Discovery of potential Aurora-A kinase inhibitors by 3D QSAR pharmacophore modeling, virtual screening, docking, and MD simulation studies

The Aurora-kinase family comprises of cell cycle-regulated serine/threonine kinases playing a vital role during mitosis. Aurora-A kinase is involved in multiple mitotic events in cell cycle and is a major regulator of centrosome function during mitosis. Aurora-A is overexpressed in breast, lung, colon, ovarian, glial, and pancreatic cancer. Hence, Aurora-A kinase is a promising target in cancer therapy. In our current study, a four-point 3D QSAR pharmacophore model has been generated using substituted pyrimidine class of Aurora-A kinase inhibitors. It had a fixed cost value 88.7429. The model mapped well to the external test set comprising of clinically active molecules, with a correlation coefficient r = 0.99. From the mapping, it was found that the hydrophobic features (HY) of a molecule play an important role for Aurora-A kinase inhibitory activity, whereas the ring aromatic feature provides geometric constraint for spatial alignment of different functional group. The hypothesis, with one hydrogen bond acceptor, two ring aromatic features, and one hydrophobic feature, was selected to screen miniMaybridge database. The screened ligands were filtered on the basis of activity, shape, and drug likeliness. This led to the identification of five top hits. These identified potential leads were further subjected to docking with the ATP-binding site of Aurora-A kinase. The molecular dynamic simulation studies of top lead molecules having diverse scaffolds endorsed that the identified molecules had distinctive ability to inhibit Aurora-A kinase. Thus, this study may facilitate the medicinal chemists to design promising ligands with various scaffolds to inhibit Aurora-A kinase. Communicated by Ramaswamy H. Sarma.

Pharmaceutical interest of in-silico approaches

The virtual environment within the computer using software performed on the computer is known as in-silico studies. These drugs designing software play a vital task in discovering new drugs in the field of pharmaceuticals. These designing programs and software are employed in gene sequencing, molecular modeling, and in assessing the three-dimensional structure of the molecule, which can further be used in drug designing and development. Drug development and discovery is not only a powerful, extensive, and an interdisciplinary system but also a very complex and time-consuming method. This book chapter mainly focused on different types of in-silico approaches along with their pharmaceutical applications in numerous diseases.

Drug repurposing using transcriptome sequencing and virtual drug screening in a patient with glioblastoma

Background Precision medicine and drug repurposing are attractive strategies, especially for tumors with worse prognosis. Glioblastoma is a highly malignant brain tumor with limited treatment options and short survival times. We identified novel BRAF (47-438del) and PIK3R1 (G376R) mutations in a glioblastoma patient by RNA-sequencing. Methods The protein expression of BRAF and PIK3R1 as well as the lack of EGFR expression as analyzed by immunohistochemistry corroborated RNA-sequencing data. The expression of additional markers (AKT, SRC, mTOR, NF-κB, Ki-67) emphasized the aggressiveness of the tumor. Then, we screened a chemical library of > 1500 FDA-approved drugs and > 25,000 novel compounds in the ZINC database to find established drugs targeting BRAF47-438del and PIK3R1-G376R mutated proteins. Results Several compounds (including anthracyclines) bound with higher affinities than the control drugs (sorafenib and vemurafenib for BRAF and PI-103 and LY-294,002 for PIK3R1). Subsequent cytotoxicity analyses showed that anthracyclines might be suitable drug candidates. Aclarubicin revealed higher cytotoxicity than both sorafenib and vemurafenib, whereas idarubicin and daunorubicin revealed higher cytotoxicity than LY-294,002. Liposomal formulations of anthracyclines may be suitable to cross the blood brain barrier. Conclusions In conclusion, we identified novel small molecules via a drug repurposing approach that could be effectively used for personalized glioblastoma therapy especially for patients carrying BRAF47-438del and PIK3R1-G376R mutations.

Pharmacophore Modeling, Synthesis, Scaffold Hopping and Biological β- Hematin Inhibition Interaction Studies for Anti-malaria Compounds

Backgound:

Exploring potent compounds is critical to generating multi-target drug discovery. Hematin crystallization is an important mechanism of malaria.

