This platform affords the intrinsic ability to observe first-hand the effects of NA-active drugs on the chemical structure, composition, and conformation of their targets, which might affect their ability to interact with cognate NAs, proteins, and other biomolecules present in a natural environment. The possibility of interfacing with high-performance separation techniques represents a multiplying factor that extends these capabilities to cover complex sample mixtures obtained from organisms that were exposed to NA-active drugs. This report provides a brief overview of these capabilities in the context of the analysis of the products of NA-drug activity and NA therapeutics. The selected examples offer proof-of-principle of the applicability of this platform to all phases of the journey undertaken by any successful NA drug from laboratory to bedside, and provide the rationale for its rapid expansion outside traditional laboratory settings in support to ever growing manufacturing operations.

Second-Shell Residues Contribute to Catalysis by Predominately Preorganizing the Apo State in PafA

Residues beyond the first coordination shell are often observed to make considerable cumulative contributions in enzymes. Due to typically indirect perturbations of multiple physicochemical properties of the active site, however, their individual and specific roles in enzyme catalysis and disease-causing mutations remain difficult to predict and understand at the molecular level. Here we analyze the contributions of several second-shell residues in phosphate-irrepressible alkaline phosphatase of flavobacterium (PafA), a representative system as one of the most efficient enzymes. By adopting a multifaceted approach that integrates quantum-mechanical/molecular-mechanical free energy computations, molecular-mechanical molecular dynamics simulations, and density functional theory cluster model calculations, we probe the rate-limiting phosphoryl transfer step and structural properties of all relevant enzyme states. In combination with available experimental data, our computational results show that mutations of the studied second-shell residues impact catalytic efficiency mainly by perturbation of the apo state and therefore substrate binding, while they do not affect the ground state or alter the nature of phosphoryl transfer transition state significantly. Several second-shell mutations also modulate the active site hydration level, which in turn influences the energetics of phosphoryl transfer. These mechanistic insights also help inform strategies that may improve the efficiency of enzyme design and engineering by going beyond the current focus on the first coordination shell.

A Comprehensive Survey on the Expediated Anti-COVID-19 Options Enabled by Metal Complexes-Tasks and Trials

Contemporary pharmacology dating back to the late 19th/early 20th centuries has benefitted largely from the incorporation of metal complexes. Various biological attributes have been successfully realized using metal/metal complex-based drugs. Among anticancer, antimicrobial, and antiviral applications, anticancer applications have extracted the maximum benefit from the metal complex, Cisplatin. The following review has compiled the various antiviral benefits harnessed through inputs from metal complexes. As a result of exploiting the pharmacological aspects of metal complexes, the anti-COVID-19 deliverables have been summarized. The challenges ahead, the gaps in this research area, the need to improvise incorporating nanoaspects in metal complexes, and the need to test metal complex-based drugs in clinical trials have been discussed and deliberated. The pandemic shook the entire world and claimed quite a percentage of the global population. Metal complex-based drugs are already established for their antiviral property with respect to enveloped viruses and extrapolating them for COVID-19 can be an effective way to manipulate drug resistance and mutant issues that the current anti-COVID-19 drugs are facing.

Benchmarking biomolecular force field-based Zn2+ for mono- and bimetallic ligand binding sites

Zn²⁺ is one of the most versatile biologically available metal ions, but accurate modeling of Zn²⁺ -containing metalloproteins at the biomolecular force field level can be challenging. Since most Zn²⁺ models are parameterized in bulk solvent, in-depth knowledge about their performance in a protein environment is limited. Thus, we systematically investigate here the behavior of non-polarizable Zn²⁺ models for their ability to reproduce experimentally determined metal coordination and ligand binding in metalloproteins. The benchmarking is performed in challenging environments, including mono- (carbonic anhydrase II) and bimetallic (metallo-β-lactamase VIM-2) ligand binding sites. We identify key differences in the performance between the Zn²⁺ models with regard to the preferred ligating atoms (charged/non-charged), attraction of water molecules, and the preferred coordination geometry. Based on these results, we suggest suitable simulation conditions for varying Zn²⁺ site geometries that could guide the further development of biomolecular Zn²⁺ models.

