Ligand-receptor Complex Research Articles

Synthesis, Urease Inhibitory Activity, Molecular Docking, Dynamics, MMGBSA and DFT Studies of Hydrazone-Schiff Bases Bearing Benzimidazole Scaffold.

In this study, eleven hydrazone-Schiff bases bearing benzimidazole moiety were synthesized successfully via three step reactions and structures of these products were deduced by HR-ESI-MS, 1H-, and 13C-NMR spectroscopic techniques. Lastly, these derivatives were tested for their in vitro urease inhibitory potential. Six compounds among the series attributed excellent inhibition with IC50 values of 7.20±0.59 to 19.61±1.10 μM better than the reference drug thiourea (IC50=22.12±1.20 μM). Similarly, three derivatives showed significant while two compounds showed less inhibitory effects against the urease enzyme. The molecular docking analysis was carried out to reveal the binding modes and types of interaction taking place between protein (urease) and synthesized compounds. The Density Functional Theory (DFT) calculations were performed at B3LYP/6-311++G(d,p) to check the structure stability. For the account of intramolecular interaction, the DFT-D3 and Reduced Density Gradient (RDG) analysis were performed. Furthermore, the chemical nature of all compounds was explored by TD-DFT method using CAM-B3LYP functional with 6-311++G(d,p) basis set. The dynamic simulation as well as MMGBSA studies validated the binding affinity and stability of the ligand receptor complex, displaying main interactions contributing in the biological activity of the product derivatives.

Exploring Moroccan Medicinal Plants for Anticancer Therapy Development Through In Silico Studies.

Angiogenesis is a crucial process in the growth and proliferation of cancer, enabling tumor growth through the formation of new vasculature and the supply of nutrients and oxygen to growing malignant cells. This disease-promoting process can be targeted through the inhibition of tyrosine kinase enzymes. The objective of this study is to evaluate the anticancer potential of various Moroccan plants from different regions. While these plants have a rich history of traditional medicinal use, they have not been extensively investigated as anticancer therapies. This study employed a multifaceted approach to evaluate the anticancer potential of various Moroccan plants. Receptor-ligand docking and virtual screening were used to assess the binding affinity of phytocompounds to the EGFR and VEGFR2 receptors. Additionally, predictive pharmacokinetic analyses were conducted to evaluate the ADMET properties of the selected compounds, followed by molecular dynamics simulations to analyze the stability of the receptor-ligand complexes. In our research, we identified three notable active compounds-catechin, 4-O-glucoside ferulic acid, and 3-glucoside resveratrol-in the Moroccan plant Ajuga iva L. These findings suggest that Ajuga iva L. may possess significant potential for cancer inhibition. This research highlights the potential of the Moroccan plant Ajuga iva L. as a source of active compounds with significant anticancer properties. Further investigation is essential to validate these findings and explore new therapeutic avenues based on these traditional resources.

Plant pattern recognition receptors: from evolutionary insight to engineering.

The plant immune system relies on germline-encoded pattern recognition receptors (PRRs) that sense foreign and plant-derived molecular patterns, and signal health threats. Genomic and pangenomic data sets provide valuable insights into the evolution of PRRs and their molecular triggers, which is furthering our understanding of plant-pathogen co-evolution and convergent evolution. Moreover, in silico and in vivo methods of PRR identification have accelerated the characterization of receptor-ligand complexes, and advances in protein structure prediction algorithms are revealing novel PRR sensor functions. Harnessing these recent advances to engineer PRRs presents an opportunity to enhance plant disease resistance against a broad spectrum of pathogens, enabling more sustainable agricultural practices. This Review summarizes both established and innovative approaches to leverage genomic data and translate resulting evolutionary insights into engineering PRR recognition specificities.

