iDrug-Target: predicting the interactions between drug compounds and target proteins in cellular networking via benchmark dataset optimization approach

References

• Berardi, M. J. , Shih, W. M. , Harrison, S. C. , & Chou, J. J. (2011). Mitochondrial uncoupling protein 2 structure determined by NMR molecular fragment searching. Nature , 476 , 109–113.10.1038/nature10257
   PubMed Web of Science ®Google Scholar
• Chang, C. , Lin, C. 2005. LIBSVM: A library for support vector machines (2001) [ Software].
   Google Scholar
• Cai, Y. D. , Zhou, G. P. , & Chou, K. C. (2003). Support vector machines for predicting membrane protein types by using functional domain composition. Biophysical Journal , 84 , 3257–3263.10.1016/S0006-3495(03)70050-2
   PubMed Web of Science ®Google Scholar
• Call, M. E. , Wucherpfennig, K. W. , & Chou, J. J. (2010). The structural basis for intramembrane assembly of an activating immunoreceptor complex. Nature Immunology , 11 , 1023–1029.10.1038/ni.1943
   PubMed Web of Science ®Google Scholar
• Cao, D. S. , Xu, Q. S. , & Liang, Y. Z. (2013). Propy: A tool to generate various modes of Chou’s PseAAC. Bioinformatics , 29 , 960–962.10.1093/bioinformatics/btt072
   PubMed Web of Science ®Google Scholar
• Chawla, N. V. , Bowyer, K. W. , Hall, L. O. , & Kegelmeyer, W. P. (2011). SMOTE: Synthetic minority over-sampling technique. Journal of Artificial Intelligence Research , 16 , 321–357.
   Google Scholar
• Chen, W. , Feng, P. M. , Deng, E. Z. , & Lin, H. (2014b). iTIS-PseTNC: A sequence-based predictor for identifying translation initiation site in human genes using pseudo trinucleotide composition. Analytical Biochemistry , 462 , 76–83.10.1016/j.ab.2014.06.022
   PubMed Web of Science ®Google Scholar
• Chen, W. , Feng, P. M. , & Lin, H. (2013). iRSpot-PseDNC: Identify recombination spots with pseudo dinucleotide composition. Nucleic Acids Research , 41 , e68.10.1093/nar/gks1450
   PubMed Web of Science ®Google Scholar
• Chen, W. , Feng, P. M. , & Lin, H. (2014). iSS-PseDNC: Identifying splicing sites using pseudo dinucleotide composition. Biomed Research International , 2014 , 623149.
   PubMed Web of Science ®Google Scholar
• Chen, J. , Liu, H. , Yang, J. , & Chou, K. C. (2007). Prediction of linear B-cell epitopes using amino acid pair antigenicity scale. Amino Acids , 33 , 423–428.10.1007/s00726-006-0485-9
   PubMed Web of Science ®Google Scholar
• Chen, L. , Zeng, W. M. , Cai, Y. D. , & Feng, K. Y. (2012). Predicting anatomical therapeutic chemical (ATC) classification of drugs by integrating chemical–chemical interactions and similarities. PLoS ONE , 7 , e35254.10.1371/journal.pone.0035254
   PubMed Web of Science ®Google Scholar
• Chou, K. C. (1993). A vectorized sequence-coupling model for predicting HIV protease cleavage sites in proteins. Journal of Biological Chemistry , 268 , 16938–16948.
   PubMed Web of Science ®Google Scholar
• Chou, K. C. (2001a). Prediction of protein signal sequences and their cleavage sites. Proteins: Struct, Funct, Genet , 42 , 136–139.10.1002/(ISSN)1097-0134
   PubMed Web of Science ®Google Scholar
• Chou, K. C. (2001b). Prediction of signal peptides using scaled window. Peptides , 22 , 1973–1979.10.1016/S0196-9781(01)00540-X
   PubMed Web of Science ®Google Scholar
• Chou, K. C. (2001c). Prediction of protein cellular attributes using pseudo amino acid composition. PROTEINS: Structure, Function, and Genetics (Erratum: ibid., 2001, Vol. 44, 60) , 43 , 246–255.