Inorganic Drugs as a Tool for Protein Structure Solving and Studies on Conformational Changes

Inorganic drugs are capable of tight interactions with proteins through coordination towards aminoacidic residues, and this feature is recognized as a key aspect for their pharmacological action. However, the "protein metalation process" is exploitable for solving the phase problem and structural resolution. In fact, the use of inorganic drugs bearing specific metal centers and ligands capable to drive the binding towards the desired portions of the protein target could represent a very intriguing and fruitful strategy. In this context, a theoretical approach may further contribute to solve protein structures and their refinement. Here, we delineate the main features of a reliable experimental-theoretical integrated approach, based on the use of metallodrugs, for protein structure solving.

On the Role of Molecular Conformation of the 8-Oxoguanine Lesion in Damaged DNA Processing by Polymerases

A common and insidious DNA damage is 8-oxoguanine (8OG), bypassed with low catalytic efficiency and high error frequency by polymerases (Pols) during DNA replication. This is a fundamental process with far-reaching implications in cell function and diseases. However, the molecular determinants of how 8OG exactly affects the catalytic efficiency of Pols remain largely unclear. By examining ternary deoxycytidine triphosphate/DNA/Pol complexes containing the 8OG damage, we found that 8OG consistently adopts different conformations when bound to Pols, compared to when in isolated DNA. Equilibrium molecular dynamics and metadynamics free energy calculations quantified that 8OG is in the lowest energy conformation in isolated DNA. In contrast, 8OG adopts high-energy conformations often characterized by intramolecular steric repulsion when bound to Pols. We show that the 8OG conformation can be regulated by mutating Pol residues interacting with the 8OG phosphate group. These findings propose the 8OG conformation as a factor in Pol-mediated processing of damaged DNA.

Progress of Metal-Based Anticancer Chemotherapeutic Agents in Last two Decades and their Comprehensive Biological (DNA/RNA Binding, Cleavage and Cytotoxicity Activity) Studies

During last two decades, there has been an enormous growth in the discovery of innovative active inorganic anticancer complexes (exerting remarkable cytotoxicity at sub micro-molar levels) derived from myriad ligand scaffolds, mainly acting on cancerous vs healthy cells by either halting or inhibiting their uncontrolled growth. The phenomenal success of cisplatin to treat numerous forms of solid malignancies has placed metal-based drugs to the forefront of treatment strategies against cancers. More than 10,000 platinum anticancer complexes have been developed during the past 40 years, but only five drugs have been approved for usage in humans while ten more complexes are currently undergoing clinical trials. Most of the compounds have failed either at R&D stages or in preclinical trails. This has led to extensive investigations by researchers of medicinal chemistry, including our group to design and prepare tailored 3d-metallo-drugs and organotin(IV) compounds from some naturally occurring bioactive compounds, such as amino-acids, peptides, chromone derivatives and NSAID's etc. that were used either alone or in cocktail combination, capable of specifically targeting DNA, lnc RNAs and proteins. Furthermore, 3d-metal ions such as copper, cobalt and zinc etc. incorporated in these ligand framework are biocompatible and induce a unique multi-modal mechanism of cytotoxic action involving angiogenesis, ROS-induced DNA damage, apoptosis by p53 mitochondrial genes and caspases etc. The results observed a positive correlation between the binding affinity of complexes with DNA (as quantified by intrinsic binding constant values) and their cytotoxic behavior. Complexes with high DNA binding propensity were typically lethal against a diverse panel of malignant cell types compared to normal cells.

GPDOCK: highly accurate docking strategy for metalloproteins based on geometric probability

Accurately predicting the interaction modes for metalloproteins remains extremely challenging in structure-based drug design and mechanism analysis of enzymatic catalysis due to the complexity of metal coordination in metalloproteins. Here, we report a docking method for metalloproteins based on geometric probability (GPDOCK) with unprecedented accuracy. The docking tests of 10 common metal ions with 9360 metalloprotein-ligand complexes demonstrate that GPDOCK has an accuracy of 94.3% in predicting binding pose. What is more, it can accurately realize the docking of metalloproteins with ligand when one or two water molecules are engaged in the metal ion coordination. Since GPDOCK only depends on the three-dimensional structure of metalloprotein and ligand, structure-based machine learning model is employed for the scoring of binding poses, which significantly improves computational efficiency. The proposed docking strategy can be an effective and efficient tool for drug design and further study of binding mechanism of metalloproteins. The manual of GPDOCK and the code for the logistical regression model used to re-rank the docking results are available at https://github.com/wangkai-zhku/GPDOCK.git.

