Discovery of potentially biased agonists of mu-opioid receptor (MOR) through molecular docking, pharmacophore modeling, and MD simulation

Synergistic suppression of cell growth: Phenmiazine derivatives targeting p53 and MDM2 unveiled through hybrid computational method

Lung cancer is the leading cause of mortality in both men and women due to genetic and epigenetic modifications. Our study focuses on fabricating phenmiazine ring leads by a functional group-based drug design to inhibit p53 -7A1W and MDM2-7AU9 proteins responsible for cancer cell growth. One hundred molecules are designed and allowed to bind inside the active site of 7A1W and 7AU9 protein using a glide dock platform and subjected to find MMGBSA. The stability and interaction were confirmed by MD simulation analysis at 100 ns and DFTB chemical stability study. The result gave the best binding energy of -8.16 kcal/mol for aminobenzoic acid substituted molecule and the MD simulation head map illustrates that majorly 9 amino acids form hydrophobic and h-bond interactions. DFTB analysis reveals the energy gaps of 0.0508 signifying stability and lower chemical reactivity of the Phenmiazine ring derivatives. These findings conclude that the Phenmiazine ring derivative will be a better lead molecule to eradicate lung cancer.

Investigating the toxicity of malachite green and copper sulfate in brine shrimp: In-vivo and computational study

Colour is crucial for enhancing the appetizing value and consumer acceptance of food products. The commonly used food colourants and food preservatives such as Malachite Green (MG) and Copper Sulfate (CS) can cause severe health problems. This study investigates the toxicity of these food-grade colourants through acute exposure using in vivo cytotoxicity using the brine shrimp model including 3D surface analysis (3DSA) and in-silico studies Brine shrimp were treated with various concentrations of MG and CS. The cytotoxic effect was confirmed by brine shrimp lethality assay and 3DSA. Molecular docking and Molecular Dynamic simulation were done using hAChE binding cavity. Results showed that concentrations (2.5-10 µg/ml) of MG and CS significantly decreased locomotor behaviour within 1 h, while higher concentrations (10-100 µg/ml) caused high mortality rates. Morphological studies revealed that there is a significant reduction (p<0.05) in shrimp length treated with MG and CS. The 3DSA indicates that there is an inappropriate surface of the shrimp morphology. Interestingly, MG-treated shrimps had shown significant inhibition of AChE in homogenates, indicating cholinergic nerve-mediated toxicity. Computational studies showed MG confined active binding with human acetylcholinesterase (hAChE), with a binding energy MMGBSA of -51.3 kcal/mol. MD simulation confirmed reversible binding stability inside the hAChE pocket. It can be concluded that acute exposure to brine shrimps with MG and CS exhibited cytotoxicity as evidenced by the increase in mortality of the shrimps. This study further warrants the investigation of MG and CS residues from commonly used fruits and vegetables and their putative toxic effect using in-vivo studies.

Assessing the structural and foaming property changes in egg yolk proteins due to malondialdehyde: Experimental and molecular docking studies

This study evaluated the effects of varying levels of malondialdehyde (MDA) on the structural and foaming properties of the egg yolk proteins (EYPs), and the interaction between them was explored by molecular docking. The results showed that oxidative modification due to MDA increased the carbonyl content of EYPs by 4.49 times. Simultaneously, the total sulfhydryl content was reduced by 21.47%, and the solubility of EYPs was significantly decreased (p < 0.05). Continuous oxidation disorders the previously ordered structure of EYPs. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis indicated that some proteins underwent crosslinking and aggregation with increased MDA oxidation, aligning with changes in particle size and zeta-potential. Moderate oxidation (<1 mmol/L) enhanced the foaming capacity and foam stability of EYPs. Additionally, molecular docking results uncovered favorable interactions between MDA and specific EYPs, primarily through hydrogen bonding. This research offers valuable insights into managing the functional and quality changes of yolk products during processing.

