In silico structure prediction, molecular docking and dynamic simulation studies on G Protein-Coupled Receptor 116: a novel insight into breast cancer therapy

In-silico screening of missense nsSNPs in Delta-opioid receptor protein and their restoring tendency on MCRT interaction; focusing on dynamic nature

Delta-opioid receptor protein (OPRD1) is one of the potential targets for treating pain. The presently available opioid agonists are known to cause unnecessary side effects. To discover a novel opioid agonist, our research group has synthesized a chimeric peptide MCRT and proved its potential activity through in vivo analysis. Non-synonymous SNPs (nsSNPs) missense mutations affect the functionality and stability of proteins leading to diseases. The current research was focused on understanding the role of MCRT in restoring the binding tendency of OPRD1 nsSNPs missense mutations on dynamic nature in comparison with Deltorphin-II and morphiceptin. The deleterious effects of nsSNPs were analyzed using various bioinformatics tools for predicting structural, functional, and oncogenic influence. The shortlisted nine nsSNPs were predicted for allergic reactions, domain changes, post-translation modification, multiple sequence alignment, secondary structure, molecular dynamic simulation (MDS), and peptide docking influence. Further, the docked complex of three shortlisted deleterious nsSNPs was analyzed using an MDS study, and the highly deleterious shortlisted nsSNP A149T was further analyzed for higher trajectory analysis. MCRT restored the binding tendency influence caused by nsSNPs on the dynamics of stability, functionality, binding affinity, secondary structure, residues connection, motion, and folding of OPRD1 protein.

The adhesion-GPCR ADGRF5 fuels breast cancer progression by suppressing the MMP8-mediated antitumorigenic effects

ADGRF5 (GPR116) has been identified as a facilitator of breast cancer cell migration and metastasis, yet the underlying mechanisms remain largely elusive. Our current study reveals that the absence of ADGRF5 in breast cancer cells impairs extracellular matrix (ECM)-associated cell motility and impedes in vivo tumor growth. This correlates with heightened expression of matrix metalloproteinase 8 (MMP8), a well-characterized antitumorigenic MMP, and a shift in the polarization of tumor-associated neutrophils (TANs) towards the antitumor N1 phenotype in the tumor microenvironment (TME). Mechanistically, ADGRF5 inhibits ERK1/2 activity by enhancing RhoA activation, leading to decreased phosphorylation of C/EBPβ at Thr235, hindering its nuclear translocation and subsequent activation. Crucially, two C/EBPβ binding motifs essential for MMP8 transcription are identified within its promoter region. Consequently, ADGRF5 silencing fosters MMP8 expression and CXCL8 secretion, attracting increased infiltration of TANs; simultaneously, MMP8 plays a role in decorin cleavage, which leads to trapped-inactivation of TGF-β in the TME, thereby polarizing TANs towards the antitumor N1 neutrophil phenotype and mitigating TGF-β-enhanced cell motility in breast cancer. Our findings reveal a novel connection between ADGRF5, an adhesion G protein-coupled receptor, and the orchestration of the TME, which dictates malignancy progression. Overall, the data underscore ADGRF5 as a promising therapeutic target for breast cancer intervention.

Computational Characterization of Membrane Proteins as Anticancer Targets: Current Challenges and Opportunities

Cancer remains a leading cause of mortality worldwide and calls for novel therapeutic targets. Membrane proteins are key players in various cancer types but present unique challenges compared to soluble proteins. The advent of computational drug discovery tools offers a promising approach to address these challenges, allowing for the prioritization of "wet-lab" experiments. In this review, we explore the applications of computational approaches in membrane protein oncological characterization, particularly focusing on three prominent membrane protein families: receptor tyrosine kinases (RTKs), G protein-coupled receptors (GPCRs), and solute carrier proteins (SLCs). We chose these families due to their varying levels of understanding and research data availability, which leads to distinct challenges and opportunities for computational analysis. We discuss the utilization of multi-omics data, machine learning, and structure-based methods to investigate aberrant protein functionalities associated with cancer progression within each family. Moreover, we highlight the importance of considering the broader cellular context and, in particular, cross-talk between proteins. Despite existing challenges, computational tools hold promise in dissecting membrane protein dysregulation in cancer. With advancing computational capabilities and data resources, these tools are poised to play a pivotal role in identifying and prioritizing membrane proteins as personalized anticancer targets.

