Docking Strategy Research Articles

Network Pharmacology Combined with Molecular Docking Approach to Investigate the Mechanism of ChuShiWeiLing Decoction against Perianal Eczema.

ChuShiWeiLing Decoction (CSWLD) is a famous classical Chinese prescription for the treatment of eczema with desirable effect in clinical practice. It has gradually exerted good curative effects on perianal eczema (PE) in recent years, but its specific mechanism is not elucidated yet. This research explores the underlying pharmacological mechanism of CSWLD in addressing PE through network pharmacology combined with molecular docking strategy. The key chemical compounds and potential target genes of CSWLD were screened by bioinformatics. The major targets of CSWLD were discovered using network modules. Functional annotation of Gene Ontology (GO) was undertaken, as well as pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG). Molecular docking of core protein-ligand interactions was modeled using AutoDock software. Pymol software was used to perform a molecular dynamics simulation for the ideal core protein-ligand that was discovered by molecular docking. A total of 2,853 active compounds and 922 targets of CSWLD were collected. The target with a higher degree was identified through the PPI network, namely TNF, IL6, ALB, STAT3, EGFR, TLR4, CXCL8 and PTPRC. GO and KEGG analyses suggested that CSWLD treatment of PE mainly involves cellular activation, activation of leukocytes, and adhesion among leukocytes. The molecular docking results showed that wogonin, hederagenin and quercetin of CSWLD could bind to IL-6 and TNF, respectively. Our results indicated that the bioactives, potential targets, and molecular mechanism of CSWLD against PE.

Network toxicology and molecular docking for the toxicity analysis of food contaminants: A case of Aflatoxin B1

The present study aims to promote network toxicology and molecular docking strategies for the efficient evaluation of the toxicity of food contaminants. With the example of liver injury induced by the food contaminant Aflatoxin B1(AFB1), this study effectively investigated the putative toxicity of food contaminants and the potentially molecular mechanisms. The study found that AFB1 regulates multiple signalling pathways by modulating core targets such as AKT1, BCL2, TNF, CASP3, SRC and EGFR. These pathways encompass Pathways in cancer, PI3K-Akt signalling pathway, Endocrine resistance, Lipid and atherosclerosis, Apoptosis and other pathways, subsequently impacting immunotoxicity, inflammatory responses, apoptosis, cytogenetic mutations, and ultimately leading to liver injury. We provide a theoretical basis for understanding the molecular mechanisms of AFB1 hepatotoxicity and for the prevention and treatment of cancers caused by the food contaminant AFB1. Furthermore, our network toxicology and molecular docking methods also provide an effective method for the rapid evaluation of the toxicity of food contaminants, which effectively solves the cost and ethical problems associated with the use of experimental animals.

Antitumor studies on celastrol and its derivatives as RORα agonists and RORγ inhibitors based on Alphafold reverse docking strategy

Antitumor studies on celastrol and its derivatives as RORα agonists and RORγ inhibitors based on Alphafold reverse docking strategy

In silico study to identify novel NEK7 inhibitors from natural sources by a combination strategy.

Cancer poses a significant global health challenge and significantly contributes to mortality. NEK7, related to the NIMA protein kinase family, plays a crucial role in spindle assembly and cell division. The dysregulation of NEK7 is closely linked to the onset and progression of various cancers, especially colon and breast cancer, making it a promising target for cancer therapy. Nevertheless, the shortage of high-quality NEK7 inhibitors highlights the need for new therapeutic strategies. In this study, we utilized a multidisciplinary approach, including virtual screening, molecular docking, pharmacokinetics, molecular dynamics simulations (MDs), and MM/PBSA calculations, to evaluate natural compounds as NEK7 inhibitors comprehensively. Through various docking strategies, we identified three natural compounds: (-)-balanol, digallic acid, and scutellarin. Molecular docking revealed significant interactions at residues such as GLU112 and ALA114, with docking scores of -15.054, -13.059, and -11.547kcal/mol, respectively, highlighting their potential as NEK7 inhibitors. MDs confirmed the stability of these compounds at the NEK7-binding site. Hydrogen bond analysis during simulations revealed consistent interactions, supporting their strong binding capacity. MM/PBSA analysis identified other crucial amino acids contributing to binding affinity, including ILE20, VAL28, ILE75, LEU93, ALA94, LYS143, PHE148, LEU160, and THR161, crucial for stabilizing the complex. This research demonstrated that these compounds exceeded dabrafenib in binding energy, according to MM/PBSA calculations, underscoring their effectiveness as NEK7 inhibitors. ADME/T predictions showed lower oral toxicity for these compounds, suggesting their potential for further development. This study highlights the promise of these natural compounds as bases for creating more potent derivatives with significant biological activities, paving the way for future experimental validation.

