Ligand-receptor Binding Affinity Research Articles

Dually Labeled Neurotensin NTS1R Ligands for Probing Radiochemical and Fluorescence-Based Binding Assays.

The determination of ligand-receptor binding affinities plays a key role in the development process of pharmaceuticals. While the classical radiochemical binding assay uses radioligands, fluorescence-based binding assays require fluorescent probes. Usually, radio- and fluorescence-labeled ligands are dissimilar in terms of structure and bioactivity, and can be used in either radiochemical or fluorescence-based assays. Aiming for a close comparison of both assay types, we synthesized tritiated fluorescent neurotensin receptor ligands ([3H]13, [3H]18) and their nontritiated analogues (13, 18). The labeled probes were studied in radiochemical and fluorescence-based (high-content imaging, flow cytometry, fluorescence anisotropy) binding assays. Equilibrium saturation binding yielded well-comparable ligand-receptor affinities, indicating that all these setups can be used for the screening of new drugs. In contrast, discrepancies were found in the kinetic behavior of the probes, which can be attributed to technical differences of the methods and require further studies with respect to the elucidation of the underlying mechanisms.

In Silico and In Vivo Studies of β-Sitosterol Nanoparticles as a Potential Therapy for Isoprenaline-Induced Cognitive Impairment in Myocardial Infarction, Targeting Myeloperoxidase.

This study aimed to compare the effects of β-sitosterol nanoparticles (BETNs) and β-sitosterol (BET) on cognitive impairment, oxidative stress, and inflammation in a myocardial infarction (MI) rat model using in silico and in vivo methods. β-Sitosterol (BET) and myeloperoxidase (MPO) ligand-receptor binding affinities were evaluated using Autodock Vina for docking and Gromacs for dynamics simulations. BET nanoparticles, prepared via solvent evaporation, had their size confirmed by a nanoparticle analyzer. ISO-induced cognitive impairment in rats was assessed through Morris water maze and Cook's pole climbing tests. Oxidative stress, inflammation, and cardiac injury were evaluated by measuring GSH, SOD, MDA, MPO, CkMB, LDH, lipid profiles, and ECGs. Histopathology of the CA1 hippocampus and myocardial tissue was performed using H&E staining. In silico analyses revealed strong binding affinities between BET and MPO, suggesting BET's potential anti-inflammatory effect. BETN (119.6 ± 42.6 nm; PDI: 0.809) significantly improved MI-induced cognitive dysfunction in rats (p < 0.001 ***), increased hippocampal GSH (p < 0.01 **) and SOD (p < 0.01 **) levels, and decreased hippocampal MDA (p < 0.05 *) and MPO levels (p < 0.01 **). BETNs also elevated cardiac GSH (p < 0.01 **) and SOD (p < 0.01 **) levels and reduced cardiac MPO (p < 0.01 **), CkMB (p < 0.001 **) and LDH (p < 0.001 **) levels. It restored lipid profiles, normalized ECG patterns, and improved histology in the hippocampal CA1 region and myocardium. Compared with BET treatment, BETNs were more effective in improving cognitive impairment, oxidative damage, and inflammation in MI rats, suggesting its potential in treating cognitive dysfunction and associated pathological changes in MI.

Potential inhibitors of VEGFR1, VEGFR2, and VEGFR3 developed through Deep Learning for the treatment of Cervical Cancer

