Ligand- and protein-based modeling studies of the inhibitors of human cytochrome P450 2D6 and a virtual screening for potential inhibitors from the Chinese herbal medicine, Scutellaria baicalensis (Huangqin,Baikal Skullcap)

We have previously examined the binding patterns of various substrates to human cytochrome P450 2D6 (CYP2D6) using a series of molecular modeling methods. In this study, we further explored the binding modes of various types of inhibitors to CYP2D6 using a combination of ligand- and protein-based modeling approaches. Firstly, we developed and validated a pharmacophore model for CYP2D6 inhibitors, which consisted of two hydrophobic features and one hydrogen bond acceptor feature. Secondly, we constructed and validated a quantitative structure-activity relationship (QSAR) model for CYP2D6 inhibitors which gave a poor to moderate prediction accuracy. Thirdly, a panel of CYP2D6 inhibitors were subject to molecular docking into the active site of wild-type and mutated CYP2D6 enzyme. We demonstrated that 8 residues in the active site (Leu213, Glu216, Ser217, Gln244, Asp301, Ser304, Ala305, and Phe483) played an important role in the binding to the inhibitors via hydrogen bond formation and/or π-π stacking interaction. Apparent changes in the binding modes of the inhibitors have been observed with Phe120Ile, Glu216Asp, Asp301Glu mutations in CYP2D6. Finally, we screened for potential binders/inhibitors from the Chinese herbal medicine Scutellaria baicalensis (Huangqin, Baikal Skullcap) using the established pharmacophore model for CYP2D6 inhibitors and molecular docking approach. Overall, 18 out of 40 compounds from S. baicalensis were mapped to the pharmacophore model of CYP2D6 inhibitors and most herbal compounds from S. baicalensis could be docked into the active site of CYP2D6. Our study has provided insights into the molecular mechanisms of interaction of synthetic and herbal compounds with human CYP2D6 and further benchmarking studies are needed to validate our modeling and virtual screening results.     

Efficient 3D database screening for novel HIV-1 IN inhibitors

We describe the use of pharmacophore modeling as an efficient tool in the discovery of novel HIV-1 integrase (IN) inhibitors. A three-dimensional hypothetical model for the binding of diketo acid analogues to the enzyme was built by means of the Catalyst program. Using these models as a query for virtual screening, we found several compounds that contain the specified 3D patterns of chemical functions. Biological testing shows that our strategy was successful in searching for new structural leads as HIV-1 IN inhibitors.     

Pharmacophore modeling,virtual screening and molecular docking of ATPase inhibitors of HSP70

Heat shock protein 70 is an effective anticancer target as it influences many signaling pathways. Hence the study investigated the important pharmacophore feature required for ATPase inhibitors of HSP70 by generating a ligand based pharmacophore model followed by virtual based screening and subsequent validation by molecular docking in Discovery studio V4.0. The most extrapolative pharmacophore model (hypotheses 8) consisted of four hydrogen bond acceptors. Further validation by external test set prediction identified 200 hits from Mini Maybridge, Drug Diverse, SCPDB compounds and Phytochemicals. Consequently, the screened compounds were refined by rule of five, ADMET and molecular docking to retain the best competitive hits. Finally Phytochemical compounds Muricatetrocin B, Diacetylphiladelphicalactone C, Eleutheroside B and 5-(3-{[1-(benzylsulfonyl)piperidin-4-yl]amino}phenyl)- 4-bromo-3-(carboxymethoxy)thiophene-2-carboxylic acid were obtained as leads to inhibit the ATPase activity of HSP70 in our findings and thus can be proposed for further in vitro and in vivo evaluation.     

Discovery and design of new PI3K inhibitors through pharmacophore-based virtual screening,molecular docking,and binding free energy analysis

Phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT)/the mammalian target of rapamycin (mTOR) signaling pathway is one of the sought after therapeutic target for treating human cancers. This pathway is often hyper activated in cancers. In the present study, pharmacophore-based virtual screening, molecular docking, and binding free energy calculations were performed on a series of quinoline derivatives which were reported to be effective against PI3Kα. A five-point pharmacophore hypothesis with one hydrogen bond acceptor (A), one hydrogen bond donor (D), one hydrophobic group (H), and two aromatic rings (R) was developed with acceptable R² and Q² values of 0.93 and 0.60 respectively. Eventually, common pharmacophore hypothesis-based screening was conducted against TOSLab, CPP, and ASINEX macrocylce databases, and potential hits were identified which were further subjected to rigorous docking process in order to screen out drug like molecules having crucial interactions with the target PI3Kα. Finally, binding free energy analysis was carried out for the top hits obtained from docking process. We also designed new 1, 3, 4-oxadiazole-based cyclic peptides by incorporating the structural features of the hits obtained from the above databases. Among the designed cyclic peptides, the cyclic peptide with tryptophan moiety showed good interactions and free binding energy values. On the whole, this study helped us in identifying new promising molecules as PI3Kα inhibitors which can be explored further to generate greater number of compounds with better pharmacokinetic properties.     

