Unveiling the Structural Insights into the Selective Inhibition of Protein Kinase D1

Author(s): Raju Dash*, Md. Arifuzzaman, Sarmistha Mitra, Md. Abdul Hannan, Nurul Absar, S.M. Zahid Hosen*

Journal Name: Current Pharmaceutical Design

Volume 25 , Issue 10 , 2019

Become EABM
Become Reviewer
Call for Editor


Background: Although protein kinase D1 (PKD1) has been proved to be an efficient target for anticancer drug development, lack of structural details and substrate binding mechanisms are the main obstacles for the development of selective inhibitors with therapeutic benefits.

Objective: The present study described the in silico dynamics behaviors of PKD1 in binding with selective and non-selective inhibitors and revealed the critical binding site residues for the selective kinase inhibition.

Methods: Here, the three dimensional model of PKD1 was initially constructed by homology modeling along with binding site characterization to explore the non-conserved residues. Subsequently, two known inhibitors were docked to the catalytic site and the detailed ligand binding mechanisms and post binding dyanmics were investigated by molecular dynamics simulation and binding free energy calculations.

Results: According to the binding site analysis, PKD1 serves several non-conserved residues in the G-loop, hinge and catalytic subunits. Among them, the residues including Leu662, His663, and Asp665 from hinge region made polar interactions with selective PKD1 inhibitor in docking simulation, which were further validated by the molecular dynamics simulation. Both inhibitors strongly influenced the structural dynamics of PKD1 and their computed binding free energies were in accordance with experimental bioactivity data.

Conclusion: The identified non-conserved residues likely to play critical role on molecular reorganization and inhibitor selectivity. Taken together, this study explained the molecular basis of PKD1 specific inhibition, which may help to design new selective inhibitors for better therapies to overcome cancer and PKD1 dysregulated disorders.

Keywords: PKD1, ligand binding mechanism, molecular docking, molecular dynamics simulation, inhibitors, homology modeling.

