Identification of Novel Ribonucleotide Reductase Inhibitors for Therapeutic Application in Bile Tract Cancer: An Advanced Pharmacoinformatics Study.

Biliary tract cancer (BTC) is constituted by a heterogeneous group of malignant tumors that may develop in the biliary tract, and it is the second most common liver cancer. Human ribonucleotide reductase M1 (hRRM1) has already been proven to be a potential BTC target. In the current study, a de novo design approach was used to generate novel and effective chemical therapeutics for BTC. A set of comprehensive pharmacoinformatics approaches was implemented and, finally, seventeen potential molecules were found to be effective for the modulation of hRRM1 activity. Molecular docking, negative image-based ShaEP scoring, absolute binding free energy, in silico pharmacokinetics, and toxicity assessments corroborated the potentiality of the selected molecules. Almost all molecules showed higher affinity in comparison to gemcitabine and naphthyl salicylic acyl hydrazone (NSAH). On binding interaction analysis, a number of critical amino acids was found to hold the molecules at the active site cavity. The molecular dynamics (MD) simulation study also indicated the stability between protein and ligands. High negative MM-GBSA (molecular mechanics generalized Born and surface area) binding free energy indicated the potentiality of the molecules. Therefore, the proposed molecules might have the potential to be effective therapeutics for the management of BTC.

Design of a Structurally Novel Multipotent Drug Candidate by the Scaffold Architecture Technique for ACE-II, NSP15, and Mpro Protein Inhibition: Identification and Isolation of a Natural Product to Prevent the Severity of Future Variants of Covid 19 and a Colorectal Anticancer Drug.

Scaffold architecture in the sectors of biotechnology and drug discovery research include scaffold hopping and molecular modelling techniques and helps in searching for potential drug candidates containing different core structures using computer-based software, which greatly aids medicinal and pharmaceutical chemistry. Going ahead, the computational method of scaffold architecture is thought to produce new scaffolds, and the method is capable of helping search engines toward producing new scaffolds that are likely to represent potent compounds with high therapeutic applications, which is a possibility in this case as well. Here we probate a different interactive design by natural product hopping, molecular modelling, pharmacophore modelling, modification, and combination of the phytoconstituents present in different medicinal plants for developing a pharmacophore-guided good drug candidate for the variants of SARS-CoV-2 or Covid 19. In the modern era, these approaches are carried out at every level of development of scaffold queries, which are increasingly summarized from chemical structures. In this context, we report on a successfully designed drug-like candidate having a high-binding-affinity "compound SLP" by understanding the relationships between the compounds' pharmacophores, scaffold functional groups, and biological activities beyond their individual applications that abide by Lipinski's rule of five, Ghose rule, Veber rule etc. The new scaffold generated by altering the core of the known phyto-compounds holds a good predicted ADMET profile and is examined with iMODS server to check the molecular dynamics simulation with normal mode analysis (NMA). The scaffold's three-dimensional (3D) structure yields a searchable natural product koenimbine from a conformer database having good ADMET property and high availability in spice Murraya koenigii leaves. M. koenigii leaves are easily available in the market, and might ensure the immunity, good health, and well-being of people if affected with any of the variants of Covid 19. The cell viability studies of koenimbine on murine colorectal carcinoma cell line (CT-26) showed no toxicity on normal mice lymphocyte cells (MLCs). The anticancer mechanism of koenimbine was displayed by its enhanced capacity to produce intercellular reactive oxygen species (ROS) in the colorectal carcinoma cell line.

In silico identification of small molecule modulators for disruption of Hsp90-Cdc37 protein-protein interaction interface for cancer therapeutic application.

The protein-protein interactions (PPIs) in the biological systems are important to maintain a number of cellular processes. Several disorders including cancer may be developed due to dysfunction in the assembly of PPI networks. Hence, targeting intracellular PPIs can be considered as a crucial drug target for cancer therapy. Among the enormous and diverse group of cancer-enabling PPIs, the Hsp90-Cdc37 is prominent for cancer therapeutic development. The successful inhibition of Hsp90-Cdc37 PPI interface can be an important therapeutic option for cancer management. In the current study, a set of more than sixty thousand compounds belong to four databases were screened through a multi-steps molecular docking study in Glide against the Hsp90-Cdc37 interaction interface. The Glide-score and Prime-MM-GBSA based binding free energy of DCZ3112, standard Hsp90-Cdc37 inhibitor were found to be -6.96 and -40.46 kcal/mol, respectively. The above two parameters were used as cut-off score to reduce the chemical space from all successfully docked molecules. Furthermore, the in-silico pharmacokinetics parameters, common-feature pharmacophore analyses and the molecular binding interactions were used to wipe out the inactive molecules. Finally, four molecules were found to be important to modulate the Hsp90-Cdc37 interface. The potentiality of the final four molecules was checked through several drug-likeness characteristics. The molecular dynamics (MD) simulation study explained that all four molecules retained inside the interface of Hsp90-Cdc37. The binding free energy of each molecule obtained from the MD simulation trajectory was clearly explained the strong affection towards the Hsp90-Cdc37. Hence, the proposed molecule might be crucial for successful inhibition of the Hsp90-Cdc37 interface.Communicated by Ramaswamy H. Sarma.

