881
Views
3
CrossRef citations to date
0
Altmetric
Research Paper

The importance of physicochemical characteristics and nonlinear classifiers in determining HIV-1 protease specificity

&
Pages 65-78 | Received 04 Dec 2015, Accepted 26 Jan 2016, Published online: 20 May 2016

References

  • Barre-Sinoussi F, Chermann J, Rey F, Nugeyre M, Chamaret S, Gruest J, Dauguet C, Axler-Blin C, Vezinet-Brun F, Rouzioux C, et al. Isolation of a T-lymphotropic retrovirus from a patient at risk for acquired immune deficiency syndrome (AIDS). Science (80- ) 1983; 220:868-71; PMID:6189183; http://dx.doi.org/10.1126/science.6189183
  • Gallo R, Sarin P, Gelmann E, Robert-Guroff M, Richardson E, Kalyanaraman V, Mann D, Sidhu G, Stahl R, Zolla-Pazner S, et al. Isolation of human T-cell leukemia virus in acquired immune deficiency syndrome (AIDS). Science (80- ) 1983; 220:865-7; PMID:6601823
  • Sousa SF, Tamames B, Fernandes PA, Ramos MJ. Detailed Atomistic Analysis of the HIV-1 Protease Interface. J Phys Chem B 2011; 115:7045-57; PMID:21545127; http://dx.doi.org/10.1021/jp200075s
  • Kohl NE, Emini EA, Schleif WA, Davis LJ, Heimbach JC, Dixon RA, Scolnick EM, Sigal IS. Active human immunodeficiency virus protease is required for viral infectivity. Proc Natl Acad Sci 1988; 85:4686-90; PMID:3290901; http://dx.doi.org/10.1073/pnas.85.13.4686
  • WHO. Number of deaths due to HIV/AIDS. [cited 2015 Oct 22]; Available from: http://www.who.int/gho/hiv/epidemic_status/deaths_text/en/
  • CDC. HIV in the United States, Statistics Overview [Internet]. [cited 2015 Oct 22]; Available from: http://www.cdc.gov/hiv/statistics/basics/ataglance.html
  • Coffin J. HIV population dynamics in vivo: implications for genetic variation, pathogenesis, and therapy. Science (80- ) 1995; 267:483-9; PMID:7824947
  • Kontijevskis A, Wikberg JES, Komorowski J. Computational proteomics analysis of HIV-1 protease interactome. Proteins 2007; 68:305-12; PMID:17427231; http://dx.doi.org/10.1002/prot.21415
  • Nalam MNL, Schiffer CA. New approaches to HIV protease inhibitor drug design II: testing the substrate envelope hypothesis to avoid drug resistance and discover robust inhibitors. Curr Opin HIV AIDS 2008; 3:642-6; PMID:19373036; http://dx.doi.org/10.1097/COH.0b013e3283136cee
  • Ohtaka H, Freire E. Adaptive inhibitors of the HIV-1 protease. Prog Biophys Mol Biol 2005; 88:193-208; PMID:15572155; http://dx.doi.org/10.1016/j.pbiomolbio.2004.07.005
  • Abramowitz N, Schechter I, Berger A. On the size of the active site in proteases II. Carboxypeptidase-A. Biochem Biophys Res Commun 1967; 29:862-7; PMID:5624785; http://dx.doi.org/10.1016/0006-291X(67)90299-9
  • duVerle DA, Mamitsuka H. A review of statistical methods for prediction of proteolytic cleavage. Brief Bioinform 2012; 13:337-49; PMID:22138323; http://dx.doi.org/10.1093/bib/bbr059
  • Salzberg S. On comparing classifiers: Pitfalls to avoid and a recommended approach. Data Min Knowl Discov 1997; 1:317–28. http://dx.doi.org/ 10.1023/A:1009752403260
  • You L, Garwicz D, Rognvaldsson T. Comprehensive Bioinformatic Analysis of the Specificity of Human Immunodeficiency Virus Type 1 Protease. J Virol 2005; 79:12477-86; PMID:16160175; http://dx.doi.org/10.1128/JVI.79.19.12477-12486.2005
  • Schilling O, Overall CM. Proteome-derived, database-searchable peptide libraries for identifying protease cleavage sites. Nat Biotechnol 2008; 26:685-94; PMID:18500335; http://dx.doi.org/10.1038/nbt1408
  • Impens F, Timmerman E, Staes A, Moens K, Ariën KK, Verhasselt B, Vandekerckhove J, Gevaert K. A catalogue of putative HIV-1 protease host cell substrates. Biol Chem 2012; 393:915-31; PMID:22944692; http://dx.doi.org/10.1515/hsz-2012-0168
  • Alvarez E, Castelló A, Menéndez-Arias L, Carrasco L. HIV protease cleaves poly(A)-binding protein. Biochem J 2006; 396:219-26; PMID:16594896; http://dx.doi.org/10.1042/BJ20060108