Multiple receptor-ligand based pharmacophore modeling and molecular docking to screen the selective inhibitors of matrix metalloproteinase-9 from natural products

Matrix metalloproteinase-9 (MMP-9) is an attractive target for cancer therapy. In this study, the pharmacophore model of MMP-9 inhibitors is built based on the experimental binding structures of multiple receptor-ligand complexes. It is found that the pharmacophore model consists of six chemical features, including two hydrogen bond acceptors, one hydrogen bond donor, one ring aromatic regions, and two hydrophobic (HY) features. Among them, the two HY features are especially important because they can enter the S1′ pocket of MMP-9 which determines the selectivity of MMP-9 inhibitors. The reliability of pharmacophore model is validated based on the two different decoy sets and relevant experimental data. The virtual screening, combining pharmacophore model with molecular docking, is performed to identify the selective MMP-9 inhibitors from a database of natural products. The four novel MMP-9 inhibitors of natural products, NP-000686, NP-001752, NP-014331, and NP-015905, are found; one of them, NP-000686, is used to perform the experiment of in vitro bioassay inhibiting MMP-9, and the IC₅₀ value was estimated to be only 13.4 µM, showing the strongly inhibitory activity of NP-000686 against MMP-9, which suggests that our screening results should be reliable. The binding modes of screened inhibitors with MMP-9 active sites were discussed. In addition, the ADMET properties and physicochemical properties of screened four compounds were assessed. The found MMP-9 inhibitors of natural products could serve as the lead compounds for designing the new MMP-9 inhibitors by carrying out structural modifications in the future.     

Development of predictive pharmacophore model for in silico screening,and 3D QSAR CoMFA and CoMSIA studies for lead optimization,for designing of potent tumor necrosis factor alpha converting enzyme inhibitors

A chemical feature-based pharmacophore model was developed for Tumor Necrosis Factor-α converting enzyme (TACE) inhibitors. A five point pharmacophore model having two hydrogen bond acceptors (A), one hydrogen bond donor (D) and two aromatic rings (R) with discrete geometries as pharmacophoric features was developed. The pharmacophore model so generated was then utilized for in silico screening of a database. The pharmacophore model so developed was validated by using four compounds having proven TACE inhibitory activity which were grafted into the database. These compounds mapped well onto the five listed pharmacophoric features. This validated pharmacophore model was also used for alignment of molecules in CoMFA and CoMSIA analysis. The contour maps of the CoMFA/CoMSIA models were utilized to provide structural insight for activity improvement of potential novel TACE inhibitors. The pharmacophore model so developed could be used for in silico screening of any commercial/in house database for identification of TACE inhibiting lead compounds, and the leads so identified could be optimized using the developed CoMSIA model. The present work highlights the tremendous potential of the two mutually complementary ligand-based drug designing techniques (i.e. pharmacophore mapping and 3D-QSAR analysis) using TACE inhibitors as prototype biologically active molecules.     

Identification of critical chemical features for Aurora kinase-B inhibitors using Hip-Hop, virtual screening and molecular docking

This study was performed to find the selective chemical features for Aurora kinase-B inhibitors using the potent methods like Hip-Hop, virtual screening, homology modeling, molecular dynamics and docking. The best hypothesis, Hypo1 was validated toward a wide range of test set containing the selective inhibitors of Aurora kinase-B. Homology modeling and molecular dynamics studies were carried out to perform the molecular docking studies. The best hypothesis Hypo1 was used as a 3D query to screen the chemical databases. The screened molecules from the databases were sorted based on ADME and drug like properties. The selective hit compounds were docked and the hydrogen bond interactions with the critical amino acids present in Aurora kinase-B were compared with the chemical features present in the Hypo1. Finally, we suggest that the chemical features present in the Hypo1 are vital for a molecule to inhibit the Aurora kinase-B activity.     

