New lead discovery for novel M_1 agonists:pharmacophore model based on DISCO computation and virtual screening

To discover new lead compounds for M1 agonists. Ten typical M1 agonists were superimposed to build a M1 agonists 3D-pharmacophore model using distance-comparisons （DISCO） method without the previous knowledge of the three-dimensional structure of M1 receptor. Virtual screening strategy was used to analyze the Available Chemicals Directory-Screening Compounds （ACD-SC） to identify possible new hits. Twenty-two compounds which fit the pharmacophore model well and are not similar with known M1 agonists were purchased in order to evaluate their M1 receptor agonist activity. One of them shows M1 receptor agonist activity with EC50 of 4.90 μmol/L and maximum response. Multiple of 10.0 which shows it worthy of further study as a new lead compound for M1 agonists.

Building the Pharmacophore Model of HIV-1 Integrase Strand Transfer Inhibitors and Studying Their Inhibition Mechanism

The replication of HIV-1 requires the integration of its cyclic DNA into host DNA by HIV-1 integrase （IN）, which includes two important reactions, 3＇-processing and strand transfer, both catalyzed by HIV-1 IN. Disrupting either of the reactions will fulfill the purpose of inhibiting the replication of HIV-1. In this paper, pharmacophore modeling and molecular docking are employed to investigate the inhibition mechanism of the HIV-1 IN strand transfer inhibitors （INSTIs）. Based on the results, we suggest that the inhibition mechanism of INSTIs involves the inhibitor chelating the cofactors Mg2＋ and its forming hydrogen bonds with some crucial residues adjacent to the DDE active center.

Discovery of a Novel 5-HT_(2A) Inhibitor by Pharmacophore-based Virtual Screening

The serotonin 2A（5-HT2A） receptor has been implicated in several neurological conditions and potent 5-HT2A antagonists have therapeutic effects in the treatment of schizo phrenia and depression.In this study,a potent novel 5-HT2A inhibitor 05245768 with a Ki value of （593.89±34.10） nmol/L was discovered by integrating a set of computational approaches and experiments（protein structure prediction,pharmacophore-based virtual screening,automated molecular docking and pharmacological bioassay）.The 5-HT2A receptor showed a negatively charged bin-ding pocket.The binding mode of compound 05245768 with 5-HT2A was obtained by GOLD docking procedure,which revealed the conserved interaction between protonated nitrogen in compound 05245768 and carboxylate group of D3.32 at the active site of 5-HT2A.

A Novel Pharmacophore Model Derived from a Class of Capsid Protein Enterovirus 71 Inhibitors

Capsid protein enterovirus 71 （EV71） is one of the major viruses that cause the severe encephalitis and thus result in a high mortality in children less than 5 years of age.In an effort to discover new potent inhibitors against EV71,a novel three-dimensional pharmacophore model was developed on 24 inhibitors with different molecular structures and bioactivities.The best hypothesis （Hypo1） has a high predictive power and consists of four features,namely,one hydrophobic point （HY） and three hydrogen-bond acceptors （HA）.Two key features of the best Hypo1,HY1 and HA3 match well with an important narrow hydrophobic canyon and with the surface of LYS274 in the target EV71 active site,respectively.The more versatile feature,HA1,is firstly found to be very influential on these compounds’ bioactivities,which may interact with the other side of the active site in the EV71 receptor.The application of the model is successful in predicting the activities of 30 known EV71 inhibitors with a correlation coefficient of 0.831.Furthermore,Hypo1 demonstrates a superior screening capability for retrieving inhibitors from the database with a high enrichment factor of 70.This study provides some important clues in search for more potent inhibitors against EV71 infection.