Structure-based identification of galectin-1 selective modulators in dietary food polyphenols: a pharmacoinformatics approach.

In this study, a set of dietary polyphenols was comprehensively studied for the selective identification of the potential inhibitors/modulators for galectin-1. Galectin-1 is a potent prognostic indicator of tumor progression and a highly regarded therapeutic target for various pathological conditions. This indicator is composed of a highly conserved carbohydrate recognition domain (CRD) that accounts for the binding affinity of ß-galactosides. Although some small molecules have been identified as galectin-1 inhibitors/modulators, there are limited studies on the identification of novel compounds against this attractive therapeutic target. The extensive computational techniques include potential drug binding site recognition on galectin-1, binding affinity predictions of ~ 500 polyphenols, molecular docking, and dynamic simulations of galectin-1 with selective dietary polyphenol modulators, followed by the estimation of binding free energy for the identification of dietary polyphenol-based galectin-1 modulators. Initially, a deep neural network-based algorithm was utilized for the prediction of the druggable binding site and binding affinity. Thereafter, the intermolecular interactions of the polyphenol compounds with galectin-1 were critically explored through the extra-precision docking technique. Further, the stability of the interaction was evaluated through the conventional atomistic 100 ns dynamic simulation study. The docking analyses indicated the high interaction affinity of different amino acids at the CRD region of galectin-1 with the proposed five polyphenols. Strong and consistent interaction stability was suggested from the simulation trajectories of the selected dietary polyphenol under the dynamic conditions. Also, the conserved residue (His44, Asn46, Arg48, Val59, Asn61, Trp68, Glu71, and Arg73) associations suggest high affinity and selectivity of polyphenols toward galectin-1 protein.

Identification of naphthyridine and quinoline derivatives as potential Nsp16-Nsp10 inhibitors: a pharmacoinformatics study.

This research is a recent effort to explore some new heterocyclic compounds as novel and potential nonstructural protein-16-nonstructural protein-10 (Nsp16-Nsp10) inhibitors for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) inhibition. The SARS-CoV-2 is causative agent of coronavirus disease 2019 (COVID-19) pandemic. A set of 58 molecules belongs to the naphthyridine and quinoline derivatives have been recently synthesized and considered for structure-based virtual screening against Nsp16-Nsp10. Molecular docking was virtually performed to screen for anti-SARS-CoV-2 activity against Nsp16-Nsp10. Fourteen out of fifty-eight compounds were exhibited binding affinity higher than co-crystal bound ligand s-adenosylmethionine (SAM) toward Nsp16-Nsp10. Further, the in silico pharmacokinetics assessment was carried out and it was found that two molecules possess the acceptable pharmacokinetic profile, hence considered promising Nsp16-Nsp10 inhibitors. The binding interaction analysis was revealed some crucial binding interactions between the final selected two molecules and ligand-binding amino acid residues of Nsp16-Nsp10 protein. In order to explore the characteristics of the protein-ligand complex and how selected small molecules retained inside the receptor cavity in dynamic states, all-atoms conventional molecular dynamics (MD) simulation was performed. Several factors were obtained from the MD simulation trajectory evidently suggested the potentiality of the molecules and stability of the protein-ligand complex. Finally, the binding affinity of both molecules and SAM was explored through the MM-GBSA approach which explained that both molecules possess strong affection towards the Nsp16-Nsp10. Hence, from the pharmacoinformatics assessment, it can be concluded that both heterocyclic compounds might be crucial for SARS-CoV-2 inhibition, subjected to experimental validation.Communicated by Ramaswamy H. Sarma.

Identification of potent food constituents as SARS-CoV-2 papain-like protease modulators through advanced pharmacoinformatics approaches.