   Google Scholar
• Chou, K. C. (2004a). Insights from modelling three-dimensional structures of the human potassium and sodium channels. Journal of Proteome Research , 3 , 856–861.10.1021/pr049931q
   PubMed Web of Science ®Google Scholar
• Chou, K. C. (2004b). Review: Structural bioinformatics and its impact to biomedical science. Current Medicinal Chemistry , 11 , 2105–2134.10.2174/0929867043364667
   PubMed Web of Science ®Google Scholar
• Chou, K. C. (2005a). Insights from modeling the 3D structure of DNA−CBF3b complex. Journal of Proteome Research , 4 , 1657–1660.10.1021/pr050135+
   PubMed Web of Science ®Google Scholar
• Chou, K. C. (2005b). Coupling interaction between thromboxane A2 receptor and alpha-13 subunit of guanine nucleotide-binding protein. Journal of Proteome Research , 4 , 1681–1686.10.1021/pr050145a
   PubMed Web of Science ®Google Scholar
• Chou, K. C. (2005c). Modeling the tertiary structure of human cathepsin-E. Biochemical and Biophysical Research Communications , 331 , 56–60.10.1016/j.bbrc.2005.03.123
   PubMed Web of Science ®Google Scholar
• Chou, K. C. (2005d). Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes. Bioinformatics , 21 , 10–19.10.1093/bioinformatics/bth466
   PubMed Web of Science ®Google Scholar
• Chou, K. C. (2011). Some remarks on protein attribute prediction and pseudo amino acid composition (50th anniversary year review). Journal of Theoretical Biology , 273 , 236–247.10.1016/j.jtbi.2010.12.024
   PubMed Web of Science ®Google Scholar
• Chou, K. C. (2013). Some remarks on predicting multi-label attributes in molecular biosystems. Molecular BioSystems , 9 , 1092–1100.10.1039/c3mb25555g
   PubMed Web of Science ®Google Scholar
• Chou, K. C. , & Cai, Y. D. (2002). Using functional domain composition and support vector machines for prediction of protein subcellular location. Journal of Biological Chemistry , 277 , 45765–45769.10.1074/jbc.M204161200
   PubMed Web of Science ®Google Scholar
• Chou, K. C. , & Cai, Y. D. (2006). Predicting protein–protein interactions from sequences in a hybridization space. Journal of Proteome Research , 5 , 316–322.10.1021/pr050331g
   PubMed Web of Science ®Google Scholar
• Chou, K. C. , & Howe, W. J. (2002). Prediction of the tertiary structure of the beta-secretase zymogen. Biochemistry and Biophysics Research Communication , 292 , 702–708.10.1006/bbrc.2002.6686
   PubMed Web of Science ®Google Scholar
• Chou, K. C. , Jones, D. , & Heinrikson, R. L. (1997). Prediction of the tertiary structure and substrate binding site of caspase-8. FEBS Letters , 419 , 49–54.10.1016/S0014-5793(97)01246-5
   PubMed Web of Science ®Google Scholar
• Chou, K. C. , & Shen, H. B. (2006). Predicting eukaryotic protein subcellular location by fusing optimized evidence-theoretic K-nearest neighbor classifiers. Journal of Proteome Research , 5 , 1888–1897.10.1021/pr060167c
   PubMed Web of Science ®Google Scholar
• Chou, K. C. , & Shen, H. B. (2007). Review: Recent progresses in protein subcellular location prediction. Analytical Biochemistry , 370 , 1–16.10.1016/j.ab.2007.07.006
   PubMed Web of Science ®Google Scholar
• Chou, K. C. , & Shen, H. B. (2010). Cell-PLoc 2.0: An improved package of web-servers for predicting subcellular localization of proteins in various organisms. Natural Science , 2 , 1090–1103.10.4236/ns.2010.210136
   Google Scholar
• Chou, K. C. , Tomasselli, A. G. , & Heinrikson, R. L. (2000). Prediction of the tertiary structure of a caspase-9/inhibitor complex. FEBS Letters , 470 , 249–256.10.1016/S0014-5793(00)01333-8
   PubMed Web of Science ®Google Scholar
• Chou, K. C. , Wei, D. Q. , Du, Q. S. , Sirois, S. , & Zhong, W. Z. (2006). Review: Progress in computational approach to drug development against SARS. Current Medicinal Chemistry , 13 , 3263–3270.10.2174/092986706778773077
   PubMed Web of Science ®Google Scholar
• Chou, K. C. , Wei, D. Q. , & Zhong, W. Z. (2003). Binding mechanism of coronavirus main proteinase with ligands and its implication to drug design against SARS (Erratum: ibid., 2003, Vol. 310, 675). Biochemistry and Biophysics Research Communication , 308 , 148–151.10.1016/S0006-291X(03)01342-1
   PubMed Web of Science ®Google Scholar
• Chou, K. C. , Wu, Z. C. , & Xiao, X. (2011). iLoc-Euk: A multi-label classifier for predicting the subcellular localization of singleplex and multiplex eukaryotic proteins. PLoS ONE , 6 , e18258.10.1371/journal.pone.0018258
   PubMed Web of Science ®Google Scholar
• Chou, K. C. , Wu, Z. C. , & Xiao, X. (2012). iLoc-Hum: Using accumulation-label scale to predict subcellular locations of human proteins with both single and multiple sites. Molecular BioSystems , 8 , 629–641.10.1039/c1mb05420a
   PubMed Web of Science ®Google Scholar
• Chou, K. C. , & Zhang, C. T. (1995). Review: Prediction of protein structural classes. Critical Reviews in Biochemistry and Molecular Biology , 30 , 275–349.10.3109/10409239509083488
   PubMed Web of Science ®Google Scholar
• Cristianini, N. , & Shawe-Taylor, J. (2000). An introduction of support vector machines and other kernel-based learning methods . Cambridge: Cambridge University Press.10.1017/CBO9780511801389
   Google Scholar
• Ding, H. , Deng, E. Z. , Yuan, L. F. , & Liu (2014). iCTX-Type: A sequence-based predictor for identifying the types of conotoxins in targeting ion channels. BioMed Research International , 2014 , 286419.
   PubMed Web of Science ®Google Scholar
• Du, P. , Gu, S. , & Jiao, Y. (2014). PseAAC-general: Fast building various modes of general form of chou’s pseudo-amino acid composition for large-scale protein datasets. International Journal of Molecular Sciences , 15 , 3495–3506.10.3390/ijms15033495
   PubMed Web of Science ®Google Scholar
• Du, Q. S. , Huang, R. B. , & Wang, C. H. (2009). Energetic analysis of the two controversial drug binding sites of the M2 proton channel in influenza A virus. Journal of Theoretical Biology , 259 , 159–164.10.1016/j.jtbi.2009.03.003
   PubMed Web of Science ®Google Scholar
• Du, Q. S. , Huang, R. B. , & Wang, S. Q. (2010). Designing inhibitors of M2 proton channel against H1N1 swine influenza virus. PLoS ONE , 5 , e9388.10.1371/journal.pone.0009388
   PubMed Web of Science ®Google Scholar
• Du, Q. S. , Jiang, Z. Q. , & He, W. Z. (2006). Amino acid principal component analysis (AAPCA) and its applications in protein structural class prediction. Journal of Biomolecular Structure and Dynamics , 23 , 635–640.10.1080/07391102.2006.10507088
   PubMed Web of Science ®Google Scholar
• Ewing, T. J. , Makino, S. , Skillman, A. G. , & Kuntz, I. D. (2001). DOCK 4.0: Search strategies for automated molecular docking of flexible molecule databases. Journal of Computer-Aided Molecular Design , 15 , 411–428.10.1023/A:1011115820450
   PubMed Web of Science ®Google Scholar
• Fan, Y. N. , Xiao, X. , & Min, J. L. (2014). iNR-Drug: Predicting the interaction of drugs with nuclear receptors in cellular networking. International Journal of Molecular Sciences , 15 , 4915–4937.10.3390/ijms15034915
   PubMed Web of Science ®Google Scholar
• Feng, P. M. , Chen, W. , & Lin, H. (2013). iHSP-PseRAAAC: Identifying the heat shock protein families using pseudo reduced amino acid alphabet composition. Analytical Biochemistry , 442 , 118–125.10.1016/j.ab.2013.05.024
   PubMed Web of Science ®Google Scholar
• Guo, S. H. , Deng, E. Z. , Xu, L. Q. , Ding, H. , & Lin, H. (2014). iNuc-PseKNC: A sequence based predictor for predicting nucleosome positioning in genomes with pseudo k–tuple nucleotide composition. Bioinformatics , 30 , 1522–1529.10.1093/bioinformatics/btu083
   PubMed Web of Science ®Google Scholar
• Hajisharifi, Z. , Piryaiee, M. , Mohammad Beigi, M. , Behbahani, M. , & Mohabatkar, H. (2014). Predicting anticancer peptides with Chou’s pseudo amino acid composition and investigating their mutagenicity via Ames test. Journal of Theoretical Biology , 341 , 34–40.10.1016/j.jtbi.2013.08.037
   PubMed Web of Science ®Google Scholar
• He, Z. , Zhang, J. , Shi, X. H. , Hu, L. L. , & Kong, X. (2010). Predicting drug–target interaction networks based on functional groups and biological features. PLoS ONE , 5 , e9603.10.1371/journal.pone.0009603
   PubMed Web of Science ®Google Scholar
• Kotera, M. , Hirakawa, M. , Tokimatsu, T. , Goto, S. , & Kanehisa, M. (2012). The KEGG databases and tools facilitating omics analysis: Latest developments involving human diseases and pharmaceuticals. Methods in Molecular Biology , 802 , 19–39.10.1007/978-1-61779-400-1
   PubMedGoogle Scholar
• Laurikkala, J. (2001). Improving identification of difficult small classes by balancing class distribution (pp. 63–66). Berlin Heidelberg: Springer.