Cervical cancer stands as a prevalent gynaecologic malignancy affecting women globally, often linked to persistent human papillomavirus infection. Biomarkers associated with cervical cancer, including VEGF-A, VEGF-B, VEGF-C, VEGF-D, and VEGF-E, show upregulation and are linked to angiogenesis and lymphangiogenesis. This research aims to employ in-silico methods to target tyrosine kinase receptor proteins—VEGFR-1, VEGFR-2, and VEGFR-3, and identify novel inhibitors for Vascular Endothelial Growth Factors receptors (VEGFRs). A comprehensive literary study was conducted which identified 26 established inhibitors for VEGFR-1, VEGFR-2, and VEGFR-3 receptor proteins. Compounds with high-affinity scores, including PubChem ID—25102847, 369976, and 208908 were chosen from pre-existing compounds for creating Deep Learning-based models. RD-Kit, a Deep learning algorithm, was used to generate 43 million compounds for VEGFR-1, VEGFR-2, and VEGFR-3 targets. Molecular docking studies were conducted on the top 10 molecules for each target to validate the receptor-ligand binding affinity. The results of Molecular Docking indicated that PubChem IDs—71465,645 and 11152946 exhibited strong affinity, designating them as the most efficient molecules. To further investigate their potential, a Molecular Dynamics Simulation was performed to assess conformational stability, and a pharmacophore analysis was also conducted for indoctrinating interactions.

Are there sex differences in oxytocin and vasopressin V1a receptors ligand binding affinities?

There is substantial evidence for sex differences in the functioning of one of the most common receptor systems; G protein-coupled receptors (GPCRs). There are many points along the GPCR-mediated molecular signaling pathway at which males and females may differ, one of the first of which, chronologically, is in the stability of the interaction between the ligand and the receptor, or its binding affinity. Here we investigate the binding affinities of oxytocin (OT) and vasopressin (AVP) at the oxytocin receptor (OTR) and the vasopressin V1a receptor (V1aR), both of which are present in numerous in brain regions associated with social behavior. In order to investigate sex- and estrous cycle-dependent differences in ligand-receptor binding affinity, male (n = 6) Syrian hamsters (Mesocricetus auratus), females on the day of estrus (E females, n = 6), and females on the second day of diestrus (D2 females n = 6) were chosen for study. Brains from hamsters were mounted on slides and competition and saturation binding assays were conducted. We report a remarkable similarity in the binding affinities of OT and AVP in males and females. Small differences were detected, however, in receptor and ligand specificity in females depending on whether they were in the estrous or diestrous stage of their ovulatory cycle. These data suggest that sex differences in binding affinity are not a likely source of the many sex differences that have been observed in the effects of OT and AVP in hamsters and other species.

Computational-guided approach for identification of PI3K alpha inhibitor in the treatment of hepatocellular carcinoma by virtual screening and water map analysis

Hepatocellular carcinoma (HCC) is one of the most deadly disorders, with a relative survival rate of 36% in the last 5 years. After an extensive literature survey and pathophysiology analysis, PI3Kα was found to be a promising biological target as PIK3CA gene upregulation was observed in HCC, resulting in the loss of apoptosis of cells, which leads to uncontrollable growth and proliferation. Due to superior selectivity and promising therapeutic activity, the PI3K-targeted molecule library was selected, and the ligand preparation was executed. The study mainly focused on e-pharmacophore development, virtual screening and receptor–ligand docking analysis. Then, MMGBSA and ADME prediction analysis was performed with the top 10 molecules; for further analysis of ligand–receptor binding affinity at the catalytic binding site, induced fit docking was performed with the top two molecules. The analysis of quantum chemical stability descriptors, i.e., frontier molecular orbital analysis, was performed followed by molecular dynamics simulation of 100 ns to better understand the ligand-receptor binding. In this study, water map analysis played a significant role in the hit optimization and analysis of the thermodynamic properties of the receptor–ligand complex. The two hit molecules K894-1435 and K894-1045 represented superior docking scores, enhanced stability, and inhibitory action targeting Valine 851 amino acid residue at the catalytic binding site. Hence, the study has significance for the quest for selective PI3Kα inhibitors through the process of hit-to-lead optimization. Communicated by Ramaswamy H. Sarma

In Silico Activity Prediction and Docking Studies of the Binding Mechanisms of Levofloxacin Structure Derivatives to Active Receptor Sites of Bacterial Type IIA Topoisomerases

The need for new antimicrobial agents (AntAg) is driven by the persistent antibiotic resistance in microorganisms, as well as the increasing frequency of pandemics. Due to the deficiency of AntAg, research aimed at developing speedy approaches to find new drug candidates is relevant. This study aims to conduct an in silico study of the biological activity spectrum as well as the molecular binding mechanisms of four structurally different forms of levofloxacin (Lvf) with bacterial topoisomerases targets of type IIA (DNA gyrase and topoisomerase IV) to enable the development of drugs with an improved characterization of the safety profile. To achieve this goal, a number of software products were used, such as ChemicPen v. 2.6, PyMol 2.5, Avogadro 1.2.0, PASS, AutoDockTools 1.5.7 with the new generation software Autodock Vina. These software products are the first to be made available for visualization of clusters with determination of ligand-receptor pair binding affinity, as well as clustering coordinates and proposed mechanisms of action. One of the real structures of Lvf, a decarboxylated derivative, was obtained with tribochemical (TrbCh) exposure. The action spectrum of molecular ligands is described based on a Bayesian probability activity prediction model (PASS software Version 2.0). Predicted and real (PMS and RMS) molecular structures of Lvf, with decreasing levels of structural complexity, were translated into descriptors via Wiener (W), Balaban (Vs), Detour (Ip), and Electropy € indices. The 2D «structure-activity» diagrams were used to differentiate closely related structures of levofloxacin. PMS and RMS were visualized as 3D models of the ligand-receptor complexes. The contact regions of RMS and PMS with key amino acid residues—SER-79, DT-15, DG-1, DA-1—were demonstrated. The intra- and inter-molecular binding sites, data on free energy (affinity values, kcal/mol), the binding constant Kb (M−1), and the number of clusters are presented. The research results obtained from the presented in silico approach to explore the spectrum of action find quantitative “structure-activity” correlations, and predict molecular mechanisms may be of applied interest for directed drug discovery.

Expanding Training Data for Structure-Based Receptor-Ligand Binding Affinity Regression through Imputation of Missing Labels.

The success of machine learning is, in part, due to a large volume of data available to train models. However, the amount of training data for structure-based molecular property prediction remains limited. The previously described CrossDocked2020 data set expanded the available training data for binding pose classification in a molecular docking setting but did not address expanding the amount of receptor-ligand binding affinity data. We present experiments demonstrating that imputing binding affinity labels for complexes without experimentally determined binding affinities is a viable approach to expanding training data for structure-based models of receptor-ligand binding affinity. In particular, we demonstrate that utilizing imputed labels from a convolutional neural network trained only on the affinity data present in CrossDocked2020 results in a small improvement in the binding affinity regression performance, despite the additional sources of noise that such imputed labels add to the training data. The code, data splits, and imputation labels utilized in this paper are freely available at https://github.com/francoep/ImputationPaper.

Polyphenolics of purple devil fruits potentiate anti-inflammatory action by regulating the expression of inflammatory cytokines and apoptotic signaling molecules evident in extensive and combined experimental models

This research investigated the anti-inflammatory effects of Purple Devil fruit’s chloroform extract (SAF-CFE) using LPS-stimulated RAW264.7 macrophage cells and in-vivo histamine- and carrageenan-induced paw edema models as well as membrane stabilization model. Writhing and licking tests for nociception and delayed-type hypersensitivity reaction (DTHR) for immunomodulation were accomplished. SwissADME, ProTox-II, and PASS tests assessed a ligand-receptor binding affinity, and network-pharmacological tests explored the modulatory linked-genes. The MCF-7 cells were strongly inhibited by SAF-CFE, which reduced LPS-induced PGE2, IL-6, TNF-α, and IL-1β expression. The upregulation of proapoptotic (p53 and Bax) and downregulation of antiapoptotic (Bcl-2) genes were observed by SAF-CFE. It significantly reduced inflammatory indexes in anti-inflammatory models. Tris (2,4-di-tert-butylphenyl) phosphate, a natural biometabolite from SAF-CFE, had the highest target receptor-binding and drug-likeness; while NOS2, PTGER1, TRPV1, HMGCR, and TBXAS1 hub genes were highly modulated by the SAF-CFE. The results demonstrate that SAF-CFE could be a functional food source for anti-inflammatory action.

Targeting NMDA receptor in Alzheimer's disease: identifying novel inhibitors using computational approaches.

The glutamate-gated ion channels known as N-methyl-d-aspartate receptors (NMDARs) are important for both normal and pathological brain function. Subunit-selective antagonists have high therapeutic promise since many pathological conditions involve NMDAR over activation, although few clinical successes have been reported. Allosteric inhibitors of GluN2B-containing receptors are among the most potential NMDAR targeting drugs. Since the discovery of ifenprodil, a variety of GluN2B-selective compounds have been discovered, each with remarkably unique structural motifs. These results expand the allosteric and pharmacolog-ical spectrum of NMDARs and provide a new structural basis for the development of next-generation GluN2B antagonists that have therapeutic potential in brain diseases. Small molecule therapeutic inhibitors targeting NMDA have recently been developed to target CNS disorders such as Alzheimer's disease. In the current study, a cheminformatics method was used to discover potential antagonists and to identify the structural requirements for Gly/NMDA antagonism. In this case we have created a useful pharmacophore model with solid statistical values. Through pharmacophore mapping, the verified model was used to filter out virtual matches from the ZINC database. Assessing receptor-ligand binding mechanisms and affinities used molecular docking. To find the best hits, the GlideScore and the interaction of molecules with important amino acids were considered essential features. We found some molecular inhibitors, namely, ZINC13729211, ZINC07430424, ZINC08614951, ZINC60927204, ZINC12447511, and ZINC18889258 with high binding affinity using computational methods. The molecules in our studies showed characteristics such as good stability, hydrogen bonding and higher binding affinities in the solvation-based assessment method than ifenprodil with acceptable ADMET profile. Moreover, these six leads have been proposed as potential new perspectives for exploring potent Gly/NMDA receptor antagonists. In addition, it can be tested in the laboratory for potential therapeutic strategies for both in vitro and in vivo research.

Selective α3β4 Nicotinic Acetylcholine Receptor Ligand as a Potential Tracer for Drug Addiction.

α3β4 Nicotinic acetylcholine receptor (nAChR) has been recognized as an emerging biomarker for the early detection of drug addiction. Herein, α3β4 nAChR ligands were designed and synthesized to improve the binding affinity and selectivity of two lead compounds, (S)-QND8 and (S)-T2, for the development of an α3β4 nAChR tracer. The structural modification was achieved by retaining the key features and expanding the molecular structure with a benzyloxy group to increase the lipophilicity for blood-brain barrier penetration and to extend the ligand-receptor interaction. The preserved key features are a fluorine atom for radiotracer development and a p-hydroxyl motif for ligand-receptor binding affinity. Four (R)- and (S)-quinuclidine-triazole (AK1-AK4) were synthesized and the binding affinity, together with selectivity to α3β4 nAChR subtype, were determined by competitive radioligand binding assay using [3H]epibatidine as a radioligand. Among all modified compounds, AK3 showed the highest binding affinity and selectivity to α3β4 nAChR with a Ki value of 3.18 nM, comparable to (S)-QND8 and (S)-T2 and 3069-fold higher affinity to α3β4 nAChR in comparison to α7 nAChR. The α3β4 nAChR selectivity of AK3 was considerably higher than those of (S)-QND8 (11.8-fold) and (S)-T2 (294-fold). AK3 was shown to be a promising α3β4 nAChR tracer for further development as a radiotracer for drug addiction.

Mechanistic investigation into selective cytotoxic activities of gold nanoparticles functionalized with epidermal growth factor variants.