Mangiferin, an anti-HIV-1 agent targeting protease and effective against resistant strains

The anti-HIV-1 activity of mangiferin was evaluated. Mangiferin can inhibit HIV-1(Ⅲ)(B) induced syncytium formation at non-cytotoxic concentrations, with a 50% effective concentration (EC??) at 16.90 μM and a therapeutic index (TI) above 140. Mangiferin also showed good activities in other laboratory-derived strains, clinically isolated strains and resistant HIV-1 strains. Mechanism studies revealed that mangiferin might inhibit the HIV-1 protease, but is still effective against HIV peptidic protease inhibitor resistant strains. A combination of docking and pharmacophore methods clarified possible binding modes of mangiferin in the HIV-1 protease. The pharmacophore model of mangiferin consists of two hydrogen bond donors and two hydrogen bond acceptors. Compared to pharmacophore features found in commercially available drugs, three pharmacophoric elements matched well and one novel pharmacophore element was observed. Moreover, molecular docking analysis demonstrated that the pharmacophoric elements play important roles in binding HIV-1 protease. Mangiferin is a novel nonpeptidic protease inhibitor with an original structure that represents an effective drug development strategy for combating drug resistance.     

Pharmacophore Modeling and Virtual Screening of Novel Inhibitors for c-Kit Kinase

The stem cell factor receptor (c‐Kit) has been known to play critical roles in regulating numerous aspects of cellular behavior including cell growth, differentiation, migration and metabolism. In this investigation, a three‐dimensional pharmacophore model of c‐Kit inhibitors has been established by using the HypoGen algorithms implemented in the catalyst software package. The best quantitative pharmacophore model, hypothesis 1, which has the highest correlation coefficient (0.989), consists of one hydrogen bond acceptor, two hydrogen bond donors and one hydrophobic feature. To our knowledge, this is the first report on the pharmacophore modeling study of c‐Kit inhibitors. The best hypothesis, hypothesis 1, was used to screen molecular structural databases, including Specs and China Natural Products Database for potential lead compounds. The hit compounds were subsequently subjected to filtering by Lipinski's rules and docking study to refine the retrieved hits and as a result to reduce the rate of false positive. Finally 28 compounds were purchased or synthesized for further in vitro assay against several human tumour cell lines including A549, MCF‐7, HepG2 and PC‐3, in which c‐Kit is overexpressed. Two compounds show very low micromolar inhibition potency against the PC‐3 and HepG2 cell lines respectively. And they were selected for further modification and testing.     

Identification of new dual spleen tyrosine kinase (Syk) and phosphoionositide-3-kinase δ (PI3Kδ) inhibitors using ligand and structure-based integrated ideal pharmacophore models

Owing to the complex pathophysiology of autoimmune disorders, it is very challenging to develop successful treatment strategies. Single-target agents are not desired therapeutics for such multi-factorial disorders. Considering the current need for the treatment of complex autoimmune disorders, dual inhibitors of Syk and PI3Kδ have been designed using ligand and structure-based molecular modelling strategies. In the present work, structure and ligand-based pharmacophore modelling was implemented for a varied set of Syk and PI3Kδ inhibitors. Ligand-based pharmacophore models (LBPMs) were developed for two kinases: ADPR.14 (r²_train = 0.809) for Syk, comprising one hydrogen bond acceptor, one hydrogen bond donor, one positive ionisable and one ring aromatic feature, and for PI3Kδ: AAARR.45 (r²_train = 0.942) consisting of three hydrogen bond acceptor and two ring aromatic features. The generated e-pharmacophore models revealed an additional ring aromatic and hydrophobic feature important for Syk and PI3Kδ inhibition, respectively. Subsequently, LBPMs were modified resulting in APDRR.14 hypothesis for Syk inhibitors and AAAHRR.45 hypothesis for PI3Kδ inhibitors employed for virtual screening. Thus, the combination of ligand and structure-based pharmacophore modelling helped in developing ideal pharmacophore models that may be an efficient tool for the designing of novel dual inhibitors of Syk and PI3Kδ.     

基于虚拟筛选策略发现新型潜在JAK3小分子抑制剂

利用已知活性的分子采用基于配体的策略构建药效团模型,通过基于类药规则、药效团模型、多种精度的分子对接算法、MM/GBSA结合能预测以及ADMET筛选手段对含约250万个分子的数据库进行虚拟筛选。发现5种JAK3抑制剂的新型骨架,其中6个以1-苯基咪唑烷-2-酮为骨架的分子在与JAK3激酶的结合能以及分子的ADMET性质评价方面均表现优异,具备高JAK3抑制剂潜力,被认为是虚拟筛选的命中分子。     