Functional differences in the mu opioid receptor SNP 118A>G are dependent on receptor splice-variant and agonist-specific recruitment of β-arrestin

The OPRM1 gene codes for the mu opioid receptor (MOR) and polymorphisms are associated with complex patient clinical responses. The most studied single nucleotide polymorphism (SNP) in OPRM1 is adenine (A) substituted by guanine (G) at position 118 (118A>G, rs1799971) leading to a substitution of asparagine (Asn) for aspartic acid (Asp) at position 40 in the N terminus of the resulting protein. To date, no structural explanation for the associated clinical responses resulting from the 118A>G polymorphism has been proposed. We utilized computational modeling paired with functional cellular assays to predict unstructured N- and C-terminal regions of MOR-1. Using molecular docking and post-docking energy minimizations with morphine, we show that the extracellular substitution of Asn at position 40 alters the cytoplasmic C-terminal conformation, while leaving the G-protein binding interface unaffected. A real-time BRET assay measuring G-protein and β-arrestin association with MOR r generated data that tested this prediction. Consistent with this in silico prediction, we show changes in morphine-mediated β-arrestin association with receptor variants with little change in morphine-mediated G-protein association comparing MOR-1 wild type (WT) to MOR-1118A>G. We tested the system with different opioid agonists, the OPRM1 118A>G SNP, and different MOR splice variants (MOR-1 and MOR-1O). These results are consistent with the observation that patients with the 118A>G OPRM1 allele respond more readily to fentanyl than to morphine. In conclusion, the 118A>G substitution alters receptor responses to opioids through variable C-terminal domain movements that are agonist and splice variant dependent.

Relevance of G protein-coupled receptor (GPCR) dynamics for receptor activation, signalling bias and allosteric modulation

G protein-coupled receptors (GPCRs) are one of the major drug targets. In recent years, computational drug design for GPCRs has mainly focused on static structures obtained through X-ray crystallography, cryogenic electron microscopy (cryo-EM) or in silico modelling as a starting point for virtual screening campaigns. However, GPCRs are highly flexible entities with the ability to adopt different conformational states that elicit different physiological responses. Including this knowledge in the drug discovery pipeline can help to tailor novel conformation-specific drugs with an improved therapeutic profile. In this review, we outline our current knowledge about GPCR dynamics that is relevant for receptor activation, signalling bias and allosteric modulation. Ultimately, we highlight new technological implementations such as time-resolved X-ray crystallography and cryo-EM as well as computational algorithms that can contribute to a more comprehensive understanding of receptor dynamics and its relevance for GPCR functionality.

Discovery of druggable potent inhibitors of serine proteases and farnesoid X receptor by ligand-based virtual screening to obstruct SARS-CoV-2

