Pharmacophore modeling, multiple docking, and molecular dynamics studies on Wee1 kinase inhibitors

References

• Badhani, B., & Kakkar, R. (2017). In silico studies on potential MCF-7 inhibitors: a combination of pharmacophore and 3D-QSAR modeling, virtual screening, molecular docking, and pharmacokinetic analysis. Journal of Biomolecular Structure & Dynamics, 35(9):1.
   PubMed Web of Science ®Google Scholar
• Chaudhary, N., & Aparoy, P. (2016). Deciphering the mechanism behind the varied binding activities of COXIBs through molecular dynamic simulations, MM-PBSA binding energy calculations and per residue energy decomposition studies. Journal of Biomolecular Structure & Dynamics, 35(4):868–882.
   PubMed Web of Science ®Google Scholar
• Cho, A. E., Guallar, V., Berne, B. J., Friesner, R. (2005). Importance of accurate charges in molecular docking: quantum mechanical/molecular mechanical (QM/MM) approach. Journal of Computational Chemistry, 26(9):915–931.
   PubMed Web of Science ®Google Scholar
• Darden, T., York, D., & Pedersen, L. (1998). Particle mesh Ewald: an Nlog(N) method for Ewald sums in large systems. Journal of Chemical Physics, 98(12):10089–10092.
   Google Scholar
• De Witt Hamer, P. C., Mir, S. E., Noske, D., Van Noorden, C. J., Würdinger, T. (2011). WEE1 kinase targeting combined with DNA-damaging cancer therapy catalyzes mitotic catastrophe. Clinical Cancer Research, 17(13):4200–4207.
   PubMed Web of Science ®Google Scholar
• Dillon, M. T., Good, J. S., & Harrington, K. J. (2014). Selective targeting of the G2/M cell cycle checkpoint to improve the therapeutic index of radiotherapy. Clinical Oncology (Royal College of Radiologists), 26(5):257–265.
   PubMed Web of Science ®Google Scholar
• Egeland, E. V., Flatmark, K., Nesland, J. M., Flørenes, V. A.,Mælandsmo, G. M., Boye, K. (2016). Expression and clinical significance of Wee1 in colorectal cancer. Tumour Biology, 37(9):12133–12140.
   PubMedGoogle Scholar
• Francis, D. (2011). A commentary on the G2/M transition of the plant cell cycle. Annals of Botany, 107(7):1065–1070.
   PubMed Web of Science ®Google Scholar
• Glide, version 6.7, Schrödinger, LLC, New York, NY, 2015.
   Google Scholar
• Hess, B., Bekker, H., Berendsen, H. J. C., Fraaije, J. G. E. M. (2008). LINCS: a linear constraint solver for molecular simulations. Journal of Chemical Theory & Computation, 4(1):1463–1472.
   Web of Science ®Google Scholar
• Homeyer, N., & Gohlke, H. (2012). Free energy calculations by the molecular mechanics Poisson − Boltzmann surface area method. QSAR & Combinatorial Science, 31(2):114–122.
   Google Scholar
• Hou, T., Wang, J., Li, Y., Wang, W. (2011). Assessing the performance of the MM/PBSA and MM/GBSA methods. 1. The accuracy of binding free energy calculations based on molecular dynamics simulations. Journal of Chemical Information and Modeling, 51(1):69–82.
   PubMed Web of Science ®Google Scholar
• Geenen, J. J. J., & Schellens, J. H. M. (2017). Molecular pathways: targeting the protein kinase Wee1 in cancer. Clinical Cancer Research: An Official Journal of the American Association for Cancer Research, 23(16):4540–4544.
   PubMed Web of Science ®Google Scholar
• Kalva, S., Singam, E. R. A., Rajapandian, V., Saleena, L. M., Subramanian, V. (2014). Discovery of potent inhibitor for matrix metalloproteinase-9 by pharmacophore based modeling and dynamics simulation studies. Journal of Molecular Graphics & Modelling, 49(2):25–37.
   PubMedGoogle Scholar
• Kawabe, T. (2004). G2 checkpoint abrogators as anticancer drugs. Molecular Cancer Therapeutics, 3(4):513–519.
   PubMed Web of Science ®Google Scholar
• Kim, H. Y., Cho, Y., Kang, H., Yim, Y. S.,Kim, S. J.,Song, J., et al. (2016). Targeting the WEE1 kinase as a molecular targeted therapy for gastric cancer. Oncotarget, 7(31):49902–49916.
   PubMedGoogle Scholar
• Kreahling, J. M., Foroutan, P., Reed, D., Martinez, G., Razabdouski, T., Bui, M. M., et al. (2013). Wee1 inhibition by MK-1775 leads to tumor inhibition and enhances efficacy of gemcitabine in human sarcomas. Plos One, 8(3):e57523.