Molecular Docking Based Predictive Study of Bougainvillea Glabra against Mtorc1 Protein for the Treatment of Diabetic Nephropathy: Network Pharmacology

Background: The decline in kidney function experienced by people with type 1 and type 2 diabetes who are chronically ill is known as diabetic nephropathy (DN) or diabetic kidney disease. The condition is known to progress in a number of stages and is related to blood pressure and glycemic management. Nevertheless, despite strict blood sugar management, the prevalence of chronic kidney disease (CKD) in diabetic patients has not decreased over the past 20 years, which has led to the discovery of new risk factors for the illness's development. The medical characteristics of the Paper Flower, Bougainvillea spectabilis, include anti-inflammatory, anti-hepatotoxic, anti-inflammtory, anti-hyperlipidemic, antibacterial, antioxidant, and antiulcer capabilities. Alkaloids, flavonoids, glycosides, phenolics, phytobannins, quinones, saponins, tannins, and terpenoids are examples of phytoconstituents that have been claimed to have medicinal characteristics. Method: In the current study, a molecular docking technique was used to try and identify mTORC1protein inhibitors. A grid-based docking strategy was used to determine the binding using the Auto Dock software. Merck Molecular Force Field was used to build the 2D structures of compounds, convert them to 3D, and then energetically reduce them up to arms gradient of 0.01. (MMFF). Result: The molecular docking of Ferulic acid & Gallic acid with mTORC1 protein showed binding energy (Kcal/mol) -5.37 & -4.56 respectively. Conclusion: Theoretically, all the ligand molecules have shown encouraging docking score. The docking result of ferulic acid revealed that their docking scores was -5.37 kcal mol–1, and it can be predicted as good inhibitor of mTORC1 protein and thereby prevents dysregulation of intracellular protein synthesis and the metabolic balance along with decreasing oxidative stress on the kidney.

Antipyretic effects of Xiangqin Jiere granules on febrile young rats revealed by combining pharmacodynamics, metabolomics, network pharmacology, molecular biology experiments and molecular docking strategies

Xiangqin Jiere granules (XQJRG) is a proprietary Chinese medicine treating children’s colds and fevers, but its mechanism of action is unclear. The aim of this study was to explore the antipyretic mechanisms of XQJRG based on pharmacodynamics, non-targeted metabolomics, network pharmacology, molecular biology experiments, molecular docking, and molecular dynamics (MD) simulation. Firstly, the yeast-induced fever model was constructed in young rats to study antipyretic effect of XQJRG. Metabolomics and network pharmacology studies were performed to identify the key compounds, targets and pathways involved in the antipyretic of XQJRG. Subsequently, MetScape was used to jointly analyze targets from network pharmacology and metabolites from metabolomics. Finally, the key targets were validated by enzyme-linked immunosorbent assay (ELISA), and the affinity and stability of key ingredient and targets were evaluated by molecular docking and MD simulation. The animal experimental results showed that after XQJRG treatment, body temperature of febrile rats was significantly reduced, 13 metabolites were significantly modulated, and pathways of differential metabolite enrichment were mainly related to amino acid and lipid metabolism. Network pharmacology results indicated that quercetin and kaempferol were the key active components of XQJRG, TNF, AKT1, IL6, IL1B and PTGS2 were core targets. ELISA confirmed that XQJRG significantly reduced the plasma concentrations of IL-1β, IL-6, and TNF-α, and the hypothalamic concentrations of COX-2 and PGE2. Molecular docking demonstrated that the binding energies of kaempferol to the core targets were all below −5.0 kcal/mol. MD simulation results showed that the binding free energies of TNF-kaempferol, IL6-kaempferol, IL1B-kaempferol and PTGS2-kaempferol were −87.86 kcal/mol, −70.41 kcal/mol, −69.95 kcal/mol and −106.67 kcal/mol, respectively. In conclusion, XQJRG has antipyretic effects on yeast-induced fever in young rats, and its antipyretic mechanisms may be related to the inhibition of peripheral pyrogenic cytokines release by constituents such as kaempferol, the reduction of hypothalamic fever mediator production, and the amelioration of disturbances in amino acid and lipid metabolism. Communicated by Ramaswamy H. Sarma