The coronavirus, a subfamily of the coronavirinae family, is an RNA virus with over 40 variations that can infect humans, non-human mammals and birds. There are seven types of human coronaviruses, including SARS-CoV-2, is responsible for the recent COVID-19 pandemic. The current study is focused on the identification of drug molecules for the treatment of COVID-19 by targeting human proteases like transmembrane serine protease 2 (TMPRSS2), furin, cathepsin B, and a nuclear receptor named farnesoid X receptor (FXR). TMPRSS2 and furin help in cleaving the spike protein of the SARS-CoV-2 virus, while cathepsin B plays a critical role in the entry and pathogenesis. FXR, on the other hand, regulates the expression of ACE2, and its inhibition can reduce SARS-CoV-2 infection. By inhibiting these four protein targets with non-toxic inhibitors, the entry of the infectious agent into host cells and its pathogenesis can be obstructed. We have used the BioSolveIT suite for pharmacophore-based computational drug designing. A total of 1611 ligands from the ligand library were docked with the target proteins to obtain potent inhibitors on the basis of pharmacophore. Following the ADMET analysis and protein ligand interactions, potent and druggable inhibitors of the target proteins were obtained. Additionally, toxic substructures and the less toxic route of administration of the most potent inhibitors in rodents were also determined computationally. Compounds namely N-(diaminomethylene)-2-((3-((1R,3R)-3-(2-(methoxy(methyl)amino)-2-oxoethyl)cyclopentyl)propyl)amino)-2-oxoethan-1-aminium (26), (1R,3R)-3-(((2-ammonioethyl)ammonio)methyl)-1-((4-propyl-1H-imidazol-2-yl)methyl)piperidin-1-ium (29) and (1R,3R)-3-(((2-ammonioethyl)ammonio)methyl)-1-((1-propyl-1H-pyrazol-4-yl)methyl)piperidin-1-ium (30) were found as the potent inhibitors of TMPRSS2, whereas, 1-(1-(1-(1H-tetrazol-1-yl)cyclopropane-1‑carbonyl)piperidin-4-yl)azepan-2-one (6), (2R)-4-methyl-1-oxo-1-((7R,11S)-4-oxo-6,7,8,9,10,11-hexahydro-4H-7,11-methanopyrido[1,2-a]azocin-9-yl)pentan-2-aminium (12), 4-((1-(3-(3,5-dimethylisoxazol-4-yl)propanoyl)piperidin-4-yl)methyl)morpholin-4-ium (13), 1-(4,6-dimethylpyrimidin-2-yl)-N-(3-oxocyclohex-1-en-1-yl)piperidine-4-carboxamide (14), 1-(4-(1,5-dimethyl-1H-1,2,4-triazol-3-yl)piperidin-1-yl)-3-(3,5-dimethylisoxazol-4-yl)propan-1-one (25) and N,N-dimethyl-4-oxo-4-((1S,5R)-8-oxo-5,6-dihydro-1H-1,5-methanopyrido[1,2-a][1,5]diazocin-3(2H,4H,8H)-yl)butanamide (31) inhibited the FXR preferentially. In case of cathepsin B, N-((5-benzoylthiophen-2-yl)methyl)-2-hydrazineyl-2-oxoacetamide (2) and N-([2,2'-bifuran]-5-ylmethyl)-2-hydrazineyl-2-oxoacetamide (7) were identified as the most druggable inhibitors whereas 1-amino-2,7-diethyl-3,8-dioxo-6-(p-tolyl)-2,3,7,8-tetrahydro-2,7-naphthyridine-4‑carbonitrile (5) and (R)-6-amino-2-(2,3-dihydroxypropyl)-1H-benzo[de]isoquinoline-1,3(2H)-dione (20) were active against furin.

Identification of Potent Inhibitors Targeting EGFR and HER3 for Effective Treatment of Chemoresistance in Non-Small Cell Lung Cancer

Non-small cell lung cancer (NSCLC) is the most common form of lung cancer. Despite the existence of various therapeutic options, NSCLC is still a major health concern due to its aggressive nature and high mutation rate. Consequently, HER3 has been selected as a target protein along with EGFR because of its limited tyrosine kinase activity and ability to activate PI3/AKT pathway responsible for therapy failure. We herein used a BioSolveIT suite to identify potent inhibitors of EGFR and HER3. The schematic process involves screening of databases for constructing compound library comprising of 903 synthetic compounds (602 for EGFR and 301 for HER3) followed by pharmacophore modeling. The best docked poses of compounds with the druggable binding site of respective proteins were selected according to pharmacophore designed by SeeSAR version 12.1.0. Subsequently, preclinical analysis was performed via an online server SwissADME and potent inhibitors were selected. Compound 4k and 4m were the most potent inhibitors of EGFR while 7x effectively inhibited the binding site of HER3. The binding energies of 4k, 4m, and 7x were -7.7, -6.3 and -5.7 kcal/mol, respectively. Collectively, 4k, 4m and 7x showed favorable interactions with the most druggable binding sites of their respective proteins. Finally, in silico pre-clinical testing by SwissADME validated the non-toxic nature of compounds 4k, 4m and 7x providing a promising treatment option for chemoresistant NSCLC.