Common Pharmacophore Model and 3D-QSAR Analysis of Two Different Tyrphostin Families

In the present study we investigated two groups of small molecular tyrosine kinase phosphorylation inhibitors (tyrphostins) with quite different structures (19 compounds of the benzylidene malononitrile famliy and 13 compounds of the 3-substituted indolin-2-ones family). With the aid of a pharmacophore analysis method (CATALYST). a common three-dimensional pharmacophore model to these two kinds of molecules has been discovered. A better 3D-QSAR analysis based on the generated pharmacophore model was conducted (correlate coeffcient R=0.956) and the model shows very good predictive ability.

Pharmacophore approaches in protein kinase inhibitors design

Protein kinases constitute a superfamily of therapeutic targets for a number of human and animal diseases that include more than 500 members accordingly to sequencing data of the human genome. The well characterized nature of protein kinases makes them excellent targets for drug development. Pharmacophore approaches have become one of the major tools in the area of drug discovery. Application of pharmacophore modeling approaches allows reducing of expensive overall cost associated with drug development project. Pharmacophore models are important functional groups of atoms in the proper spatial position for interaction with target protein. Various ligand-based and structurebased methods have been developed for pharmacophore model generation. Despite the successes in pharmacophore models generation these approaches have not reached their full capacity in application for drug discovery. In the following review, we summarize the published data on pharmacophore models for inhibitorsof tyrosine protein kinases(EGFR, HER2, VEGFR, JAK2, JAK3, Syk, ZAP-70, Tie2) and inhibitors of serine/threonine kinases(Clk, Dyrk, Chk1, IKK2, CDK1, CDK2, PLK, JNK3, GSK3, m TOR, p38 MAPK, PKB). Here, we have described the achievements of pharmacophore modeling for protein kinase inhibitors, which provide key points for further application of generated pharmacophore hypotheses in virtual screening, de novo design and lead optimization.

<i>In-Silico</i>Identification of Anticancer Compounds;Ligand-Based Pharmacophore Approach against EGFR Involved in Breast Cancer

Objective: Breast cancer is a public health challenge on a global scale that is caused by environmental or genetic factors. Breast cancer is affecting both males and females, but there is still a lack of effective drugs with improved potency and admissibility against breast cancer as many of the breast cancer drugs have severe side effects. Methods: The docking approach has been used to find a new compound for breast cancer with more efficacy and tolerance and with lesser side effects. A ligand-based pharmacophore approach has been generated for 39 anticancer compounds with significance for the development of new drugs. Result: Through docking, the approach found new lead compounds for breast cancer. The proposed pharmacophore model in this study contains two HBAs and one HYD, one hydrophobic domain and two Aromatic rings and the estimated distance range is minimum to maximum of derived pharmacophore features. Conclusion: Based on this research, it is proposed that these two lead compounds may be able to be used against EGFR in breast cancer. New compounds can be identified based on common features in the Pharmacophore model. 3D pharmacophore triangle could be used for further studies because this pharmacophore has better merging and in the future for more studies can suggest the same distance range of pharmacophore features as this pharmacophore.

Computational Evaluation of Selectivity of Triazole-and Amide-Based Drug Candidates, Flavanone Derivatives and Synthesized Steroid Compounds for Treatment of Diabetes Type II

Inhibition of 11βHSD1 （11-beta-hydroxysteroid dehydrogenase 1） is a promising strategy in drug treatment of diabetes. Several 11βHSDI inhibitors have been proposed; however, their selectivity to 11βHSD1 over its isozyme 11βHSD2 （11-beta-hydroxysteroid dehydrogenase 2） has not been fully reported. The authors sought to provide a short list of top potent and selective compounds along with their detailed binding modes and pharmacophore models, Molecular docking was used for initial screening of a set of 23 potent inhibitors reported by previous experimental studies. After that, selected promising entries were reassessed by molecular dynamics simulations, followed by hydrogen bond analysis. Pharmacophore models of all drug candidates and binding modes of some selected drugs were analyzed. Among the 23 compounds, only four inhibitors were identified as potent and selective drug candidates. Binding energies, 3D pharmacophores and binding modes of the four compounds with 11βHSDI are also discussed in detail in this study.

Identification of Novel CDK9 Inhibitors with Better Inhibitory Activity and Higher Selectivity for Cancer Treatment by an Effective Two-Stage Virtual Screening Strategy

The aberrant overexpression of cyclin-dependent kinase 9 (CDK9) in cancer cells results in the loss of proliferative control, making it an attractive therapeutic target for various cancers. However, the highly structural similarity between CDK9 and CDK2 makes the development of novel selective CDK9 inhibitors a challenging task and thus limits their clinical applications. Here, an effective two-stage virtual screening strategy was developed to identify novel CDK9 inhibitors with better inhibitory activity and higher selectivity. The first screening stage aims to select potential compounds with better inhibitory activity than Roniciclib, one of the most effective CDK9 inhibitors, through reliable structure-based pharmacophoric virtual screening and accurate molecular docking analyses. The second stage employs a very detailed visual inspection process, in which several structural criteria describing the major difference between the binding pockets of CDK9 and CDK2 are taken into consideration, to identify compounds with higher selectivity than CAN508, one of the CDK9 inhibitors with distinguished selectivity. Finally, three compounds (NCI207113 from NCI database and TCM0004 and TCM3282 from TCM database) with better inhibitory activity and higher selectivity were successfully identified as novel CDK9 inhibitors. These three compounds also display excellent binding stabilities, great pharmacokinetic properties and low toxicity in MD simulations and ADMET predictions. Besides, the results of binding free energy calculations suggest that enhancing van der Waals interaction and nonpolar solvation energy and/or reducing polar solvation energy can significantly improve the binding affinity of these CDK9 inhibitors. Their clinical potentials to serve as anticancer drug candidates can be further evaluated through a series of in vitro/in vivo bioassays in the future. To the best of our knowledge, this is the first attempt to identify novel CDK9 inhibitors with both better inhibitory activity and higher selectivity through an effective two-stage virtual screening strategy.

3-Arylisothiazoloquinols as potent ligands for the benzodiazepine site of GABA_(A) receptors

3-Arylisothiazolo[5,4-b]quinolin-4(9H)-ones and 3-arylisoxazolo[5,4-b]quinolin-4(9H)-ones were synthesized and assayed for affinity for the benzodiazepine binding site of the GABAA receptors. While the 3-arylisothiazoloquinolin-4-ones were found to be potent ligands, with affinities (expressed as the affinity Ki value) down to 1 nM, the 3-arylisoxazoloquinolin-4-ones are less potent. This is suggested to depend on sterical repulsive interaction of the 3-arylisoxazoloquinolin-4-ones with the receptor essential volume of the binding site, and a higher electron density at the nitrogen in the azole ring (N-2) as well as the carbonyl oxygen in the isothiazoloquinolin-4-ones enabling them to interact stronger with hydrogen bond donor sites at the binding site.

Pharmacophore identification and validation for human nAChR α7 agonists

Human nAChR u7 is the potential target for schizophrenia cognitive disorders, and it is meaningful to develop selective human nAChR α7 agonists for the clinical treatment of the disease. Because the crystal structure ofα7 receptor has not been resolved, ligand-based drug design strategy was took in this work. A 3D QSAR pharmacophore model was built by HypoGen method, and its quality was evaluated by cost function. Furthermore, the pharmacophore model was validated with activity prediction of test set and was cross-validated based on Fisher＇s Randomization Method. By Enrichment Factor and AU-ROC analysis, the final pharmacophore, which is consisted of one HBA, two Hydrophobic and one PosIonizable, was selected and it fitted well with the docking result of α7 homology model and the ligand. The pharmacophore is expected for the following virtual screening and lead optimization of human nAChR α7 agonists, which is important for the development and discovery of novel antipsychotics.

Screening and Validation of Active Ingredients in Sini Decoction by Combination Method of Pharmacophore Modeling and Molecular Docking

Objective To screen the active compounds in Sini Decoction showing the potential to inhibit tumor necrosis factor α（TNFα） to alleviate Doxorubicin（DOX）-induced heart failure. Methods A chemical database of Sini Decoction was constructed from literature research. The generated pharmacophore models based on TNF-α used to screen active ingredients of Sini Decoction in the database by Discovery Studio 2.5. Molecular docking by Autodock 4.2 was adopted to demonstrate the hit compounds＇ affinities with TNFα. Furthermore, DOX-induced heart failure model on H9c2 cell line was constructed and cell viability was detected by CCK-8 to validate the therapeutic effect of potential active compounds. Results The higenamine showed potential cardiovascular protective effect through virtual screening. And the activity was identified in vitro. Conclusion In this study, we found that higenamine may inhibit TNF-ɑ through virtual docking and validated that higenamine may have the potential of treatment for heart failure in the model of doxorubicin-induced myocardial toxicity to H9c2 cells.

Nucleotide binding domain 1 pharmacophore modeling for visualization and analysis of P-glycoprotein-flavonoid molecular interactions

BACKGROUND： P-glycoprotein （P-gp） is a 170-kDa membrane protein. It provides a barrier function and help to excrete toxins from the body as a transporter. Some bioflavonoids have been shown to block P-gp activity. OBJECTIVE： To evaluate the important amino acid residues within nucleotide binding domain 1 （NBD l） of P-gp that play a key role in molecular interactions with flavonoids using structure-based pharmacophore model. METHODS： In the molecular docking with NBD 1 models, a putative binding site of flavonoids was proposed and compared with the site for ATP. The binding modes for ligands were achieved using LigandScout to generate the P-gp-flavonoid pharmacophore models. RESULTS： The binding pocket for flavonoids was investigated and found these inhibitors compete with the ATP for binding site in NBD1 including the NBD1 amino acid residues identified by the in silico techniques to be involved in the hydrogen bonding and van der Waals （hydrophobic） interactions with flavonoids. CONCLUSION： These flavonoids occupy with the same binding site of ATP in NBD1 proffering that they may act as an ATP competitive inhibitor.

Comparative pharmacophore modeling of human adenosine receptor A1 and A3 antagonists

Adenosine receptors are promising therapeutic targets in drug discovery. In this study, three-dimensional pharmacophore mod- els of human adenosine receptor A1 and A3 antagonists were developed based on 26 and 23 diverse compounds, respectively. The best A1 pharmacophore model （A1-Hopyl） consists of four features： one hydrogen bond donor, one hydrophobic point and two ring aromatics, while the best A3 pharmacophore model （A3_Hopyl） also has four features： one hydrogen bond ac- ceptor, one hydrophobic point and two ring aromatics. The correlation coefficients were 0.840 for A1 test set with 146 diverse compounds and 0.827 for A3 test set with 238 diverse compounds. In the simulated virtual screening experiments, high en- richment factors of 6.51 and 6.90 were obtained for A1_Hopyl and A3_Hopyl models, respectively. Moreover, two models also showed high subtype-selectivity in the simulated virtual screening experiments. These results could be helpful for the dis- covery of novel potent and selective A1 and A3 antagonists.

Novel Dual-Site-Binding Neuraminidase Inhibitor from Virtual Screening by Pharmacophore and Molecular Dynamics Methods

Neuraminidase is a significant anti-influenza target that plays crucial role in virus replication cycle. The discov- ery of 150-cavity in Group-1 neuraminidase provides us a novel mentality of designing inhibitor which can bind with both conserved site and 150-cavity. In order to discover novel dual-site-binding inhibitors, a 3D chemi- cal-feature-based pharmacophore model was established to cover dual-site in neuraminidase. The dual-site-binding model was consistent in predicting the binding conformation of Group-1 neuraminidase inhibitor and applied for virtual screening of Specs database. Compound 4 （ZINC05790048） that aligned well to the model was selected after multiple filtrations for molecular dynamics simulations, indicating improved binding energy with neuraminidase. It can sever as the lead compound for a novel series of inhibitors.

Key Parameters Analysis and Regulation of Singlet Oxygen Quenching Rate of Carotenoids

28 kinds of carotenoids are studied to reveal the key parameters and regulation on the singlet oxygen quenching rate.First,the quantum chemistry parameters of carotenoids calculated by Gaussian software combined with substitution parameters were used to construct the quantitative structure-activity relationship model(QSAR)of the singlet oxygen quenching rate of carotenoids.The key parameters affecting the antioxidant activity of carotenoids are revealed,and the data predicted via the QSAR model were provided for subsequent research.Then,a three-dimensional(3D)pharmacophore model was used to regulate and modify the antioxidant activity of carotenoids.The correlation coefficients of the modeling group(R2)and verification group(Rpre2)of the established QSAR model were 0.945 and 0.916,respectively,which can be used for the analysis of antioxidant activity of carotenoids;the antioxidant activity of carotenoids can be significantly regulated by the number of conjugated C=C bonds,the energy difference between frontier molecular orbitals and the partial Mulliken charge in C1 and theπ···π*excitation energy E(s);the antioxidant activity of carotenoids can be effectively regulated by the hydrogen bond acceptor pharmacophores on both sides of the conjugated C=C bonds and the hydrophobic groups on the conjugated C=C bond;the hydrophobic substituents attached to conjugated C=C bonds can effectively improve the singlet oxygen quenching rate of carotenoids.

Crystal structures, absolute configurations and molecular docking studies of naftopidil enantiomers as α1D-adrenoceptor antagonists

Chiral drug naftopidil(NAF), a specific α1D-adrenoceptor(AR) antagonist for the treatment of benign prostatic hyperplasia, was used in racemic form for several decades. Our recent work declared that NAF enantiomers showed the same antagonistic effects on the α1D-AR, but the binding mechanism of these two stereochemical NAF isomers to the α1D receptor remained unclear. Herein, we reported the crystallographic structures of optically pure NAF stereoisomers for the first time and unambiguously determined their absolute configurations. The crystal data of R and S enantiomers matched satisfactorily the pharmacophore model for α1D-selective antagonists. Based on the constructed α1D homology model,molecular docking studies shed light on the molecular mechanism of NAF enantiomers binding to α1D-AR. The results indicated that NAF enantiomers exhibited the very similar binding poses and occupied the same binding pocket.

Structure-based Screening for the Non-zinc-chelating Selective MMP-13 Inhibitors of Natural Products

Matrix metalloproteinase-13(MMP-13) has been considered as a promising therapeutic target for osteoarthritis. In this work, the experimental crystal structures of five MMP-13-ligand complexes are used to build the multiple structure-based pharmacophore model of MMP-13 inhibitors. The reliability of pharmacophore model is validated using a decoy set. The pharmacophore model contains four chemical features: two hydrogen bond acceptor(HBA), one hydrophobic(HY) feature, and one ring aromatic(RA) feature. Particularly, the HY feature is found to orient the MMP-13 inhibitors deep into the S1’ pocket of MMP-13 to produce selective inhibition. By carrying out the screening of pharmacophore model and subsequent molecular docking, the four non-zinc-chelating selective MMP-13 inhibitors of natural products(NP-015973, NP-000814, STOCK1 N-24933, and STOCK1 N-69443) are identified. It is found that the binding modes of MMP-13 with our screened four natural products are very similar to the reported experimental binding mode of MMP-13 with the most active inhibitor(GG12003, IC50: 0.67 n M), and each of them involves the interactions of a ligand with the three amino acid residues Thr226, Lys119, and His201 of MMP-13 receptor. This shows that our modeling results are in good agreement with the relevant experimental results, which strongly supports our screened MMP-13 inhibitors of natural products. These screened natural products may be used as the lead compounds of MMP-13 inhibitors in the future studies of structural modifications.