Rational drug design targeting g-protein-coupled receptors: a structural biology perspective

G protein-coupled Receptors (G protein-coupled Receptors, GPCRs) play a key role in the transmission of extracellular signals and regulation of many biological processes, which makes these membrane proteins one of the most important classes of targets for pharmacological agents. The significant increase in the number of atomic structures of GPCRs recently has paved the way for Structure Based Drug Design (SBDD). SBDD uses information on the structure of the receptor-ligand complex to search for affinity and selective ligands without the need for high-throughput experimental ligand screening and allows a significant expansion of the chemical ligand search space. In our review we describe the process of GPCR structure obtaining by X-ray diffraction analysis and cryo-electron microscopy (cryo-EM) – an important step in rational drug design targeting GPCRs. Our main goal is to highlight to a wide range of specialists the current aspects and key features of experimental structural biology methods necessary for a detailed understanding of SBDD GPCRs.

Understanding and Predicting Ligand Efficacy in the μ-Opioid Receptor through Quantitative Dynamical Analysis of Complex Structures.

The μ-opioid receptor (MOR) is a G-protein coupled receptor involved in nociception and the primary target of opioid drugs. Understanding the relationships among the ligand structure, receptor dynamics, and efficacy in activating MOR is crucial for drug discovery and development. Here, we use coarse-grained normal-mode analysis to predict ligand-induced changes in receptor dynamics with the Quantitative Dynamics Activity Relationship (QDAR) DynaSig-ML methodology, training a LASSO regression model on the entropic signatures (ESs) computed from ligand-receptor complexes. We train and validate the methodology using a data set of 179 MOR ligands with experimentally measured efficacies split into strictly chemically different cross-validation sets. By analyzing the coefficients of the ES LASSO model, we identified key residues involved in MOR activation, several of which have mutational data supporting their role in MOR activation. Additionally, we explored a contact-only LASSO model based on ligand-protein interactions. While the model showed predictive power, it failed at predicting efficacy for ligands with low structural similarity to the training set, emphasizing the importance of receptor dynamics for predicting ligand-induced receptor activation. Moreover, the low computational cost of our approach, at 3 CPU s per ligand-receptor complex, opens the door to its application in large-scale virtual screening contexts. Our work contributes to a better understanding of dynamics-function relationships in the μ-opioid receptor and provides a framework for predicting ligand efficacy based on ligand-induced changes in receptor dynamics.

Identification of novel inhibitors of plant GH3 IAA-amido synthetases through molecular docking studies.

Auxins play a critical role in several plant developmental processes and their endogenous levels are regulated at multiple levels. The enzymes of the GRETCHEN HAGEN 3 (GH3) protein family catalyze the conjugation of amino acids to indoleacetic acid (IAA), the major endogenous auxin. The GH3 proteins are encoded by multiple redundant genes in plant genomes, making it difficult to perform functional genetic studies to understand their role in auxin homeostasis. To address these challenges, we used a chemical approach that exploits the reaction mechanism of GH3 proteins to identify small molecule inhibitors of their activity from a defined chemical library. The study evaluated receptor-ligand complexes based on their binding energy and classified them accordingly. Docking algorithms were used to correct any deviations, resulting in a list of the most important inhibitory compounds for selected GH3 enzymes based on a normalized sum of energy. The study presents atomic details of protein-ligand interactions and quantifies the effect of several of the identified small molecule inhibitors on auxin-mediated root growth processes in Arabidopsis thaliana. The direct effect of these compounds on endogenous auxin levels was measured using appropriate auxin sensors and endogenous hormone measurements. Our study has identified novel compounds of the flavonoid biosynthetic pathway that are effective inhibitors of GH3 enzyme-mediated IAA conjugation. These compounds play a versatile role in hormone-regulated plant development and have potential applications in both basic research and agriculture.

In Silico Drug Designing for the Treatment of Cervical Cancer

Cervical cancer is a significant global health issue, especially in developing countries where limited resources and access to health services pose challenges. Human papillomavirus (HPV) is the primary cause of cervical cancer and plays a crucial role in its development. Despite the availability of prophylactic vaccines, effective treatment options for patients with pre-existing HPV infections or HPV-induced carcinomas remain elusive. High-risk (HR) HPV E6 and E7 oncoproteins serve as biomarkers in cervical cancer progression. Research has focused on these proteins as potential targets for novel therapeutics and to find a novel compound that can overcome the problem of drug ineffectiveness in cancerous cells as they become multi-drug resistant to the existing drugs and treatments. Computational-aided methods, including in silico approaches, have been valuable in discovering and developing small molecules that can block or inhibit the action of the E6 oncoproteins. This review discusses existing small molecules explored as HPV E6 protein blockers and outlines future perspectives in cervical cancer therapy. In molecular docking studies, it is identified that four compounds exhibit the properties of a lead molecule, possess more negative binding energy, and form a highly stable ligand-receptor complex. These four compounds will help in future research and development. Advancing these compounds through further studies will help develop potential and effective drugs for treating cervical cancer.