The current ongoing pandemic of COVID-19 urges immediate treatment measures for controlling the highly contagious SARS-CoV-2 infections. The papain-like protease (PLpro), which is released from nsp3, is presently being evaluated as a significant anti-viral drug target for COVID-19 therapy development. Particularly, PLpro is implicated in the cleavage of viral polyproteins and antagonizes the host innate immune response through its deubiquitinating and deISGylating actions, thus making it a high-profile antiviral therapeutic target. The present study reports a few specific food compounds that can bind tightly with the SARS-CoV-2 PLpro protein identified through extensive computational screening techniques. Precisely, extensive advanced computational approaches combining target-based virtual screening, particularly employing sub-structure based similarity search, molecular docking, molecular dynamics (MD) simulations, and MM-GBSA based binding free energy calculations have been employed for the identification of the most promising food compounds with substantial functional implications as SARS-CoV-2 PLpro protein inhibitors/modulators. Observations from the present research investigation also provide a deeper understanding of the binding modes of the proposed four food compounds with SARS-CoV-2 PLpro protein. In docking analyses, all compounds have established essential inter-molecular interaction profiles at the active site cavity of the SARS-CoV-2 PLpro protein. Similarly, the long-range 100 ns conventional MD simulation studies also provided an in-depth understanding of probable interactions and dynamic behaviour of the SARS-CoV-2 PLpro protein-food compound complexes. Binding free energies of all molecular systems revealed a strong interaction affinity of food compounds towards the SARS-CoV-2 PLpro protein. Moreover, clear-cut comparative analyses against the known standard inhibitor also suggest that proposed food compounds may act as potential active chemical entities for modulating the action of the SARS-CoV-2 PLpro protein.

Design, synthesis, molecular modelling and antiproliferative evaluation of novel benzothiazole trihybrids.

Colorectal cancer is the third most commonly occurring cancer with very less treatment options in case surgery fails to cure the disease. The emergence of drug resistant colon cancer poses a new threat and calls for better drugs for treatment of colon cancer patients. Novel substituted benzo[d]thiazol-2-yl)-5-(pyridin-2-yl) penta-1,4-dien-3-one trihybrid molecules were synthesized following appropriate synthetic route. These compounds were tested for their efficacy in colon cancer and drug resistant colon cancer cell lines. Their toxicity was studied on the ICR mice model and the selectivity study was performed in calorimetric assay and xenograft mice model. An attempt was also made to chalk out the feasible mechanism of action based on molecular docking and molecular dynamics simulation studies. Compounds 4f, 4h and 4i were found to be highly effective and selective towards the inhibition of the colon cancer and drug resistant colon cancer cell lines and in the xenograft method. Selective compounds from this study can be developed into potential drug candidates for the possible treatment of drug resistant colorectal cancer.

Matairesinol, an active constituent of HC9 polyherbal formulation, exhibits HDAC8 inhibitory and anticancer activity.

Histone deacetylase 8 (HDAC8) has emerged as a promising drug target for cancer therapeutics development. HDAC8 has been reported to regulate cancer cell proliferation, invasion and promote metastasis through modulation of cell cycle associated proteins. Of late, phytocompounds have been demonstrated to exhibit anticancer and anti-HDAC8 activity. Here, we have shown the HDAC8 inhibitory potential of an active phytocompound from HC9 (herbal composition-9), a polyherbal anticancer formulation based on the traditional Ayurvedic drug, Stanya Shodhan Kashaya. HC9 was recently reported to exhibit anticancer activity against breast cancer cells through induction of cell cycle arrest, decrease in migration and invasion as well as regulation of inflammation and chromatin modulators. In silico studies such as molecular docking, molecular dynamics (MD) simulation and binding free energy analyses showed greater binding energy values and interaction stability of MA with HDAC8 compared to other phytocompounds of HC9. Interestingly, in vitro validation confirmed the anti-HDAC8 activity of MA. Further, in vitro studies showed that MA significantly decreased the viability of breast and prostate cancer cell lines, thereby confirming its anticancer potential.

Identification of potential cruzain inhibitors using de novo design, molecular docking and dynamics simulations studies.

Communicated by Ramaswamy H. Sarma.

ß-secretase inhibitors for Alzheimer's disease: identification using pharmacoinformatics.

In this study we searched for potential ß-site amyloid precursor protein cleaving enzyme1 (BACE1) inhibitors using pharmacoinformatics. A large dataset containing 7155 known BACE1 inhibitors was evaluated for pharmacophore model generation. The final model (R = 0.950, RMSD = 1.094, Q2 = 0.901, se = 0.332, rm2  = 0.901, Rpred2  = 0.756, sp = 0.468, rm-test2  = 0.667) was revealed with the importance of spatial arrangement of hydrogen bond acceptor and donor, hydrophobicity and aromatic ring features. The validated model was then used to search NCI and InterBioscreen databases for promising BACE1 inhibitors. The initial hits from both databases were sorted using a number of criteria and finally three molecules from each database were considered for further validation using molecular docking and molecular dynamics studies. Different protonation states of Asp32 and Asp228 dyad were analysed and best protonated form used for molecular docking study. Observation of the number of binding interactions in the molecular docking study supported the potential of these molecules being promising inhibitors. Values of RMSD, RMSF, Rg in molecular dynamics study and binding energies unquestionably explained that final screened molecules formed stable complexes inside the receptor cavity of BACE1. Hence, it can be concluded that the final screened six compounds may be potential therapeutic agents for Alzheimer's disease.

Pharmacoinformatics-based identification of chemically active molecules against Ebola virus.

Ebola is a dangerous virus transmitted by animals and humans and to date there is no curable agent for such a deadly infectious disease. In this study, pharmacoinformatics-based methods were adopted to find effective novel chemical entities against Ebola virus. A well predictive and statistical robust pharmacophore model was developed from known Ebola virus inhibitors collected from the literature. The model explained the significance of each of hydrogen bond acceptor and donor, and two hydrophobic regions for activity. The National Cancer Institute and Asinex (Antiviral library) databases were screened using the final validated pharmacophore model. Initial hits were further screened with a set of criteria and finally eight molecules from both databases were proposed as promising anti Ebola agents. Further molecular docking and molecular dynamics studies were carried out and it was found that the proposed molecules possessed capability to interact with amino residues of Ebola protein as well as retaining equilibrium of protein-ligand systems. Finally, the binding energies were calculated using molecular mechanics Poisson-Boltzmann surface area approach and all proposed molecules showed strong binding affinity towards the Ebola protein receptor. Communicated by Ramaswamy H. Sarma.

Cinnamaldehyde, Cinnamic Acid, and Cinnamyl Alcohol, the Bioactives of Cinnamomum cassia Exhibit HDAC8 Inhibitory Activity: An In vitro and In silico Study.

BACKGROUND: The altered expression of histone deacetylase family member 8 (HDAC8) has been found to be linked with various cancers, thereby making its selective inhibition a potential strategy in cancer therapy. Recently, plant secondary metabolites, particularly phenolic compounds, have been shown to possess HDAC inhibitory activity. OBJECTIVE: In the present work, we have evaluated the potential of cinnamaldehyde (CAL), cinnamic acid (CA), and cinnamyl alcohol (CALC) (bioactives of Cinnamomum) as well as aqueous cinnamon extract (ACE), to inhibit HDAC8 activity in vitro and in silico. MATERIALS AND METHODS: HDAC8 inhibitory activity of ACE and cinnamon bioactives was determined in vitro using HDAC8 inhibitor screening kit. Trichostatin A (TSA), a well-known anti-cancer agent and HDAC inhibitor, was used as a positive control. In silico studies included molecular descriptor Analysis molecular docking absorption, distribution, metabolism, excretion, and toxicity prediction, density function theory calculation and synthetic accessibility program. RESULTS: Pharmacoinformatics studies implicated that ACE and its Bioactives (CAL, CA, and CALC) exhibited comparable activity with that of TSA. The highest occupied molecular orbitals and lowest unoccupied molecular orbitals along with binding energy of cinnamon bioactives were comparable with that of TSA. Molecular docking results suggested that all the ligands maintained two hydrogen bond interactions within the active site of HDAC8. Finally, the synthetic accessibility values showed that cinnamon bioactives were easy to synthesize compared to TSA. CONCLUSION: It was evident from both the experimental and computational data that cinnamon bioactives exhibited significant HDAC8 inhibitory activity, thereby suggesting their potential therapeutic implications against cancer. SUMMARY: Pharmacoinformatics studies revealed that cinnamon bioactives bound to the active site of HDAC8 enzyme in a way similar to that of TSAThe molecular descriptors of cinnamon compounds successfully correlated with TSA values. The binding interactions and energies were also found to be close to TSASynthetic accessibility values showed that cinnamon bioactives were easy to synthesize compared to TSA. Abbreviations used: ACE: Aqueous Cinnamon Extract; DFT: Density Function Theory; CAL: Cinnamaldehyde; CA: Cinnamic Acid; CALC: Cinnamyl Alcohol; MW: Molecular Weight; ROTBs: Rotatable Bonds; ROF: Lipinski's Rule of Five; TSA: Trichostatin A; PDB: Protein Data Bank; RMSD: Root Mean Square Deviation; HBA: Hydrogen Bond Acceptor; HBD: Hydrogen Bond Donor; ADMET: Absorption, Distribution, Metabolism, Excretion and Toxicity; FO: Frontier Orbital; HOMOs: Highest Occupied Molecular Orbitals; LUMOs: Lowest Unoccupied Molecular Orbitals; BE: Binding Energy.