A cooperative strategy for snake robots to overcome the extreme terrain

ABSTRACT The mobility of a snake robot is limited by factors such as its length, mass distribution, and torque output. To overcome these limitations, the cooperation between two snake robots can be an effective strategy, inspired by the hand-in-hand interaction of humans. In this article, the cooperative strategies for the double snake robots are presented to improve their mobility in some extreme environments. In order to achieve the force interaction between snake robots, we introduce a docking strategy, which enables them to cross ditches and climb slopes. We further study these cooperative strategies and demonstrate their effectiveness through experiments. The snake robots can dock with each other and cross ditches with a width of half the length of each robot. Additionally, the robot at the top of a slope can help the robot at the bottom climb a steep slope of 63.2 ∘ , which would be difficult to achieve with a single snake robot.

Integrated Network Ethnopharmacology, Molecular Docking, and ADMET Analysis Strategy for Exploring the Anti-Breast Cancer Activity of Ayurvedic Botanicals Targeting the Progesterone Receptor

Abstract Background: In women, breast cancer is currently among the most common cancers and the second major cause of cancer-related mortality. One therapeutic target for breast cancer is the progesterone receptor (PR), which can be inhibited by specific PR modulators. Methods: Current anti-cancer medications have notorious adverse effects. Consequently, an urgent need exists to identify less hazardous, more effective medicines with few to no adverse effects. One strategy uses ancient herbal remedies to create medications derived from nature. Herein, we used data from the Dr. Duke, IMPPAT, PubChem, Binding DB, UniProt, and DisGeNET databases to construct a network in Cytoscape 3.10.0. Through a polypharmacology approach, bioactives with similarity indices greater than 0.6 were screened and docked with the PR. The top ten ligands with good docking scores were further subjected to interaction analysis in AutoDock v.4.2 software. We additionally analyzed the ADMET properties of the phytochemicals. Results: Procurcumenol and alpha-turmerone exhibited superior interactions with PR, with binding affinities of −7.85 kcal/mol. All compounds met Lipinski’s rule of five and were effective ligands for the PR according to ADMET data analysis. Our findings suggest that procurcumenol and alpha-turmerone may serve as potential anti-breast cancer agents; specifically targeting the PR in breast cancer cells. Conclusion: Understanding of anti-breast cancer activity can be facilitated through experimental validation of network analysis and molecular docking findings.

UNREVEALING THE COMPLEX INTERPLAY: MOLECULAR DOCKING: A COMPREHENSIVE REVIEW ON CURRENT SCENARIO, UPCOMING DIFFICULTIES, FORTHCOMING INITIATIVES, AND VIEWPOINTS