  • Nie Z, Bren GD, Vlahakis SR, Schimnich AA, Brenchley JM, Trushin SA, Warren S, Schnepple DJ, Kovacs CM, Loutfy MR, et al. Human immunodeficiency virus type 1 protease cleaves procaspase 8 in vivo. J Virol 2007; 81:6947-56; PMID:17442709; http://dx.doi.org/10.1128/JVI.02798-06
  • Gerencer M, Burek V. Identification of HIV-1 protease cleavage site in human C1-inhibitor. Virus Res 2004; 105:97-100; PMID:15325085; http://dx.doi.org/10.1016/j.virusres.2004.04.010
  • Prabu-Jeyabalan M, Nalivaika E, Schiffer CA. Substrate Shape Determines Specificity of Recognition for HIV-1 Protease. Structure 2002; 10:369-81; PMID:12005435; http://dx.doi.org/10.1016/S0969-2126(02)00720-7
  • Kim H, Zhang Y, Heo Y-S, Oh H-B, Chen S-S. Specificity rule discovery in HIV-1 protease cleavage site analysis. Comput Biol Chem [Internet] 2008 [cited 2016 Jan 6]; 32:72-9; PMID:18006382. Available from: http://www.sciencedirect.com/science/article/pii/S147692710700120X
  • Xing E, Jordan M, Karp R. Feature Selection for High-Dimensional Genomic Microarray Data. In: Brodley CE, Danyluk AP, editors. Proc. 18th International Conf. on Machine Learning Morgan Kaufmann; 2001. page 601-8.
  • Rögnvaldsson T, You L, Garwicz D. Bioinformatic approaches for modeling the substrate specificity of HIV-1 protease: an overview. Expert Rev Mol Diagn 2007; 7:435-51; PMID:17620050; http://dx.doi.org/10.1586/14737159.7.4.435
  • Rögnvaldsson T, You L. Why neural networks should not be used for HIV-1 protease cleavage site prediction. Bioinformatics 2004; 20:1702-9; PMID:14988129; http://dx.doi.org/10.1093/bioinformatics/bth144
  • Rognvaldsson T, You L, Garwicz D. State of the art prediction of HIV-1 protease cleavage sites. Bioinformatics 2015; 31:1204-10; PMID:25504647; http://dx.doi.org/10.1093/bioinformatics/btu810
  • Niu B, Yuan X-C, Roeper P, Su Q, Peng C-R, Yin J-Y, Ding J, Li H, Lu W-C. HIV-1 Protease Cleavage Site Prediction Based on Two-Stage Feature Selection Method. Protein Pept Lett 2013; 20:290–8; PMID: 22591479
  • Kawashima S. AAindex: Amino Acid index database. Nucleic Acids Res 2000; 28:374-374; PMID:10592278; http://dx.doi.org/10.1093/nar/28.1.374
  • Freund Y, Schapire RE. A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting. J Comput Syst Sci 1997; 55:119-39; http://dx.doi.org/10.1006/jcss.1997.1504
  • Nanni L, Lumini A. MppS: An ensemble of support vector machine based on multiple physicochemical properties of amino acids. Neurocomputing 2006; 69:1688-90; http://dx.doi.org/10.1016/j.neucom.2006.04.001
  • Oztürk O, Aksaç A, Elsheikh A, Ozyer T, Alhajj R. A consistency-based feature selection method allied with linear SVMs for HIV-1 protease cleavage site prediction. PLoS One 2013; 8:e63145; PMID:24058397; http://dx.doi.org/10.1371/journal.pone.0063145
  • Song J, Tan H, Perry AJ, Akutsu T, Webb GI, Whisstock JC, Pike RN. PROSPER: an integrated feature-based tool for predicting protease substrate cleavage sites. PLoS One 2012; 7:e50300; PMID:23209700; http://dx.doi.org/10.1371/annotation/920bd689-3af7-418f-8149-43e683e18852
  • McGuffin LJ, Bryson K, Jones DT. The PSIPRED protein structure prediction server. Bioinformatics 2000; 16:404-5; PMID:10869041; http://dx.doi.org/10.1093/bioinformatics/16.4.404
  • Cheng J, Randall AZ, Sweredoski MJ, Baldi P. SCRATCH: a protein structure and structural feature prediction server. Nucleic Acids Res 2005; 33:W72-6; PMID:15980571; http://dx.doi.org/10.1093/nar/gki396
  • Ward JJ, Sodhi JS, McGuffin LJ, Buxton BF, Jones DT. Prediction and functional analysis of native disorder in proteins from the three kingdoms of life. J Mol Biol 2004; 337:635-45; PMID:15019783; http://dx.doi.org/10.1016/j.jmb.2004.02.002
  • Gök M, Özcerit AT. A new feature encoding scheme for HIV-1 protease cleavage site prediction. Neural Comput Appl 2012; 22:1757-61; http://dx.doi.org/10.1007/s00521-012-0967-5
  • Taylor WR. The classification of amino acid conservation. J Theor Biol 1986; 119:205-18; PMID:3461222; http://dx.doi.org/10.1016/S0022-5193(86)80075-3
  • