Novel insights on oral squamous cell carcinoma management using long non-coding RNAs.

Oral squamous cell carcinoma (OSCC) is one of the most prevalent forms of head and neck squamous cell carcinomas (HNSCC) with a poor overall survival rate (about 50%), particularly in cases of metastasis. RNA-based cancer biomarkers are a relatively advanced concept, and non-coding RNAs currently have shown promising roles in the detection and treatment of various malignancies. This review underlines the function of long non-coding RNAs (lncRNAs) in the OSCC and its subsequent clinical implications. LncRNAs, a class of non-coding RNAs, are larger than 200 nucleotides and resemble mRNA in numerous ways. However, unlike mRNA, lncRNA regulates multiple druggable and non-druggable signaling molecules through simultaneous interaction with DNA, RNA, proteins, or microRNAs depending on concentration and localization in cells. Upregulation of oncogenic lncRNAs and down-regulation of tumor suppressor lncRNAs are evident in OSCC tissues and body fluids such as blood and saliva indicating their potential as valuable biomarkers. Targeted inhibition of candidate oncogenic lncRNAs or over-expression of tumor suppressor lncRNAs showed potential therapeutic roles in in-vivo animal models. The types of lncRNAs that are expressed differentially in OSCC tissue and bodily fluids have been systematically documented with specificity and sensitivity. This review thoroughly discusses the biological functions of such lncRNAs in OSCC cell survival, proliferation, invasion, migration, metastasis, angiogenesis, metabolism, epigenetic modification, tumor immune microenvironment, and drug resistance. Subsequently, we addressed the diagnostic and therapeutic importance of lncRNAs in OSCC pre-clinical and clinical systems, providing details on ongoing research and outlining potential future directions for advancements in this field. In essence, this review could be a valuable resource by offering comprehensive and current insights into lncRNAs in OSCC for researchers in fundamental and clinical domains.

An in-silico investigation and network pharmacology based approach to explore the anti-breast-cancer potential of Tecteria coadunata (Wall.) C. Chr.

Uncontrolled cell proliferation is a common definition of cancer. After lung carcinoma, breast neoplasm is the second-most prevalent kind of cancer. The majority of breast cancer cells and healthy breast cells both have receptors for circulating oestrogen and progesterone. In order to promote the development and division of cancer cells, oestrogen and progesterone bind to the receptors and may collaborate with growth factors (such as oncogenes and mutant tumour suppressor genes). As per the literature, Tecteria coadunata (Wall.) C. Chr. has anticancer, antioxidant and anti-inflammatory potential. After the hydroalcoholic extraction of this rhizome, total of 200 phytochemicals were retrieved from HR-LCMS analysis. In this current study, Network pharmacology was carried out to explore the rationale of Tecteria coadunata (Wall.) C. Chr. by using different database using Cytoscape software. The network depicted the interaction of Bioactives with their targets and their association with several disease, especially breast cancer. Tecteria coadunata (Wall.) C. Chr. has offered new relationship with variety of genes and its applications in different types of breast cancers. Further Gene Ontology was carried out and it showed key targets were TP53, BRCA2, PGR and CHEK 2. Further Signalling pathways were also enriched. Flex-X software was used for molecular docking studies, and it verified that Dopaxanthin, Dantrolene and Orotidin shows the highest binding affinities with key targets. Additionally, Pharmacokinetic analysis revealed that all top three lead compounds which follows the Lipinski Rule (Rule of three) without interrupting the conditions of bioavailability with minimal toxicity.Communicated by Ramaswamy H. Sarma.

Pharmacoinformatics approach for the screening of Kovidra (Bauhinia variegata) phytoconstituents against tumor suppressor protein in triple negative breast cancer.