Developing Metal Complexes for Captopril Quantification in Tablets Using Potentiometric and Conductometric Methods

Potentiometric and conductometric methods were successfully applied to elucidate the interaction of 10 ions, viz., Cr³⁺, Fe³⁺, La²⁺, Th⁴⁺, Co²⁺, Mn²⁺, Pd²⁺, Sr²⁺, Ti²⁺, and Zr²⁺, with the antihypertensive drug captopril (CAP) and its role to determine CAP in pure powder and tablet forms. The ionization constant of CAP and the generated complexes' stability constants (log K) were evaluated using potentiometric and conductometric methods at 25 ± 0.1 °C and 0.05 M ionic strength (I) of NaNO₃ aqueous solution, and CAP was then determined in pure powder and tablet forms. Complexes having metal:ligand ratios of 1:1, 1:2, and/or 1:3 were produced, regardless of the type of the ligand or metal ions. Both the suggested potentiometric and conductometric procedures were utilized to confirm the stoichiometry of the M-CAP binary complexes formed. These two different techniques were utilized successfully to determine CAP in pure powder and tablet forms. Using the standard addition method (SAM) based on the Gran plot, CAP was satisfactorily determined throughout the concentration range of 0.83-13.04 mg/mL (SD = 0.20, R = 0.9986 (n = 5)), with a detection limit of 0.64 mg/mL (SD = 0.20, R = 0.9986 (n = 5)). In the presence of common tablet excipients, no interferences were observed. The percentage of CAP recovered from various dosage formulations (tablets) varied from 95.88 to 99.92%.

Acylhydrazones and Their Biological Activity: A Review

Due to the structure of acylhydrazones both by the pharmacophore -CO-NH-N= group and by the different substituents present in the molecules of compounds of this class, various pharmacological activities were reported, including antitumor, antimicrobial, antiviral, antiparasitic, anti-inflammatory, immunomodulatory, antiedematous, antiglaucomatous, antidiabetic, antioxidant, and actions on the central nervous system and on the cardiovascular system. This fragment is found in the structure of several drugs used in the therapy of some diseases that are at the top of public health problems, like microbial infections and cardiovascular diseases. Moreover, the acylhydrazone moiety is present in the structure of some compounds with possible applications in the treatment of other different pathologies, such as schizophrenia, Parkinson's disease, Alzheimer's disease, and Huntington's disease. Considering these aspects, we consider that a study of the literature data regarding the structural and biological properties of these compounds is useful.

Syntheses and Structural Characterization of Divalent Metal Complexes (Co, Ni, Pd and Zn) of Sterically Hindered Thiourea Ligand and A Theoretical Insight of their Interaction with SARS-CoV-2 Enzyme

Reacting two equivalents of sterically hindered 1,3-bis(2,6-diethylphenyl)thiourea ligand (L) with CoCl₂, NiBr₂, PdX₂ (X = Cl; Br) and ZnI₂ in acetonitrile afforded the corresponding bulky thiourea ligand stabilized four coordinated monomeric [L₂CoCl₂] (1), [L₂NiBr₂] (2), [L₂PdX₂] (3a: X = Cl; 3b: X = Br) and [L₂ZnI₂] (4.2CH₃CN) complexes. Compound 1, 2 and 4.2CH₃CN are tetrahedral whereas Pd complexes (3a and 3b) are square planar. In solution, palladium complexes are dominated by cis-isomers. Structural characterization shows inter- and intramolecular hydrogen bonding. Hirshfeld surface and fingerprint plots indicated significant intermolecular interactions in the crystal network. Molecular docking analysis revealed relatively higher SARS-CoV-2 enzyme interacting abilities of the synthesized complexes compared to the free ligand. All compounds have been characterized by elemental analyses, NMR spectroscopy and single-crystal X-ray diffraction.

