Shiliang Li

Pyrimido[4,5‐d]pyrimidin‐4(1H)‐one Derivatives as Selective Inhibitors of EGFR Threonine790 to Methionine790 (T790M) Mutants

The epidermal growth factor receptor (EGFR, erbB1, HER1) has been well-validated as a molecular target in anticancer drug discovery. In non-small-cell lung cancer patients (NSCLCs) harboring active mutations in the EGFR tyrosine kinase domain (L858R and del E746-A750), the first generation inhibitors, gefinitib and erlotinib, have achieved significant clinical benefits but emerging acquired resistance to them has become a major clinical challenge. The “gatekeeper” T790M mutation (threonine!methionine) of EGFR, by which the binding of ATP with the kinase is favored, is one of the primary mechanisms for resistance and plays a role in the circa 50 % of NSCLC patients who acquired clinical resistance. 7] Although the Cys797-chelating irreversible EGFR inhibitors displayed promising potential to overcome EGFR related resistance in animal models, their non-selective inhibition against wild-type EGFR (EGFR) and/or other kinases results in a relatively low maximal-tolerated-dose (MTD) and poor clinical outcomes in human patients. Inhibitors selectively targeting EGFR mutants are an attractive strategy for the clinical management of NSCLC patients with acquired resistance. However, because EGFR and the EGFR mutants share highly similar three-dimensional structures and have almost identical binding affinities with ATP, nearly all of the reported irreversible EGFR inhibitors displayed equal potencies against the T790M mutants and the wild-type enzyme, highlighting the challenge in the search for EGFR mutant-selective inhibitors. Only recently, WZ4002 was reported as a new irreversible EGFR inhibitor displaying moderate selectivity on EGFR mutants over the wild-type kinase. A phase I clinical trial was recently initiated on another moderately mutant-selective EGFR inhibitor CO-1686 (Kd(EGFR )/Kd(EGFR ) = 25, NCT01526928) whose chemical structure was not disclosed, and PKC412 was reported as a novel reversible T790M mutant-selective EGFR inhibitor with promising in vivo efficacy. Herein, we wish to report the successful discovery of novel pyrimido[4,5-d]pyrimidin-4(1H)-onebased EGFR inhibitors with more than 100-fold selectivity over the wild-type kinase. We have successfully designed compounds 1 and 2 (Scheme 1) as novel EGFR inhibitors with low nanomolar IC50 and Kd values. However, these compounds only displayed four-fold selectivity on EGFR mutants over EGFR. The use of conformational constraint is a general strategy with which to improve ligand selectivity for a molecular target, and accordingly a series of pyrimido[4,5d]pyrimidin-4(1H)-one derivatives 3 a–3h with more rigid conformations based on the structure-activity relationship (SAR) studies of compounds 1 and 2 (Scheme 1) were designed. The compounds were readily synthesized by using the similar procedures to that of 3a (Scheme 2; Supporting Information, Scheme S1). Briefly, a direct nucleophilic coupling of commercially available ethyl 2,4-dichloropyrimidine5-carboxylate (4) with tert-butyl-3-aminophenylcarbamate (5) produced ethyl 4-[{3-[(tert-butoxycarbonyl)amino]phenyl}amino]-2-chloropyrimidine-5-carboxylate (6). Hydrolysis of compound 6 with 1m NaOH in a H2O/THF mixed solution yielded the carboxylic acid (7). The condensation of 7 and 8a in the presence of HATU and DIPEA in dry CH2Cl2 gave the intermediate 9a. Compound 9a was coupled with aniline by nucleophilic substitution followed by deprotection with 50% trifluoroacetic acid in CH2Cl2 to yield the key precursor 10a. The new inhibitor 3a was finally obtained by acryloylation of 10a with acryloyl chloride. The binding affinities of the compounds with EGFR and its T790M mutants were determined with an active-sitedependent competition binding assay conducted by Ambit Bioscience, San Diego, USA. The kinase inhibitory activities of the compounds were also evaluated by the well-established [*] T. Xu, L. Zhang, S. Xu, J. Luo, F. Ding, X. Lu, Y. Liu, Z. Tu, Prof. D. Pei, Q. Cai, X. Ren, Prof. K. Ding Institute of Chemical Biology, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences 190 Kaiyuan Avenue, Guangzhou 510530 (China) E-mail: ding_ke@gibh.ac.cn T. Xu, S. Xu University of Chinese Academy of Sciences 19 Yuquan Road, Beijing 100049 (China)

PharmMapper 2017 update: a web server for potential drug target identification with a comprehensive target pharmacophore database

Abstract The PharmMapper online tool is a web server for potential drug target identification by reversed pharmacophore matching the query compound against an in-house pharmacophore model database. The original version of PharmMapper includes more than 7000 target pharmacophores derived from complex crystal structures with corresponding protein target annotations. In this article, we present a new version of the PharmMapper web server, of which the backend pharmacophore database is six times larger than the earlier one, with a total of 23 236 proteins covering 16 159 druggable pharmacophore models and 51 431 ligandable pharmacophore models. The expanded target data cover 450 indications and 4800 molecular functions compared to 110 indications and 349 molecular functions in our last update. In addition, the new web server is united with the statistically meaningful ranking of the identified drug targets, which is achieved through the use of standard scores. It also features an improved user interface. The proposed web server is freely available at http://lilab.ecust.edu.cn/pharmmapper/.