The computer modelling of structural complexes generated from two or more interacting molecules are referred to as molecular docking. It is an indispensable tool in computer-aided drug design and structural molecular biology. Using this technology, large libraries of compounds may be digitally screened, and the results can be graded along with structural assumptions about how the ligands impact the target's reduction. Recent advances in the synthesis of anti-infectious medicines prompted by structural insights have enabled the application of computer-assisted drug design in the quest for innovative mechanism-or structure-based drugs. Molecular docking is an important phase in the drug development process because it determines the best positions for molecules to occupy when they are coupled together and predicts how effectively two molecules will bind once they have been docked. The input structure's design is also critical, and the results are assessed using sampling methods and scoring systems. The recently developed docking software Local Move Monte Carlo provides a strong choice for customizable receptor docking strategies. Docking is a technique for determining how ligands and proteins interact. It is structurally sound and compatible with computer-assisted medication design. Successful docking discovers high-dimensional spaces and ranks function utilisation, resulting in a candidate docking rating that is acceptable. It may also be used to screen vast libraries of molecules and offer structural hypotheses for the process.

Docking strategies for predicting protein-ligand interactions and their application to structure-based drug design

Docking strategies for predicting protein-ligand interactions and their application to structure-based drug design

Network pharmacology and molecular docking reveals the therapeutic mechanism of Musa acuminata against obsessive-compulsive disorder

Network pharmacology integrates systems biology and bioinformatics to explore the intricate relationships among drugs, targets, diseases, and other molecular docking used to explore the effect of Musa acuminata against obsessive-compulsive disorder (OCD). OCD is a behavioral and mental neurological condition. The occurrence of patients with OCD has increased in recent times due to both genetic and environmental factors. Genetic factors involve variations in certain genes that give instructions for proteins that react to or transport the neurotransmitter known as serotonin which has been associated with an increased risk of OCD. Thus, the present study aims to establish the therapeutic properties of M. acuminata, that is, banana against environment-induced OCD. The active components of M. acuminata were screened through IMPPAT 2.0, NPASS, and HMDB databases. Corresponding gene targets of active ingredients were found by using STITCH and comparative toxicogenomics database databases. Similarly, the genes involved in OCD were screened with the help of the Gene Cards and DisGeNET database. Utilizing the Gene Cards and DisGeNET database, 2,966 gene targets of OCD were obtained. The network interaction map of gene targets was created using STRING and the CytoHubba plugin of Cytoscape, and the top interacting targets were then filtered away. Finally, the prophylactic activity of active ingredients of M. acuminata against OCD was studied through a molecular docking strategy. This research utilized a network pharmacology-integrated molecular docking approach to study the therapeutic properties of M. acuminata against OCD.

An Omnidirectional Compliant Docking Strategy for Non-cooperative On-orbit Targets: Principle, Design, Modeling and Experiment

An Omnidirectional Compliant Docking Strategy for Non-cooperative On-orbit Targets: Principle, Design, Modeling and Experiment

Lactoferrin docking NIR-II cyanine dye as a potentiated phototheranostic for synchronous multimodal bioimaging and tumor photo-immunotherapy.

Rationale: A promising dye for phototheranostics, IR-1048 is a near-infrared region II (NIR-II) cyanine dye that exhibits exceptional optical characteristics in NIR-II spectrum. Unfortunately, the biological applications of IR-1048 are challenged by its hydrophobic nature, the formation of face-to-face stacked dimeric aggregates (H-aggregates) that result in pronounced spectral blue shifts, and issues related to fluorescence quenching. Method: We present a novel docking strategy involving bovine serum albumin (BSA) and lactoferrin (Lf) to construct BSA@IR-1048 and Lf@IR-1048 nanoprobes. The NIR-II optical characteristics of these nanoprobes have been thoroughly investigated through both theoretical and experimental approaches. In addition, we conducted in vitro and in vivo evaluations of their NIR-II photothermal and photodynamic properties, multimodal imaging capabilities, and effectiveness in photoimmunotherapy. Results: Following the protein docking process, both BSA@IR-1048 and Lf@IR-1048 probes exhibited a red-shifted absorbance peak and an "ON" state in NIR-II fluorescence. Theoretical analyses alongside experimental results indicate that Lf@IR-1048, which has a higher docking binding energy of -10.83 kcal/mol, significantly enhances optical characteristics in the NIR-II region. Notably, when utilizing a single NIR-II light source, Lf@IR-1048 was effective in producing single-linear state oxygen and converting photons into heat energy, achieving a photo-thermal conversion efficiency of 41.9%. The overexpression of transferrin receptors in tumor cells also improved tumor-targeting and enrichment capabilities of Lf@IR-1048, as demonstrated vitro and in vivo studies. Comparatively, Lf@IR-1048 facilitated multimodal imaging-guided NIR-II phototherapy, showing an impressive tumor development inhibition rate of 94.8%. Furthermore, in bilateral CT26 tumor-bearing mice, the Lf@IR-1048-based photo-immunotherapy exhibited significant antitumor activity, attributed to enhanced dendritic cell maturation and infiltration of cytotoxic T lymphocytes. Conclusion: Lf@IR-1048 displays a powerful combination of photothermal therapy, photodynamic therapy, and tumor-targeting potential for effective multimodal imaging-guided NIR-II phototherapy, leading to substantial inhibition of tumor growth.