MeDBA: the Metalloenzyme Data Bank and Analysis platform

Metalloenzymes are attractive research targets in fields of chemistry, biology, and medicine. Given that metalloenzymes can manifest conservation of metal-coordination and ligand binding modes, the excavation and expansion of metalloenzyme-specific knowledge is of interest in bridging metalloenzyme-related fields. Building on our previous metalloenzyme-ligand association database, MeLAD, we have expanded the scope of metalloenzyme-specific knowledge and services, by forming a versatile platform, termed the Metalloenzyme Data Bank and Analysis (MeDBA). The MeDBA provides: (i) manual curation of metalloenzymes into different categories, that this M-I, M-II and M-III; (ii) comprehensive information on metalloenzyme activities, expression profiles, family and disease links; (iii) structural information on metalloenzymes, in particular metal binding modes; (iv) metalloenzyme substrates and bioactive molecules acting on metalloenzymes; (v) excavated metal-binding pharmacophores and (vi) analysis tools for structure/metal active site comparison and metalloenzyme profiling. The MeDBA is freely available at https://medba.ddtmlab.org.

Metal-based complexes against SARS-CoV-2

The first appearance of SARS-CoV-2 is dated back to 2019. This new member of the coronavirus family has caused more than 5 million deaths worldwide up until the end of January 2022. At the moment, and after intensive vaccination programmes throughout the world, the pandemic is still active, whilst new mutations constantly appear. Researchers are working intensively to discover antiviral drugs to combat the severe cases in intensive care units, giving the overloaded hospital units a breather. Alongside various research projects focusing on developing small pharmaceutical molecules, a significant proportion of the research community has shifted towards paying attention to metal drugs. In this small review, we make brief reference to the use of metal drugs in therapeutics and provide some examples of metal drugs that are of extreme interest in the current pandemic. At the same time, we will also examine some of their promising mechanisms of action and possible effectiveness against COVID-19.

Antiproliferative Ruthenium Complexes Containing Curcuminoid Ligands Tested In Vitro on Human Ovarian Tumor Cell Line A2780, towards Their Capability to Modulate the NF-κBTranscription Factor, FGF-2 Growth Factor, and MMP-9 Pathway

So far, the polyphenolic components of turmeric have shown a significant pharmacological preventative activity for a wide spectrum of diseases, including oncological disorders. This type of natural product could be of great interest for the inhibition of cancer cell proliferation, displaying less side effects in comparison to classical chemotherapeutics. The poor bioavailability and quick metabolism of such natural compounds require new investigative methods to improve their stability in the organisms. A synthetic approach to increase the efficiency of curcuminoids is to coordinate them to metals through the beta-dicarbonyl moiety. We report the synthesis and the biological attempts on human ovarian carcinoma A2780 of ruthenium(II) complexes 1–4, containing curcuminoid ligands. The cytotoxicity of complexes 1–4 proves their antiproliferative capability, and a correlation between the IC50 values and NF-κB transcription factor, FGF-2, and MMP-9 levels was figured out through the principal component analysis (PCA).

Molecular Modeling in Anion Exchange Membrane Research: A Brief Review of Recent Applications

Anion Exchange Membrane (AEM) fuel cells have attracted growing interest, due to their encouraging advantages, including high power density and relatively low cost. AEM is a polymer matrix, which conducts hydroxide (OH-) ions, prevents physical contact of electrodes, and has positively charged head groups (mainly quaternary ammonium (QA) groups), covalently bound to the polymer backbone. The chemical instability of the quaternary ammonium (QA)-based head groups, at alkaline pH and elevated temperature, is a significant threshold in AEMFC technology. This review work aims to introduce recent studies on the chemical stability of various QA-based head groups and transportation of OH- ions in AEMFC, via modeling and simulation techniques, at different scales. It starts by introducing the fundamental theories behind AEM-based fuel-cell technology. In the main body of this review, we present selected computational studies that deal with the effects of various parameters on AEMs, via a variety of multi-length and multi-time-scale modeling and simulation methods. Such methods include electronic structure calculations via the quantum Density Functional Theory (DFT), ab initio, classical all-atom Molecular Dynamics (MD) simulations, and coarse-grained MD simulations. The explored processing and structural parameters include temperature, hydration levels, several QA-based head groups, various types of QA-based head groups and backbones, etc. Nowadays, many methods and software packages for molecular and materials modeling are available. Applications of such methods may help to understand the transportation mechanisms of OH- ions, the chemical stability of functional head groups, and many other relevant properties, leading to a performance-based molecular and structure design as well as, ultimately, improved AEM-based fuel cell performances. This contribution aims to introduce those molecular modeling methods and their recent applications to the AEM-based fuel cells research community.