人类免疫缺陷病毒整合酶二酮酸类抑制剂的三维药效团构建

应用遗传算法相似性程序(GASP), 以作用于I型人类免疫缺陷病毒(human immun-odeficiency virus type 1, HIV-1)整合酶(IN)的二酮酸类(diketoacids, DKAs)抑制剂构建药效团模型. 所选训练集分子均具有可靠的类药性特征及DKAs药效团特征. 尝试将抑制剂与药效团叠合后的构象和抑制剂与IN的对接构象进行叠合, 得到药效团模型与分子对接构象中IN残基的相对位置, 并基于抑制剂的药效团模型特征与周围IN氨基酸残基位置的匹配情况进行药效团特征的修改. 所得最优药效团由1个疏水特征、3对氢键特征和1个氢键供体特征组成. 该药效团的命中物质量(goodness of hit, GH)为0.56, 产出率(Y)达63.6%, 假阳性率(FP)为0.41%. 该药效团具有较好的置信度, 产出率较高而假阳性率较低, 可用于数据库搜索发现新的具有DKAs药效团特征的活性化合物, 也可为先导化合物的改造提供帮助.     

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.     

Identification of novel PfDHODH inhibitors as antimalarial agents via pharmacophore-based virtual screening followed by molecular docking and in vivo antimalarial activity

Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) catalyses the fourth reaction of de novo pyrimidine biosynthesis in parasites, and represents an important target for the treatment of malaria. In this study, we describe pharmacophore-based virtual screening combined with docking study and biological evaluation as a rational strategy for identification of novel hits as antimalarial agents. Pharmacophore models were established from known PfDHODH inhibitors using the GALAHAD module with IC₅₀ values ranging from 0.033 μM to 142 μM. The best pharmacophore model consisted of three hydrogen bond acceptor, one hydrogen bond donor and one hydrophobic features. The pharmacophore models were validated through receiver operating characteristic and Günere–Henry scoring methods. The best pharmacophore model as a 3D search query was searched against the IBS database. Several compounds with different structures (scaffolds) were retrieved as hit molecules. Among these compounds, those with a Q_FIT value of more than 81 were docked in the PfDHODH enzyme to further explore the binding modes of these compounds. In silico pharmacokinetic and toxicities were predicted for the best docked molecules. Finally, the identified hits were evaluated in vivo for their antimalarial activity in a parasite inhibition assay. The hits reported here showed good potential to become novel antimalarial agents.     

Pharmacophore modeling,atom based 3D-QSAR,molecular docking and molecular dynamics studies on Escherichia coli ParE inhibitors

ATP dependent ParE enzyme is as an attractive target for the development of antibacterial agents. Atom based 3D-QSAR model AADHR.187 was developed based on the thirty eight Escherichia coli ParE inhibitors. The generated model showed statistically significant coefficient of determinations for the training (R² = 0.985) and test (R² = 0.86) sets. The cross-validated correlation coefficient (q2) was 0.976. The utility of the generated model was validated by the enrichment study. The model was also validated with structurally diverse external test set of ten compounds. Contour plot analysis of the generated model unveiled the chemical features necessary for the E. coli ParE enzyme inhibition. Extra-precision docking result revealed that hydrogen bonding and ionic interactions play a major role in ParE protein-ligand binding. Binding free energy was computed for the data set inhibitors to validate the binding affinity. A 30-ns molecular dynamics simulation showed high stability and effective binding of inhibitor 34 within the active site of ParE enzyme. Using the best fitted model AADHR.187, pharmacophore-based high-throughput virtual screening was performed to identify virtual hits. Based on the above studies three new molecules are proposed as E. coli ParE inhibitors with high binding affinity and favourable ADME properties.     

Pharmacophore generation,atom-based 3D-QSAR and molecular dynamics simulation analyses of pyridine-3-carboxamide-6-yl-urea analogues as potential gyrase B inhibitors

DNA gyrase subunit B (GyrB) is an attractive drug target for the development of antibacterial agents with therapeutic potential. In the present study, computational studies based on pharmacophore modelling, atom-based QSAR, molecular docking, free binding energy calculation and dynamics simulation were performed on a series of pyridine-3-carboxamide-6-yl-urea derivatives. A pharmacophore model using 49 molecules revealed structural and chemical features necessary for these molecules to inhibit GyrB. The best fitted model AADDR.13 was generated with a coefficient of determination (r²) of 0.918. This model was validated using test set molecules and had a good r² of 0.78. 3D contour maps generated by the 3D atom-based QSAR revealed the key structural features responsible for the GyrB inhibitory activity. Extra precision molecular docking showed hydrogen bond interactions with key amino acid residues of ATP-binding pocket, important for inhibitor binding. Further, binding free energy was calculated by the MM-GBSA rescoring approach to validate the binding affinity. A 10 ns MD simulation of inhibitor #47 showed the stability of the predicted binding conformations. We identified 10 virtual hits by in silico high-throughput screening. A few new molecules were also designed as potent GyrB inhibitors. The information obtained from these methodologies may be helpful to design novel inhibitors of GyrB.     