   Google Scholar
• Li, X. B. , Wang, S. Q. , Xu, W. R. , & Wang, R. L. (2011). Novel inhibitor design for hemagglutinin against H1N1 influenza virus by core hopping method. PLoS ONE , 6 , e28111.10.1371/journal.pone.0028111
   PubMed Web of Science ®Google Scholar
• Liao, Q. H. , Gao, Q. Z. , & Wei, J. (2011). Docking and molecular dynamics study on the inhibitory activity of novel inhibitors on epidermal growth factor receptor (EGFR). Medicinal Chemistry , 7 , 24–31.10.2174/157340611794072698
   PubMed Web of Science ®Google Scholar
• Lin, H. , Deng, E. Z. , Ding, H. , & Chen, W. (2014). iPro54-PseKNC: A sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition. Nucleic Acids Research , 42 , 12961–12972.10.1093/nar/gku1019
   PubMed Web of Science ®Google Scholar
• Lin, W. Z. , Fang, J. A. , & Xiao, X. (2013). iLoc-Animal: A multi-label learning classifier for predicting subcellular localization of animal proteins. Molecular BioSystems , 9 , 634–644.10.1039/c3mb25466f
   PubMed Web of Science ®Google Scholar
• Lin, S. X. , & Lapointe, J. (2013). Theoretical and experimental biology in one. Journal Biomedical Science and Engineering (JBiSE) , 6 , 435–442.10.4236/jbise.2013.64054
   Google Scholar
• Lindsay, M. A. (2003). Target discovery. Nature Reviews Drug Discovery , 2 , 831–838.10.1038/nrd1202
   PubMed Web of Science ®Google Scholar
• Liu, H. , Wang, M. , & Chou, K. C. (2005). Low-frequency Fourier spectrum for predicting membrane protein types. Biochem Biophys Research Communication (BBRC) , 336 , 737–739.10.1016/j.bbrc.2005.08.160
   PubMed Web of Science ®Google Scholar
• Liu, Z. , Xiao, X. , Qiu, W. R. (2015). iDNA-Methyl: Identifying DNA methylation sites via pseudo trinucleotide composition. Analytical Biochemistry , in press.
   PubMed Web of Science ®Google Scholar
• Liu, B. , Xu, J. , Lan, X. , Xu, R. , & Zhou, J. (2014a). iDNA-Prot|dis: Identifying DNA-binding proteins by incorporating amino acid distance-pairs and reduced alphabet profile into the general pseudo amino acid composition. PLoS ONE , 9 , e106691.10.1371/journal.pone.0106691
   PubMed Web of Science ®Google Scholar
• Liu, B. , Zhang, D. , Xu, R. , Xu, J. , Wang, X. , & Chen, Q. (2014b). Combining evolutionary information extracted from frequency profiles with sequence-based kernels for protein remote homology detection. Bioinformatics , 30 , 472–479.10.1093/bioinformatics/btt709
   PubMed Web of Science ®Google Scholar
• Ma, Y. , Wang, S. Q. , & Xu, W. R. (2012). Design novel dual agonists for treating type-2 diabetes by targeting peroxisome proliferator-activated receptors with core hopping approach. PLoS ONE , 7 , e38546.10.1371/journal.pone.0038546
   PubMed Web of Science ®Google Scholar
• Min, J. L. , Xiao, X. , & Chou, K. C. (2013). iEzy-Drug: A web server for identifying the interaction between enzymes and drugs in cellular networking. Biomedical Research International , 2013 , 701317.