Design, Synthesis, X-ray Crystallographic Analysis, and Biological Evaluation of Thiazole Derivatives as Potent and Selective Inhibitors of Human Dihydroorotate Dehydrogenase

Human dihydroorotate dehydrogenase (HsDHODH) is a flavin-dependent mitochondrial enzyme that has been certified as a potential therapeutic target for the treatment of rheumatoid arthritis and other autoimmune diseases. On the basis of lead compound 4, which was previously identified as potential HsDHODH inhibitor, a novel series of thiazole derivatives were designed and synthesized. The X-ray complex structures of the promising analogues 12 and 33 confirmed that these inhibitors bind at the putative ubiquinone binding tunnel and guided us to explore more potent inhibitors, such as compounds 44, 46, and 47 which showed double digit nanomolar activities of 26, 18, and 29 nM, respectively. Moreover, 44 presented considerable anti-inflammation effect in vivo and significantly alleviated foot swelling in a dose-dependent manner, which disclosed that thiazole-scaffold analogues can be developed into the drug candidates for the treatment of rheumatoid arthritis by suppressing the bioactivity of HsDHODH.

iDrug: a web-accessible and interactive drug discovery and design platform

BackgroundThe progress in computer-aided drug design (CADD) approaches over the past decades accelerated the early-stage pharmaceutical research. Many powerful standalone tools for CADD have been developed in academia. As programs are developed by various research groups, a consistent user-friendly online graphical working environment, combining computational techniques such as pharmacophore mapping, similarity calculation, scoring, and target identification is needed.ResultsWe presented a versatile, user-friendly, and efficient online tool for computer-aided drug design based on pharmacophore and 3D molecular similarity searching. The web interface enables binding sites detection, virtual screening hits identification, and drug targets prediction in an interactive manner through a seamless interface to all adapted packages (e.g., Cavity, PocketV.2, PharmMapper, SHAFTS). Several commercially available compound databases for hit identification and a well-annotated pharmacophore database for drug targets prediction were integrated in iDrug as well. The web interface provides tools for real-time molecular building/editing, converting, displaying, and analyzing. All the customized configurations of the functional modules can be accessed through featured session files provided, which can be saved to the local disk and uploaded to resume or update the history work.ConclusionsiDrug is easy to use, and provides a novel, fast and reliable tool for conducting drug design experiments. By using iDrug, various molecular design processing tasks can be submitted and visualized simply in one browser without installing locally any standalone modeling softwares. iDrug is accessible free of charge at http://lilab.ecust.edu.cn/idrug.

Discovery and Rational Design of Natural-Product-Derived 2-Phenyl-3,4-dihydro-2H-benzo[f]chromen-3-amine Analogs as Novel and Potent Dipeptidyl Peptidase 4 (DPP-4) Inhibitors for the Treatment of Type 2 Diabetes

Starting from the lead isodaphnetin, a natural product inhibitor of DPP-4 discovered through a target fishing docking based approach, a series of novel 2-phenyl-3,4-dihydro-2H-benzo[f]chromen-3-amine derivatives as potent DPP-4 inhibitors are rationally designed utilizing highly efficient 3D molecular similarity based scaffold hopping as well as electrostatic complementary methods. Those ingenious drug design strategies bring us approximate 7400-fold boost in potency. Compounds 22a and 24a are the most potent ones (IC50 ≈ 2.0 nM) with good pharmacokinetic profiles. Compound 22a demonstrated stable pharmacological effect. A 3 mg/kg oral dose provided >80% inhibition of DPP-4 activity within 24 h, which is comparable to the performance of the long-acting control omarigliptin. Moreover, the efficacy of 22a in improving the glucose tolerance is also comparable with omarigliptin. In this study, not only promising DPP-4 inhibitors as long acting antidiabetic that are clinically on demand are identified, but the target fish docking and medicinal chemistry strategies were successfully implemented.

Identification of Inhibitors against p90 Ribosomal S6 Kinase 2 (RSK2) through Structure-Based Virtual Screening with the Inhibitor-Constrained Refined Homology Model

P90 ribosomal S6 kinase 2 (RSK2), which was shown to be overexpressed in human cancers, is a serine/threonine kinase and a potential target for cancer treatment. RSK2 comprises two terminal kinase domains (NTKD and CTKD) that can be inhibited by binding with different types of inhibitors at the ATP binding sites. In the absence of a crystal structure of RSK2, we constructed a model for the 3D structure of the RSK2 NTKD by homology modeling and stepwise constrained refinement with the reported inhibitors using a molecular docking method. Structure-based virtual screening was subsequently performed against a library containing commercially available compounds using the refined model. This resulted in the identification of seven novel RSK2 inhibitors with IC₅₀ values ranging from 2.4 to 14.45 μM.

