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.

[1]  A. Cuddihy,et al.  Inhibition of Chk1-dependent G2 DNA damage checkpoint radiosensitizes p53 mutant human cells , 2001, Oncogene.

[2]  T. Kawabe.  G2 checkpoint abrogators as anticancer drugs. , 2004, Molecular cancer therapeutics.

[3]  Y. Sánchez,et al.  Chk1 in the DNA damage response: conserved roles from yeasts to mammals. , 2004, DNA repair.

[4]  Andrew Potter,et al.  Structure-based design of novel Chk1 inhibitors: insights into hydrogen bonding and protein-ligand affinity. , 2005, Journal of medicinal chemistry.

[5]  Jiri Bartek,et al.  Targeting the checkpoint kinases: chemosensitization versus chemoprotection , 2004, Nature Reviews Cancer.

[6]  Ji-Xia Ren,et al.  Pharmacophore modeling studies of type I and type II kinase inhibitors of Tie2. , 2009, Journal of molecular graphics & modelling.

[7]  R. Simmer,et al.  Blocking Chk1 expression induces apoptosis and abrogates the G2 checkpoint mechanism. , 2001, Neoplasia.

[8]  Y. Martin,et al.  A general and fast scoring function for protein-ligand interactions: a simplified potential approach. , 1999, Journal of medicinal chemistry.

[9]  S. Elledge,et al.  The DNA damage response: putting checkpoints in perspective , 2000, Nature.

[10]  B. Pfeiffer,et al.  Novel 5-azaindolocarbazoles as cytotoxic agents and Chk1 inhibitors. , 2008, Bioorganic & medicinal chemistry.

[11]  Shi-Dong Luo,et al.  Pharmacophore modeling and virtual screening for designing potential PLK1 inhibitors. , 2008, Bioorganic & medicinal chemistry letters.

[12]  J. Wendoloski,et al.  Identification of compounds with nanomolar binding affinity for checkpoint kinase-1 using knowledge-based virtual screening. , 2004, Journal of medicinal chemistry.

[13]  Chang Park,et al.  Structure-based design, synthesis, and biological evaluation of potent and selective macrocyclic checkpoint kinase 1 inhibitors. , 2007, Journal of medicinal chemistry.

[14]  Gennady M Verkhivker,et al.  Molecular recognition of the inhibitor AG-1343 by HIV-1 protease: conformationally flexible docking by evolutionary programming. , 1995, Chemistry & biology.

[15]  Baoguang Zhao,et al.  Inhibition of Chk1 by the G2 DNA damage checkpoint inhibitor isogranulatimide. , 2004, Molecular cancer therapeutics.

[16]  T. N. Bhat,et al.  The Protein Data Bank , 2000, Nucleic Acids Res..

[17]  Ajay N. Jain.  Scoring noncovalent protein-ligand interactions: A continuous differentiable function tuned to compute binding affinities , 1996, J. Comput. Aided Mol. Des..

[18]  Y. Ho,et al.  Checkpoint kinase 1‐mediated phosphorylation of Cdc25C and bad proteins are involved in antitumor effects of loratadine‐induced G2/M phase cell‐cycle arrest and apoptosis , 2006, Molecular carcinogenesis.

[19]  Madhu Chopra,et al.  Molecular modeling study on chemically diverse series of cyclooxygenase-2 selective inhibitors: generation of predictive pharmacophore model using Catalyst , 2008, Journal of molecular modeling.

[20]  W. Denny,et al.  Synthesis and structure-activity relationships of soluble 8-substituted 4-(2-chlorophenyl)-9-hydroxypyrrolo[3,4-c]carbazole-1,3(2H,6H)-diones as inhibitors of the Wee1 and Chk1 checkpoint kinases. , 2008, Bioorganic & medicinal chemistry letters.

[21]  Markus A Lill,et al.  Multi-dimensional QSAR in drug discovery. , 2007, Drug discovery today.