Rozengurt E, Rey O, Waldron RT. Protein kinase D signaling. J Biol Chem 2005; 280(14): 13205-8.
[http://dx.doi.org/10.1074/jbc.R500002200] [PMID: 15701647]
LaValle CR, George KM, Sharlow ER, Lazo JS, Wipf P, Wang QJ. Protein kinase D as a potential new target for cancer therapy. Biochim Biophys Acta 2010; 1806(2): 183-92.
[http://dx.doi.org/10.1016/j.bbcan.2010.05.003] [PMID: 20580776]
Sturany S, Van Lint J, Müller F, et al. Molecular cloning and characterization of the human protein kinase D2. A novel member of the protein kinase D family of serine threonine kinases. J Biol Chem 2001; 276(5): 3310-8.
[http://dx.doi.org/10.1074/jbc.M008719200] [PMID: 11062248]
Auer A, von Blume J, Sturany S, et al. Role of the regulatory domain of protein kinase D2 in phorbol ester binding, catalytic activity, and nucleocytoplasmic shuttling. Mol Biol Cell 2005; 16(9): 4375-85.
[http://dx.doi.org/10.1091/mbc.e05-03-0251] [PMID: 15975900]
Chang JK, Ni Y, Han L, et al. Protein kinase D1 (PKD1) phosphorylation on Ser203 by type I p21-activated kinase (PAK) regulates PKD1 localization. J Biol Chem 2017; 292(23): 9523-39.
[http://dx.doi.org/10.1074/jbc.M116.771394] [PMID: 28408623]
Rozengurt E. Protein kinase D signaling: multiple biological functions in health and disease. Physiology (Bethesda) 2011; 26(1): 23-33.
[http://dx.doi.org/10.1152/physiol.00037.2010] [PMID: 21357900]
von Blume J, Knippschild U, Dequiedt F, et al. Phosphorylation at Ser244 by CK1 determines nuclear localization and substrate targeting of PKD2. EMBO J 2007; 26(22): 4619-33.
[http://dx.doi.org/10.1038/sj.emboj.7601891] [PMID: 17962809]
Papazyan R, Rozengurt E, Rey O. The C-terminal tail of protein kinase D2 and protein kinase D3 regulates their intracellular distribution. Biochem Biophys Res Commun 2006; 342(3): 685-9.
[http://dx.doi.org/10.1016/j.bbrc.2006.02.013] [PMID: 16494840]
Avkiran M, Rowland AJ, Cuello F, Haworth RS. Protein kinase d in the cardiovascular system: emerging roles in health and disease. Circ Res 2008; 102(2): 157-63.
[http://dx.doi.org/10.1161/CIRCRESAHA.107.168211] [PMID: 18239146]
Valverde AM, Sinnett-Smith J, Van Lint J, Rozengurt E. Molecular cloning and characterization of protein kinase D: a target for diacylglycerol and phorbol esters with a distinctive catalytic domain. Proc Natl Acad Sci USA 1994; 91(18): 8572-6.
[http://dx.doi.org/10.1073/pnas.91.18.8572] [PMID: 8078925]
Rozengurt E, Rey O, Waldron RT. Protein kinase D signaling. J Biol Chem 2005; 280(14): 13205-8.
[http://dx.doi.org/10.1074/jbc.R500002200] [PMID: 15701647]
Johannes FJ, Prestle J, Eis S, Oberhagemann P, Pfizenmaier K. PKCu is a novel, atypical member of the protein kinase C family. J Biol Chem 1994; 269(8): 6140-8.
[PMID: 8119958]
Sharlow ER, Giridhar KV, LaValle CR, et al. Potent and selective disruption of protein kinase D functionality by a benzoxoloazepinolone. J Biol Chem 2008; 283(48): 33516-26.
[http://dx.doi.org/10.1074/jbc.M805358200] [PMID: 18829454]
Trauzold A, Schmiedel S, Sipos B, et al. PKCmu prevents CD95-mediated apoptosis and enhances proliferation in pancreatic tumour cells. Oncogene 2003; 22(55): 8939-47.
[http://dx.doi.org/10.1038/sj.onc.1207001] [PMID: 14654790]
Storz P, Toker A. Protein kinase D mediates a stress-induced NF-kappaB activation and survival pathway. EMBO J 2003; 22(1): 109-20.
[http://dx.doi.org/10.1093/emboj/cdg009] [PMID: 12505989]
Sinnett-Smith J, Zhukova E, Hsieh N, Jiang X, Rozengurt E. Protein kinase D potentiates DNA synthesis induced by Gq-coupled receptors by increasing the duration of ERK signaling in swiss 3T3 cells. J Biol Chem 2004; 279(16): 16883-93.