Epidermal growth factor (EGF) gains unique selective cytotoxicity against cancer cells upon conjugation with gold nanoparticles (GNPs). We have previously developed several lysine-free EGF mutants for favorable interactions between the nanoparticle conjugates with EGF receptor (EGFR) and found one mutant (SR: K28S/K48R) showing stronger anticancer activities. However, the exact mechanisms for the selective cytotoxicity enhancement in the SR mutant remained unsolved. In this study, we analyzed how the nanoparticle conjugates of EGF variants interacted differently with A431 cancer cells, in terms of receptor binding, activation, and trafficking. Our results indicate that the essential feature of the SR-GNP conjugates in the cytotoxicity enhancement is their preferential activation of the clathrin-independent endocytosis pathway. It is suggested that we should focus on not only ligand-receptor binding affinity but also the selectivity of the receptor endocytic route to optimize the anticancer effects in this modality.

CADMA-Chem: A Computational Protocol Based on Chemical Properties Aimed to Design Multifunctional Antioxidants.

A computational protocol aimed to design new antioxidants with versatile behavior is presented. It is called Computer-Assisted Design of Multifunctional Antioxidants and is based on chemical properties (CADMA-Chem). The desired multi-functionality consists of in different methods of antioxidant protection combined with neuroprotection, although the protocol can also be used to pursue other health benefits. The dM38 melatonin derivative is used as a study case to illustrate the protocol in detail. This was found to be a highly promising candidate for the treatment of neurodegeneration, in particular Parkinson's and Alzheimer's diseases. This also has the desired properties of an oral-drug, which is significantly better than Trolox for scavenging free radicals, and has chelates redox metals, prevents the ●OH production, via Fenton-like reactions, repairs oxidative damage in biomolecules (lipids, proteins, and DNA), and acts as a polygenic neuroprotector by inhibiting catechol-O-methyl transferase (COMT), acetylcholinesterase (AChE) and monoamine oxidase B (MAOB). To the best of our best knowledge, CADMA-Chem is currently the only protocol that simultaneously involves the analyses of drug-like behavior, toxicity, manufacturability, versatile antioxidant protection, and receptor-ligand binding affinities. It is expected to provide a starting point that helps to accelerate the discovery of oral drugs with the potential to prevent, or slow down, multifactorial human health disorders.

Insightful Valorization of Biological Activities of Flax Seed (Linum usitatissimum) through Experimental and Computer Aided Mechanisms

Flax also known as common flax or linseed, is a flowering plant, Linum usitatissimum, in the family Linaceae. The current study used haloperidol-induced catalepsy and reserpine antagonism to investigate in vivo anti- Parkinson's activity and in silico approaches like docking studies (schrodinger software), Ramchandran plot (procheck), ADME and biological activity score using (molinspiration) online software. The n-hexane extract of Linum usitatissinum (HELU) (flax seeds) exhibited various phytochemical constituents like carbohydrates, lignans, alkaloids, phenolic compounds, flavonoids, fatty acids, coumarin derivatives and sterols. Pharmacological tests were studied at 200 mg/kg bd.wt and 400 mg/kg bd.wt, using in vivo behavioural effects like muscular rigidity, tremors, akinesia, grip strength, and locomotory activity. The experiment was designed by giving haloperidol to induce catalepsy and Reserpne to induce Parkinson’s disease-like symptoms. The increased cataleptic scores were significantly decreased by HELU (200 and 400 mg/kg bd.wt., p.o.) in reserpine antagonism model. Docking studies for natural chemicals against PDB ID: 4I6B, 7JOZ, 4XUD, 4OYX were conducted to better understand the ligand-binding affinity of the extract's active ingredients. The results revealed that D-xylose, D-arabinose, L-rhamnose, L-fucose, hesperidin, herbacetin, β-carboline, isoquinoline, ferulic acid, eicosapentanoic acid, docosahexaenoic acid, beta sitosterol, niacin, aesculetin and standard drug levodopa, carbidopa had shown highest glide scores with all the selected proteins which indicate a stronger receptor-ligand binding affinity. Our findings revealed that Linum usitatissimum n-hexane extract has strong anti Parkinson's action.