[22]  Stephen Green,et al.  AZD7762, a novel checkpoint kinase inhibitor, drives checkpoint abrogation and potentiates DNA-targeted therapies , 2008, Molecular Cancer Therapeutics.

[23]  Ming-Li Xiang,et al.  Pharmacophore Modelling and Virtual Screening for Identification of New Aurora‐A Kinase Inhibitors , 2008, Chemical biology & drug design.

[24]  Andrew Smellie,et al.  Poling: Promoting conformational variation , 1995, J. Comput. Chem..

[25]  Lawrence C Kuo,et al.  Optimization of a pyrazoloquinolinone class of Chk1 kinase inhibitors. , 2007, Bioorganic & medicinal chemistry letters.

[26]  R. Clark,et al.  Consensus scoring for ligand/protein interactions. , 2002, Journal of molecular graphics & modelling.

[27]  Chang Park,et al.  Synthesis and biological evaluation of 1-(2,4,5-trisubstituted phenyl)-3-(5-cyanopyrazin-2-yl)ureas as potent Chk1 kinase inhibitors. , 2006, Bioorganic & medicinal chemistry letters.

[28]  M. Karplus,et al.  CHARMM: A program for macromolecular energy, minimization, and dynamics calculations , 1983 .

[29]  Hans-Joachim Böhm,et al.  Prediction of binding constants of protein ligands: A fast method for the prioritization of hits obtained from de novo design or 3D database search programs , 1998, J. Comput. Aided Mol. Des..

[30]  David E. Williams,et al.  Inhibition of the G2 DNA Damage Checkpoint and of Protein Kinases Chk1 and Chk2 by the Marine Sponge Alkaloid Debromohymenialdisine* , 2001, The Journal of Biological Chemistry.

[31]  Z. Ni,et al.  4-(Aminoalkylamino)-3-benzimidazole-quinolinones as potent CHK-1 inhibitors. , 2006, Bioorganic & medicinal chemistry letters.

[32]  A. Gunasekera,et al.  Chk1 Mediates S and G2 Arrests through Cdc25A Degradation in Response to DNA-damaging Agents* , 2003, Journal of Biological Chemistry.

[33]  G. Schwartz,et al.  Targeting Checkpoint Kinase 1 in Cancer Therapeutics , 2007, Clinical Cancer Research.

[34]  A. Cuddihy,et al.  Cell-cycle responses to DNA damage in G2. , 2003, International review of cytology.

[35]  K. Chou,et al.  Recent advances in QSAR and their applications in predicting the activities of chemical molecules, peptides and proteins for drug design. , 2008, Current protein & peptide science.

[36]  C. Venkatachalam,et al.  LigandFit: a novel method for the shape-directed rapid docking of ligands to protein active sites. , 2003, Journal of molecular graphics & modelling.

[37]  Shi-Dong Luo,et al.  A Specific Pharmacophore Model of Aurora B Kinase Inhibitors and Virtual Screening Studies Based on it , 2009, Chemical biology & drug design.

[38]  Philip J. Merta,et al.  Synthesis and in-vitro biological activity of macrocyclic urea Chk1 inhibitors. , 2007, Bioorganic & medicinal chemistry letters.

[39]  Chang Park,et al.  Design, synthesis, and biological activity of 5,10-dihydro-dibenzo[b,e][1,4]diazepin-11-one-based potent and selective Chk-1 inhibitors. , 2007, Journal of medicinal chemistry.

[40]  Yu-Quan Wei,et al.  Pharmacophore modeling study based on known spleen tyrosine kinase inhibitors together with virtual screening for identifying novel inhibitors. , 2009, Bioorganic & medicinal chemistry letters.

[41]  Hans-Joachim Böhm,et al.  The development of a simple empirical scoring function to estimate the binding constant for a protein-ligand complex of known three-dimensional structure , 1994, J. Comput. Aided Mol. Des..