Globally, 2.3 million women were diagnosed with breast cancer, with 6,85000 mortalities in year 2021; making it the world's most prevalent cancer. This growing global burden necessitates a new treatment option, and plant-based medicines offers a promising alternative to conventional cancer treatment. In this work, screening of phytoconstituents of an indigenous therapeutic plant, Bauhinia variegata carried out for potential regulator of tumor suppressor protein p53. Here, an in-silico analysis was employed to develop more effective, pharmaceutically potent small drug-like compounds that target tumor suppressor protein p53. The methanol and aqueous powdered extracts of Bauhinia variegata were prepared and phytochemically evaluated along with antioxidant property evaluation. The LC50 of methanol (325.33 µg/ml) and aqueous extract (361.15 µg/ml) showed their cytotoxic characteristics. Further, GCMS analysis of both the extracts reveals total 57 secondary metabolites. Among these, four lead compounds; compound 1, compound 2, compound 3 and compound 4 were found to have the highest binding ability (-8.15 to -5.40 kcal/mol) with p53. MD simulation and binding free energy validates these findings with highest binding free energy (-67.09 ± 4.87 kcal/mol) towards p53 by the lead phytocompound 2. Selected compounds exhibit excellent pharmacokinetic features and drug-like characteristics. The acute toxicity (LD50) values of the lead phytocompounds ranges from 670 mg/kg to 3100 mg/kg, with toxicity classes of IV and V. As a result, these druggable phytochemicals could serve as potential lead applicants for triple negative breast cancer treatment. However, more in vitro and in vivo research is planned to produce future breast cancer medicine. HIGHLIGHTSScreening of phytoconstituents of an indigenous therapeutic plant, Bauhinia variegata, for potential regulator of tumor suppressor protein p53.The LC50 of methanol (325.33µg/ml) and aqueous extract (361.15µg/ml) showed their cytotoxic characteristics.GCMS analysis of both the extracts reveals total 57 secondary metabolites. Among these, four lead compounds were found to have the highest binding affinity (-8.153 to -5.401 kcal/mol) with tumor suppressor protein p53.MD simulation along with the Prime MM/GBSA binding free energy validates this discovery with highest binding free energy (-67.09 ± 4.87 kcal/mol) towards p53 by the lead compound 2.The acute toxicity (LD50) values of the lead phytocompounds ranges from 670 mg/kg to 3100 mg/kg, with toxicity classes of IV and V.As a result, these druggable phytochemicals could serve as potential lead applicants for triple negative breast cancer treatment.Communicated by Ramaswamy H. Sarma.

Exploring Potential Non-steroidal Aromatase Inhibitors for Therapeutic Application against Estrogen-dependent Breast Cancer.

BACKGROUND: Breast cancer is one of the most commonly diagnosed cancer types among women worldwide. Cytochrome P450 aromatase (CYP19A1) is an enzyme in vertebrates that selectively catalyzes the biosynthesis of estrogens from androgenic precursors. Researchers have increasingly focused on developing non-steroidal aromatase inhibitors (NSAIs) for their potential clinical use, avoiding steroidal side effects. OBJECTIVES: The objective of the present work is to search for potential lead compounds from the ZINC database through various in silico approaches. METHODS: In the present study, compounds from the ZINC database were initially screened through receptor independent-based pharmacophore virtual screening. These screened molecules were subjected to several assessments, such as Lipinski rule of 5, SMART filtration, ADME prediction using SwissADME and lead optimization. Molecular docking was further applied to study the interaction of the filtered compounds with the active site of aromatase. Finally, the obtained hit compounds, consequently represented to be ideal lead candidates, were escalated to the MD simulations. RESULTS: The results indicated that the lead compounds might be potential anti-aromatase drug candidate. CONCLUSION: The findings provided a valuable approach in developing novel anti-aromatase inhibitors for the treatment of ER+ breast cancer.

Dual inhibition of cyclooxygenase-2 (COX-2) and 5-lipoxygenase (5-LOX) by resveratrol derivatives in cancer therapy: in silico approach.

In a number of human cancers, both cycloxygenase-2 (COX-2) and 5-lipoxygenase (5-LOX) are up-regulated and co-expressed, promoting cancer cell proliferation and angiogenesis. Resveratrol (3,4',5-trihydroxy-trans-stilbene) is a natural polyphenolic phytoalexin found in a variety of plants that influences various signal-transduction pathways which control apoptosis, cell growth and cell division, metastasis, angiogenesis and inflammation, and has an impact on cancer stages ranging from initiation to progression. In this work, molecular docking and molecular dynamics simulation method are employed to design resveratrol derivatives for COX-2 and 5-LOX enzymes. By attaching several functional groups on four different places of the resveratrol scaffold, the R group enumeration approach was employed to build four libraries of resveratrol derivatives. Thus, R group enumeration is done to focus on the enhancement of potency of compounds and other chemical characteristics like solubility. Drug-like filters such as REOS 1, 2, 3 and PAINS were applied to the libraries, generating a total of 5557 compounds. Drug-like filters such as REOS and PAINS-1, 2 and 3 were applied to the libraries, generating a total of 5557 compounds. All of these compounds were docked with both enzymes using the Glide SP and XP docking methods. Enrichment calculations were performed using 40 compounds from XP docking along with resveratrol, and 1000 decoy compounds from the DUD-E database to validate the docking protocol. The stability of the complexes was further studied using molecular dynamics simulation, radius of gyration, MM/GBSA, H bond monitoring and electrostatic potential surface (EPS). ADMET properties of compounds were studied using SwissADME and pkCSM server.Communicated by Ramaswamy H. Sarma.