New Coordination Compounds Based on a Pyrazine Derivative: Design, Characterization, and Biological Study

New coordination compounds of Mn(II), Fe(III), Co(II), and Ni(II) and the biologically active ligand L (N′-benzylidenepyrazine-2-carbohydrazonamide) were synthesized and characterized by appropriate analytical techniques: elemental analysis (EA), thermogravimetric analysis (TG–DTG), infrared spectroscopy (FTIR), and flame-atomic absorption spectrometry (F-AAS). The biological activity of the obtained compounds was then comprehensively investigated. Rational use of these compounds as potential drugs was proven by ADME analysis. All obtained compounds were screened in vitro for antibacterial, antifungal, and anticancer activities. Some of the studied complexes exhibited significantly higher activity than the ligand alone.

Insights into the Pharmacological Effects of Flavonoids: The Systematic Review of Computer Modeling

Computer modeling is a method that is widely used in scientific investigations to predict the biological activity, toxicity, pharmacokinetics, and synthesis strategy of compounds based on the structure of the molecule. This work is a systematic review of articles performed in accordance with the recommendations of PRISMA and contains information on computer modeling of the interaction of classical flavonoids with different biological targets. The review of used computational approaches is presented. Furthermore, the affinities of flavonoids to different targets that are associated with the infection, cardiovascular, and oncological diseases are discussed. Additionally, the methodology of bias risks in molecular docking research based on principles of evidentiary medicine was suggested and discussed. Based on this data, the most active groups of flavonoids and lead compounds for different targets were determined. It was concluded that flavonoids are a promising object for drug development and further research of pharmacology by in vitro, ex vivo, and in vivo models is required.

Targeting undruggable carbohydrate recognition sites through focused fragment library design

Carbohydrate-protein interactions are key for cell-cell and host-pathogen recognition and thus, emerged as viable therapeutic targets. However, their hydrophilic nature poses major limitations to the conventional development of drug-like inhibitors. To address this shortcoming, four fragment libraries were screened to identify metal-binding pharmacophores (MBPs) as novel scaffolds for inhibition of Ca²⁺-dependent carbohydrate-protein interactions. Here, we show the effect of MBPs on the clinically relevant lectins DC-SIGN, Langerin, LecA and LecB. Detailed structural and biochemical investigations revealed the specificity of MBPs for different Ca²⁺-dependent lectins. Exploring the structure-activity relationships of several fragments uncovered the functional groups in the MBPs suitable for modification to further improve lectin binding and selectivity. Selected inhibitors bound efficiently to DC-SIGN-expressing cells. Altogether, the discovery of MBPs as a promising class of Ca²⁺-dependent lectin inhibitors creates a foundation for fragment-based ligand design for future drug discovery campaigns.

Relevance of Fluorinated Ligands to the Design of Metallodrugs for Their Potential Use in Cancer Treatment

Fluorination of pharmaceutical agents has afforded crucial modifications to their pharmacological profiles, leading to important advances in medicinal chemistry. On the other hand, metallodrugs are considered to be valuable candidates in the treatment of several diseases, albeit with the caveat that they may exhibit pharmacological disadvantages, such as poor water solubility, low bioavailability and short circulating time. To surmount these limitations, two approaches have been developed: one based on the design of novel metallodrug-delivering carriers and the other based on optimizing the structure of the ligands bound to the metal center. In this context, fluorination of the ligands may bring beneficial changes (physicochemical and biological) that can help to elude the aforementioned drawbacks. Thus, in this review, we discuss the use of fluorinated ligands in the design of metallodrugs that may exhibit potential anticancer activity.