A computational biology approach for the identification of potential SARS-CoV-2 main protease inhibitors from natural essential oil compounds.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has fomented a climate of fear worldwide due to its rapidly spreading nature, and high mortality rate. The World Health Organization (WHO) declared it as a global pandemic on 11th March, 2020. Many endeavors have been made to find appropriate medications to restrain the SARS CoV-2 infection from spreading but there is no specific antiviral therapy to date. However, a computer-aided drug design approach can be an alternative to identify probable drug candidates within a short time. SARS-CoV-2 main protease is a proven drug target, and it plays a pivotal role in viral replication and transcription. Methods: In this study, we identified a total of 114 essential oil compounds as a feasible anti-SARS-CoV-2 agent from several online reservoirs. These compounds were screened by incorporating ADMET profiling, molecular docking, and 50 ns of molecular dynamics simulation to identify potential drug candidates against the SARS-CoV-2 main protease. The crystallized SARS-CoV-2 main protease structure was collected from the RCSB PDB database (PDB ID 6LU7). Results: According to the results of the ADMET study, none of the compounds have any side effects that could reduce their druglikeness or pharmacokinetic properties. Out of 114 compounds, we selected bisabololoxide B, eremanthin, and leptospermone as our top drug candidates based on their higher binding affinity scores, and strong interaction with the Cys 145-His 41 catalytic dyad. Finally, the molecular dynamics simulation was implemented to evaluate the structural stability of the ligand-receptor complex. MD simulations disclosed that all the hits showed conformational stability compared to the positive control α-ketoamide. Conclusions: Our study showed that the top three hits might work as potential anti-SARS-CoV-2 agents, which can pave the way for discovering new drugs, but for experimental validation, they will require more in vivo trials.

Assessment of the conceivable inhibitory activity of pathogenic microorganisms extracted from seaweed using phytochemicals, antioxidants, and in-silico molecular dynamic simulation

Turbinaria ornata, Polycladia myrica, and Padina pavonica is a perennial Mediterranean-native seaweed that is commonly used for mass display. The principal aims of this reconnaissance were the isolation of various compounds from methanolic seaweeds extraction and screening the potential effect as antibacterial, and antioxidant. The micro-dilution method was used to measure antibacterial activity. Gas chromatography-mass spectrophotometry (GC. Mass) abused to analyze the chemical components of the methanolic seaweed extract. The existence of 19 secondary metabolites was discovered using GC–MS analysis: 8 different compounds for each seaweed's species. Among these bioactive compounds, 4 compounds from P. pavonica extract showed the binding affinity and ability to react with Beta-ketoacyl synthase (PDB ID 1EK4) of Escherichia coli. The phytocompounds' drug-like and poisonous characteristics were predicted. Auto Dock was used to examine the ligand receptor complexes' binding strength. T. ornate and P. pavonica had the highest activity against K. pneumonia, with 22.50 mm (0.78 µg/ml) and 22.23 mm (5.10 µg/ml) obtained, respectively. In a concentration-dependent manner, the extract components demonstrated substantial antioxidant activity. P. pavonica had the highest scavenging activity (78.00%, IC50 = 6.35 µg/ml), while ascorbic acid had a 96.45% scavenging impact. Because the chemicals bind to the Lipinski Ro5, they have drug-like characteristics. The compounds had no hepatotoxic effects. P. pavonica extract has the prospect of being used as a source of medicinal drug-like chemicals. The docking investigation found a strong correlation between the experimental results and the docking results. Finally, brown seaweed extract, particularly P. pavonica extract, demonstrated strong antibacterial, antioxidant, and free radical scavenging properties.