GC-MS profiling of Bauhinia variegata major phytoconstituents with computational identification of potential lead inhibitors of SARS-CoV-2 Mpro.

Severe acute respiratory syndrome coronavirus 2 was originally identified in Wuhan city of China in December 2019 and it spread rapidly throughout the globe, causing a threat to human life. Since targeted therapies are deficient, scientists all over the world have an opportunity to develop novel drug therapies to combat COVID-19. After the declaration of a global medical emergency, it was established that the Food and Drug Administration (FDA) could permit the use of emergency testing, treatments, and vaccines to decrease suffering, and loss of life, and restore the nation's health and security. The FDA has approved the use of remdesivir and its analogs as an antiviral medication, to treat COVID-19. The primary protease of SARS-CoV-2, which has the potential to regulate coronavirus proliferation, has been a viable target for the discovery of medicines against SARS-CoV-2. The present research deals with the in silico technique to screen phytocompounds from a traditional medicinal plant, Bauhinia variegata for potential inhibitors of the SARS-CoV-2 main protease. Dried leaves of the plant B. variegata were used to prepare aqueous and methanol extract and the constituents were analyzed using the GC-MS technique. A total of 57 compounds were retrieved from the aqueous and methanol extract analysis. Among these, three lead compounds (2,5 dimethyl 1-H Pyrrole, 2,3 diphenyl cyclopropyl methyl phenyl sulphoxide, and Benzonitrile m phenethyl) were shown to have the highest binding affinity (-5.719 to -5.580 kcal/mol) towards SARS-CoV-2 Mpro. The post MD simulation results also revealed the favorable confirmation and stability of the selected lead compounds with Mpro as per trajectory analysis. The Prime MM/GBSA binding free energy supports this finding, the top lead compound 2,3 diphenyl cyclopropyl methyl phenyl sulphoxide showed high binding free energy (-64.377 ± 5.24 kcal/mol) towards Mpro which reflects the binding stability of the molecule with Mpro. The binding free energy of the complexes was strongly influenced by His, Gln, and Glu residues. All of the molecules chosen are found to have strong pharmacokinetic characteristics and show drug-likeness properties. The lead compounds present acute toxicity (LD50) values ranging from 670 mg/kg to 2500 mg/kg; with toxicity classifications of 4 and 5 classes. Thus, these compounds could behave as probable lead candidates for treatment against SARS-CoV-2. However further in vitro and in vivo studies are required for the development of medication against SARS-CoV-2.

Novel B, C-ring truncated deguelin derivatives reveals as potential inhibitors of cyclin D1 and cyclin E using molecular docking and molecular dynamic simulation.

The overexpression of cyclin D1 and cyclin E due to their oncogenic potential and amplification has been associated with a higher mortality rate in many cancers. The deguelin is a natural compound, has shown promising anti-cancer activity by directly binding cyclin D1 and cyclin E and thus suppressing its function. The C7a atomic position of deguelin structure contains a proton that generates stabilized radical, as a result, decomposed deguelin reduces its structural stability and significantly decreases its biological activity. To design deguelin derivatives with the reduced potential side effect, series of B, C-ring truncated derivatives were investigated as cyclin D1 and cyclin E inhibitors. R-group-based enumeration was implemented in the deguelin scaffold using the R-group enumeration module of Schrödinger. Drug-Like filters like, REOS and PAINs series were applied to the enumerated compound library to remove compounds containing reactive functional groups. Further, screened compounds were docked within the ligand-binding cavity of cyclin D1 and cyclin E crystal structure, using Glide SP and XP protocol to obtain docking poses. Enrichment calculations were done using SchrÖdinger software, with 1000 decoy compounds (from DUD.E database) and 60 compounds (XP best poses) along with deguelin, to validate the docking protocol. The receiver operating characteristic (ROC) curve indicates R2 = 0.94 for cyclin D1 and R2 = 0.79 for cyclin E, suggesting that the docking protocol is valid. Besides, we explored molecular dynamics simulation to probe the binding stability of deguelin and its derivatives within the binding cavity of cyclin D1 and cyclin E structures which are associated with the cyclin D1 and cyclin E inhibitory mechanism.