Oncoinformatic screening of the gene clusters involved in the HER2-positive breast cancer formation along with the in silico pharmacodynamic profiling of selective long-chain omega-3 fatty acids as the metastatic antagonists

The HER2-positive patients occupy ~ 30% of the total breast cancer patients globally where no prevalent drugs are available to mitigate the frequent metastasis clinically except lapatinib and neratinib. This scarcity reinforced researchers' quest for new medications where natural substances are significantly considered. Valuing the aforementioned issues, this research aimed to study the ERBB2-mediated string networks that work behind the HER2-positive breast cancer formation regarding co-expression, gene regulation, GAMA-receptor-signaling pathway, cellular polarization, and signal inhibition. Following the overexpression, promotor methylation, and survivability profiles of ERBB2, the super docking position of HER2 was identified using the quantum tunneling algorithm. Supramolecular docking was conducted to study the target specificity of EPA and DHA fatty acids followed by a comprehensive molecular dynamic simulation (100 ns) to reveal the RMSD, RMSF, Rg, SASA, H-bonds, and MM/GBSA values. Finally, potential drug targets for EPA and DHA in breast cancer were constructed to determine the drug-protein interactions (DPI) at metabolic stages. Considering the values resulting from the combinational models of the oncoinformatic, pharmacodynamic, and metabolic parameters, long-chain omega-3 fatty acids like EPA and DHA can be considered as potential-targeted therapeutics for HER2-positive breast cancer treatment.

The clinical relevance of the adhesion G protein-coupled receptor F5 for human diseases and cancers

Among the numerous adhesion G protein-coupled receptors (GPCRs), adhesion G protein-coupled estrogen receptor F5 (ADGRF5) contains unique domains in the long N-terminal tail which can determine cell-cell and cell-matrix interaction as well as cell adhesion. Nevertheless, the biology of ADGRF5 is complex and still poorly explored. Accumulating evidence suggests that the ADGRF5 activity is fundamental in health and disease. For instance, ADGRF5 is essential in the proper function of lungs and kidney as well as the endocrine system, and its signification in vascularization and tumorigenesis has been demonstrated. The most recent studies have provided findings about the diagnostic potential of ADGRF5 in osteoporosis and cancers, and ongoing studies suggest other diseases as well. Here, we elaborate on the current state of knowledge about the ADGRF5 in the physiology and pathophysiology of human diseases and highlight its high potential as a novel target in various therapeutic areas.

The Expression Pattern of Adhesion G Protein-Coupled Receptor F5 Is Related to Cell Adhesion and Metastatic Pathways in Colorectal Cancer-Comprehensive Study Based on In Silico Analysis

Adhesion G protein-coupled receptor F5 (ADGRF5) is involved inthe neoplastic transformation of some cancer types. However, the significance of ADGRF5 expression signature and the impact of signaling pathways mediated by ADGRF5 during neoplastic transformation of the colon and colorectal cancer (CRC) progression has been poorly examined. Using Gene Expression Omnibus and The Cancer Genome Atlas datasets, we showed that ADGRF5 is overexpressed in the colons of patients with CRC. In line, combined analysis of ADGRF5 expression with clinical characterization revealed an increased expression of ADGRF5 in patients with more advanced stages of CRC compared to patients with early stages of CRC. The Spearman correlation analysis documented numerous genes positively and negatively correlated with the expression pattern of ADGRF5 in the colon of patients with CRC. In the colon of CRC patients, the expression signature of ADGRF5 was associated with genes participating in phosphatidylinositol 3-kinase/Akt, focal adhesion, cell adhesion molecules, and ribosome signaling pathways. Of note, ADGRF5 expression correlated with the levels of tumor-infiltrating immune cells in the colon of CRC patients. Moreover, we found that CRC patients with high expression of ADGRF5 had a significantly lower probability of overall survival and disease-free survival. In conclusion, our results support the prognostic value of ADGRF5 and its potent therapeutic implication in CRC.