[http://dx.doi.org/10.1074/jbc.M313225200] [PMID: 14963034]
Chen J, Deng F, Singh SV, Wang QJ. Protein kinase D3 (PKD3) contributes to prostate cancer cell growth and survival through a PKCepsilon/PKD3 pathway downstream of Akt and ERK 1/2. Cancer Res 2008; 68(10): 3844-53.
[http://dx.doi.org/10.1158/0008-5472.CAN-07-5156] [PMID: 18483269]
Sinnett-Smith J, Zhukova E, Rey O, Rozengurt E. Protein kinase D2 potentiates MEK/ERK/RSK signaling, c-Fos accumulation and DNA synthesis induced by bombesin in Swiss 3T3 cells. J Cell Physiol 2007; 211(3): 781-90.
[http://dx.doi.org/10.1002/jcp.20984] [PMID: 17226786]
Jaggi M, Chauhan SC, Du C, Balaji KC. Bryostatin 1 modulates β-catenin subcellular localization and transcription activity through protein kinase D1 activation. Mol Cancer Ther 2008; 7(9): 2703-12.
[http://dx.doi.org/10.1158/1535-7163.MCT-08-0119] [PMID: 18765827]
Mak P, Jaggi M, Syed V, et al. Protein kinase D1 (PKD1) influences androgen receptor (AR) function in prostate cancer cells. Biochem Biophys Res Commun 2008; 373(4): 618-23.
[http://dx.doi.org/10.1016/j.bbrc.2008.06.097] [PMID: 18602367]
Huck B, Duss S, Hausser A, Olayioye MA. Elevated protein kinase D3 (PKD3) expression supports proliferation of triple-negative breast cancer cells and contributes to mTORC1-S6K1 pathway activation. J Biol Chem 2014; 289(6): 3138-47.
[http://dx.doi.org/10.1074/jbc.M113.502633] [PMID: 24337579]
Harikumar KB, Kunnumakkara AB, Ochi N, et al. A novel small-molecule inhibitor of protein kinase D blocks pancreatic cancer growth in vitro and in vivo. Mol Cancer Ther 2010; 9(5): 1136-46.
[http://dx.doi.org/10.1158/1535-7163.MCT-09-1145] [PMID: 20442301]
Lavalle CR, Bravo-Altamirano K, Giridhar KV, et al. Novel protein kinase D inhibitors cause potent arrest in prostate cancer cell growth and motility. BMC Chem Biol 2010; 10(1): 5.
[http://dx.doi.org/10.1186/1472-6769-10-5] [PMID: 20444281]
Sharlow ER, Leimgruber S, Yellow-Duke A, Barrett R, Wang QJ, Lazo JS. Development, validation and implementation of immobilized metal affinity for phosphochemicals (IMAP)-based high-throughput screening assays for low-molecular-weight compound libraries. Nat Protoc 2008; 3(8): 1350-63.
[http://dx.doi.org/10.1038/nprot.2008.111] [PMID: 18714303]
Sharlow ER, Mustata Wilson G, Close D, et al. Discovery of diverse small molecule chemotypes with cell-based PKD1 inhibitory activity. PLoS One 2011; 6(10): e25134.
[http://dx.doi.org/10.1371/journal.pone.0025134] [PMID: 21998636]
Long C, Li W, Liang P, Liu S, Zuo Y. Transcriptome Comparisons of Multi-Species Identify Differential Genome Activation of Mammals Embryogenesis. IEEE Access 2019; 7: 7794-802.
Bairoch A, Apweiler R, Wu CH, et al. The universal protein resource (UniProt). Nucleic Acids Res 2005; 33(Database issue): D154-9.
[http://dx.doi.org/10.1093/nar/gki070] [PMID: 15608167]
Mount DW. Using the basic local alignment search tool (BLAST). Cold Spring Harb Protoc 2007; 2007(14)
Doğan H, Otu HH. Objective functions. Methods Mol Biol 2014; 1079: 45-58.
[http://dx.doi.org/10.1007/978-1-62703-646-7_3] [PMID: 24170394]
Thompson JD, Higgins DG, Gibson TJ. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res 1994; 22(22): 4673-80.
[http://dx.doi.org/10.1093/nar/22.22.4673] [PMID: 7984417]
Kneller DG, Cohen FE, Langridge R. Improvements in protein secondary structure prediction by an enhanced neural network. J Mol Biol 1990; 214(1): 171-82.
[http://dx.doi.org/10.1016/0022-2836(90)90154-E] [PMID: 2370661]
Li J, Abel R, Zhu K, Cao Y, Zhao S, Friesner RA. The VSGB 2.0 model: a next generation energy model for high resolution protein structure modeling. Proteins 2011; 79(10): 2794-812.