Molecular and cellular factors determining the functional pleiotropy of cytokines.

Cytokines are soluble factors vital for mammalian physiology. Cytokines elicit highly pleiotropic activities, characterized by their ability to induce a wide spectrum of functional responses in a diverse range of cell subsets, which makes their study very challenging. Cytokines activate signalling via receptor dimerization/oligomerization, triggering activation of the JAK (Janus kinase)/STAT (signal transducer and activator of transcription) signalling pathway. Given the strong crosstalk and shared usage of key components of cytokine signalling pathways, a long-standing question in the field pertains to how functional diversity is achieved by cytokines. Here, we discuss how biophysical - for example, ligand-receptor binding affinity and topology - and cellular - for example, receptor, JAK and STAT protein levels, endosomal compartment - parameters contribute to the modulation and diversification of cytokine responses. We review how these parameters ultimately converge into a common mechanism to fine-tune cytokine signalling that involves the control of the number of Tyr residues phosphorylated in the receptor intracellular domain upon cytokine stimulation. This results in different kinetics of STAT activation, and induction of specific gene expression programs, ensuring the generation of functional diversity by cytokines using a limited set of signalling intermediaries. We describe how these first principles of cytokine signalling have been exploited using protein engineering to design cytokine variants with more specific and less toxic responses for immunotherapy.

Anti-ulcer Activity of Ethanolic Extract of Alstonia scholaris Bark: An in vivo and in silico Approach

Aims: The present research is focused on screening in vivo anti-ulcer activity using pylorus ligation and ethanol induced ulcer model. &#x0D; Study Design: Fourty eight rats, randomly divided into eight groups, were used in this study. Bark of Alstonia scholaris were air-dried, ground into fine powder and used in the preparation of an ethanolic extract.&#x0D; Place and Duration of Study: Department of Pharmacology, Osmania University, Hyderabad between December 2020 and September 2021.&#x0D; Methodology: Ethanol related ulcer was induced using 1 mL/kg b.w, p.o. Treated rats received ethanolic extract of Alstonia scholaris at various doses of 200 and 400 mg/kg b.w. Ulcer index, % ulcer protection were calculated and histological studies were conducted at 6 hr after pylorous ligation respectively.&#x0D; Results: Pharmacological estimations were done by means of 200 mg/kg, b.w. and 400 mg/kg, b.w. The total acidity and free acidity were decreased, pH was increased and ulcer index was decreased by Ethanolic extract of Alstonia scholaris (EEAS 200 and 400 mg/kg b.w., p.o.) in pylorus ligation model. Treatment with EEAS (200 and 400 mg/kg b.w. p.o.) has significantly decreased the ulcer index by ethanol induced ulcer model. To appreciate the ligand-binding attraction of the dynamic ingredients of the excerpt, docking trainings were accomplished for natural compounds against protein data bank (PDB) ID: 5A5N, PDB ID: 6Q2T, PDB ID: 7MBX, PDB ID: 2FV5. The results revealed that vanillic acid, venoterpine, loganetin, dibutyl phthalate, guaia-3,9- diene, 3,6-Bis[2-methylphenyl]-2,5-dihydropyrrolo[3,4-c] pyrrole-1,4- dione, 2H-1-Benzopyran- 2-one,7-acetyl-8-[acetyloxy]-4, n-hexadecanoic acid, stigmasterol, diospyrolide, D- Friedoolean-14-en-3-one, betulin, lupeol acetate, pentanoic acid and standard drug omeprazole had shown highest glide scores with all the selected proteins which indicate a stronger receptor-ligand binding affinity.&#x0D; Conclusion: From in vivo and in silico results it is evident that ethanolic bark extract of Alstonia scholaris possessed significant anti-ulcer activity.