HIF1 inhibition of the biflavonoids against pancreas cancer: drug-likeness, bioavailability, ADMET, PASS, molecular docking, molecular dynamics, and MM/GBSA calculations

Pancreatic cancer is an aggressive disease with a high death rate and is difficult to treat. This disease, in the most cases, is asymptomatic until it progresses to an advanced stage. Therefore, the search for bioactive molecules is urgent to combat pancreatic cancer. Then, this work analyzed the interaction potential of agathisflavone and amentoflavone molecules against the HIF1 target using the ADMET, molecular docking, and molecular dynamics simulations. More recent drug-likeness filters that combine physicochemical and physiological parameters have shown that high polar surface area (TPSA > 75 Ų) drives biflavonoids out of the toxic drug space of Pfizer dataset. Regarding the pharmacokinetic descriptors, it was possible to notice that Amentoflavone showed a better order of passive cell permeability (P_app = 8 × 10^-6cm/s) and better metabolic stability, biotransformed by aromatic hydroxylation reactions by the CYP3A4 isoenzyme on the human liver, that favor its hepatic clearance. The molecular docking and molecular dynamics simulations indicated the high interaction potential and stability between the ligands analyzed (highlighted the amentoflavone molecule), respectively. The MM/GBSA calculations showed that the amentoflavone ligand registered the highest ΔG binding value of -32.6957 kcal/mol with the HIF1 target. Then, this molecule may be used as a potential inhibitor of pancreatic cancer. In this perspective, the present work represents an initial step in the virtual bioprospecting a pharmacological tool for treating of pancreatic cancer.Communicated by Ramaswamy H. Sarma.

Computational Studies on T2Rs Agonist-Based Anti-COVID-19 Drug Design

The expeditious and world pandemic viral disease of new coronavirus (SARS-CoV-2) has formed a prompt urgency to discover auspicious target-based ligand for the treatment of COVID-19. Symptoms of novel coronavirus disease (COVID-19) typically include dry cough, fever, and shortness of breath. Recent studies on many COVID-19 patients in Italy and the United Kingdom found increasing anosmia and ageusia among the COVID-19-infected patients. SARS-CoV-2 possibly infects neurons in the nasal passage and disrupts the senses of smell and taste, like other coronaviruses, such as SARS-CoV and MERS-CoV that could target the central nervous system. Developing a drug based on the T2Rs might be of better understanding and worth finding better molecules to act against COVID-19. In this research, we have taken a taste receptor agonist molecule to find a better core molecule that may act as the best resource to design a drug or corresponding derivatives. Based on the computational docking studies, the antibiotic tobramycin showed the best interaction against 6LU7 COVID-19 main protease. Aromatic carbonyl functional groups of the molecule established intermolecular hydrogen bonding interaction with GLN189 amino acid and it showed the two strongest carbonyl interactions with receptor protein resulting in a glide score of -11.159. To conclude, depending on the molecular recognition of the GPCR proteins, the agonist molecule can be recognized to represent the cell secondary mechanism; thus, it provides enough confidence to design a suitable molecule based on the tobramycin drug.

Synthesis and Cytotoxic Activity of Novel Indole Derivatives and Their in silico Screening on Spike Glycoprotein of SARS-CoV-2

This work investigated the interaction of indole with SARS-CoV-2. Indole is widely used as a medical material owing to its astounding biological activities. Indole and its derivatives belong to a significant category of heterocyclic compounds that have been used as a crucial component for several syntheses of medicine. A straightforward one-pot three-component synthesis of indole, coupled with Mannich base derivatives 1a-1j, was synthesized without a catalyst. The products were confirmed by IR, 1H-NMR, 13C-NMR, mass spectra, and elemental analysis. The indole derivatives were tested for cytotoxic activity, using three cancer cell lines and normal cell lines of Human embryonic kidney cell (HEK293), liver cell (LO2), and lung cell (MRC5) by MTT assay using doxorubicin as the standard drug. The result of cytotoxicity indole compound 1c (HepG2, LC50-0.9 μm, MCF-7, LC50-0.55 μm, HeLa, LC50-0.50 μm) was found to have high activity compared with other compounds used for the same purpose. The synthesized derivatives have revealed their safety by exhibiting significantly less cytotoxicity against the normal cell line (HEK-293), (LO2), and (MRC5) with IC50 > 100 μg/ml. Besides, we report an in silico study with spike glycoprotein (SARS-CoV-2-S). The selective molecules of compound 1c exhibited the highest docking score -2.808 (kcal/mol) compared to other compounds. This research work was successful in synthesizing a few compounds with potential as anticancer agents. Furthermore, we have tried to emphasize the anticipated role of indole scaffolds in designing and discovering the much-awaited anti-SARS CoV-2 therapy by exploring the research articles depicting indole moieties as targeting SARS CoV-2 coronavirus.