Pharmacoinformatics-based identification of transmembrane protease serine-2 inhibitors from Morus Alba as SARS-CoV-2 cell entry inhibitors.

Transmembrane protease serine-2 (TMPRSS2) is a cell-surface protein expressed by epithelial cells of specific tissues including those in the aerodigestive tract. It helps the entry of novel coronavirus (n-CoV) or Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in the host cell. Successful inhibition of the TMPRSS2 can be one of the crucial strategies to stop the SARS-CoV-2 infection. In the present study, a set of bioactive molecules from Morus alba Linn. were screened against the TMPRSS2 through two widely used molecular docking engines such as Autodock vina and Glide. Molecules having a higher binding affinity toward the TMPRSS2 compared to Camostat and Ambroxol were considered for in-silico pharmacokinetic analyses. Based on acceptable pharmacokinetic parameters and drug-likeness, finally, five molecules were found to be important for the TMPRSS2 inhibition. A number of bonding interactions in terms of hydrogen bond and hydrophobic interactions were observed between the proposed molecules and ligand-interacting amino acids of the TMPRSS2. The dynamic behavior and stability of best-docked complex between TRMPRSS2 and proposed molecules were assessed through molecular dynamics (MD) simulation. Several parameters from MD simulation have suggested the stability between the protein and ligands. Binding free energy of each molecule calculated through MM-GBSA approach from the MD simulation trajectory suggested strong affection toward the TMPRSS2. Hence, proposed molecules might be crucial chemical components for the TMPRSS2 inhibition.

In Silico Exploration of Phytoconstituents From Phyllanthus emblica and Aegle marmelos as Potential Therapeutics Against SARS-CoV-2 RdRp.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) worldwide has increased the importance of computational tools to design a drug or vaccine in reduced time with minimum risk. Earlier studies have emphasized the important role of RNA-dependent RNA polymerase (RdRp) in SARS-CoV-2 replication as a potential drug target. In our study, comprehensive computational approaches were applied to identify potential compounds targeting RdRp of SARS-CoV-2. To study the binding affinity and stability of the phytocompounds from Phyllanthus emblica and Aegel marmelos within the defined binding site of SARS-CoV-2 RdRp, they were subjected to molecular docking, 100 ns molecular dynamics (MD) simulation followed by post-simulation analysis. Furthermore, to assess the importance of features involved in the strong binding affinity, molecular field-based similarity analysis was performed. Based on comparative molecular docking and simulation studies of the selected phytocompounds with SARS-CoV-2 RdRp revealed that EBDGp possesses a stronger binding affinity (-23.32 kcal/mol) and stability than other phytocompounds and reference compound, Remdesivir (-19.36 kcal/mol). Molecular field-based similarity profiling has supported our study in the validation of the importance of the presence of hydroxyl groups in EBDGp, involved in increasing its binding affinity toward SARS-CoV-2 RdRp. Molecular docking and dynamic simulation results confirmed that EBDGp has better inhibitory potential than Remdesivir and can be an effective novel drug for SARS-CoV-2 RdRp. Furthermore, binding free energy calculations confirmed the higher stability of the SARS-CoV-2 RdRp-EBDGp complex. These results suggest that the EBDGp compound may emerge as a promising drug against SARS-CoV-2 and hence requires further experimental validation.

Biofilm inhibition and anti-quorum sensing activity of phytosynthesized silver nanoparticles against the nosocomial pathogen Pseudomonas aeruginosa.