   PubMed Web of Science ®Google Scholar
• Mohabatkar, H. , Beigi, M. M. , Abdolahi, K. , & Mohsenzadeh, S. (2013). Prediction of allergenic proteins by means of the concept of Chou’s pseudo amino acid composition and a machine learning approach. Medicinal Chemistry , 9 , 133–137.10.2174/157340613804488341
   PubMed Web of Science ®Google Scholar
• Mondal, S. , & Pai, P. P. (2014). Chou’s pseudo amino acid composition improves sequence-based antifreeze protein prediction. Journal of Theoretical Biology , 356 , 30–35.10.1016/j.jtbi.2014.04.006
   PubMed Web of Science ®Google Scholar
• Morris, G. M. , Goodsell, D. S. , Halliday, R. S. , Huey, R. , Hart, W. E. , Belew, R. K. , & Olson, A. J. (1998). Automated docking using a lamarckian genetic algorithm and empirical binding free energy function. Journal of Computational Chemistry , 19 , 1639–1662.10.1002/(ISSN)1096-987X
   Web of Science ®Google Scholar
• Nanni, L. , Brahnam, S. , & Lumini, A. (2014). Prediction of protein structure classes by incorporating different protein descriptors into general Chou’s pseudo amino acid composition. Journal of Theoretical Biology , 360C , 109–116.10.1016/j.jtbi.2014.07.003
   Web of Science ®Google Scholar
• OuYang, B. , & Chou, J. J. (2014). The minimalist architectures of viroporins and their therapeutic implications. Biochimica et Biophysica Acta , 1838 , 1058–1067.10.1016/j.bbamem.2013.09.004
   PubMed Web of Science ®Google Scholar
• OuYang, B. , Xie, S. , Berardi, M. J. , Zhao, X. M. , Dev, J. , Yu, W. , … Chou, J. J. (2013). Unusual architecture of the p7 channel from hepatitis C virus. Nature , 498 , 521–525.10.1038/nature12283
   PubMed Web of Science ®Google Scholar
• Oxenoid, K. , & Chou, J. J. (2005). The structure of phospholamban pentamer reveals a channel-like architecture in membranes. Proceedings of the National Academy of Sciences , 102 , 10870–10875.10.1073/pnas.0504920102
   PubMed Web of Science ®Google Scholar
• Pielak, R. M. , & Chou, J. J. (2010). Solution NMR structure of the V27A drug resistant mutant of influenza A M2 channel. Biochemical and Biophysical Research Communications , 401 , 58–63.10.1016/j.bbrc.2010.09.008
   PubMed Web of Science ®Google Scholar
• Pielak, R. M. , Schnell, Jason R. , & Chou, J. J. (2009). Mechanism of drug inhibition and drug resistance of influenza A M2 channel. Proceedings of National Academy of Science, USA , 106 , 7379–7384.10.1073/pnas.0902548106
   PubMed Web of Science ®Google Scholar
• Qiu, W. R. , Xiao, X. , & Chou, K. C. (2014a). iRSpot-TNCPseAAC: Identify recombination spots with trinucleotide composition and pseudo amino acid components. International Journal of Molecular Sciences , 15 , 1746–1766.10.3390/ijms15021746
   PubMed Web of Science ®Google Scholar
• Qiu, W. R. , Xiao, X. , & Lin, W. Z. (2014b). iUbiq-Lys: Prediction of lysine ubiquitination sites in proteins by extracting sequence evolution information via a grey system model. Journal of Biomolecular Structure and Dynamics (JBSD) , doi:10.1080/07391102.2014.968875.
   Google Scholar
• Qiu, W. R. , Xiao, X. , & Lin, W. Z. (2014c). iMethyl-PseAAC: Identification of protein methylation sites via a pseudo amino acid composition approach. Biomedical Research International , 2014 , 947416.