Small Molecule Compound DHPA Screened by Computer-Aided Drug Design and Molecular Dynamics Simulation Inhibits Neuroblastoma Cell Proliferation by Targeting TrkB.

Neuroblastoma (NB) is a rare and malignant pediatric solid tumor. Due to its heterogeneity, it poses significant challenges for treatment, resulting in a high mortality rate. This study aimed to identify new therapeutic drugs by modeling the TrkB receptor from PDB 4AT5 and conducting virtual screening of compounds from the YaTCM database (containing 47,696 compounds derived from 6220 Traditional Chinese Medicines). The screening utilized the E-pharmacophore approach to select compounds with potential binding affinity to TrkB. The binding abilities of these compounds were tested through molecular dynamics simulations, stretch dynamics simulations, and US simulations. Among the top 11 optimized hit compounds, DHPA and 3″-demethylhexahydrocurcumin are prominent. Further simulations reveal that they form stable receptor-ligand binary complexes with TrkB. In subsequent in vitro cell experiments, 3″-demethylhexahydrocurcumin is eliminated due to its high IC50 for killing NB cells. Low concentrations of DHPA can significantly kill NB cells. Additionally, DHPA can inhibit the expression of TrkB, the activation of TrkB's downstream signaling pathways, and affect the thermal stability of TrkB protein and its response to streptase protease degradation. DHPA may be a potential TrkB inhibitor.

<i>In silico</i> Pharmacokinetic, Molecular Docking and Molecular Dynamics Simulation Studies of Phytochemicals isolated from <i>Cascabela thevetia</i> as Potential Anticancer Agents

Cascabela thevetia generally recognized as yellow oleander, Lippold or lucky nut (in English) and Peeli Kaner (in Hindi), is Indigenous to Central America and Mexico and widely distributed in the Indian subcontinent as well, is a medicinally important herb that has long been employed to treat disorders like ulcers, scabies, haemorrhoids, and tumour dissolution. Seven Cardenolides (Compounds 1-7) isolated from fruits of Cascabela thevetia are selected as ligands for in silico pharmacokinetic (ADME properties) and drug-likeness studies via the Swiss ADME online server. Further, molecular docking studies were accomplished for the selected ligands via the Auto Dock Vina module of PyRx to explore the receptor-ligand interaction with β-tubulin (a potential target for anticancer drugs, PDB ID: 1SA0), to find out potential therapeutic ligands for cancer chemotherapy. From the studies performed it was found that most of the ligands (compounds) have the capability of good binding affinity with the receptor, β-tubulin, good drug-likeness and ADME properties among which compounds 3, 6 and 7 are the best drug candidates because they followed the Lipinski rule of 5 with 0 violation and also have good binding affinities (-8.3, -8.0 and -7.9 kcal/mol respectively) against the target protein. Hence, compounds 3, 6 and 7 can be developed as novel therapeutic agents in cancer chemotherapy. Further, a Molecular Dynamics (MD) simulation study of best-docked ligand 3 was performed to establish its stability and validate molecular docking results. Based on simulation results, it may be stated that ligand 3 was firmly attached to the receptor protein during MD simulation since none of the conformations of the receptor-ligand complex were unstable, and no folding or unfolding of the complex took place. Therefore, compound 3 can be considered a good inhibitor of β-tubulin after validation of various parameters of drug discovery.

Influence of Trp-Cage on the Function and Stability of GLP-1R Agonist Exenatide Derivatives.

Exenatide (Ex4), a GLP-1 incretin mimetic polypeptide, is an effective therapeutic agent against diabetes and obesity. We highlight the indirect role of Ex4's structure-stabilizing Trp-cage (Tc) motif in governing GLP-1 receptor (GLP-1R) signal transduction. We use various Ex4 derivatives to explore how Tc compactness influences thermal stability, aggregation, enhancement of insulin secretion, and GLP-1R binding. We found that Ex4 variants decorated with fortified Tc motifs exhibit increased resistance to unfolding and aggregation but show an inverse relationship between the bioactivity and stability. Molecular dynamics simulations coupled with a rigid-body segmentation protocol to analyze dynamic interconnectedness revealed that the constrained Tc motifs remain intact within the receptor-ligand complexes but interfere with one of the major stabilizing contacts and recognition loci on the extracellular side of GLP-1R, dislodging the N-terminal activating region of the hormone mimetics, and restrict the free movement of TM6, the main signal transduction device of GLP-1R.