Quorum sensing (QS), the communication signaling network, regulates biofilm formation and several virulence factors in Pseudomonas aeruginosa PAO1, a nosocomial opportunistic pathogen. QS is considered to be a challenging target for compounds antagonistic to virulent factors. Biologically synthesized silver nanoparticles (AgNPs) are reported as anti-QS and anti-biofilm drugs against bacterial infections. The present study reports on the synthesis and characterization of Piper betle (Pb) mediated AgNPs (Pb-AgNPs). The anti-QS activity of Pb-AgNPs against Chromobacterium violaceum and the potential effect of Pb-AgNPs on QS-regulated phenotypes in PAO1 were studied. FTIR analysis exhibited that Pb-AgNPs had been capped by phytochemical constituents of Pb. Eugenol is one of the active phenolic phytochemicals in Pb leaves, therefore molecular docking of eugenol-conjugated AgNPs on QS regulator proteins (LasR, LasI and MvfR) was performed. Eugenol-conjugated AgNPs showed considerable binding interactions with QS-associated proteins. These results provide novel insights into the development of phytochemically conjugated nanoparticles as promising anti-infective candidates.

Molecular interaction studies of Deguelin and its derivatives with Cyclin D1 and Cyclin E in cancer cell signaling pathway: The computational approach.

Deguelin is a major active ingredient and principal component in several plants and it is a potential molecule to target proteins of cancer cell signaling pathway. As a complex natural extract, deguelin interacts with various molecular targets to exert its anti-tumor properties at nanomolar level. It induces cell apoptosis by blocking anti-apoptotic pathways, while inhibiting tumor cell multiplication and malignant transformation through p27-cyclin-E-pRb-E2F1- cell cycle control and HIF-1alphaVEGF antiangiogenic pathways. In silico studies of deguelin and its derivatives is performed to explore interactions with Cyclin D1 and Cyclin E to understand the molecular insights of derivatives with the receptors. Deguelin and its derivatives are minimized by Avogadro to achieve stable conformation. All docking simulation are performed with AutoDockVina and virtual screening of docked ligands are carried out based on binding energy and number of hydrogen bonds. Molecular dynamics (MD) and Simulation of Cyclin D1 and Cyclin E1 is performed for 100 ns and stable conformation is obtained at 78 ns and 19 ns respectively. Ligands thus obtained from docking studies may be probable target to inhibit cancer cell signaling pathways.

Molecular Modeling, Docking, Dynamics and Simulation of Gefitinib and its Derivatives with EGFR in Non-small Cell Lung Cancer.

BACKGROUND: Gefitinib (lressa) is the most prescribed drug, highly effective to treat nonsmall cell lung cancer; primarily it was considered that targeted therapy is a kinase inhibitor. The nonsmall cell lung cancer is caused by mutation in the Epithelial Growth Factor Receptor (EGFR) gene. Iressa works by blocking the EGFR protein that helps the cancer cell growth. EGFR protein has lead to the development of anticancer therapeutics directed against EGFR inhibitor including Gefitinib for non-small cell lung cancer. METHODS: To explore the interaction between Gefitinib and its derivatives with crystal structure of EGFR to understand the better molecular insights interaction strategies. Molecular modeling of ligands (Gefitinib and its derivatives) was carried out by Avogadro software till atomic angle stable confirmation was obtained. The partial charges for the ligands were assigned as per standard protocol for molecular docking. All docking simulations were performed with AutoDockVina. Virtual screening was carried out based on binding energy and hydrogen bonding affinity. Molecular dynamics (MD) and Simulation EGFR were done using GROMACS 5.1.1 software to explore the interaction stability in a cell. RESULTS: The stable conformation for EGFR protein trajectories were captured at various time intervals 0-20ns. Few compounds screen based on high affinity as the inhibitor for EGFR may inhibit the cell cycle signaling in non-small cell lung cancer. CONCLUSION: These result suggested a computer-aided screening approach of Gefitinib derivatives with regard to their binding to EGFR for identifying novel drugs for the treatment of non-small cell lung cancer.

Exploring benzcyclo derivatives as potent aromatase inhibitors using ligand-based modeling studies.