Novel In Silico and In Vivo Insights of Flavonoids as Anti-Diabetic and Anti-Oxidant in Rodent Models

Insulin sensitivity is a symptom of diabetes, which is caused by insulin resistance, decreasing insulin production and ultimately pancreatic cancer. The current study is focused on the anti-diabetic and antioxidant properties of Chrysanthemum indicum flower extract and to scientifically validate the claim by in silico docking studies of natural compounds present in the extract for their respective sites against selected proteins. Pharmacological evaluations were done using 200 and 400 mg/kg body weight of the extract. Upon treatment with methanolic extract of Chrysanthemum indicum at 200 mg/kg body weight, 400 mg/kg body weight and glibenclamide 0.5 mg/kg body weight, significant reduction in blood glucose levels was observed. The extract was screened against reducing power assay and hydrogen peroxide scavenging assay for its anti-oxidant potential and the results were compared with the standard ascorbic acid. In both assays, the findings clearly demonstrated the extract's ability to scavenge free radicals. Docking studies were performed for natural compounds present in the extract such as epigallactocatechin, quercetin, kaempferol, apigenin, myrcetin, rutin, luteolin and standard drug glibenclamide against protein data bank ID: 1VA5, protein data bank ID: 1Z2C, protein data bank ID: 5WUA using Mcule software. The statistical verification of the model was evaluated with PROCHEK; a structure verification program relies on Ramachandran plot which determines the quality of the predicted structures. The results revealed that epigallactocatechin and rutin had shown highest glide scores which indicates a stronger receptor-ligand binding affinity among the various phytochemical constituents present in the extract and this might be the possible mechanism by which the extract showed antidiabetic and antioxidant activities. From the above it is concluded that the extract possess anti-diabetic and anti-oxidant activity.

Attenuation of ongoing neuropathic pain by peripheral acting opioid involves activation of central dopaminergic neurocircuitry

Background and purposeOngoing neuropathic pain is one of the most challenging clinical problems which have detrimental effects on a patient’s life quality. Conventional therapies for chronic neuropathic pain majorly includes centrally acting analgesics. Unfortunately, the unceasing use of these drugs results in adverse effects, such as CNS in-coordination, respiratory depression and substance use disorder. DALDA ([D-Arg2, Lys4]-Dermorphin-(1–4)-amide), a peripherally acting opioid have been shown to possess potent analgesic activity without causing CNS toxicities in nerve-injured rats. However, the mechanism(s) underpinning DALDA induced-attenuation of ongoing neuropathic pain is yet to identify [1]. Experimental designIn this study, we have measured the in–silico ligand-receptor binding affinity of DALDA against potential inflammatory targets by utilizing glide module of schrödinger software. Effect of DALDA on oxido-inflammatory stress was evaluated in LPS-induced C6 glial cells. In-vitro studies were followed by the behavioral assessments, where effect of DALDA was measured in chronic constriction injured rats. To examine the effect of DALDA on dopaminergic neurotransmission, cerebrospinal fluid of nerve-injured rats was assessed using LC-MS/QToF (Liquid Chromatography-Mass spectrometry/ Quadrapole time of flight Analyzer). ResultsDALDA has shown a good binding affinity with chemokine receptor type-2 (CCR2), chemokine CX3C receptor 1 (CX3CR1) and purinergic receptor (P2×4), major receptor subtypes involved in pain and inflammation. Findings from the in-vitro studies suggest that DALDA possesses potent anti-oxidant activity leading to inhibition of p38-MAPK pathway [1]. Moreover, the subcutaneous administration of DALDA leads to dose-dependent attenuation of thermal and mechanical hypersensitivity along with inhibition of neuroinflammatory mediators in serum and spinal cord of nerve-injured rats. Most importantly, DALDA treated neuropathic rats showed a preference for the DALDA-treated chamber, which was attenuated on pre-treatment with dopaminergic receptor antagonist, flupenthixol. LC-MS analysis further confirms the enhanced dopaminergic transmission in the brain of DALDA-treated neuropathic rats. ConclusionOur findings suggest that DALDA mediated attenuation of ongoing neuropathic pain may be associated with a decrease in spinal neuroinflammatory signalling and subsequent increase in the brain dopamine level; may serve a potential therapeutic for the treatment of ongoing neuropathic pain.