Design of new dipeptide inhibitors against SARS-CoV 3CLpro: 3D-QSAR, molecular docking, MD simulation, ADMET studies and retrosynthesis strategy

The 3CL protease plays a crucial role in the life cycle of SARS-CoV. This protease is considered an important antiviral target. In the present work, the 3D-QSAR study was performed on a set composed of twenty-six dipeptide SARS-CoV 3CLpro inhibitors in order to propose the new potent anti-SARS agents with a high predicted activity value. The model of CoMSIA/SH is the optimal, with good statistical results presenting a high value of the cross-validation coefficient Q2 = 0.796 and a good value of the determination coefficient R2 = 0.887, the external validation of this model is justified by the high value of the prediction coefficient R2pred = 0.884 and the validation of Globraikh, Roy and Tropsha criteria. The exploitation of the different results provided key information about the structures favored to improve the inhibitory activity against 3CLpro, and has enabled us to propose seven new potent inhibitors with significant predictive activity values, notably compound M−1 with pKipred = 7.080. Then, a molecular docking study was performed to determine the binding energy and to identify the key interactions between the receptor (PDB ID: 1WOF) and the ligands. All the newly designed compounds showed low binding energy values as compared to the Remdesivir −8.144 kcal. mol−1 especially for compounds M−5 and M−4 with the binding affinity values −10.022 kcal. mol−1 and −9.727 kcal.mol−1 respectively. In addition, these inhibitors were verified for in silico pharmacokinetic proprieties and toxicity profile using ADMET. Two compounds M−4 and M−5 with potential results in the molecular docking were selected for the molecular dynamic simulation of 100 ns. The MM-GBSA results show that the predicted compound M−5 has the lowest free energy with −38.200 KJ/mol. We exploited the computer-aided synthesis technology using the ASKCOS website to perform a retrosynthetic analysis of compound M−5.

Exploring the hub genes and potential drugs involved in Fanconi anemia using microarray datasets and bioinformatics analysis

Fanconi anemia (FA) is a genetic disorder that occurs when certain genes responsible for repairing DNA replication and promoting homologous recombination fail to function properly. This leads to severe clinical symptoms and a wide range of cancer-related characteristics. Recent treatment approaches for FA involve hematopoietic stem cell transplantation (HSCT), which helps restore the population of stem cells. A survival study using p-values indicated that specific hub genes play a significant role in diagnosing and predicting the disease. To find potential medications that interact with the identified hub genes, researchers inferred drugs. Among hub genes, TP53 was found to be particularly promising through computational analysis. Further investigation focused on two drugs, Topiramate and Tocofersolan predicted based on drug bank database analysis. Molecular docking strategies were employed to assess the best binding pose of these drugs with TP53. Topiramate showed a binding affinity of −6.5 kcal/mol, while Tocofersolan showed −8.5 kcal/mol against the active residues within the binding pocket. Molecular dynamics (MD) simulations were conducted to observe the stability of each drug’s interaction with the TP53 protein over time. Both drugs exhibited stable confirmation with only slight changes in the loop region of the TP53 protein during the simulation intervals. Results also shows that there was a high fluctuation observed during apo-sate simulation time intervals as compared to complex system. Hence, it is suggested that the exploration of structure-based drug design holds promising results to specific target. This could potentially lead to a breakthrough in future experimental approaches for FA treatment. Communicated by Ramaswamy H. Sarma