Aromatase inhibition is an attractive strategy for the treatment of hormone-dependent breast cancer. Quantitative structure activity relationship (QSAR) and pharmacophore space modeling studies are performed on benzcyclo- pentane/hexane derivatives to generate statistically significant models. Linear free energy QSAR model (R(2) = 0.874, Q(2) = 0.824, R(pred)(2) = 0.757) showed the importance of hydrophobicity and atomic charge functionality of the molecule for the activity. 3D QSAR models generated with molecular field (CoMFA, R(2) = 0.973, Q(2) = 0.702, R(pred)(2) = 0.612) and similarity analysis (CoMSIA, R(2) = 0.976, Q(2) = 0.803, R(pred)(2) = 0.706) studies indicated the importance of electrostatic and steric fields along with hydrophobicity of the molecule as important features for inhibiting aromatase enzyme. Further pharmacophore space modeling study (Q(2) = 0.845, R(pred)(2) = 0.648) confirmed that molecular hydrophobicity plays key role for aromatase inhibition. The structure-function characterization is adjudged in the active site of the target (3EQM).

Modeling of diarylalkyl-imidazole and diarylalkyl-triazole derivatives as potent aromatase inhibitors for treatment of hormone-dependent cancer.

Aromatase is an enzyme that catalyzes the final step in the conversion of androgen to estrogen. It has become an attractive target for the treatment of estrogen responsive breast cancer. The study has been focused on designing aromatase inhibitors (AIs) that can be selected as probable drug candidate for the treatment of breast cancer. In the present study, long chain diarylalkyl-imidazole and -triazole scaffolds have been considered for exploring pharmacophores as potent AIs using QSAR (Quantitative SAR) and pharmacophore mapping studies. The model generated in linear free energy QSAR study (R(2) = 0.905, Q(2)= 0.885, R(2)(pred(ts)) = 0.763) showed the importance of hydrophobicity, size and shape of the molecule, van der Waals surface and hydrogen atom contribution influence the activity. 3D QSAR of comparative molecular field analysis (CoMFA, R(2)= 0.921, Q(2) = 0.741, R(2)(pred(ts))= 0.583) showed that steric and electrostatic features along with hydrophobicity and electronic charge contribution at C(4) (Fig. 1) influence on the inhibitory activity. Comparative molecular similarity analysis (CoMSIA, R(2) = 0.874, Q(2) = 0.716, R(2)(pred(ts)) = 0.591) study adjudged the presence of steric, electrostatic and hydrophobic fields together with hydrogen bond (HB) donor and acceptor play significant role in inhibitory activity to aromatase enzyme. Further pharmacophore mapping study (Q(2) = 0.947, Delta(cost) = 113.171, R(2)(pred(ts)) = 0.857) suggested that presence of HB acceptor, hydrophobicity with aromatic ring, and the importance of steric contribution influence on the activity. The critical distances among the features are also important for the inhibitor activity.

Pharmacophore search for anti-fertility and estrogenic potencies of estrogen analogs.

Estrogen mediates its action following binding to the estrogen receptor to form an estrogen-receptor complex. The complex initiates gene transcription and produces estrogen-induced cell and/or tissue responses, i.e., estrogenic actions. High doses of estrogen can be used effectively as a contraceptive but are associated with side effects. Considering the long-term benefit-to-risk ratio of estrogen analogs as oral contraceptives, the present study was performed to deduce the active pharmacophore features required to differentiate the anti-fertility potency from the estrogenic activity of the steroidal motif. Implementing classical quantitative structure-activity relationship (QSAR) studies, substitution by an electron-donating group at the C17 position and the presence of a hydrogen bond acceptor at C11, along with the orientation and conformational rigidity of the molecule, were found to be critically important features for estrogenic potency, including anti-fertility activity. However, low electron density at C2 and high electronegativity at C16, which may be due to substitution on those and/or neighboring atoms, favor contraceptive potency, whereas high electron density at C5 and substitution by an electron-withdrawing group at C7, which may confer hydrophobicity on the steroidal scaffold and an overall increment of electron affinity of the molecule, are favorable for estrogenicity. Further CATALYST-based 3D space modeling demonstrates that the presence of the aromatic ring (ring A), hydrophobic zone (ring B), and hydrogen bond acceptor at C17 in ring D, along with steric influence due to conformational rigidity of the compound, impart estrogenic contraceptive activity, but the presence of a second acceptor in ring A, and the critical distances between these features, selectively differentiate the anti-fertility potency from the estrogenic activity.

Molecular design based on receptor-independent pharmacophore: application to estrogen receptor ligands.