Exploration of 4-tolyl-5-(p-tolyloxymethyl)-4H-1,2,4-triazole thioethers as potent 15-LOX inhibitors supported by in vitro, in silico, MD simulation and DNA binding studies

Inflammation is an intricate process exacerbated by the sequential release of lipid mediators during arachidonic acid metabolism through the LOX and COX pathways. The inhibition of enzymes accountable for the arachidonic acid metabolism is attributed to a synergistic anti-inflammatory impact with a broader spectrum of activity. The present study was concerned with the search for lead 15-LOX inhibitors. A new series of alkyl/aralkyl substituted 4-tolyl-5-(p-tolyloxymethyl)-4H-1,2,4-triazole (6a-h) was designed, synthesized, and characterized to determine their 15-LOX inhibitory potential. The analogue 3-(phenethylthio)-4-tolyl-5-(p-tolyloxymethyl)-4H-1,2,4-triazole (6h) was the most potent with IC50 2.73 ± 0.15 µM while 6g, 6d, 6f, 6c exhibited excellent inhibitory activities with IC50 values between 11.39 ± 0.13 and 14.63 ± 0.17 µM. All analogues maintained > 72 % blood mononuclear cells viability at 0.25 mM concentration during MTT assay. In silico ADME profiles predicted druggability potential. The molecular docking studies disclosed binding free energies of -9.78 to -7.94 kcal/mol and His373 and His378 were majorly involved in π-interactions in all molecules. Van der Waals interactions dominated hydrogen bonding in the stabilization of ligand-receptor complexes. MD simulations and free energy calculations revealed the significance of complexes in stabilizing the biomolecular system and helped in identifying the key active site residues that contributed towards the energetics. Studies against DNA dodecamer displayed minor groove binding and intercalation, suggesting a possible role in modulating DNA-related processes. The results approve the active analogues possessing promising druglike properties and work is in progress on the synthesis of more analogues in search for leads as 15-LOX inhibitors.

Discovery of MAO-A Inhibitors as Antidepressant Based on Virtual Screening

Aim: Major depression and anxiety have increased significantly worldwide since the 2019 outbreak of COVID-19. The development of highly effective antidepressants with low side effects is attracting researchers. Methods: Monoamine oxidase A (MAO-A) is a key enzyme that catalyzes the metabolism of norepinephrine (NE), dopamine (DA), and serotonin (5-HT), etc. Elevated level of MAO-A would lead to increased metabolism of its substrates, thereby causing a decrease in the levels of these neurotransmitter monoamines in the brain leading to depression. Consequently, inhibition of MAO-A was thought to be an effective strategy, as this would treat the root cause of depression. Results and Discussion: Based on the crystal structure of MAO-A, 4 star-hits, as potential MAO-A inhibitors was screened from the compound libraries with central nervous system (CNS) activity by using various computational techniques. Molecular dynamics simulation was used to verify the stability of the ligand- receptor complexes. Conclusion: Furthermore, the ADMET (absorption, distribution, metabolism, excretion and toxicity properties) of the virtual hits were predicted in order to evaluate their lead-like properties and safety. This work provides ideas for the drugs discovery of antidepressant.

Unveiling the antibacterial efficacy of thiazolo [3,2-a] pyrimidine: Synthesis, molecular docking, and molecular dynamic simulation.