   PubMed Web of Science ®Google Scholar
• Schenone, M. , Dančík, V. , Wagner, B. K. , & Clemons, P. A. (2013). Target identification and mechanism of action in chemical biology and drug discovery. Nature Chemical Biology , 9 , 232–240.10.1038/nchembio.1199
   PubMed Web of Science ®Google Scholar
• Schnell, J. R. , & Chou, J. J. (2008). Structure and mechanism of the M2 proton channel of influenza A virus. Nature , 451 , 591–595.10.1038/nature06531
   PubMed Web of Science ®Google Scholar
• Shen, H. B. , & Chou, K. C. (2010). Virus-mPLoc: A fusion classifier for viral protein subcellular location prediction by incorporating multiple sites. Journal of Bimoleculor Structural Dynamics , 28 , 175–186.10.1080/07391102.2010.10507351
   PubMed Web of Science ®Google Scholar
• Shen, H. B. , Yang, J. , & Chou, K. C. (2007). Euk-PLoc: An ensemble classifier for large-scale eukaryotic protein subcellular location prediction. Amino Acids , 33 , 57–67.10.1007/s00726-006-0478-8
   PubMed Web of Science ®Google Scholar
• Sirois, S. , Hatzakis, G. E. , & Wei, D. Q. (2005). Assessment of chemical libraries for their druggability. Computational Biology and Chemistry , 29 , 55–67.10.1016/j.compbiolchem.2004.11.003
   PubMed Web of Science ®Google Scholar
• Sirois, S. , Wei, D. Q. , & Du, Q. S. (2004). Virtual screening for SARS-CoV protease based on KZ7088 pharmacophore points. Journal of Chemical Information and Computer Sciences , 44 , 1111–1122.
   PubMedGoogle Scholar
• Steffen, A. , Kogej, T. , Tyrchan, C. , & Engkvist, O. (2009). comparison of molecular fingerprint methods on the basis of biological profile data. Journal of Chemical Information and Modeling , 49 , 338–347.10.1021/ci800326z
   PubMed Web of Science ®Google Scholar
• Sun, Y. , Wong, A. K. , & Kamel, M. S. (2009). Classification of imbalanced data: A review. International Journal of Pattern Recognition and Artificial Intelligence , 23 , 687–719.10.1142/S0218001409007326
   Web of Science ®Google Scholar
• Wang, J. F. , & Chou, K. C. (2011). Insights from modeling the 3D structure of New Delhi metallo-beta-lactamase and its binding interactions with antibiotic drugs. PLoS ONE , 6 , e18414.10.1371/journal.pone.0018414
   PubMed Web of Science ®Google Scholar
• Wang, J. F. , & Chou, K. C. (2012). Insights into the mutation–induced HHH syndrome from modeling human mitochondrial ornithine transporter–1. PLoS ONE , 7 , e31048.10.1371/journal.pone.0031048
   PubMed Web of Science ®Google Scholar
• Wang, S. Q. , Du, Q. S. , & Chou, K. C. (2007b). Study of drug resistance of chicken influenza A virus (H5N1) from homology-modeled 3D structures of neuraminidases. Biochemical and Biophysical Research Communications , 354 , 634–640.10.1016/j.bbrc.2006.12.235
   PubMed Web of Science ®Google Scholar
• Wang, S. Q. , Du, Q. S. , Huang, R. B. , & Zhang, D. W. (2009b). Insights from investigating the interaction of oseltamivir (Tamiflu) with neuraminidase of the 2009 H1N1 swine flu virus. Biochemical and Biophysical Research Communications , 386 , 432–436.10.1016/j.bbrc.2009.06.016
   PubMed Web of Science ®Google Scholar
• Wang, J. , Pielak, R. M. , & McClintock, M. A. (2009a). Solution structure and functional analysis of the influenza B proton channel. Nature Structural & Molecular Biology , 16 , 1267–1271.