Profiling the Structural determinants of pyrrolidine derivative as gelatinases (MMP-2 and MMP-9) inhibitors using in silico approaches

Quantitative structure activity relationship (QSAR) studies on pyrrolidine derivatives have been established using CoMFA, CoMSIA, and Hologram QSAR analysis to estimate the values (pIC₅₀) of gelatinase inhibitors. When the CoMFA cross-validation value, Q², was 0.625, the training set coefficient of determination, R² was 0.981. In CoMSIA, Q² was 0.749 and R² was 0.988. In the HQSAR, Q² was 0.84 and R² was 0.946. Visualization of these models was performed by contour maps showing favorable and unfavorable regions for activity, while visualization of HQSAR model was performed by a colored atomic contribution graph. Based on the results obtained of external validation, the CoMSIA model was statistically more significant and robust and was selected as the best model to predict new, more active inhibitors. To study the modes of interactions of the predicted compounds in the active site of MMP-2 and MMP-9, a simulation of molecular docking was realized. A combined study of MD simulations and calculation of free binding energy, were also carried out to validate the results obtained on the best predicted and most active compound in dataset and the compound NNGH as control compound. The results confirm the molecular docking results and indicate that the predicted ligands were stable in the binding site of MMP-2 and MMP-9.

Biological Membrane-Penetrating Peptides: Computational Prediction and Applications

Peptides comprise a versatile class of biomolecules that present a unique chemical space with diverse physicochemical and structural properties. Some classes of peptides are able to naturally cross the biological membranes, such as cell membrane and blood-brain barrier (BBB). Cell-penetrating peptides (CPPs) and blood-brain barrier-penetrating peptides (B3PPs) have been explored by the biotechnological and pharmaceutical industries to develop new therapeutic molecules and carrier systems. The computational prediction of peptides’ penetration into biological membranes has been emerged as an interesting strategy due to their high throughput and low-cost screening of large chemical libraries. Structure- and sequence-based information of peptides, as well as atomistic biophysical models, have been explored in computer-assisted discovery strategies to classify and identify new structures with pharmacokinetic properties related to the translocation through biomembranes. Computational strategies to predict the permeability into biomembranes include cheminformatic filters, molecular dynamics simulations, artificial intelligence algorithms, and statistical models, and the choice of the most adequate method depends on the purposes of the computational investigation. Here, we exhibit and discuss some principles and applications of these computational methods widely used to predict the permeability of peptides into biomembranes, exhibiting some of their pharmaceutical and biotechnological applications.

Gonçalves Vianez JL, Santana da Costa K, de Molfetta FA, Nahum Alves C. Analysis of Kojic Acid Derivatives as Competitive Inhibitors of Tyrosinase: A Molecular Modeling Approach

Tyrosinases belong to the functional copper-containing proteins family, and their structure contains two copper atoms, in the active site, which are coordinated by three histidine residues. The biosynthesis of melanin in melanocytes has two stages depending on the actions of the natural substrates L-DOPA and L-tyrosine. The dysregulation of tyrosinase is involved in skin cancer initiation. In the present study, using molecular modeling tools, we analyzed the inhibition activity of tyrosinase activity using kojic acid (KA) derivatives designed from aromatic aldehydes and malononitrile. All derivatives showed conformational affinity to the enzyme active site, and a favorable distance to chelate the copper ion, which is essential for enzyme function. Molecular dynamics simulations revealed that the derivatives formed promising complexes, presenting stable conformations with deviations between 0.2 and 0.35 Å. In addition, the investigated KA derivatives showed favorable binding free energies. The most stable KA derivatives showed the following binding free energies: -17.65 kcal mol-1 (D6), -18.07 kcal mol-1 (D2), -18.13 (D5) kcal mol-1, and -10.31 kcal mol-1 (D4). Our results suggest that these derivatives could be potent competitive inhibitors of the natural substrates of L-DOPA (-12.84 kcal mol-1) and L-tyrosine (-9.04 kcal mol-1) in melanogenesis.