Systematic Analysis of the Multiple Bioactivities of Green Tea through a Network Pharmacology Approach

During the past decades, a number of studies have demonstrated multiple beneficial health effects of green tea. Polyphenolics are the most biologically active components of green tea. Many targets can be targeted or affected by polyphenolics. In this study, we excavated all of the targets of green tea polyphenolics (GTPs) though literature mining and target calculation and analyzed the multiple pharmacology actions of green tea comprehensively through a network pharmacology approach. In the end, a total of 200 Homo sapiens targets were identified for fifteen GTPs. These targets were classified into six groups according to their related disease, which included cancer, diabetes, neurodegenerative disease, cardiovascular disease, muscular disease, and inflammation. Moreover, these targets mapped into 143 KEGG pathways, 26 of which were more enriched, as determined though pathway enrichment analysis and target-pathway network analysis. Among the identified pathways, 20 pathways were selected for analyzing the mechanisms of green tea in these diseases. Overall, this study systematically illustrated the mechanisms of the pleiotropic activity of green tea by analyzing the corresponding “drug-target-pathway-disease” interaction network.

Rational Design of Benzylidenehydrazinyl-Substituted Thiazole Derivatives as Potent Inhibitors of Human Dihydroorotate Dehydrogenase with in Vivo Anti-arthritic Activity

Human dihydroorotate dehydrogenase (hDHODH) is an attractive therapeutic target for the treatment of rheumatoid arthritis, transplant rejection and other autoimmune diseases. Based on the X-ray structure of hDHODH in complex with lead compound 7, a series of benzylidenehydrazinyl-substituted thiazole derivatives as potent inhibitors of hDHODH were designed and synthesized, of which 19 and 30 were the most potent with IC50 values in the double-digit nanomolar range. Moreover, compound 19 displayed significant anti-arthritic effects and favorable pharmacokinetic profiles in vivo. Further X-ray structure and SAR analyses revealed that the potencies of the designed inhibitors were partly attributable to additional water-mediated hydrogen bond networks formed by an unexpected buried water between hDHODH and the 2-(2-methylenehydrazinyl)thiazole scaffold. This work not only elucidates promising scaffolds targeting hDHODH for the treatment of rheumatoid arthritis, but also demonstrates that the water-mediated hydrogen bond interaction is an important factor in molecular design and optimization.

Isoindole-1,3-dione derivatives as RSK2 inhibitors: synthesis, molecular docking simulation and SAR analysis

RSK2 (p90 ribosomal S6 kinase 2) is a serine/threonine kinase expressed in a variety of cancers. Molecular-targeted inhibition of RSK2 as a potential therapeutic strategy for human cancers has been documented. In this work, a series of isoindole-1,3-dione derivatives as novel RSK2 inhibitors were designed and synthesized from a hit discovered in our previous study. Some compounds were confirmed to be moderately potent RSK2 inhibitors with IC50 values of about 0.5 μM. Structure–activity relationship analysis and binding mode studies by molecular docking were performed.

RD-Metabolizer: an integrated and reaction types extensive approach to predict metabolic sites and metabolites of drug-like molecules

BackgroundExperimental approaches for determining the metabolic properties of the drug candidates are usually expensive, time-consuming and labor intensive. There is a great deal of interest in developing computational methods to accurately and efficiently predict the metabolic decomposition of drug-like molecules, which can provide decisive support and guidance for experimentalists.ResultsHere, we developed an integrated, low false positive and reaction types extensive metabolism prediction approach called RD-Metabolizer (Reaction Database-based Metabolizer). RD-Metabolizer firstly employed the detailed reaction SMARTS patterns to encode different metabolism reaction types with the aim of covering larger chemical reaction space. 2D fingerprint similarity calculation model was built to calculate the metabolic probability of each site in a molecule. RDKit was utilized to act on pre-written reaction SMARTS patterns to correct the metabolic ranking of each site in a molecule generated by the 2D fingerprint similarity calculation model as well as generate corresponding structures of metabolites, thus helping to reduce the false positive metabolites. Two test sets were adopted to evaluate the performance of RD-Metabolizer in predicting SOMs and structures of metabolites. The results indicated that RD-Metabolizer was better than or at least as good as several widely used SOMs prediction methods. Besides, the number of false positive metabolites was obviously reduced compared with MetaPrint2D-React.ConclusionsThe accuracy and efficiency of RD-Metabolizer was further illustrated by a metabolism prediction case of AZD9291, which is a mutant-selective EGFR inhibitor. RD-Metabolizer will serve as a useful toolkit for the early metabolic properties assessment of drug-like molecules at the preclinical stage of drug discovery.Graphical abstractA visual example of the metabolic site and the corresponding metabolite of Chloroquine predicted by RD-Metabolizer