Identification of Influenza PAN Endonuclease Inhibitors via 3D-QSAR Modeling and Docking-Based Virtual Screening

Structural and biochemical studies elucidate that PA_N may contribute to the host protein shutdown observed during influenza A infection. Thus, inhibition of the endonuclease activity of viral RdRP is an attractive approach for novel antiviral therapy. In order to envisage structurally diverse novel compounds with better efficacy as PA_N endonuclease inhibitors, a ligand-based-pharmacophore model was developed using 3D-QSAR pharmacophore generation (HypoGen algorithm) methodology in Discovery Studio. As the training set, 25 compounds were taken to generate a significant pharmacophore model. The selected pharmacophore Hypo1 was further validated by 12 compounds in the test set and was used as a query model for further screening of 1916 compounds containing 71 HIV-1 integrase inhibitors, 37 antibacterial inhibitors, 131 antiviral inhibitors and other 1677 approved drugs by the FDA. Then, six compounds (Hit01–Hit06) with estimated activity values less than 10 μM were subjected to ADMET study and toxicity assessment. Only one potential inhibitory ‘hit’ molecule (Hit01, raltegravir’s derivative) was further scrutinized by molecular docking analysis on the active site of PA_N endonuclease (PDB ID: 6E6W). Hit01 was utilized for designing novel potential PA_N endonuclease inhibitors through lead optimization, and then compounds were screened by pharmacophore Hypo1 and docking studies. Six raltegravir’s derivatives with significant estimated activity values and docking scores were obtained. Further, these results certainly do not confirm or indicate the seven compounds (Hit01, Hit07, Hit08, Hit09, Hit10, Hit11 and Hit12) have antiviral activity, and extensive wet-laboratory experimentation is needed to transmute these compounds into clinical drugs.     

基于药效团的BRD4靶向小分子抑制剂虚拟筛选

BRD4靶点和多种肿瘤密切相关,是具有良好成药性的热门靶点。本文选取活性较好且结构差异较大的BRD4小分子抑制剂作为训练集分子,基于配体小分子共同特征(HipHop)方法使用Discovery Studio 3.0分子模拟软件构建了药效团。药效团通过测试集验证、ROC曲线验证(SE(sensitivity)=0.93765、SP(specificity)=0.89500、(AUC)=0.956),结果表明构建得到的药效团具有较强的可靠性和较高的可信度。药效团模型含有1个芳环中心、1个疏水基团、2个氢键受体四个药效特征元素。此药效团被用于ZINC数据库进行虚拟筛选,共筛选了861203个分子,命中率为0.782%。再对筛选得到的分子经过分子对接、ADMET成药性预测、构象分析并讨论分子-蛋白相互作用模式,最终得到了21个有潜力的BRD4小分子抑制剂。     

Identification of Novel β3-Adrenoceptor Agonists Using Energetic Analysis, Structure Based Pharmacophores and Virtual Screening

β3 Adrenergic receptor (β3-AR), is a potential therapeutic target for the treatment of type II diabetes and obesity. We report the identification of novel compounds as β3-AR agonists by integrating different approaches of energetic analysis, structure based pharmacophore designing and virtual screening. In a step wise filtering protocol, structure based virtual screening of 2,33,450 compounds was done. These molecules were docked into the active site of the receptor utilizing three levels of accuracy; ligands passing the HTVS (high throughput virtual screening) step were subsequently analyzed in Glide SP (Standard Precision) and finally in Glide XP (Extra Precision) to estimate the receptor ligand binding affinities. In the second step a total of 300 pharmacophore hypotheses were generated from a set of known and diverse β3-AR agonists. The best hypothesis showed six features: three hydrogen bond acceptors, one positively charged group, and two aromatic rings. To cross validate, pharmacophore filtering was done on the set of shortlisted compounds from structure based VS (virtual screening). The different screening techniques employed were validated using enrichment factor calculations. The energetic based Pharmacophore performed fairly well at distinguishing active from the inactive compounds and yielded a greater diversity of active molecules whereas the number of actives retrieved in the case of structure based screening was the highest.