   PubMed Web of Science ®Google Scholar
• Kumari, R., Kumar, R., & Lynn, A. (2014). g_mmpbsa-a GROMACS tool for high-throughput MM-PBSA calculations. Journal of Chemical Information and Modeling, 54(7):1951–1962.
   PubMed Web of Science ®Google Scholar
• Kuzmanic, A., & Zagrovic, B. (2010). Determination of ensemble-average pairwise root mean-square deviation from experimental B-factors. Biophysical Journal, 98(5):861–871.
   PubMed Web of Science ®Google Scholar
• Lee, M. R., Duan, Y., & Kollman P. A. (2015). Use of MM-PB/SA in estimating the free energies of proteins: application to native, intermediates, and unfolded villin headpiece. Proteins Structure Function & Bioinformatics, 39(4):309–316.
   Google Scholar
• Lemkul, J. A., Allen, W. J., & Bevan, D. R. (2010). Practical considerations for building GROMOS-compatible small-molecule topologies. Journal of Chemical Information and Modeling, 50(12):2221–2235.
   PubMed Web of Science ®Google Scholar
• LigPrep, version 3.4, Schrödinger, LLC, New York, NY, 2015.
   Google Scholar
• Lu, S. Y., Jiang, Y. J., Lv, J., Wu, T. X., Yu, Q. S., Zhu, W. L. (2010). Molecular docking and molecular dynamics simulation studies of GPR40 receptor-agonist interactions. Journal of Molecular Graphics and Modeling, 28(8):766–774.
   PubMed Web of Science ®Google Scholar
• Matheson, C. J., Venkataraman, S., Amani, V., Harris, P. S.,Backos, D. S.,Donson, A. M., et al. (2016). A WEE1 inhibitor analog of AZD1775 maintains synergy with cisplatin and demonstrates reduced single-agent cytotoxicity in medulloblastoma cells. ACS Chemical Biology, 11(4):921–930.
   PubMed Web of Science ®Google Scholar
• Medina, R., Ghule, P. N., Cruzat, F., Barutcu,A. R.,Montecino, M.,Stein, J. L., et al. (2012). Epigenetic control of cell cycle dependent histone gene expression is a principal component of the abbreviated pluripotent cell cycle. Molecular and Cellular Biology, 32(19):3860–3871.
   PubMed Web of Science ®Google Scholar
• Murrow, L. M., Garimella, S. V., Jones, T. L., Caplen, N. J.,Lipkowitz, S. (2010). Identification of WEE1 as a potential molecular target in cancer cells by RNAi screening of the human tyrosine kinome. Breast Cancer Research and Treatment, 122(2):347–357.
   PubMed Web of Science ®Google Scholar
• Palmer, B. D., Smaill, J. B., Rewcastle, G. W., Dobrusin, E. M.,Kraker, A.,Moore, C. W., et al. (2005). Structure-activity relationships for 2-anilino-6-phenylpyrido[2,3-]pyrimidin-7(8)-ones as inhibitors of the cellular checkpoint kinase Wee1. Bioorganic & Medicinal Chemistry Letters, 15(7):1931–1935.
   PubMed Web of Science ®Google Scholar
• Palmer, B. D., Thompson, A. M., Booth, R. J., Dobrusin, E. M., Kraker, A. J., Lee, H. H., et al. (2006). 4-Phenylpyrrolo[3,4-c]carbazole-1,3(2H,6H)-dione inhibitors of the checkpoint kinase Wee1. Structure-activity relationships for chromophore modification and phenyl ring substitution. Journal of Medicinal Chemistry, 49(16):4896–4911.
   PubMed Web of Science ®Google Scholar
• Phase, version 4.3, Schrödinger, LLC, New York, NY, 2015.
   Google Scholar
• Prime, version 4.0, Schrödinger, LLC, New York, NY, 2015.
   Google Scholar
• Protein Preparation Wizard 2015-2; Epik version 2.4, Schrödinger, LLC, New York, NY, 2015; Impact version 5.9, Schrödinger, LLC, New York, NY, 2015; Prime version 3.2, Schrödinger, LLC, New York, NY, 2015.
   Google Scholar
• QikProp Descriptors and Properties, Schrödinger, LLC, New York, NY, 2015.
   Google Scholar
• QikProp, version 4.4, Schrödinger, LLC, New York, NY, 2015.
   Google Scholar
• QM-Polarized Ligand Docking protocol 2015-2; Glide version 5.9, Jaguar version 8.0, QSite version 5.9, Schrödinger, LLC, New York, NY, 2015.