[http://dx.doi.org/10.1002/prot.23106] [PMID: 21905107]
Krieger E, Darden T, Nabuurs SB, Finkelstein A, Vriend G. Making optimal use of empirical energy functions: force-field parameterization in crystal space. Proteins 2004; 57(4): 678-83.
[http://dx.doi.org/10.1002/prot.20251] [PMID: 15390263]
Arifuzzaman M, Mitra S, Jahan SI, et al. A Computational workflow for the identification of the potent inhibitor of type II secretion system traffic ATPase of Pseudomonas aeruginosa. Comput Biol Chem 2018; 76: 191-201.
[http://dx.doi.org/10.1016/j.compbiolchem.2018.07.012] [PMID: 30053700]
Laskowski RA, Rullmannn JA, MacArthur MW, Kaptein R, Thornton JM. AQUA and PROCHECK-NMR: programs for checking the quality of protein structures solved by NMR. J Biomol NMR 1996; 8(4): 477-86.
[http://dx.doi.org/10.1007/BF00228148] [PMID: 9008363]
Ramachandran GN, Ramakrishnan C, Sasisekharan V. Stereochemistry of polypeptide chain configurations. J Mol Biol 1963; 7(1): 95-9.
[http://dx.doi.org/10.1016/S0022-2836(63)80023-6] [PMID: 13990617]
Eisenberg D, Lüthy R, Bowie JU. VERIFY3D: assessment of protein models with three-dimensional profiles. Methods Enzymol 1997; 277: 396-404.
[http://dx.doi.org/10.1016/S0076-6879(97)77022-8] [PMID: 9379925]
Colovos C, Yeates TO. Verification of protein structures: patterns of nonbonded atomic interactions. Protein Sci 1993; 2(9): 1511-9.
[http://dx.doi.org/10.1002/pro.5560020916] [PMID: 8401235]
Pontius J, Richelle J, Wodak SJ. Deviations from standard atomic volumes as a quality measure for protein crystal structures. J Mol Biol 1996; 264(1): 121-36.
[http://dx.doi.org/10.1006/jmbi.1996.0628] [PMID: 8950272]
Benkert P, Tosatto SC, Schomburg D. QMEAN: A comprehensive scoring function for model quality assessment. Proteins 2008; 71(1): 261-77.
[http://dx.doi.org/10.1002/prot.21715] [PMID: 17932912]
Chen VB, Arendall WB III, Headd JJ, et al. MolProbity: all-atom structure validation for macromolecular crystallography. Acta Crystallogr D Biol Crystallogr 2010; 66(Pt 1): 12-21.
[http://dx.doi.org/10.1107/S0907444909042073] [PMID: 20057044]
Wiederstein M, Sippl MJ. ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res 2007; 35(Web Server issue)(Suppl. 2): W407-10.
[http://dx.doi.org/10.1093/nar/gkm290]] [PMID: 17517781]
Wallner B, Elofsson A. Can correct protein models be identified? Protein Sci 2003; 12(5): 1073-86.
[http://dx.doi.org/10.1110/ps.0236803] [PMID: 12717029]
Doman TN, McGovern SL, Witherbee BJ, et al. Molecular docking and high-throughput screening for novel inhibitors of protein tyrosine phosphatase-1B. J Med Chem 2002; 45(11): 2213-21.
[http://dx.doi.org/10.1021/jm010548w] [PMID: 12014959]
Hoover WG. Canonical dynamics: Equilibrium phase-space distributions. Phys Rev A Gen Phys 1985; 31(3): 1695-7.
[http://dx.doi.org/10.1103/PhysRevA.31.1695] [PMID: 9895674]
Martyna GJ, Tobias DJ, Klein ML. Constant pressure molecular dynamics algorithms. J Chem Phys 1994; 101(5): 4177-89.
Reddy SV, Reddy KT, Kumari VV, Basha SH. Molecular docking and dynamic simulation studies evidenced plausible immunotherapeutic anticancer property by Withaferin A targeting indoleamine 2,3-dioxygenase. J Biomol Struct Dyn 2015; 33(12): 2695-709.
[http://dx.doi.org/10.1080/07391102.2015.1004834] [PMID: 25671592]
Basha SH, Bethapudi P, Majji Rambabu F. Anti-angiogenesis property by Quercetin compound targeting VEGFR2 elucidated in a computational approach. Euro J Biotechnol Biosci 2014; 2(6): 30-46.
