Identification of novel drug scaffolds for inhibition of SARS-CoV 3-Chymotrypsin-like protease using virtual and high-throughput screenings

We have used a combination of virtual screening (VS) and high-throughput screening (HTS) techniques to identify novel, non-peptidic small molecule inhibitors against human SARS-CoV 3CLpro. A structure-based VS approach integrating docking and pharmacophore based methods was employed to computationally screen 621,000 compounds from the ZINC library. The screening protocol was validated using known 3CLpro inhibitors and was optimized for speed, improved selectivity, and for accommodating receptor flexibility. Subsequently, a fluorescence-based enzymatic HTS assay was developed and optimized to experimentally screen approximately 41,000 compounds from four structurally diverse libraries chosen mainly based on the VS results. False positives from initial HTS hits were eliminated by a secondary orthogonal binding analysis using surface plasmon resonance (SPR). The campaign identified a reversible small molecule inhibitor exhibiting mixed-type inhibition with a K_i value of 11.1 μM. Together, these results validate our protocols as suitable approaches to screen virtual and chemical libraries, and the newly identified compound reported in our study represents a promising structural scaffold to pursue for further SARS-CoV 3CLpro inhibitor development.     

Binding mode analysis between membrane dipeptidase and its substrates

Membrane dipeptidase (MDP) is a membrane-bound glycoprotein involved in the hydrolysis of dipeptides, showing specific activity for dipeptides. Recent study showed that membrane dipeptidase was the receptor for a lung-targeting peptide identified by in vivo phage display and the crystal structure of the cilastatin-liganded human renal dipeptidase was determined. We performed a pharmacophore-based virtual screening and molecular docking in order to characterize MDP binding interactions with its substrates. A ligand-based pharmacophore model represented only a slight enrichment because of a lacked variety and centralization of ligand features. Molecular docking study was used to incorporate ligand conformational changes in the binding sites and the performance was much better than pharmacophore model; only 10% of compound library needed to be screened in order to detect all included active compounds. In addition, we found that one of the crystallographically observed water molecules plays an important role in the binding modes between MDP and its substrate.     

Computational approach to the identification of novel Aurora-A inhibitors

Aurora kinase A has been emerging as a key therapeutic target for the design of anticancer drugs. For the purpose of finding biologically active and novel compounds and providing new ideas for drug-design, we performed virtual screening using commercially available databases. A three-dimensional common feature pharmacophore model was developed with the HipHop program provided in the Catalyst software package, and this model was used as a query for screening the databases. A recursive partitioning (RP) model was developed as a filtering system, which was able to classify active and inactive compounds. Eventually, a step-wise virtual screening procedure was conducted by applying the common feature pharmacophore and the RP model in succession to discover novel potent Aurora-A inhibitors. A total of 68 compounds were selected for testing of their in vitro anticancer activities against various human cancer cell lines. Based on the activity data, we have identified fifteen compounds that warrant further investigation. Several compounds have a high inhibition rate (above 80% at 10 ??M) and a GI₅₀ lower than 5 ??M for the cell lines DU145 and HT29. Enzyme assay for these compounds identified hits with micro molar activity. Compound C11 has the highest activity (IC₅₀ = 5.09 ??M). The hits obtained from this screening scheme could be potential drug candidates after further optimization.     

Virtual screening and bioassay study of novel inhibitors for dengue virus mRNA cap (nucleoside-2'O)-methyltransferase

We report high-throughput structure-based virtual screening of putative Flavivirus 2′-O-methyltransferase inhibitors together with results from subsequent bioassay tests of selected compounds. Potential inhibitors for the S-adenosylmethionine binding site were explored using 2D similarity searching, pharmacophore filtering and docking. The inhibitory activities of 15 top-ranking compounds from the docking calculations were tested on a recombinant methyltransferase with the RNA substrate ^7MeGpppAC₅. Local and global docking simulations were combined to estimate the ligand selectivity for the target site. The results of the combined computational and experimental screening identified a novel inhibitor, with a previously unknown scaffold, that has an IC₅₀ value of 60 μM.     

Discovery of a novel pyrazole series of group X secreted phospholipase A2 inhibitor (sPLA2X) via fragment based virtual screening

The discovery of potent novel pyrazole containing group X secreted phospholipase A2 inhibitors via structure based virtual screening is reported. Docking was applied on a large set of in-house fragment collection and pharmacophore feature matching was used to filter docking poses. The selected virtual screening hits was run in NMR screening, a potent pyrazole containing fragment hit was identified and confirmed by its complex X-ray structure and the following biochemical assay result. Expansion on the fragment hit has led to further improvement of potency while maintaining high ligand efficiency, thus supporting the further development of this chemical series.     