Methods:

A series of chloroquine analogues were designed using a repositioning approach to develop new anticancer compounds. Protein-ligand interaction fingerprints and ADMET descriptors were used to assess docking performance in virtual screenings to design chloroquine hybrid β-hematin inhibitors. A PLS algorithm was applied to correlate the molecular descriptors to IC50 values. The modeling presented excellent predictive power with correlation coefficients for calibration and cross-validation of r2 = 0.93 and q2 = 0.72. Using the model, a series of 4-aminoquinlin hybrids were synthesized and evaluated for their biological activity as an external test series. These compounds were evaluated for cytotoxic cell lines and β-hematin inhibition.

Results:

The target compounds exhibited high β-hematin inhibition activity and were 3-9 times more active than the positive control. Furthermore, all the compounds exhibited moderate to high cytotoxic activity. The most potent compound in the dataset was docked with hemoglobin and its pharmacophore features were generated. These features were used as input to the Pharmit server for screening of six databases.

Conclusion:

The compound with the best score from ChEMBL was 2016904, previously reported as a VEGFR-2 inhibitor. The 11 compounds selected presented the best Gold scores with drug-like properties and can be used for drug development.

A thienopyridine, CB-20, exerts diuretic activity by inhibiting urea transporters

Urea transporters (UTs) are transmembrane proteins selectively permeable to urea and play an important role in urine concentration. UT-knockout mice exhibit the urea-selective urine-concentrating defect, without affecting electrolyte balance, suggesting that UT-B inhibitors have the potential to be developed as novel diuretics. In this study, we characterized a novel compound 5-ethyl-2-methyl-3-amino-6-methylthieno[2,3-b]pyridine-2,5-dicarboxylate (CB-20) with UT inhibitory activity as novel diuretics with excellent pharmacological properties. This compound was discovered based on high-throughput virtual screening combined with the erythrocyte osmotic lysis assay. Selectivity of UT inhibitors was assayed using transwell chambers. Diuretic activity of the compound was examined in rats and mice using metabolic cages. Pharmacokinetic parameters were detected in rats using LC-MS/MS. Molecular docking was employed to predict the potential binding modes for the CB-20 with human UT-B. This compound dose-dependently inhibited UT-facilitated urea transport with IC50 values at low micromolar levels. It exhibited nearly equal inhibitory activity on both UT-A1 and UT-B. After subcutaneous administration of CB-20, the animals showed polyuria, without electrolyte imbalance and abnormal metabolism. CB-20 possessed a good absorption and rapid clearance in rat plasma. Administration of CB-20 for 5 days did not cause significant morphological abnormality in kidney or liver tissues of rats. Molecular docking showed that CB-20 was positioned near several residues in human UT-B, including Leu364, Val367, and so on. This study provides proof of evidence for the prominent diuretic activity of CB-20 by specifically inhibiting UTs. CB-20 or thienopyridine analogs may be developed as novel diuretics.

Discovery of Novel DPP-IV Inhibitors as Potential Candidates for the Treatment of Type 2 Diabetes mellitus Predicted by 3D QSAR Pharmacophore Models, Molecular Docking and de novo Evolution

Dipeptidyl peptidase-IV (DPP-IV) rapidly breaks down the incretin hormones glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic peptide (GIP). Thus, the use of DPP-IV inhibitors to retard the degradation of endogenous GLP-1 is a possible mode of therapy correcting the defect in incretin-related physiology. The aim of this study is to find a new small molecule and explore the inhibition activity to the DPP-IV enzyme using a computer aided simulation. In this study, the predicted compounds were suggested as potent anti-diabetic candidates. Chosen structures were applied following computational strategies: The generation of the three-dimensional quantitative structure-activity relationship (3D QSAR) pharmacophore models, virtual screening, molecular docking, and de novo Evolution. The method also validated by performing re-docking and cross-docking studies of seven protein systems for which crystal structures were available for all bound ligands. The molecular docking experiments of predicted compounds within the binding pocket of DPP-IV were conducted. By using 25 training set inhibitors, ten pharmacophore models were generated, among which hypo1 was the best pharmacophore model with the best predictive power on account of the highest cost difference (352.03), the lowest root mean squared deviation (RMSD) (2.234), and the best correlation coefficient (0.925). Hypo1 pharmacophore model was used for virtual screening. A total of 161 compounds including 120 from the databases, 25 from the training set, 16 from the test set were selected for molecular docking. Analyzing the amino acid residues of the ligand-receptor interaction, it can be concluded that Arg125, Glu205, Glu206, Tyr547, Tyr662, and Tyr666 are the main amino acid residues. The last step in this study was de novo Evolution that generated 11 novel compounds. The derivative dpp4_45_Evo_1 by all scores CDOCKER_ENERGY (CDOCKER, -41.79), LigScore1 (LScore1, 5.86), LigScore2 (LScore2, 7.07), PLP1 (-112.01), PLP2 (-105.77), PMF (-162.5)—have exceeded the control compound. Thus the most active compound among 11 derivative compounds is dpp4_45_Evo_1. Additionally, for derivatives dpp4_42_Evo_1, dpp4_43_Evo2, dpp4_46_Evo_4, and dpp4_47_Evo_2, significant upward shifts were recorded. The consensus score for the derivatives of dpp4_45_Evo_1 from 1 to 6, dpp4_43_Evo2 from 4 to 6, dpp4_46_Evo_4 from 1 to 6, and dpp4_47_Evo_2 from 0 to 6 were increased. Generally, predicted candidates can act as potent occurring DPP-IV inhibitors given their ability to bind directly to the active sites of DPP-IV. Our result described that the 6 re-docked and 27 cross-docked protein-ligand complexes showed RMSD values of less than 2 Å. Further investigation will result in the development of novel and potential antidiabetic drugs.

Inhibition of Oncogenic Kinases: An In Vitro Validated Computational Approach Identified Potential Multi-Target Anticancer Compounds

Tumorigenesis in humans is a multistep progression that imitates genetic changes leading to cell transformation and malignancy. Oncogenic kinases play a central role in cancer progression, rendering them putative targets for the design of anti-cancer drugs. The presented work aims to identify the potential multi-target inhibitors of oncogenic receptor tyrosine kinases (RTKs) and serine/threonine kinases (STKs). For this, chemoinformatics and structure-based virtual screening approaches were combined with an in vitro validation of lead hits on both cancerous and non-cancerous cell lines. A total of 16 different kinase structures were screened against ~739,000 prefiltered compounds using diversity selection, after which the top hits were filtered for promising pharmacokinetic properties. This led to the identification of 12 and 9 compounds against RTKs and STKs, respectively. Molecular dynamics (MD) simulations were carried out to better comprehend the stability of the predicted hit kinase-compound complexes. Two top-ranked compounds against each kinase class were tested in vitro for cytotoxicity, with compound F34 showing the most promising inhibitory activity in HeLa, HepG2, and Vero cell lines with IC50 values of 145.46 μM, 175.48 μM, and 130.52 μM, respectively. Additional docking of F34 against various RTKs was carried out to support potential multi-target inhibition. Together with reliable MD simulations, these results suggest the promising potential of identified multi-target STK and RTK scaffolds for further kinase-specific anti-cancer drug development toward combinatorial therapies.

Predicting tyrosinase inhibition by 3D QSAR pharmacophore models and designing potential tyrosinase inhibitors from Traditional Chinese medicine database

BACKGROUND

Tyrosinase plays a key role in the formation of skin melanin. The excessive accumulation of skin melanin will cause the serious aesthetic problems for human beings.

HYPOTHESIS/PURPOSE

To find the potent tyrosinase inhibitors using computational simulation from TCM Database@Taiwan.

STUDY DESIGN

Inhibitors of tyrosinase have been thought as potential drugs for the decrease of melanin synthesis in the process of pigmentation. To develop new tyrosinase inhibitors, we performed a virtual screening from Traditional Chinese medicine (TCM) and Druglike Databases using the best 3D QSAR pharmacophore model as a 3D search query.

METHODS

A total of 109 compounds were obtained after filtering by Lipinski's rule of five. Finally, 148 compounds (22 from training set, 17 from test set, 109 from TCM and Druglike databases) were selected for further docking studies. De Novo Evolution designed the top 10 candidates from the docking results.

RESULTS

Hypo1 was selected as the best quantitative pharmacophore model, because Hypo1 has characters of the highest cost difference (353.773), the lowest RMS (1.985), the lowest Error (121.440), and the best correlation coefficient (0.933). By the analysis of interaction amino acids in the top 10 hits including two controls, HIS42, HIS60, HIS204, HIS208, ARG209 and VAL218 are identified as the key binding site residues, ARG209 and VAL218 are the critical residues for the inhibitory activity of tyrosinase. This finding is consistent with the results from literatures.

CONCLUSION

De Novo Evolution study suggested Tyrosinase_1*_Evo_4, Tyrosinase_23*_Evo_7, magnolone.cdx_15_Evo_4, compound_2.cdx_2_Evo_2, Compound_B_Evo_5, Compound_C_Evo_9, Compound_D_Evo_6 and malabaricone_C.cdx_3_Evo_10 as the potential tyrosinase inhibitor candidates. De Novo Evolution study also suggested compound_2.cdx_2_Evo_2 as the most potential tyrosinase inhibitor candidate. A total of ten novel leading compounds were identified to have the favorable interaction with tyrosinase by the docking analyses.

Synthesis and antiproliferative activity of 2-chlorophenyl carboxamide thienopyridines

3-Amino-2-arylcarboxamide-thieno[2,3-b]pyridines are a known class of antiproliferative compounds with activity against the phospholipase C enzyme. To further investigate the structure activity relationships of these derivatives a series of analogues were prepared modifying key functional groups. It was determined that modification of the 3-amino and 2-aryl carboxamide functionalities resulted in complete elimination of activity, whilst modification at C-5 allowed compounds of greater activity to be prepared.

Search for Potent and Selective Aurora A Inhibitors Based on General Ser/Thr Kinase Pharmacophore Model

Based on the data for compounds known from the literature to be active against various types of Ser/Thr kinases, a general pharmachophore model for these types of kinases was developed. The search for the molecules fitting to this pharmacophore among the ASINEX proprietary library revealed a number of compounds, which were tested and appeared to possess some activity against Ser/Thr kinases such as Aurora A, Aurora B and Haspin. Our work on the optimization of these molecules against Aurora A kinase allowed us to achieve several hits in a 3–5 nM range of activity with rather good selectivity and Absorption, Distribution, Metabolism, and Excretion (ADME) properties, and cytotoxicity against 16 cancer cell lines. Thus, we showed the possibility to fine-tune the general Ser/Thr pharmacophore to design active and selective compounds against desired types of kinases.

General Ser/Thr Kinases Pharmacophore Approach for Selective Kinase Inhibitors Search as Exemplified by Design of Potent and Selective Aurora A Inhibitors

A general pharmachophore model for various types of Ser/Thr kinases was developed. Search for the molecules fitting to this pharmacophore among ASINEX proprietary library revealed a number of compounds, which were tested and appeared to possess some activity against several Ser/Thr kinases such as Aurora A, Aurora B and Haspin. The possibility of performing the fine-tuning of the general Ser/Thr pharmacophore to desired types of kinase to get active and selective inhibitors was exemplified by Aurora A kinase. As a result, several hits in 3-5 nm range of activity against Aurora A kinase with rather good selectivity and ADME properties were obtained.

Identification of Aurora-A Inhibitors by Ligand and Structure-Based Virtual Screening

Aurora kinase A has been identified as one of the most attractive targets for cancer therapy because of its critical role in the regulation of the cell cycle. In order to identify active compounds with structural diversity we performed virtual screening. 3D-QSAR pharmacophore models were developed and the best model was used as a query for screening the databases. Ligand and structure-based virtual screening protocol was conducted sequentially by applying the common feature pharmacophore and molecular docking to discover potent Aurora-A inhibitors. A total of eighty-eight compounds were selected for the in vitro activities against various human cancer cell lines (DU145 and HT29). Considering the activity data, we have identified seven compounds to be considered for the next step, among which four compounds had high inhibition rate (above 50 %) at 10 µM with GI50 lower than 10 µM. Based on the cell line and enzyme assay (Aurora-A & B) result, these four compounds were used as template/query molecule for similarity search. The best result was obtained for similarity hit SH3. It had IC50 of 0.578 and 11.77 µM for Aurora-A and B respectively, which implies 20-fold selectivity over Aurora-B. The hits obtained from this screening scheme could be potential drug candidates after further optimization.

Identification of novel anaplastic lymphoma kinase (ALK) inhibitors using a common feature pharmacophore model derived from known ligands crystallized with ALK

In this investigation, a common feature pharmacophore model of anaplastic lymphoma kinase inhibitors was developed based on several known anaplastic lymphoma kinase inhibitors that were co-crystallized with anaplastic lymphoma kinase. The established pharmacophore model Hypo1 was carefully validated and then adopted to screen two in silico chemical databases, Specs (202 408 compounds) and Enamine (1 105 894 compounds), for retrieving novel anaplastic lymphoma kinase inhibitors. The hit compounds were further filtered using a fast bumping-check tool and molecular docking. Finally, 25 compounds were selected and purchased from market. The bioactivity of these compounds was firstly measured at the cellular level against a typical anaplastic lymphoma kinase mutant-driven cancer cell line, Karpas299. And six of them showed a good anti-viability activity. The kinase inhibitory potency against the recombinant human anaplastic lymphoma kinase kinase was tested to the most active compound at the cellular level, T0508-5181 (from Specs), which gave a half maximal inhibitory concentration (IC(50)) of 5.3 μM.

QSAR studies on imidazopyrazine derivatives as Aurora A kinase inhibitors

Aurora kinases have emerged as attractive targets for the development of novel anti-cancer agents. A combined study of molecular docking, pharmacophore modelling and 3D-QSAR was performed on a series of imidazo [1, 2-a] pyrazines as novel Aurora kinase inhibitors to gain insights into the structural determinants and their structure-activity relationship. An ensemble of conformations based on molecular docking was used for PHASE pharmacophore studies. The developed best-fitted pharmacophore model was validated by diverse chemotypes of Aurora A kinase inhibitors and was consistent with the structural requirements for the docked binding mechanism. Subsequently, the pharmacophore-based alignment was used to develop PHASE and comparative molecular similarity indices analysis (CoMSIA) 3D-QSAR models. The best CoMSIA model showed good statistics (q (2 )= 0.567, r (2 )= 0.992), and the predictive ability of the model was validated using an external test set of 13 compounds giving a satisfactory prediction ([Formula: see text]). The 3D contour maps provided insight into the binding mechanism and highlighted key structural features that are essential to the inhibitory activity. Based on the PHASE and CoMSIA 3D-QSAR results, a set of novel Aurora A inhibitors were designed that showed excellent potencies.

SKLB70326, a novel small-molecule inhibitor of cell-cycle progression, induces G₀/G₁ phase arrest and apoptosis in human hepatic carcinoma cells

We previously reported the potential of a novel small molecule 3-amino-6-(3-methoxyphenyl)thieno[2.3-b]pyridine-2-carboxamide (SKLB70326) as an anticancer agent. In the present study, we investigated the anticancer effects and possible mechanisms of SKLB70326 in vitro. We found that SKLB70326 treatment significantly inhibited human hepatic carcinoma cell proliferation in vitro, and the HepG2 cell line was the most sensitive to its treatment. The inhibition of cell proliferation correlated with G(0)/G(1) phase arrest, which was followed by apoptotic cell death. The SKLB70326-mediated cell-cycle arrest was associated with the downregulation of cyclin-dependent kinase (CDK) 2, CDK4 and CDK6 but not cyclin D1 or cyclin E. The phosphorylation of the retinoblastoma protein (Rb) was also observed. SKLB70326 treatment induced apoptotic cell death via the activation of PARP, caspase-3, caspase-9 and Bax as well as the downregulation of Bcl-2. The expression levels of p53 and p21 were also induced by SKLB70326 treatment. Moreover, SKLB70326 treatment was well tolerated. In conclusion, SKLB70326, a novel cell-cycle inhibitor, notably inhibits HepG2 cell proliferation through the induction of G(0)/G(1) phase arrest and subsequent apoptosis. Its potential as a candidate anticancer agent warrants further investigation.

In-silico studies in Chinese herbal medicines' research: evaluation of in-silico methodologies and phytochemical data sources, and a review of research to date

The available databases that catalogue information on traditional Chinese medicines are reviewed in terms of their content and utility for in-silico research on Chinese herbal medicines, as too are the various protein database resources, and the software available for use in such studies. The software available for bioinformatics and 'omics studies of Chinese herbal medicines are summarised, and a critical evaluation given of the various in-silico methods applied in screening Chinese herbal medicines, including classification trees, neural networks, support vector machines, docking and inverse docking algorithms. Recommendations are made regarding any future in-silico studies of Chinese herbal medicines.

Novel pyrazolo[3,4-d]pyrimidine derivatives as potential antitumor agents: exploratory synthesis, preliminary structure-activity relationships, and in vitro biological evaluation

In a cell-based screen of novel anticancer agents, the hit compound 1a which bears a pyrazolo[3,4-d]pyrimidine scaffold exhibited high inhibitory activity against a panel of four different types of tumor cell lines. In particular, the IC₅₀ for A549 cells was 2.24 µM, compared with an IC₅₀ of 9.20 µM for doxorubicin, the positive control. Four synthetic routes of the key intermediate 3 of 1a were explored and 1a was prepared via route D on the gram scale for further research. Two analogs of 1a were synthesized and their preliminary structure-activity relationships were studied. Flow cytometric analysis revealed that compound 1a could significantly induce apoptosis in A549 cells in vitro at low micromolar concentrations. These results suggest that the target compound 1a and its analogs with the pyrazolo[3,4-d]pyrimidine scaffold might potentially constitute a novel class of anticancer agents, which requires further studies.

TCM grammar systems: an approach to aid the interpretation of the molecular interactions in Chinese herbal medicine

ETHNOPHARMACOLOGICAL RELEVANCE

Interpreting the molecular interactions in Chinese herbal medicine will help to understand the molecular mechanisms of Traditional Chinese medicines (TCM) and predict the new pharmacological effects of TCM. Yet, we still lack a method which could integrate the concerned pieces of parsed knowledge about TCM.

MATERIALS AND METHODS

To solve the problem, a new method named TCM grammar systems was proposed in the present article. The possibility to study the interactions of TCM at the molecular level using TCM grammar systems was explored using Herba Ephedrae Decoction (HED) as an example.

RESULTS

A platform was established based on the formalism of TCM grammar systems. The related molecular network of Herba Ephedrae Decoction (HED) can be extracted automatically. The molecular network indicates that Beta2 adrenergic receptor, Glucocorticoid receptor and Interleukin12 are the relatively important targets for the anti-anaphylaxis asthma function of HED. Moreover, the anti-anaphylaxis asthma function of HED is also related with suppressing inflammation process. The results show the feasibility using TCM grammar systems to interpret the molecular mechanism of TCM. Although the results obtained depend on the database absolutely, recombination of existing knowledge in this method provides new insight for interpreting the molecular mechanism of TCM.

CONCLUSIONS

TCM grammar systems could aid the interpretation of the molecular interactions in TCM to some extent. Moreover, it might be useful to predict the new pharmacological effects of TCM. The method is an in silico technology. In association with the experimental techniques, this method will play an important role in the understanding of the molecular mechanisms of TCM.

Integrated computational model of cell cycle and checkpoint reveals different essential roles of Aurora-A and Plk1 in mitotic entry

Understanding the regulation of mitotic entry is one of the most important goals of modern cell biology, and computational modeling of mitotic entry has been a subject of several recent studies. However, there are still many regulation mechanisms that remain poorly characterized. Two crucial aspects are how mitotic entry is controlled by its upstream regulators Aurora-A and Plk1, and how mitotic entry is coordinated with other biological events, especially G2/M checkpoint. In this context, we reconstructed a comprehensive computational model that integrates the mitotic entry network and the G2/M checkpoint system. Computational simulation of this model and subsequent experimental verification revealed that Aurora-A and Plk1 are redundant to the activation of cyclin B/Cdk1 during normal mitotic entry, but become especially important for cyclin B/Cdk1 activation during G2/M checkpoint recovery. Further analysis indicated that, in response to DNA damage, Chk1-mediated network rewiring makes cyclin B/Cdk1 more sensitive to the down-regulation of Aurora-A and Plk1. In addition, we demonstrated that concurrently targeting Aurora-A and Plk1 during G2/M checkpoint recovery achieves a synergistic effect, which suggests the combinational use of Aurora-A and Plk1 inhibitors after chemotherapy or radiotherapy. Thus, the results presented here provide novel insights into the regulation mechanism of mitotic entry and have potential value in cancer therapy.

QSAR studies on aminothiazole derivatives as aurora a kinase inhibitors

Quantitative structure-activity relationship studies on 54 aminothiazole derivatives as Aurora A kinase inhibitors were performed to explore the important factors affecting their biologic activity. For 2D-quantitative structure-activity relationship study, genetic algorithm combined with multiple linear regression was used to select significant molecular descriptors. The MLR model gave squared correlation coefficient of 0.828 and squared cross-validated correlation coefficient of 0.771 for the training set compounds. Comparative molecular field analysis and comparative molecular similarity indices analysis were used to develop 3D-quantitative structure-activity relationship models. The comparative molecular field analysis model gave cross-validated correlation coefficient q² of 0.695 and non-cross-validated correlation coefficient r² of 0.977. For comparative molecular similarity indices analysis model, the corresponding q² and r² were 0.698 and 0.960, respectively. The proposed 3D-quantitative structure-activity relationship models were validated by the test set compounds not used in the modeling process, with r²(pred) values of 0.788 for comparative molecular field analysis and 0.798 for comparative molecular similarity indices analysis. The 3D contour maps suggested that further modification of the aniline group of compound 22 considering electrostatic, hydrophobic and hydrogen bond properties would influence the inhibitory activity. The results from quantitative structure-activity relationship models would be very useful to understand the structure-activity relationship of these inhibitors and to guide the further structural modification of new potential inhibitors.

Virtual screening of selective multitarget kinase inhibitors by combinatorial support vector machines

Multitarget agents have been increasingly explored for enhancing efficacy and reducing countertarget activities and toxicities. Efficient virtual screening (VS) tools for searching selective multitarget agents are desired. Combinatorial support vector machines (C-SVM) were tested as VS tools for searching dual-inhibitors of 11 combinations of 9 anticancer kinase targets (EGFR, VEGFR, PDGFR, Src, FGFR, Lck, CDK1, CDK2, GSK3). C-SVM trained on 233-1,316 non-dual-inhibitors correctly identified 26.8%-57.3% (majority >36%) of the 56-230 intra-kinase-group dual-inhibitors (equivalent to the 50-70% yields of two independent individual target VS tools), and 12.2% of the 41 inter-kinase-group dual-inhibitors. C-SVM were fairly selective in misidentifying as dual-inhibitors 3.7%-48.1% (majority <20%) of the 233-1,316 non-dual-inhibitors of the same kinase pairs and 0.98%-4.77% of the 3,971-5,180 inhibitors of other kinases. C-SVM produced low false-hit rates in misidentifying as dual-inhibitors 1,746-4,817 (0.013%-0.036%) of the 13.56 M PubChem compounds, 12-175 (0.007%-0.104%) of the 168 K MDDR compounds, and 0-84 (0.0%-2.9%) of the 19,495-38,483 MDDR compounds similar to the known dual-inhibitors. C-SVM was compared to other VS methods Surflex-Dock, DOCK Blaster, kNN and PNN against the same sets of kinase inhibitors and the full set or subset of the 1.02 M Zinc clean-leads data set. C-SVM produced comparable dual-inhibitor yields, slightly better false-hit rates for kinase inhibitors, and significantly lower false-hit rates for the Zinc clean-leads data set. Combinatorial SVM showed promising potential for searching selective multitarget agents against intra-kinase-group kinases without explicit knowledge of multitarget agents.

In-silico approaches to multi-target drug discovery : computer aided multi-target drug design, multi-target virtual screening

Multi-target drugs against selective multiple targets improve therapeutic efficacy, safety and resistance profiles by collective regulations of a primary therapeutic target together with compensatory elements and resistance activities. Efforts have been made to employ in-silico methods for facilitating the search and design of selective multi-target agents. These methods have shown promising potential in facilitating drug discovery directed at selective multiple targets.

Pharmacophore modeling and virtual screening studies of checkpoint kinase 1 inhibitors

In this study, chemical feature-based 3-dimensional (3D) pharmacophore models of Checkpoint kinase 1 (Chk1) inhibitors were developed based on the known inhibitors of Chk1. The best pharmacophore model Hypo1 was characterized by the best correlation coefficient (0.9577), and the lowest root mean square deviation (0.8871). Hypo1 consists of one hydrogen-bond acceptor, one hydrogen-bond donor, and two hydrophobic features, as well as one excluded volume. This pharmacophore model was further validated by both test set and cross validation methods. A comparison analysis of Hypo1 with chemical features in the active site of Chk1 indicates that the pharmacophore model Hypo1 can correctly reflect the interactions between Chk1 and its ligands. Then Hypo1 was used to screen chemical databases, including Specs and Chinese Nature Product Database (CNPD) for potential lead compounds. The hit compounds were subsequently subjected to filtering by Lipinski's rule of five and docking study to refine the retrieved hits. Finally some of the most potent (estimated) compounds were selected from the final refined hits and suggested for further experimental investigation.

Structure-based drug design of novel Aurora kinase A inhibitors: structural basis for potency and specificity

Aurora kinases have emerged as attractive targets for the design of anticancer drugs. Through structure-based virtual screening, novel pyrazole hit 8a was identified as Aurora kinase A inhibitor (IC(50) = 15.1 microM). X-ray cocrystal structure of 8a in complex with Aurora A protein revealed the C-4 position ethyl carboxylate side chain as a possible modification site for improving the potency. On the basis of this insight, bioisosteric replacement of the ester with amide linkage and changing the ethyl substituent to hydrophobic 3-acetamidophenyl ring led to the identification of 12w with a approximately 450-fold improved Aurora kinase A inhibition potency (IC(50) = 33 nM), compared to 8a. Compound 12w showed selective inhibition of Aurora A kinase over Aurora B/C, which might be due to the presence of a unique H-bond interaction between the 3-acetamido group and the Aurora A nonconserved Thr217 residue, which in Aurora B/C is Glu and found to sterically clash with the 3-acetamido group in modeling studies.

Pharmacophore modeling study based on known spleen tyrosine kinase inhibitors together with virtual screening for identifying novel inhibitors

In this investigation, chemical features based 3D pharmacophore models were developed based on the known inhibitors of Spleen tyrosine kinase (Syk) with the aid of hiphop and hyporefine modules within catalyst. The best quantitative pharmacophore model, Hypo1, was used as a 3D structural query for retrieving potential inhibitors from chemical databases including Specs, NCI, MayBridge, and Chinese Nature Product Database (CNPD). The hit compounds were subsequently subjected to filtering by Lipinski's rule of five and docking studies to refine the retrieved hits. Finally 30 compounds were selected from the top ranked hit compounds and conducted an in vitro kinase inhibitory assay. Six compounds showed a good inhibitory potency against Syk, which have been selected for further investigation.