Structural requirements for potential HIV-integrase inhibitors identified using pharmacophore-based virtual screening and molecular dynamics studies.

Acquired immunodeficiency syndrome (AIDS) is a life-threatening disease which is a collection of symptoms and infections caused by a retrovirus, human immunodeficiency virus (HIV). There is currently no curative treatment and therapy is reliant on the use of existing anti-retroviral drugs. Pharmacoinformatics approaches have already proven their pivotal role in the pharmaceutical industry for lead identification and optimization. In the current study, we analysed the binding preferences and inhibitory activity of HIV-integrase inhibitors using pharmacoinformatics. A set of 30 compounds were selected as the training set of a total 540 molecules for pharmacophore model generation. The final model was validated by statistical parameters and further used for virtual screening. The best mapped model (R = 0.940, RMSD = 2.847, Q(2) = 0.912, se = 0.498, Rpred(2) = 0.847 and rm(test)(2) = 0.636) explained that two hydrogen bond acceptor and one aromatic ring features were crucial for the inhibition of HIV-integrase. From virtual screening, initial hits were sorted using a number of parameters and finally two compounds were proposed as promising HIV-integrase inhibitors. Drug-likeness properties of the final screened compounds were compared to FDA approved HIV-integrase inhibitors. HIV-integrase structure in complex with the most active and final screened compounds were subjected to 50 ns molecular dynamics (MD) simulation studies to check comparative stability of the complexes. The study suggested that the screened compounds might be promising HIV-integrase inhibitors. The new chemical entities obtained from the NCI database will be subjected to experimental studies to confirm potential inhibition of HIV integrase.

Design, synthesis and anticancer activity of Michael-type thiol adducts of α-santonin analogue with exocyclic methylene.

A series of Michael-type analogues were generated on the C-ring of α-santonin (α-methylene-γ-butyrolactone) upon reaction with various thiols. All the thiol adducts synthesized were evaluated for their anticancer activity against four human cancer cell lines (PC-3, HCT-15, A-549 and MCF-7). Bioassay results indicated that even though most of the synthesized compounds exhibited a good anticancer activity against various cancer cells in vitro, some of the compounds like 9e, 9g and 9q were found to be the most promising analogues in this series, with compound 9e showing IC50 values of 1.5 µM, 0.6 µM, 2.4 µM and 1.2 µM on PC-3, MCF-7, A-549 and HCT-116 cell lines respectively. Further, flow cytometry studies showed that MCF-7 cells treated with the compounds 9e, 9g and 9q were arrested in the sub G1 phase of the cell cycle in a concentration dependent manner. These lead molecules were further studied for NF-κB, p65 transcription factor inhibitory activity which confirmed concentration dependent inhibition against NF-κB, p65 with analogue 9e showing 57% inhibition at 2 µM, 9g showing 62% inhibition at 3 µM and 9q showing 54% inhibition at 2 µM concentration.

Exploration of the structural requirements of HIV-protease inhibitors using pharmacophore, virtual screening and molecular docking approaches for lead identification.

Pharmacoinformatics approaches are widely used in the field of drug discovery as it saves time, investment and animal sacrifice. In the present study, pharmacore-based virtual screening was adopted to identify potential HIV-protease ligands as anti-HIV agents. Pharmacophore is the 3D orientation and spatial arrangement of functional groups that are critical for binding at the active site cavity. Virtual screening retrieves potential hit molecules from databases based on imposed criteria. A set of 30 compounds were selected with inhibition constant as training set from 129 compounds of dataset set and subsequently the pharmacophore model was developed. The selected best model consists of hydrogen bond acceptor and donor, hydrophobic and aromatic ring, features critical for HIV-protease inhibitors. The model exhibits high correlation (R=0.933), less rmsd (1.014), high cross validated correlation coefficient (Q(2)=0.872) among the ten models examined and validated by Fischer's randomization test at 95% confidence level. The acceptable parameters of test set prediction, such as R(pred)(2)=0.768 and r(m(test))(2)=0.711 suggested that external predictivity of the model was significant. The pharmacophore model was used to perform a virtual screening employing the NCI database. Initial hits were sorted using a number of parameters and finally seven compounds were proposed as potential HIV-protease molecules. One potential HIV-protease ligand is reportedly confirmed as an active agent for anti-HIV screening, validating the current approach. It can be postulated that the pharmacophore model facilitates the selection of novel scaffold of HIV-protease inhibitors and can also allow the design of new chemical entities.

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.