Virtual screening and biochemical evaluation to identify new inhibitors of mammalian target of rapamycin (mTOR)

Mammalian target of rapamycin (mTOR) is a promising target for the development of anticancer medicines. Here, we report the first example for a successful application of the structure-based virtual screening to identify new mTOR inhibitors. Using the scoring function improved by implementing the ligand solvation effects on protein–ligand association, six novel mTOR inhibitors are found with IC₅₀ values ranging from 8 to 60 μM. Because these new inhibitors are also computationally screened for having desirable physicochemical properties as a drug candidate, they deserve consideration for further development by structure–activity relationship studies to optimize the inhibitory and anticancer activities. Structural features relevant to the stabilization of the inhibitors in the ATP-binding site of mTOR are addressed in detail.     

Potent and novel 11β-HSD1 inhibitors identified from shape and docking based virtual screening

Several potent and novel 11β-hydroxysteroid dehydrogenase 1 (11β-HSD1) inhibitors were discovered from in silico screening the commercially available Maybridge database. Among them, seven hit compounds showed good affinity, with IC(50) values lower than 100 nM and the best one 3.7 nM. To select the lead for further optimization, computational ADME/T prediction, the CYP3A4 inhibition and 11β-HSD1 over 11β-HSD2 selectivity test were also performed. Taking all of the above factors into consideration, two promising compounds were selected as lead structures for further development. The employed hierarchical virtual screening protocol not only demonstrates its efficiency, but also provides novel and selective compounds for developing 11β-HSD1 inhibitors to protect against metabolic syndrome.     

Design and development of topoisomerase inhibitors using molecular modelling studies

Topoisomerase inhibitors are used as anticancer and antibacterial agents. A series of novel 2,4,6-tri-substituted pyridine derivatives reported as topoisomerase inhibitors were used for quantitative structure–activity relationship (QSAR) study. In order to understand the structural requirement of these topoisomerase inhibitors, a ligand-based pharmacophore and atom-based 3D-QSAR model have been developed. A five-point pharmacophore with one hydrophobic group (H4), four aromatic rings (R5, R6, R7 and R8) was obtained. The pharmacophore hypothesis yielded a 3D-QSAR model with good partial least-square (PLS) statistic results. The training set correlation is characterized by PLS factors (r² = 0.7892, SD = 0.2948, F = 49.9, P = 1.379). The test set correlation is characterized by PLS factors (q² = 0.7776, root mean squared error = 0.2764, Pearson R = 0.8926). The docking study revealed the binding orientations of these inhibitors at active site amino acid residues of topoisomerases enzyme. The results of pharmacophore hypothesis and 3D-QSAR provided the detail structural insights as well as highlighted the important binding features of novel 2,4,6-tri-substituted pyridine derivatives and can be developed as potent topoisomerase inhibitors.

Figure

Open in a separate windowKey structural requirement for topoisomerase activity     

结合分子相似性、药效团和分子对接筛选新的HIV-1蛋白酶抑制剂

结合分子相似性、药效团和分子对接建立兼顾计算效率和预测准确度的HIV-1蛋白酶抑制剂筛选方法。首先通过对现有HIV-1蛋白酶抑制剂分子进行相似性分析,选取代表性的HIV-1蛋白酶抑制剂作为模板分子,构建和优化药效团模型,并从1万个化合物中优先筛选出500个化合物。而后采用分子对接方法进一步考察化合物与HIV-1蛋白酶结合情况,得到4个新的活性候选化合物,并进行其结合自由能计算和抗突变性分析。结果表明新候选化合物ST025723和HIV-1蛋白酶表现出较好的相互作用和抗突变性,具有深入研究的价值,同时也证明分子相似性、药效团和分子对接相结合能够快速有效地发现新颖活性候选化合物。     

Structure-based identification of novel PPAR gamma ligands

Peroxisome proliferator-activated receptor γ (PPARγ) is a nuclear receptor with an important role in the glucose metabolism and a target for type 2 diabetes mellitus therapy. The recent findings relating the use of the receptor full agonist rosiglitazone and the incidence of myocardial infarction raised concerns regarding whether receptor activation can actually be useful for diabetes management. The discovery of MRL-24 and GQ-16, ligands that can partially activate PPARγ and prevent weight gain and fluid retention, showed that a submaximal receptor activation can be a goal in the development of new ligands for PPARγ. Additionally, two previously described receptor antagonists, SR-202 and BADGE, were also shown to improve insulin sensitivity and decrease TNF-α level, revealing that receptor antagonism may also be an approach to pursue. Here, we used a structure-based approach to screen the subset ‘Drugs-Now’ of ZINC database. Fifteen ligands were selected after visual inspection and tested for their ability to bind to PPARγ. A benzoimidazol acetate, a bromobenzyl-thio-tetrazol benzoate and a [[2-[(1,3-dioxoinden-2-ylidene)methyl]phenoxy]methyl]benzoate were identified as PPARγ ligands, with IC₅₀ values smaller than 10 μM. Molecular dynamic simulations showed that the residues H323, H449, Y327, Y473, K367 and S289 are key structural elements for the molecular recognition of these ligands and the polar arm of PPARγ binding pocket.     