Consensus docking aid to model the activity of an inhibitor of DNA methyltransferase 1 inspired by de novo design

The structure-activity relationships data available in public databases of inhibitors of DNA methyltransferases (DNMTs), families of epigenetic targets, plus the structural information of DNMT1, enables the development of a robust structure-based drug design strategy to study, at the molecular level, the activity of DNMTs inhibitors. In this study, we discuss a consensus molecular docking strategy to aid in explaining the activity of small molecules tested as inhibitors of DNMT1. The consensus docking approach, which was based on three validated docking algorithms of different designs, had an overall good agreement with the experimental enzymatic inhibition assays reported in the literature. The docking protocol was used to explain, at the molecular level, the activity profile of a novel DNMT1 inhibitor with a distinct chemical scaffold whose identification was inspired by de novo design and complemented with similarity searching.

Structural Regulation and Transformation of Oxalate-Bridged Polyoxo-Titanium Nanoclusters: Intercluster Docking Strategy and Polyiodides Induced Rearrangement.

Although significant progress has been made in the synthetic and structural chemistry of polyoxo-titanium clusters (PTCs), the rational regulation of their geometric and electronic configurations is rather difficult. Meanwhile, it is also challenging to induce their systematic structural transformation, thereby customizing their physicochemical properties. In this work, we illustrate the intercluster docking strategy, which utilizes oxalates as multidentate ligands to connect and regulate the modular assembly of polynuclear Ti-O subunits into nanoclusters Ti24(μ3-O)26(μ2-O)4(OiPr)34(Oxal) (PTC-361), Ti28(μ4-O)2(μ3-O)28(μ2-O)8(OtBu)22(PA)12(Oxal) (PTC-362), Ti10(μ3-O)6(OtBu)14(PA)6(Oxal)2(tBC)2 (PTC-363), and Ti24(μ3-O)20(μ2-O)12(PA)12(Oxal)2(Hoxal)8(PyA)8 (PTC-364) (H2Oxal = oxalic acid; HOiPr = isopropanol; HOtBu = t-butanol; H2tBC = 4-tert-butylcatechol; HPA = propionic acid; and HPyA = 2-picolinic acid). Furthermore, the stepwise addition of iodine gives rise to polyiodide I3- to assist the controllable structure transformation of PTC-361 to [Ti12(μ-O)15(OiPr)17]I3 (PTC-365) and even to [Ti24(μ2-O)2(μ3-O)30(OiPr)30](I3)2 (PTC-366) with increasing polyiodide content. Moreover, modification with 4-tert-butylcatecholate as light absorbent material on the surface layers of PTCs and polyiodide I3- incorporation in PTCs expand their light response to the visible region and reduce their highest occupied molecular orbital-lowest unoccupied molecular orbital gaps. This work successfully develops an intercluster docking strategy and gives precise modulation on the geometry of nanoclusters as well as the optimization of their desired properties.

Triclocarban exhibits higher adipogenic activity than triclosan through peroxisome proliferator-activated receptors pathways