Two series of C-Mannich base derivatives were synthesized and evaluated through the reaction of formaldehyde, two thiazolo-pyrimidine compounds, and various 2°-amines. The chemical structures and inherent properties of the synthesized compounds were authenticated using a variety of spectroscopic techniques. The aseptic bactericidal potential of the compounds was assessed alongside five common bacterial microbes, with Ampicillin employed as the reference drug. Compounds 9b and 9d demonstrated comparable antibacterial activity to ampicillin against Bacillus subtilis and Bacillus megaterium, respectively, at 100 μg/mL. Furthermore, compounds 9f and 10f exhibited noteworthy action against Staphylococcus aureus (MIC: 250 μg/mL). Compounds 10b and 10f displayed excellent efficacy versus Escherichia coli, boasting (MIC: 50 μg/mL). Molecular docking studies elucidated the necessary connections and energies of molecular entities with the E. coli DNA gyrase B enzyme, a pivotal target in bacterial DNA replication. Further thermodynamic stability of the ligand-receptor complex of 10b and 10f were further validated though 200 ns molecular dynamics simulation. The findings highlight the potential of these synthesized derivatives as effective antibacterial agents and provide valuable insights into their mechanism of action.

QSTR Models in Dioxins and Dioxin-like Compounds Provide Insights into Gene Expression Dysregulation.

Polychlorinated dibenzo-p-dioxins and polychlorinated dibenzo-p-furans (PCDD/Fs) are a group of organic chemicals containing three-ring structures that can be substituted with one to eight chlorine atoms, leading to 75 dioxin and 135 furan congeners. As endocrine-disrupting chemicals (EDCs), they can alter physiological processes causing a number of disorders. In this study, quantitative structure-toxicity relationship (QSTR) studies were used to determine the correlations between the PCDD/Fs' molecular structures and various toxicity endpoints. Strong QSTR models, with the coefficients of determination (r2) values greater than 0.95 and ANOVA p-values less than 0.0001 were established between molecular descriptors and the endpoints of bioconcentration, fathead minnow LC50, and Daphnia magna LC50. The ability of PCDD/Fs to bind to several nuclear receptors was investigated via molecular docking studies. The results show comparable, and in some instances better, binding affinities of PCDD/Fs toward the receptors relative to their natural agonistic and antagonistic ligands, signifying possible interference with the receptors' natural biological activities. These studies were accompanied by the molecular dynamics simulations of the top-binding PCDD/Fs to show changes in the receptor-ligand complexes during binding and provide insights into these compounds' ability to interfere with transcription and thereby modify gene expression. This introspection of PCDD/Fs at the molecular level provides a deeper understanding of these compounds' toxicity and opens avenues for future studies.

Phytochemical Analysis, Biological Activities, and Docking of Phenolics from Shoot Cultures of Hypericum perforatum L. Transformed by Agrobacterium rhizogenes.

Hypericum perforatum transformed shoot lines (TSL) regenerated from corresponding hairy roots and non-transformed shoots (NTS) were comparatively evaluated for their phenolic compound contents and in vitro inhibitory capacity against target enzymes (monoamine oxidase-A, cholinesterases, tyrosinase, α-amylase, α-glucosidase, lipase, and cholesterol esterase). Molecular docking was conducted to assess the contribution of dominant phenolic compounds to the enzyme-inhibitory properties of TSL samples. The TSL extracts represent a rich source of chlorogenic acid, epicatechin and procyanidins, quercetin aglycone and glycosides, anthocyanins, naphthodianthrones, acyl-phloroglucinols, and xanthones. Concerning in vitro bioactivity assays, TSL displayed significantly higher acetylcholinesterase, tyrosinase, α-amylase, pancreatic lipase, and cholesterol esterase inhibitory properties compared to NTS, implying their neuroprotective, antidiabetic, and antiobesity potential. The docking data revealed that pseudohypericin, hyperforin, cadensin G, epicatechin, and chlorogenic acid are superior inhibitors of selected enzymes, exhibiting the lowest binding energy of ligand-receptor complexes. Present data indicate that H. perforatum transformed shoots might be recognized as an excellent biotechnological system for producing phenolic compounds with multiple health benefits.

Potential Therapeutic Approach using Aromatic l-amino Acid Decarboxylase and Glial-derived Neurotrophic Factor Therapy Targeting Putamen in Parkinson's Disease.