Metallo-β-Lactamase Inhibitor Phosphonamidate Monoesters

Being the second leading cause of death and the leading cause of disability-adjusted life years worldwide, infectious diseases remain-contrary to earlier predictions-a major consideration for the public health of the 21^st century. Resistance development of microbes to antimicrobial drugs constitutes a large part of this devastating problem. The most widely spread mechanism of bacterial resistance operates through the degradation of existing β-lactam antibiotics. Inhibition of metallo-β-lactamases is expected to allow the continued use of existing antibiotics, whose applicability is becoming ever more limited. Herein, we describe the synthesis, the metallo-β-lactamase inhibition activity, the cytotoxicity studies, and the NMR spectroscopic determination of the protein binding site of phosphonamidate monoesters. The expression of single- and double-labeled NDM-1 and its backbone NMR assignment are also disclosed, providing helpful information for future development of NDM-1 inhibitors. We show phosphonamidates to have the potential to become a new generation of antibiotic therapeutics to combat metallo-β-lactamase-resistant bacteria.

Interactions between mitochondria-damaging platinum(IV) prodrugs and cytochrome c

In this work, we present the first study about the interactions of mitochondria-damaging Pt(IV) prodrugs with cytochrome c. We synthesized a cisplatin-based Pt(IV) prodrug bearing a lipophilic hydrocarbon tail and anionic dansyl head group. The amphiphilic structure facilitates its accumulation in the mitochondria of cancer cells, which was validated using graphite furnace atomic absorption spectroscopy (GFAAS) and fluorescence imaging. Accordingly, this Pt(IV) prodrug is able to trigger mitochondrial damage and apoptosis. Overall, the Pt(IV) prodrug exhibits superior therapeutic effects against a panel of human cancer cells compared to cisplatin. It also overcomes drug resistance in ovarian cancer. Notably, HPLC analysis indicates that cytochrome c accelerates reduction (or activation) of the Pt(IV) prodrug in the presence of the electron donor nicotinamide adenine dinucleotide (NADH). More interestingly, additional studies indicate that cytochrome c was platinated by the reduced product of Pt(IV) prodrugs, and that empowers the proapoptotic peroxidase activity.

Modulations of a Metal-Ligand Interaction and Photophysical Behaviors by Hückel-Möbius Aromatic Switching

In organometallic complexes containing π-conjugated macrocyclic chelate ligands, conformational change significantly affects metal-ligand electronic interactions, hence tuning properties of the complexes. In this regard, we investigated the metal-ligand interactions in hexaphyrin mono-Pd(II) complexes Pd[28]M and Pd[26]H, which exhibit a redox-induced switching of Hückel-Möbius aromaticity and subsequent molecular conformation, and their effect on the electronic structure and photophysical behaviors. In Möbius aromatic Pd[28]M, the weak metal-ligand interaction leads to the π electronic structure of the hexaphyrin ligand remaining almost intact, which undergoes efficient intersystem crossing (ISC) assisted by the heavy-atom effect of the Pd metal. In Hückel aromatic Pd[26]H, the significant metal-ligand interaction results in ligand-to-metal charge-transfer (LMCT) in the excited-state dynamics. These contrasting metal-ligand electronic interactions have been revealed by time-resolved electronic and vibrational spectroscopies and time-dependent DFT calculations. This work indicates that the conspicuous modulation of metal-ligand interaction by Hückel-Möbius aromaticity switching is an appealing approach to manipulate molecular properties of metal complexes, further enabling the fine-tuning of metal-ligand interactions and the novel design of functional organometallic materials.

Metal Complexes as DNA Synthesis and/or Repair Inhibitors: Anticancer and Antimicrobial Agents

Medicinal inorganic chemistry involving the utilization of metal-based compounds as therapeutics has become a field showing distinct promise. DNA and RNA are ideal drug targets for therapeutic intervention in the case of various diseases, such as cancer and microbial infection. Metals play a vital role in medicine, with at least 10 metals known to be essential for human life and a further 46 nonessential metals having been involved in drug therapies and diagnosis. These metal-based complexes interact with DNA in various ways, and are often delivered as prodrugs which undergo activation in vivo. Metal complexes cause DNA crosslinking, leading to the inhibition of DNA synthesis and repair. In this review, the various interactions of metal complexes with DNA nucleic acids, as well as the underlying mechanism of action, were highlighted. Furthermore, we also discussed various tools used to investigate the interaction between metal complexes and the DNA. The tools included in vitro techniques such as spectroscopy and electrophoresis, and in silico studies such as protein docking and density-functional theory that are highlighted for preclinical development.