Previous epidemiological and animal studies have showed the lipid metabolic disruption of antimicrobial triclocarban (TCC) and triclosan (TCS). However, the present in vivo researches were mainly devoted to the hepatic lipid metabolism, while the evidence about the impacts of TCC/TCS on the adipose tissue is very limited and the potential mechanism is unclear, especially the molecular initiation events. Moreover, little is known about the toxic difference between TCC and TCS. This study aimed to demonstrate the differential adipogenic activity of TCC/TCS as well as the potential molecular mechanism via peroxisome proliferator-activated receptors (PPARα/β/γ). The in vitro experiment based on 3T3-L1 cells showed that TCC/TCS promoted the differentiation of preadipocytes into mature adipocytes at nanomolar to micromolar concentrations, which was approach to their human exposure levels. We revealed for the first time by reporter gene assay that TCC could activate three PPARs signaling pathways in a concentration-dependent manner, while TCS only activate PPARβ. The molecular docking strategy was applied to simulate the interactions of TCC/TCS with PPARs, which explained well the different PPARs activities between TCC and TCS. TCC up-regulated the mRNA expression of three PPARs, but TCS only up-regulated PPARβ and PPARγ significantly. Meanwhile, TCC/TCS also promoted the expression of adipogenic genes targeted by PPARs to different extent. The cellular and simulating studies demonstrated that TCC exerted higher adipogenic effects and PPARs activities than TCS. Our mice in vivo experiment showed that TCC could lead to adipocyte size increase, adipocyte lipid accumulation growing, fat weight and body weight gain at human-related exposure levels, and high fat diet exacerbated these effects. Moreover, male mice tended to be more susceptible to TCC induced obesogenic effect than female mice. This work highlights the potential obesogenic risks of TCC/TCS via PPARs signaling pathways, and TCC deserves more concerns for its higher activity.

Self-assembly, virtual screening of a new cobalt complex: Synthesis, empirical, DFT calculations, biological activity investigations and identification of inhibitory activity on the main protease of COVID-19 and SARS-CoV2 by molecular docking strategy of (C6H6NF)2[Co(SCN)2

The present work undertakes the study of a new thiocyanic complex (C6H6NF)2[Co(SCN)2], a synergy between the two experimental and theoretical approach allows us to characterize and evaluate our crystal. (C6H6NF)2[Co(SCN)2] has been successfully synthesized at room temperature by slow evaporation and crystallized in monoclinic system with P21/c space group, in addition the X-ray powder diffraction to punctuate the obtention of a pure phase of the desired complex. Infrared spectrum was registered to revel the vibrational modes of the coordination compound. To highlight the optical properties, the UV–visible analysis was performed using a polar solvent. Thermal analyses were carried out to account for the thermal decomposition of complex. In order to gain insights into the role of weak molecular interactions in the complex that influence the self-assembly process and crystal packing, Hirshfeld surface analysis and DFT calculation were also performed. Furthermore, molecular docking and molecular dynamic simulations were performed for the compounds against different antibacterial targets to identify to which target the compounds show the best binding affinity. The MurF enzyme, which catalyzed the last cytoplasmic step of bacterial peptidoglycan synthesis, among the target was revealed to show better interactions with the enzyme and formed strong and stable intermolecular complex. Molecular docking analysis reveals that 1EPBN might display the inhibitory activity against coronavirus proteins (COVID-19 and SARS-CoV2).

Rudimentary Review on Molecular Docking: A Beginner’s Guide

The computer modelling of structural complexes generated from two or more interacting molecules are referred to as molecular docking. It is an indispensable tool in computer-aided drug design and structural molecular biology. Using this technology, large libraries of compounds may be digitally screened, and the results can be graded along with structural assumptions about how the ligands impact the target's reduction. Recent advances in the synthesis of anti-infectious medicines prompted by structural insights have enabled the application of computer-assisted drug design in the quest for innovative mechanism- or structure-based drugs. Molecular docking is an important phase in the drug development process because it determines the best positions for molecules to occupy when they are coupled together and predicts how effectively two molecules will bind once they have been docked. The input structure's design is also critical, and the results are assessed using sampling methods and scoring systems. The recently developed docking software Local Move Monte Carlo [LMMC] provides a strong choice for customizable receptor docking strategies. Docking is a technique for determining how ligands and proteins interact. It is structurally sound and compatible with computer-assisted medication design. Successful docking discovers high-dimensional spaces and ranks function utilisation, resulting in a candidate docking rating that is acceptable. It may also be used to screen vast libraries of molecules and offer structural hypotheses for the process.