Parkinson's disease (PD) is a neurodegenerative illness characterized by specific loss of dopaminergic neurons, resulting in impaired motor movement. Its prevalence is twice as compared to the previous 25 years and affects more than 10 million individuals. Lack of treatment still uses levodopa and other options as disease management measures. Treatment shifts to gene therapy (GT), which utilizes direct delivery of specific genes at the targeted area. Therefore, the use of aromatic L-amino acid decarboxylase (AADC) and glial-derived neurotrophic factor (GDNF) therapy achieves an effective control to treat PD. Patients diagnosed with PD may experience improved therapeutic outcomes by reducing the frequency of drug administration while utilizing provasin and AADC as dopaminergic protective therapy. Enhancing the enzymatic activity of tyrosine hydroxylase (TH), glucocorticoid hormone (GCH), and AADC in the striatum would be useful for external L-DOPA to restore the dopamine (DA) level. Increased expression of glutamic acid decarboxylase (GAD) in the subthalamic nucleus (STN) may also be beneficial in PD. Targeting GDNF therapy specifically to the putaminal region is clinically sound and beneficial in protecting the dopaminergic neurons. Furthermore, preclinical and clinical studies supported the role of GDNF in exhibiting its neuroprotective effect in neurological disorders. Another Ret receptor, which belongs to the tyrosine kinase family, is expressed in dopaminergic neurons and sounds to play a vital role in inhibiting the advancement of PD. GDNF binding on those receptors results in the formation of a receptor-ligand complex. On the other hand, venous delivery of recombinant GDNF by liposome-based and encapsulated cellular approaches enables the secure and effective distribution of neurotrophic factors into the putamen and parenchyma. The current review emphasized the rate of GT target GDNF and AADC therapy, along with the corresponding empirical evidence.

Combining the Fragment Molecular Orbital and GRID Approaches for the Prediction of Ligand-Metalloenzyme Binding Affinity: The Case Study of hCA II Inhibitors.

Polarization and charge-transfer interactions play an important role in ligand-receptor complexes containing metals, and only quantum mechanics methods can adequately describe their contribution to the binding energy. In this work, we selected a set of benzenesulfonamide ligands of human Carbonic Anhydrase II (hCA II)-an important druggable target containing a Zn2+ ion in the active site-as a case study to predict the binding free energy in metalloprotein-ligand complexes and designed specialized computational methods that combine the ab initio fragment molecular orbital (FMO) method and GRID approach. To reproduce the experimental binding free energy in these systems, we adopted a machine-learning approach, here named formula generator (FG), considering different FMO energy terms, the hydrophobic interaction energy (computed by GRID) and logP. The main advantage of the FG approach is that it can find nonlinear relations between the energy terms used to predict the binding free energy, explicitly showing their mathematical relation. This work showed the effectiveness of the FG approach, and therefore, it might represent an important tool for the development of new scoring functions. Indeed, our scoring function showed a high correlation with the experimental binding free energy (R2 = 0.76-0.95, RMSE = 0.34-0.18), revealing a nonlinear relation between energy terms and highlighting the relevant role played by hydrophobic contacts. These results, along with the FMO characterization of ligand-receptor interactions, represent important information to support the design of new and potent hCA II inhibitors.

Developing Lead Compounds of eEF2K Inhibitors Using Ligand–Receptor Complex Structures

The eEF2K, a member of the α-kinase family, plays a crucial role in cellular differentiation and the stability of the nervous system. The development of eEF2K inhibitors has proven to be significantly important in the treatment of diseases such as cancer and Alzheimer’s. With the advancement of big data in pharmaceuticals and the evolution of molecular generation technologies, leveraging artificial intelligence to expedite research on eEF2K inhibitors shows great potential. Based on the recently published structure of eEF2K and known inhibitor molecular structures, a generative model was used to create 1094 candidate inhibitor molecules. Analysis indicates that the model-generated molecules can comprehend the principles of molecular docking. Moreover, some of these molecules can modify the original molecular frameworks. A molecular screening strategy was devised, leading to the identification of five promising eEF2K inhibitor lead compounds. These five compound molecules demonstrated excellent thermodynamic performance when docked with eEF2K, with Vina scores of −12.12, −16.67, −15.07, −15.99, and −10.55 kcal/mol, respectively, showing a 24.27% improvement over known active inhibitor molecules. Additionally, they exhibited favorable drug-likeness. This study used deep generative models to develop eEF2K inhibitors, enabling the treatment of cancer and neurological disorders.