Response Surface Study on Molecular Docking Simulations of Citalopram and Donepezil as Potent CNS Drugs.

Computer-aided drug design provides broad structural modifications to evolving bioactive molecules without an immediate requirement to observe synthetic restraints or tedious protocols. Subsequently, the most promising guidelines with regard to synthetic and biological resources may be focused on upcoming steps. Molecular docking is common in-silico drug design techniques since it predicts ligand-receptor interaction modes and associated binding affinities. Current docking simulations suffer serious constraints in estimating accurate ligand-receptor binding affinities despite several advantages and historical results. Response surface method (RSM) is an efficient statistical approach for modeling and optimization of various pharmaceutical systems. With the aim of unveiling the full potential of RSM in optimizing molecular docking simulations, this study particularly focused on binding affinity prediction of citalopram-serotonin transporter (SERT) and donepezil-acetyl cholinesterase (AChE) complexes. For this purpose, Box-Behnken design of experiments (DOE) was used to develop a trial matrix for simultaneous variations of AutoDock4.2 driven binding affinity data with selected factor levels. Responses of all docking trials were considered as estimated protein inhibition constants with regard to validated data for each drug. The output matrix was subjected to statistical analysis and constructing polynomial quadratic models. Numerical optimization steps to attain ideal docking accuracies revealed that more accurate results might be envisaged through the best combination of factor levels and considering factor interactions. Results of the current study indicated that the application of RSM in molecular docking simulations might lead to optimized docking protocols with more stable estimates of ligand-target interactions and hence better correlation of in-silico in-vitro data.

Fungicidal activity and molecular modeling of fusarubin analogues from Fusarium oxysporum

Fusarubin analogues of Fusarium oxysporum f. sp. ciceris were investigated for antifungal activity in vitro against five soil borne phytopathogenic fungi. 3-O-Methyl-8-O-methyl-fusarubin was inhibitory towards S. sclerotiorum (EC50 0.33 mmol L−1) and Sclerotium rolfsii (EC50 0.38 mmol L−1). A structure–antifungal activity relationship of fusarubin analogues was established from their activity performance. Possible mechanism of action of these compounds was studied using molecular docking and simulations against three target enzymes which revealed receptor ligand binding affinity. Docking of 3-O-methyl-8-O-methyl-fusarubin into the succinate dehydrogenase site revealed formation of salt bridge, hydrogen bond, π–anion, π–alkyl, and Van der Waals interactions.

Insight of druggable cannabinoids against estrogen receptor β in breast cancer

Breast cancer (BC) is the second most prevalent cancer worldwide. Estrogen receptor beta (ERβ) is an essential protein of breast cells to suppress estrogen-induced uncontrolled proliferation. Thus, small molecules that can modulate and enhance ERβ expression would be an effective agent to suppress BC development. Studies showed that cannabinoid (CB), specifically delta-9-tetrahydrocannabinol (Del9THC), can increase the expression of ERβ and inhibits BC cell proliferation. In this study, less psychoactive and structurally similar analogs of Del9THC were chosen as drug candidates and ERβ was targeted as a therapeutic receptor. Delta-8-tetrahydrocannabinol (Del8THC) and delta-4-isotetrahydrocannabinol (Del4isoTHC) were the drug candidates selected on the basis of literature reports, absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties, medicinal chemistry profile, and physicochemical features. Molecular docking simulations were carried out to determine ligand receptor interactions and binding affinity based on free binding energy. To get a better drug, the structural modification was done on Del8THC and generated a new CB analog called Cannabinoid A. Finally, molecular interaction analysis revealed that two CBs and one of their analog interact with the active site residues of ERβ. Therefore, this study revealed a new way to discover novel drug(s) for BC patients. Communicated by Ramaswamy H. Sarma