   Google Scholar
• Ravikumar, M., Pavan, S., Bairy, S., Pramod, A. B., Sumakanth, M., Kishore, M., et al. (2008). Virtual screening of cathepsin K inhibitors using docking and pharmacophore models. Chemical Biology and Drug Design, 72(1):79–90.
   PubMed Web of Science ®Google Scholar
• Sakthivel, S., & Habeeb, S. (2018). Combined pharmacophore, virtual screening and molecular dynamics studies to identify Bruton's tyrosine kinase inhibitors. Journal of Biomolecular Structure & Dynamics, 10:1–18.
   Google Scholar
• Shen, M., Zhou, S., Li, Y., Pan, P., Zhang, L., Hou, T. (2013). Discovery and optimization of triazine derivatives as ROCK1 inhibitors: molecular docking, molecular dynamics simulations and free energy calculations. Molecular Biosystems, 9(3):361–374.
   PubMed Web of Science ®Google Scholar
• Singh, R. K., Kabbaj, M. H., Paik, J., Gunjan, A., et al. (2009). Histone levels are regulated by phosphorylation and ubiquitylation-dependent proteolysis. Nature Cell Biology, 11(8):925–933.
   PubMed Web of Science ®Google Scholar
• Slipicevic, A., Holth, A., Hellesylt, E., Tropé, C. G.,Davidson, B., Flørenes, V. A. (2014). Wee1 is a novel independent prognostic marker of poor survival in post-chemotherapy ovarian carcinoma effusions. Gynecologic Oncology, 135(1):118–124.
   PubMed Web of Science ®Google Scholar
• Smaill, J. B., Lee, H. H., Palmer, B. D., Thompson, A. M., Squire, C. J., Baker, E. N., et al. (2008). 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. Bioorganic & Medicinal Chemistry Letters, 18(3):929–933.
   PubMed Web of Science ®Google Scholar
• Tan, J. J., Chen, W. Z., & Wang, C. X. (2006). Investigating interactions between HIV-1 gp41 and inhibitors by molecular dynamics simulation and MM–PBSA/GBSA calculations. Journal of Molecular Structure Theochem, 766(2–3):77–82.
   Web of Science ®Google Scholar
• Tong, Y., Torrent, M., Florjancic, A. S., Bromberg, K. D., Buchanan, F. G.,Ferguson, D. C.,et al. (2015). Pyrimidine-based tricyclic molecules as potent and orally efficacious inhibitors of wee1 kinase. ACS Medicinal Chemistry Letters, 6(1):58.
   PubMed Web of Science ®Google Scholar
• Tran, V., Lim, C., Xie, J., Chen, X. (2012). Asymmetric division of Drosophila male germline stem cell shows asymmetric histone distribution. Science, 338(6107):679–682.
   PubMed Web of Science ®Google Scholar
• Tripathy, S., Azam, M. A., Jupudi, S., Sahu, S. K. (2017). Pharmacophore generation, atom-based 3D-QSAR, molecular docking and molecular dynamics simulation studies on benzamide analogues as FtsZ inhibitors. Journal of Biomolecular Structure & Dynamics, DOI: 10.1080/07391102.2017.1384401.
   PubMed Web of Science ®Google Scholar
• Verma, P., Tiwari, M., & Tiwari, V. (2017). In-silico high throughput virtual screening and molecular dynamics simulation study to identify inhibitor for AdeABC efflux pump of Acinetobacter baumannii. Journal of Biomolecular Structure & Dynamics, 36(5):1.
   Web of Science ®Google Scholar
• Wagner, A. B. (2006). SciFinder Scholar 2006: an empirical analysis of research topic query processing. Journal of Chemical Information and Modeling, 46(2):767.
   PubMed Web of Science ®Google Scholar
• Wichapong, K., Lindner, M., Pianwanit, S., Kokpol, S.,Sippl, W. (2009). Receptor-based 3D-QSAR studies of checkpoint Wee1 kinase inhibitors. European Journal of Medicinal Chemistry, 44(4): 1383–1395.
   PubMed Web of Science ®Google Scholar
• Wong, S., Amaro, R. E., & Mccammon J. A. (2011). MM-PBSA captures key role of intercalating water molecules at a protein − protein interface. Journal of Chemical Theory & Computation, 2011, 5(2):422.
   Web of Science ®Google Scholar
• Zhang, H., Xiang, M. L., Liang, J. Y., Zeng, T.,Zhang, X. N.,Zhang, J., et al. (2013). Combination of pharmacophore hypothesis, genetic function approximation model, and molecular docking to identify novel inhibitors of S6K1. Molecular Diversity, 17(4):767–772.
   PubMed Web of Science ®Google Scholar