Grant BJ, Rodrigues AP, ElSawy KM, McCammon JA, Caves LS. Bio3d: an R package for the comparative analysis of protein structures. Bioinformatics 2006; 22(21): 2695-6.
[http://dx.doi.org/10.1093/bioinformatics/btl461] [PMID: 16940322]
Ichiye T, Karplus M. Collective motions in proteins: a covariance analysis of atomic fluctuations in molecular dynamics and normal mode simulations. Proteins 1991; 11(3): 205-17.
[http://dx.doi.org/10.1002/prot.340110305] [PMID: 1749773]
Shlens J. A tutorial on principal component analysis. arXiv preprint arXiv 2014; 14041100.
Salmas RE, Yurtsever M, Durdagi S. Investigation of inhibition mechanism of chemokine receptor CCR5 by micro-second molecular dynamics simulations. Sci Rep 2015; 5: 13180.
[http://dx.doi.org/10.1038/srep13180] [PMID: 26299310]
Vijayakumar B, Umamaheswari A, Puratchikody A, Velmurugan D. Selection of an improved HDAC8 inhibitor through structure-based drug design. Bioinformation 2011; 7(3): 134-41.
[http://dx.doi.org/10.6026/97320630007134] [PMID: 22125384]
Li J, Abel R, Zhu K, Cao Y, Zhao S, Friesner RA. The VSGB 2.0 model: a next generation energy model for high resolution protein structure modeling. Proteins 2011; 79(10): 2794-812.
[http://dx.doi.org/10.1002/prot.23106] [PMID: 21905107]
Chen F, Liu H, Sun H, et al. Assessing the performance of the MM/PBSA and MM/GBSA methods. 6. Capability to predict protein-protein binding free energies and re-rank binding poses generated by protein-protein docking. Phys Chem Chem Phys 2016; 18(32): 22129-39.
[http://dx.doi.org/10.1039/C6CP03670H] [PMID: 27444142]
Xu L, Sun H, Li Y, Wang J, Hou T. Assessing the performance of MM/PBSA and MM/GBSA methods. 3. The impact of force fields and ligand charge models. J Phys Chem B 2013; 117(28): 8408-21.
[http://dx.doi.org/10.1021/jp404160y] [PMID: 23789789]
Sun H, Li Y, Tian S, Xu L, Hou T. Assessing the performance of MM/PBSA and MM/GBSA methods. 4. Accuracies of MM/PBSA and MM/GBSA methodologies evaluated by various simulation protocols using PDBbind data set. Phys Chem Chem Phys 2014; 16(31): 16719-29.
[http://dx.doi.org/10.1039/C4CP01388C] [PMID: 24999761]
Sun H, Li Y, Shen M, et al. Assessing the performance of MM/PBSA and MM/GBSA methods. 5. Improved docking performance using high solute dielectric constant MM/GBSA and MM/PBSA rescoring. Phys Chem Chem Phys 2014; 16(40): 22035-45.
[http://dx.doi.org/10.1039/C4CP03179B] [PMID: 25205360]
Hou T, Li N, Li Y, Wang W. Characterization of domain-peptide interaction interface: prediction of SH3 domain-mediated protein-protein interaction network in yeast by generic structure-based models. J Proteome Res 2012; 11(5): 2982-95.
[http://dx.doi.org/10.1021/pr3000688] [PMID: 22468754]
Dash R, Mitra S, Arifuzzaman M, Zahid Hosen SM. In silico quest of selective naphthyl-based CREBBP bromodomain inhibitor. In Silico Pharmacol 2018; 6(1): 1.
[http://dx.doi.org/10.1007/s40203-018-0038-4] [PMID: 30607314]
Dash R, Junaid M, Mitra S, Arifuzzaman M, Hosen SMZ. Structure-based identification of potent VEGFR-2 inhibitors from in vivo metabolites of a herbal ingredient. J Mol Model 2019; 25(4): 98.
[http://dx.doi.org/10.1007/s00894-019-3979-6] [PMID: 30904971]
George KM, Frantz M-C, Bravo-Altamirano K, et al. Design, synthesis, and biological evaluation of PKD inhibitors. Pharmaceutics 2011; 3(2): 186-228.
[http://dx.doi.org/10.3390/pharmaceutics3020186] [PMID: 22267986]
Meredith EL, Beattie K, Burgis R, et al. Identification of potent and selective amidobipyridyl inhibitors of protein kinase D. J Med Chem 2010; 53(15): 5422-38.
[http://dx.doi.org/10.1021/jm100076w] [PMID: 20684592]
