Identification of novel polo-like kinase 1 inhibitors by a hybrid virtual screening

Polo-like kinase 1 is an important and attractive oncological target that plays a key role in mitosis and cytokinesis. A combined pharmacophore- and docking-based virtual screening was performed to identify novel polo-like kinase 1 inhibitors. A total of 34 hit compounds were selected and tested in vitro, and some compounds showed inhibition of polo-like kinase 1 and human tumor cell growth. The most potent compound (66) inhibited polo-like kinase 1 with an IC(50) value of 6.99 μm. The docked binding models of two hit compounds were discussed in detail. These compounds contained novel chemical scaffolds and may be used as foundations for the development of novel classes of polo-like kinase 1 inhibitors.     

New uses for old drugs: pharmacophore-based screening for the discovery of P-glycoprotein inhibitors

P-glycoprotein (P-gp) is one of the best characterized transporters responsible for the multidrug resistance phenotype exhibited by cancer cells. Therefore, there is widespread interest in elucidating whether existing drugs are candidate P-gp substrates or inhibitors. With this aim, a pharmacophore model was created based on known P-gp inhibitors and it was used to screen a database of existing drugs. The P-gp modulatory activity of the best hits was evaluated by several methods such as the rhodamine-123 accumulation assay using K562Dox cell line, and a P-gp ATPase activity assay. The ability of these compounds to enhance the cytotoxicity of doxorubicin was assessed with the sulphorhodamine-B assay. Of the 21 hit compounds selected in silico, 12 were found to significantly increase the intracellular accumulation of Rhodamine-123, a P-gp substrate. In addition, amoxapine and loxapine, two tetracyclic antidepressant drugs, were discovered to be potent non-competitive inhibitors of P-gp, causing a 3.5-fold decrease in the doxorubicin GI(50) in K562Dox cell line. The overall results provide important clues for the non-label use of known drugs as inhibitors of P-gp. Potent inhibitors with a dibenzoxazepine scaffold emerged from this study and they will be further investigated in order to develop new P-gp inhibitors.     

Discovery of novel DPP IV inhibitors: application of pharmacophore-based virtual screening

Dipeptidyl peptidase IV (DPP-IV) is a potential drug target for type-2 diabetes and DPP-IV inhibitors are known to efficiently improve glucose tolerance. In the present study, pharmacophore model for a set of 29 DPP-IV inhibitors was generated by ligand-based pharmacophore generation process. The best hypothesis, hypo 1, consisting of four chemical features, namely, one hydrogen bond donor, one hydrogen bond acceptor, one hydrophobe and one ring aromatic was validated by cost function analysis, test set prediction and Fischer test. The validated pharmacophore model was then used for searching new lead compounds from Maybridge and NCI database. Four compounds (CD01797, CD06202, CD02493, and AW01077) from Maybridge database and three compounds (NSC997, NSC2450, and NSC5815) from NCI database were identified as structurally diverse druggable novel leads with nM activity against DPP-IV.     

Discovery, synthesis and evaluation of novel cholesterol absorption inhibitors

Chemical-based common feature pharmacophore modelling of Niemann Pick C1 Like 1 inhibitors was performed to provide some insights on the important pharmacophore features essential for Niemann Pick C1 Like 1 inhibition using Discovery Studio V2.5. After in-house database screening, a new series of substituted oxazolidinones, selected from the top ranked hits, have been synthesized and evaluated as novel cholesterol absorption inhibitors. All compounds demonstrated effect of different degrees in lowering the total cholesterol in serum, especially compounds 1a, 2a and 2d, the potency of which was comparable to that of ezetimibe. It was also found that 1a, 1d and 2d could raise high-density lipoprotein cholesterol levels markedly. Interestingly, compounds 2a-2f appeared to have the moderate potential to lower triglyceride levels, which were superior to that of normal cholesterol absorption inhibitors including ezetimibe.     

The discovery of novel vascular endothelial growth factor receptor tyrosine kinases inhibitors: pharmacophore modeling, virtual screening and docking studies

We have applied pharmacophore generation, database searching and docking methodologies to discover new structures for the design of vascular endothelial growth factor receptors, the tyrosine kinase insert domain-containing receptor kinase inhibitors. The chemical function based pharmacophore models were built for kinase insert domain-containing receptor kinase inhibitors from a set of 10 known inhibitors using the algorithm HipHop, which is implemented in the CATALYST software. The highest scoring HipHop model consists of four features: one hydrophobic, one hydrogen bond acceptor, one hydrogen bond donor and one ring aromatic function. Using the algorithm CatShape within CATALYST, the bound conformation of 4-amino-furo [2, 3-d] pyrimidine binding to kinase insert domain-containing receptor kinase was used to generate a shape query. A merged shape and hypothesis query that is in an appropriate alignment was then built. The combined shape and hypothesis model was used as a query to search Maybridge database for other potential lead compounds. A total of 39 compounds were retrieved as hits. The hits obtained were docked into kinase insert domain-containing receptor kinase active site. One novel potential lead was proposed based on CATALYST fit value, LigandFit docking scores, and examination of how the hit retain key interactions known to be required for kinase binding. This compound inhibited vascular endothelial growth factor stimulated kinase insert domain-containing receptor phosphorylation in human umbilical vein endothelial cells.     

Pharmacophore modelling and virtual screening for identification of new Aurora-A kinase inhibitors

Aurora-A has been identified as one of the most attractive targets for cancer therapy and a considerable number of Aurora-A inhibitors have been reported recently. In order to clarify the essential structure-activity relationship for the known Aurora-A inhibitors as well as identify new lead compounds against Aurora-A, 3D pharmacophore models were developed based on the known inhibitors. The best hypothesis, Hypo1, 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, 39 compounds were purchased for further in vitro assay against several human tumour cell lines including A549, MCF-7, HepG2 and PC-3, in which Aurora-A is overexpressed. Two compounds show very low micromolar inhibition potency against some of these tumour cells. And they have been selected for further investigation.     

3-heptylamino-5-phenylpyridazine derivatives as analogues of Acyl-CoA: cholesterol acyltransferase inhibitors containing the N-heptyl-N'-arylureidic moiety

A series of novel Acyl-CoA: cholesterol acyltransferase (ACAT) inhibitors 8a-f was synthesized; the substances were characterized by the presence of a 2,5-dimethylpyrazin-3-yl moiety at one end and a 3-heptylamino-5-phenylpyridazine system at the other one, linked through linear alkyl spacers of different length. The new derivatives were designed based on the hypothesis that the 3-amino-5-phenylpyridazine moiety could mimic the aryl substituted urea, which was present in a number of ACAT inhibitors previously described. The choice of the 2,5-dimethylpyrazin-3-yl substituent was supported by a preliminary investigation, which indicated that this moiety is the most powerful in conferring ACAT inhibitory properties to the new series. The pharmacological results proved the idea to be sound. Finally, compounds 9a-c, lacking the phenylpyridazine moiety were prepared and tested to further strengthen our hypothesis.     

Identification of novel inhibitors of dipeptidylcarboxypeptidase of Leishmania donovani via ligand-based virtual screening and biological evaluation

Current treatment of leishmaniasis is based on chemotherapy, which relies on a handful of drugs with serious limitations, such as high cost, toxicity, and lack of efficacy in endemic regions. Therefore, development of new, effective, and affordable anti-leishmanial drugs is a global health priority. Dipeptidylcarboxypeptidase has been characterized and established as a drug target for antileishmanial drug discovery. We virtually screened a large chemical library of 15 452 compounds against a 3D model of dipeptidylcarboxypeptidase to identify novel inhibitors. The initial virtual screening using a ligand-based pharmacophore model identified 103 compounds. Forty-six compounds were shortlisted based on the docking scores and other scoring functions. Further, these compounds were subjected to biological assay, and four of them belonging to two chemical classes were identified as the lead compounds. Identification of these novel and chemically diverse inhibitors should provide leads to be optimized into candidates to treat these protozoan infections.     

In silico identification,synthesis and biological evaluation of novel tetrazole inhibitors of MurB

In the context of antibacterial drug discovery resurgence, novel therapeutic targets and new compounds with alternative mechanisms of action are of paramount importance. We focused on UDP‐N‐acetylenolpyruvylglucosamine reductase (i.e. MurB), an underexploited target enzyme that is involved in early steps of bacterial peptidoglycan biosynthesis. On the basis of the recently reported crystal structure of MurB in complex with NADP⁺, a pharmacophore model was generated and used in a virtual screening campaign with combined structure‐based and ligand‐based approaches. To explore chemical space around hit compounds, further similarity search and organic synthesis were employed to obtain several compounds with micromolar IC₅₀ values on MurB. The best inhibitors in the reported series of 5‐substituted tetrazol‐2‐yl acetamides were compounds 13 , 26 and 30 with IC₅₀ values of 34, 28 and 25 μm , respectively. None of the reported compounds possessed in vitro antimicrobial activity against Staphylococcus aureus and Escherichia coli.     

Proposing novel MDM2 inhibitors: Combined physics‐driven high‐throughput virtual screening and in vitro studies

The mouse double minute 2 (MDM2) protein acts as a negative regulator of the p53 tumor suppressor. It directly binds to the N terminus of p53 and promotes p53 ubiquitination and degradation. Since the most common p53‐suppressing mechanisms involve the MDM2, proposing novel inhibitors has been the focus of many in silico and also experimental studies. Thus, here we screened around 500,000 small organic molecules from Enamine database at the binding pocket of this oncogenic target. The screening was achieved systematically with starting from the high‐throughput virtual screening method followed by more sophisticated docking approaches. The initial high number of screened molecules was reduced to 100 hits which then were studied extensively for their therapeutic activity and pharmacokinetic properties using binary QSAR models. The structural and dynamical profiles of the selected molecules at the binding pocket of the target were studied thoroughly by all‐atom molecular dynamics simulations. The free energy of the binding of the hit molecules was estimated by the MM/GBSA method. Based on docking simulations, binary QSAR model results, and free energy calculations, 11 compounds ( E1 – E11 ) were selected for in vitro studies. HUVEC vascular endothelium, colon cancer, and breast cancer cell lines were used for testing the binding affinities of the identified hits and for further cellular effects on human cancer cell. Based on in vitro studies, six compounds ( E1 , E2 , E5 , E6 , E9 , and E11 ) in breast cancer cell lines and six compounds ( E1 , E2 , E5 , E6 , E8 , and E10 ) in colon cancer cell lines were found as active. Our results showed that these compounds inhibit proliferation and lead to apoptosis.     

Identification of novel antitubulin agents by using a virtual screening approach based on a 7-point pharmacophore model of the tubulin colchi-site

Tubulin inhibition represents an established target in the field of anticancer research, and over the last 20 years, an intensive search for new antimicrotubule agents has occurred. Indeed, in silico models have been presented that might aid the discovery of novel agents. Among these, a 7-point pharmacophore model has been recently proposed. As a formal proof of this model, we carried out a ligand-based virtual screening on the colchicine-binding site. In vitro testing demonstrated that two compounds displayed a cytotoxic profile on neuroblastoma cancer cells (SH-SY5H) and one had an antitubulinic profile.     

Identification of promising DNA GyrB inhibitors for Tuberculosis using pharmacophore‐based virtual screening,molecular docking and molecular dynamics studies

In this study, we searched for potential DNA GyrB inhibitors using pharmacophore‐based virtual screening followed by molecular docking and molecular dynamics simulation approaches. For this purpose, a set of 248 DNA GyrB inhibitors was collected from the literature and a well‐validated pharmacophore model was generated. The best pharmacophore model explained that two each of hydrogen bond acceptors and hydrophobicity regions were critical for inhibition of DNA GyrB. Good statistical results of the pharmacophore model indicated that the model was robust in nature. Virtual screening of molecular databases revealed three molecules as potential antimycobacterial agents. The final screened promising compounds were evaluated in molecular docking and molecular dynamics simulation studies. In the molecular dynamics studies, RMSD and RMSF values undoubtedly explained that the screened compounds formed stable complexes with DNA GyrB. Therefore, it can be concluded that the compounds identified may have potential for the treatment of TB.     

Ligand-based virtual screening and molecular docking studies to identify the critical chemical features of potent cathepsin D inhibitors

Cathepsin D is a major component of lysosomes and plays a major role in catabolism and degenerative diseases. The quantitative structure-activity relationship study was used to explore the critical chemical features of cathepsin D inhibitors. Top 10 hypotheses were built based on 36 known cathepsin D inhibitors using HypoGen/Discovery Studio v2.5. The best hypothesis Hypo1 consists of three hydrophobic, one hydrogen bond acceptor lipid, and one hydrogen bond acceptor features. The selected Hypo1 model was cross-validated using Fischer's randomization method to identify the strong correlation between experimental and predicted activity value as well as the test set and decoy sets used to validate its predictability. Moreover, the best hypothesis was used as a 3D query in virtual screening of Scaffold database. Subsequently, the screened hit molecules were filtered by applying Lipinski's rule of five, absorption, distribution, metabolism, and toxicity, and molecular docking studies. Finally, 49 compounds were obtained as potent cathepsin D inhibitors based on the consensus scoring values, critical interactions with protein active site residues, and predicted activity values. Thus, we suggest that the application of Hypo1 could assist in the selection of potent cathepsin D leads from various databases. Hence, this model was used as a valuable tool to design new candidate for cathepsin D inhibitors.     

Investigation of potential glycogen synthase kinase 3 inhibitors using pharmacophore mapping and virtual screening

Glycogen synthase kinase-3 is a serine/threonine kinase that has attracted significant drug discovery attention in recent years. To investigate the identification of new potential glycogen synthase kinase-3 inhibitors, a pharmacophore mapping study was carried out using a set of 21 structurally diverse glycogen synthase kinase-3 inhibitors. A hypothesis containing four features: two hydrophobic, one hydrogen bond donor and another hydrogen bond acceptor was found to be the best from the 10 common feature hypotheses produced by HipHop module of Catalyst. The best hypothesis has a high cost of 156.592 and higher best fit values were obtained for the 21 inhibitors using this best hypothesis than the other HipHop hypotheses. The best hypothesis was then used to screen electronically the NCI2000 database. The hits obtained were docked into glycogen synthase kinase-3beta active site. A total of five novel potential leads were proposed after: (i) visual examination of how well they dock into the glycogen synthase kinase-3beta-binding site, (ii) comparative analysis of their FlexX, G-Score, PMF-Score, ChemScore and D-Scores values, (iii) comparison of their best fit value with the known inhibitors and (iv) examination of the how the hits retain interactions with the important amino acid residues of glycogen synthase kinase-3beta-binding site.     

Discovery of novel Bruton's tyrosine kinase inhibitors using a hybrid protocol of virtual screening approaches based on SVM model, pharmacophore and molecular docking

Bruton's tyrosine kinase has emerged as a potential target for the treatment for B-cell malignancies and autoimmune diseases. Discovery of Bruton's tyrosine kinase inhibitors has thus attracted much attention recently. In this investigation, we introduced a hybrid protocol of virtual screening methods including support vector machine model-based virtual screening, pharmacophore model-based virtual screening and docking-based virtual screening for retrieving new Bruton's tyrosine kinase inhibitors from commercially available chemical databases. Performances of the hybrid virtual screening approach were evaluated against a test set, which results showed that the hybrid virtual screening approach significantly shortened the overall screening time, and considerably increased the hit rate and enrichment factor compared with the individual method (SB-VS, PB-VS and DB-VS) or their combinations by twos. This hybrid virtual screening approach was then applied to screen several chemical databases including Specs (202,408 compounds) and Enamine (980,000 compounds) databases. Thirty-nine compounds were selected from the final hits and have been shifted to experimental studies.     

Pharmacophore-based virtual screening and density functional theory approach to identifying novel butyrylcholinesterase inhibitors

Aim:

To identify the critical chemical features, with reliable geometric constraints, that contributes to the inhibition of butyrylcholinesterase (BChE) function.

Methods:

Ligand-based pharmacophore modeling was used to identify the critical chemical features of BChE inhibitors. The generated pharmacophore model was validated using various techniques, such as Fischer''s randomization method, test set, and decoy set. The best pharmacophore model was used as a query in virtual screening to identify novel scaffolds that inhibit BChE. Compounds selected by the best hypothesis in the virtual screening were tested for drug-like properties, and molecular docking study was applied to determine the optimal orientation of the hit compounds in the BChE active site. To find the reactivity of the hit compounds, frontier orbital analysis was carried out using density functional theory.

Results:

Based on its correlation coefficient (0.96), root mean square (RMS) deviation (1.01), and total cost (105.72), the quantitative hypothesis Hypo1 consisting of 2 HBA, 1 Hy-Ali, and 1 Hy-Ar was selected as the best hypothesis. Thus, Hypo1 was used as a 3D query in virtual screening of the Maybridge and Chembridge databases. The hit compounds were filtered using ADMET, Lipinski''s Rule of Five, and molecular docking to reduce the number of false positive results. Finally, 33 compounds were selected based on their critical interactions with the significant amino acids in BChE''s active site. To confirm the inhibitors'' potencies, the orbital energies, such as HOMO and LUMO, of the hit compounds and 7 training set compounds were calculated. Among the 33 hit compounds, 10 compounds with the highest HOMO values were selected, and this set was further culled to 5 compounds based on their energy gaps important for stability and energy transfer. From the overall results, 5 hit compounds were confirmed to be potential BChE inhibitors that satisfied all the pharmacophoric features in Hypo1.

Conclusion:

This study pinpoints important chemical features with geometric constraints that contribute to the inhibition of BChE activity. Five compounds are selected as the best hit BchE-inhibitory compounds.     

Structure-based drug design of a novel family of chalcones as PPARα agonists： virtual screening, synthesis, and biological activities in vitro

Aim： To design and synthesize a novel class of peroxisome proliferator-activated receptors （PPAR）ct agonists, which is obtained by the combination of the classi- cal fibrate “head group”, a linker with appropriate length and a chalcone. Methods： Thirty seven compounds were designed and identified employing the virtual screening approach. Six compounds were then selected for synthesis and bioas- say according to the virtual screening results, structural similarity, and synthetic complexity. Results： Six new compounds （4b and 4d-h） were synthesized and bioassayed. All were found to be potent PPARct agonists, compound 4 h being the most prominent with a 50% effective concentration value of 0.06 μmol/L. Condusion： This study provides a promising novel family of chalcones with a potential hypolipidemic effect.     

Identification of novel topoisomerase II alpha inhibitors by virtual screening,molecular docking,and bioassay

Breast cancer is one of the most common tumors, and its treatment still leaves room for improvement. Topoisomerase II alpha is a potential target for the treatment of human diseases such as breast cancer. In this article, we attempted to discover a novel anticancer drug. We have used the topoisomerase II alpha protein-Homo sapiens (Human) to hierarchically screen the Maybridge database. Based on their docking score, the top hit compounds have been assayed for inhibition in a topoisomerase II pBR322 DNA relaxation assay in vitro. Candidate compound 6 (CP6) was found to have the best inhibitory effect for topoisomerase II among the 20 tested compounds. In addition, CP6 had potent cytotoxicity against eight tested tumor cell lines. At the same time, CP6 was shown to have potential anti-multidrug resistance capabilities. This study identifies CP6, which can contribute to the development of new topoisomerase II inhibitors as anticancer agents.     

应用虚拟筛选方法寻找链阳霉素A乙酰转移酶抑制剂

维吉尼亚霉素乙酰转移酶D(VatD)通过灭活链阳霉素A而在链阳霉素耐药性的产生中起重要作用。本研究采用虚拟筛选技术寻找VatD的抑制剂,此VatD抑制剂可以和链阳霉素联合使用,从而提供新的治疗耐药菌感染的方法。作者首次应用基于结构的虚拟筛选方法(分子对接)从含300 000化合物的商业化数据库中筛选对抗VatD底物结合位点的化合物,从200个评分最高的化合物中选取26个测定对VatD酶活性的抑制作用。将构建的质粒pRSET B/vatD转染宿主细胞E.coli(TrxB)用于过表达,纯化的VatD对维吉尼亚霉素M1表现乙酰转移酶活性。26个化合物中有3个对VatD表现抑制作用,IC₅₀分别为168.6,91.0和55.2 μmol·L^-1。其他化合物在反应体系中不溶解和/或对酶活性的抑制作用很小(IC₅₀>200 μmol·L^-1)。本文首次设计VatD的小分子化合物抑制剂,发现了3个有活性的化合物,希望其可作为先导化合物进一步发展为新的对抗链阳霉素耐药性的药物。