Estrogens, a group of steroid hormones, act primarily by regulating gene expression after binding with estrogen receptor (ER), a nuclear ligand-activated transcription factor, translocates to the nucleus after dimer formation, enhances the gene transcription. Estrogen Receptor Modulators (ERMs) have selective agonist and antagonist effects to different tissues, and the purpose of research on ERMs is to identify new potent and less toxic drug molecules. The present study has been focused on finding the structural requirements of ER ligand, using receptor-independent pharmacophore space modeling studies that can explore 3D structural features and configurations, responsible for the biological activity of structurally diverse compounds. The studies show (R=0.945, RMSD=2.186, Deltacost=677.354) the importance of hydrogen bond acceptors in the aromatic rings and a planner hydrophobic region in the molecular architecture along with critical geometrical distance between features are effectively crucial for binding with ER.

Pharmacophore mapping of flavone derivatives for aromatase inhibition.

Aromatase, which catalyses the final step in the steroidogenesis pathway of estrogen, has been target for the design of inhibitor in the treatment of hormone dependent breast cancer for postmenopausal women. The extensive SAR studies performed in the last 30 years to search for potent, selective and less toxic compounds, have led to the development of second and third generation of non-steroidal aromatase inhibitors (AI). Besides the development of synthetic compounds, several naturally occurring and synthetic flavonoids, which are ubiquitous natural phenolic compounds and mediate the host of biological activities, are found to demonstrate inhibitory effects on aromatase. The present study explores the pharmacophores, i.e., the structural requirements of flavones (Fig. 1) for inhibition of aromatase activity, using quantitative structure activity relationship (QSAR) and space modeling approaches. The classical QSAR studies generate the model (R (2) = 0.924, Q (2) = 0.895, s = 0.233) that shows the importance of aromatic rings A and C, along with substitutional requirements in meta and para positions of ring C for the activity. 3D QSAR of Comparative Molecular Field Analysis (CoMFA, R (2) = 0.996, R(2)(cv) = 0.791) and Comparative Molecular Similarity Analysis (CoMSIA, R (2) = 0.992, R(2)(cv) = 0.806) studies show contour maps of steric and hydrophobic properties and contribution of acceptor and donor of the molecule, suggesting the presence of steric hindrance due to ring C and R''-substituent, bulky hydrophobic substitution in ring A, along with acceptors at positions 11, and alpha and gamma of imidazole ring, and donor in ring C favor the inhibitory activity. Further space modeling (CATALYST) study (R = 0.941, Delta( cost ) = 96.96, rmsd = 0.876) adjudge the presence of hydrogen bond acceptor (keto functional group), hydrophobic (ring A) and aromatic rings (steric hindrance) along with critical distance among features are important for the inhibitory activity.

Pharmacophore mapping of arylbenzothiophene derivatives for MCF cell inhibition using classical and 3D space modeling approaches.

Considering the worth of developing non-steroidal estrogen analogs, the present study explores the pharmacophore features of arylbenzothiophene derivatives for inhibitory activity to MCF-7 cells using classical QSAR and 3D space modeling approaches. The analysis shows that presence of phenolic hydroxyl group and ketonic linkage in the basic side chain of 2-arylbenzothiophene core of raloxifene derivatives are crucial. Additionally piperidine ring connected through ether linkage is favorable for inhibition of breast cancer cell line. These features for inhibitory activity are also highlighted through 3D space modeling approach that explored importance of critical inter features distance among HB-acceptor lipid, hydrophobic and HB-donor features in the arylbenzothiophene scaffold for activity.

Pharmacophore mapping of selective binding affinity of estrogen modulators through classical and space modeling approaches: exploration of bridged-cyclic compounds with diarylethylene linkage.

Research on Selective Estrogen Receptor Modulators (SERMs) has been driven by interest in discovering target selective molecules. In view of such significance, the present work explored the pharmacophores of estrogen receptor (ER) subtypes specific binding affinities of diverse compounds belonging to the category of bridged bicyclic-1,1-diarylethylene derivatives. Implementing classical QSAR and CATALYST based space-modeling approaches, it has been explored that attachment of aryl ring systems to unsaturated linkages, availability of phenolic hydroxyl group, global hydrophobicity, and stereochemistry of certain functional groups might be important for governing the subtype specific estrogenic behavior of this group of compounds. Supplementing this deduction, critical interfeature distances between hydrogen bond acceptor, hydrophobic, and ring aromatic features along with steric influence are found to primarily influence the ER-subtypes specific binding of this series of compounds.