Meredith EL, Ardayfio O, Beattie K, et al. Identification of orally available naphthyridine protein kinase D inhibitors. J Med Chem 2010; 53(15): 5400-21.
[http://dx.doi.org/10.1021/jm100075z] [PMID: 20684591]
Gamber GG, Meredith E, Zhu Q, et al. 3,5-diarylazoles as novel and selective inhibitors of protein kinase D. Bioorg Med Chem Lett 2011; 21(5): 1447-51.
[http://dx.doi.org/10.1016/j.bmcl.2011.01.014] [PMID: 21300545]
Tandon M, Wang L, Xu Q, Xie X, Wipf P, Wang QJ. A targeted library screen reveals a new inhibitor scaffold for protein kinase D. PLoS One 2012; 7(9): e44653.
[http://dx.doi.org/10.1371/journal.pone.0044653] [PMID: 23028574]
Zhao YS, Xu Y, Wang K, et al. Homology Modeling and Molecular Dynamics Study of C-Terminal Catalytic Domain of Human Protein Kinase D1. Asian J Chem 2013; 25(3): 1259.
Zhao Y-S, Wang K, Zeng H, Zhang H-X, Zhang J-H. A comparative analysis of binding sites between human PKD1 and PKC1 based on homology modelling, molecular dynamics simulation and docking studies. Mol Simul 2012; 38(4): 309-14.
Krieger E, Joo K, Lee J, et al. Improving physical realism, stereochemistry, and side-chain accuracy in homology modeling: Four approaches that performed well in CASP8. Proteins 2009; 77(Suppl. 9): 114-22.
[http://dx.doi.org/10.1002/prot.22570] [PMID: 19768677]
Wallner B, Elofsson A. Can correct protein models be identified? Protein Sci 2003; 12(5): 1073-86.
[http://dx.doi.org/10.1110/ps.0236803] [PMID: 12717029]
Ghose AK, Herbertz T, Pippin DA, Salvino JM, Mallamo JP. Knowledge based prediction of ligand binding modes and rational inhibitor design for kinase drug discovery. J Med Chem 2008; 51(17): 5149-71.
[http://dx.doi.org/10.1021/jm800475y] [PMID: 18710211]
Nolen B, Taylor S, Ghosh G. Regulation of protein kinases; controlling activity through activation segment conformation. Mol Cell 2004; 15(5): 661-75.
[http://dx.doi.org/10.1016/j.molcel.2004.08.024] [PMID: 15350212]
Shan Y, Seeliger MA, Eastwood MP, et al. A conserved protonation-dependent switch controls drug binding in the Abl kinase. Proc Natl Acad Sci USA 2009; 106(1): 139-44.
[http://dx.doi.org/10.1073/pnas.0811223106] [PMID: 19109437]
Dash R, Junaid M, Islam N, et al. Molecular insight and binding pattern analysis of Shikonin as a potential VEGFR-2 inhibitor. Curr Enzym Inhib 2017; 13(3): 235-44.
Treiber DK, Shah NP. Ins and outs of kinase DFG motifs. Chem Biol 2013; 20(6): 745-6.
[http://dx.doi.org/10.1016/j.chembiol.2013.06.001] [PMID: 23790484]
Storz P, Döppler H, Johannes FJ, Toker A. Tyrosine phosphorylation of protein kinase D in the pleckstrin homology domain leads to activation. J Biol Chem 2003; 278(20): 17969-76.
[http://dx.doi.org/10.1074/jbc.M213224200] [PMID: 12637538]
Zuo Y, Li Y, Chen Y, Li G, Yan Z, Yang L. PseKRAAC: a flexible web server for generating pseudo K-tuple reduced amino acids composition. Bioinformatics 2017; 33(1): 122-4.
[http://dx.doi.org/10.1093/bioinformatics/btw564] [PMID: 27565583]
Feng PM, Chen W, Lin H, Chou KC. iHSP-PseRAAAC: Identifying the heat shock protein families using pseudo reduced amino acid alphabet composition. Anal Biochem 2013; 442(1): 118-25.
[http://dx.doi.org/10.1016/j.ab.2013.05.024] [PMID: 23756733]
Pan Y, Wang S, Zhang Q, et al. Analysis and prediction of animal toxins by various Chou’s pseudo components and reduced amino acid compositions. J Theor Biol 2019; 462: 221-9.
[http://dx.doi.org/10.1016/j.jtbi.2018.11.010] [PMID: 30452961]
Fabbro D, Cowan-Jacob SW, Moebitz H. Ten things you should know about protein kinases: IUPHAR Review 14. Br J Pharmacol 2015; 172(11): 2675-700.
[http://dx.doi.org/10.1111/bph.13096] [PMID: 25630872]