Design checkpoint kinase 2 inhibitors by pharmacophore modeling and virtual screening techniques

Damage to DNA is caused by ionizing radiation, genotoxic chemicals or collapsed replication forks. When DNA is damaged or cells fail to respond, a mutation that is associated with breast or ovarian cancer may occur. Mammalian cells control and stabilize the genome using a cell cycle checkpoint to prevent damage to DNA or to repair damaged DNA. Checkpoint kinase 2 (Chk2) is one of the important kinases, which strongly affects DNA-damage and plays an important role in the response to the breakage of DNA double-strands and related lesions. Therefore, this study concerns Chk2. Its purpose is to find potential inhibitors using the pharmacophore hypotheses (PhModels) and virtual screening techniques. PhModels can identify inhibitors with high biological activities and virtual screening techniques are used to screen the database of the National Cancer Institute (NCI) to retrieve compounds that exhibit all of the pharmacophoric features of potential inhibitors with high interaction energy. Ten PhModels were generated using the HypoGen best algorithm. The established PhModel, Hypo01, was evaluated by performing a cost function analysis of its correlation coefficient (r), root mean square deviation (RMSD), cost difference, and configuration cost, with the values 0.955, 1.28, 192.51, and 16.07, respectively. The result of Fischer’s cross-validation test for the Hypo01 model yielded a 95% confidence level, and the correlation coefficient of the testing set (r_test) had a best value of 0.81. The potential inhibitors were then chosen from the NCI database by Hypo01 model screening and molecular docking using the cdocker docking program. Finally, the selected compounds exhibited the identified pharmacophoric features and had a high interaction energy between the ligand and the receptor. Eighty-three potential inhibitors for Chk2 are retrieved for further study.     

Exploration of new scaffolds as potential MAO-A inhibitors using pharmacophore and 3D-QSAR based in silico screening

Monoamine oxidase-A (MAO-A) inhibitors are of particular importance in the treatment of depressive disorders. Herein described is pharmacophore generation and atom-based 3D-QSAR analysis of previously reported pyrrole based MAO-A inhibitors in order to get insight into their structural requirements responsible for high affinity. The best pharmacophore model generated consisted of four features DHHR: a hydrogen bond donor (D), two hydrophobic groups (H) and an aromatic ring (R). Based on model generated, a statistically valid 3D-QSAR with good predictability was developed. Derived pharmacophore was used as a query to search Zinc ‘clean drug-like’ database. Hits retrieved were passed progressively through filters like fitness score, predicted activity and docking scores. The survived hits present new scaffolds with a potential for MAO-A inhibition.     

Structure-based design of eugenol analogs as potential estrogen receptor antagonists

Eugenol is an essential oil mainly found in the buds and leaves of clove (Syzygium aromaticum (L.) Merrill and Perry), which has been reported to have activity on inhibition of cell proliferation and apoptosis induction in human MCF-7 breast cancer cells. This biological activity is correlated to its activity as an estrogen receptor antagonist. In this article, we present the construction and validation of structure-based virtual screening (SBVS) protocols to identify the potent estrogen receptor α (ER) antagonists. The selected protocol, which gave acceptable enrichment factors as a virtual screening protocol, subsequently used to virtually screen eugenol, its analogs and their dimers. Based on the virtual screening results, dimer eugenol of 4-[4-hydroxy-3-(prop-2-en-1- yl)phenyl]-2-(prop-2-en-1-yl)phenol is recommended to be developed further in order to discover novel and potent ER antagonists.     

Design, synthesis and biological evaluation of small molecule inhibitors of CD4-gp120 binding based on virtual screening

The low-molecular-weight compound JRC-II-191 inhibits infection of HIV-1 by blocking the binding of the HIV-1 envelope glycoprotein gp120 to the CD4 receptor and is therefore an important lead in the development of a potent viral entry inhibitor. Reported here is the use of two orthogonal screening methods, gold docking and ROCS shape-based similarity searching, to identify amine-building blocks that, when conjugated to the core scaffold, yield novel analogs that maintain similar affinity for gp120. Use of this computational approach to expand SAR produced analogs of equal inhibitory activity but with diverse capacity to enhance viral infection. The novel analogs provide additional lead scaffolds for the development of HIV-1 entry inhibitors that employ protein-ligand interactions in the vestibule of gp120 Phe 43 cavity.