   PubMed Web of Science ®Google Scholar
• Wang, J. F. , Wei, D. Q. , Li, L. , Zheng, S. Y. (2007a). 3D structure modeling of cytochrome P450 2C19 and its implication for personalized drug design. Biochemical and Biophysical Research Communications (Corrigendum: ibid, 2007, Vol. 357, 330) , 355, 513–519.10.1016/j.bbrc.2007.01.185
   Google Scholar
• Wei, D. Q. , Du, Q. S. , & Sun, H. (2006). Insights from modeling the 3D structure of H5N1 influenza virus neuraminidase and its binding interactions with ligands. Biochemical and Biophysical Research Communications , 344 , 1048–1055.10.1016/j.bbrc.2006.03.210
   PubMed Web of Science ®Google Scholar
• Wei, H. , Wang, C. H. , Du, Q. S. , & Meng, J. (2009). Investigation into adamantane-based M2 inhibitors with FB-QSAR. Medicinal Chemistry , 5 , 305–317.10.2174/157340609788681430
   PubMed Web of Science ®Google Scholar
• Willett, P. (2006). Similarity-based virtual screening using 2D fingerprints. Drug Discovery Today , 11 , 1046–1053.10.1016/j.drudis.2006.10.005
   PubMed Web of Science ®Google Scholar
• Xiao, X. , Min, J. L. , & Wang, P. (2013a). iCDI-PseFpt: Identify the channel-drug interaction in cellular networking with PseAAC and molecular fingerprints. Journal of Theoretical Biology , 337C , 71–79.10.1016/j.jtbi.2013.08.013
   Web of Science ®Google Scholar
• Xiao, X. , Min, J. L. , & Wang, P. (2013b). iGPCR–Drug: A web server for predicting interaction between GPCRs and drugs in cellular networking. PLoS ONE , 8 , e72234.10.1371/journal.pone.0072234
   PubMed Web of Science ®Google Scholar
• Xiao, X. , Wang, P. , Lin, W. Z. , & Jia, J. H. (2013c). iAMP-2L: A two-level multi-label classifier for identifying antimicrobial peptides and their functional types. Analytical Biochemistry , 436 , 168–177.10.1016/j.ab.2013.01.019
   PubMed Web of Science ®Google Scholar
• Xiao, X. , Wu, Z. C. , & Chou, K. C. (2011). iLoc–virus: A multi-label learning classifier for identifying the subcellular localization of virus proteins with both single and multiple sites. Journal of Theoretical Biology , 284 , 42–51.10.1016/j.jtbi.2011.06.005
   PubMed Web of Science ®Google Scholar
• Xu, Y. , Shao, X. J. , & Wu, L. Y. (2013). iSNO-AAPair: Incorporating amino acid pairwise coupling into PseAAC for predicting cysteine S-nitrosylation sites in proteins. PeerJ , 1 , e171.10.7717/peerj.171
   PubMed Web of Science ®Google Scholar
• Xu, Y. , Wen, X. , Shao, X. J. , & Deng, N. Y. (2014b). iHyd-PseAAC: Predicting hydroxyproline and hydroxylysine in proteins by incorporating dipeptide position-specific propensity into pseudo amino acid composition. International Journal of Molecular Sciences , 15 , 7594–7610.10.3390/ijms15057594
   PubMed Web of Science ®Google Scholar
• Xu, Y. , Wen, X. , Wen, L. S. , & Wu, L. Y. (2014c). iNitro-Tyr: Prediction of nitrotyrosine sites in proteins with general pseudo amino acid composition. PLoS ONE , 9 , e105018.10.1371/journal.pone.0105018
   PubMed Web of Science ®Google Scholar
• Xu, R. , Zhou, J. , Liu, B. , He, Y. A. , & Zou, Q. (2014a). Identification of DNA-binding proteins by incorporating evolutionary information into pseudo amino acid composition via the top-n-gram approach. Journal of Biomolecular Structure & Dynamics . doi:10.1080/07391102.2014.968624
   Web of Science ®Google Scholar
• Yap, C. W. (2011). PaDEL-descriptor: An open source software to calculate molecular descriptors and fingerprints. Journal of Computational Chemistry , 32 , 1466–1474.10.1002/jcc.v32.7
   PubMed Web of Science ®Google Scholar
• Zhang, C. T. , & Chou, K. C. (1992). Monte Carlo simulation studies on the prediction of protein folding types from amino acid composition. Biophysical Journal , 63 , 1523–1529.10.1016/S0006-3495(92)81728-9
   PubMed Web of Science ®Google Scholar
• Zhang, C. T. , & Chou, K. C. (1995). An analysis of protein folding type prediction by seed-propagated sampling and jackknife test. Journal of Protein Chemistry , 14 , 583–593.10.1007/BF01886884
   PubMedGoogle Scholar
• Zhong, W. Z. , & Zhou, S. F. (2014). Molecular science for drug development and biomedicine. International Journal of Molecular Sciences , 15 , 20072–20078.10.3390/ijms151120072
   PubMed Web of Science ®Google Scholar