Badrinarayan P, Sastry GN. Specificity rendering ‘hot-spots’ for aurora kinase inhibitor design: the role of non-covalent interactions and conformational transitions. PLoS One 2014; 9(12): e113773.
[http://dx.doi.org/10.1371/journal.pone.0113773] [PMID: 25485544]
Lonsdale R, Ward RA. Structure-based design of targeted covalent inhibitors. Chem Soc Rev 2018; 47(11): 3816-30.
[http://dx.doi.org/10.1039/C7CS00220C] [PMID: 29620097]
Frazzetto M, Suphioglu C, Zhu J, et al. Dissecting isoform selectivity of PI3K inhibitors: the role of non-conserved residues in the catalytic pocket. Biochem J 2008; 414(3): 383-90.
[http://dx.doi.org/10.1042/BJ20080512] [PMID: 18489260]
Brinton R, Nilsen J. Sex hormones and their brain receptors 2001.
[http://dx.doi.org/10.1016/B0-08-043076-7/03453-7] ]
Scapin G. Structural biology in drug design: selective protein kinase inhibitors. Drug Discov Today 2002; 7(11): 601-11.
[http://dx.doi.org/10.1016/S1359-6446(02)02290-0] [PMID: 12047871]
Tian F, Zhou P, Kang W, et al. The small-molecule inhibitor selectivity between IKKα and IKKβ kinases in NF-κB signaling pathway. J Recept Signal Transduct Res 2015; 35(4): 307-18.
[http://dx.doi.org/10.3109/10799893.2014.980950] [PMID: 25386663]
Mitra S, Dash R. Structural dynamics and quantum mechanical aspects of shikonin derivatives as CREBBP bromodomain inhibitors. J Mol Graph Model 2018; 83: 42-52.
[http://dx.doi.org/10.1016/j.jmgm.2018.04.014] [PMID: 29758466]
Liu D, Li G, Zuo Y. Function determinants of TET proteins: the arrangements of sequence motifs with specific codes. Brief Bioinform 2018.
[http://dx.doi.org/10.1093/bib/bby053] [PMID: 29947743]
Harikumar KB, Kunnumakkara AB, Ochi N, et al. A novel small-molecule inhibitor of protein kinase D blocks pancreatic cancer growth in vitro and in vivo. Mol Cancer Ther 2010; 9(5): 1136-46.
[http://dx.doi.org/10.1158/1535-7163.MCT-09-1145] [PMID: 20442301]
Venardos K, De Jong KA, Elkamie M, Connor T, McGee SL. The PKD inhibitor CID755673 enhances cardiac function in diabetic db/db mice. PLoS One 2015; 10(3): e0120934.
[http://dx.doi.org/10.1371/journal.pone.0120934] [PMID: 25798941]
Amadei A, Linssen AB, Berendsen HJ. Essential dynamics of proteins. Proteins 1993; 17(4): 412-25.
[http://dx.doi.org/10.1002/prot.340170408] [PMID: 8108382]
Kornev AP, Taylor SS. Defining the conserved internal architecture of a protein kinase. Biochim Biophys Acta 2010; 1804(3): 440-4.
[http://dx.doi.org/10.1016/j.bbapap.2009.10.017] [PMID: 19879387]
Lu B, Wong CF, McCammon JA. Release of ADP from the catalytic subunit of protein kinase A: a molecular dynamics simulation study. Protein Sci 2005; 14(1): 159-68.
[http://dx.doi.org/10.1110/ps.04894605] [PMID: 15608120]
Mustafa M, Mirza A, Kannan N. Conformational regulation of the EGFR kinase core by the juxtamembrane and C-terminal tail: a molecular dynamics study. Proteins 2011; 79(1): 99-114.
[http://dx.doi.org/10.1002/prot.22862] [PMID: 20938978]
Guan S, Wang T, Kuai Z, et al. Exploration of binding and inhibition mechanism of a small molecule inhibitor of influenza virus H1N1 hemagglutinin by molecular dynamics simulation. Sci Rep 2017; 7(1): 3786.
[http://dx.doi.org/10.1038/s41598-017-03719-4] [PMID: 28630402]
Bharathi AC, Yadav PK, Syed Ibrahim B. Sequence diversity and ligand-induced structural rearrangements of viper hyaluronidase. Mol Biosyst 2016; 12(4): 1128-38.
[http://dx.doi.org/10.1039/C5MB00786K] [PMID: 26867694]

Rights & PermissionsPrintExport Cite as

Article Details

Year: 2019
Published on: 04 August, 2019
Page: [1059 - 1074]
Pages: 16
DOI: 10.2174/1381612825666190527095510
Price: $65

Article Metrics

PDF: 22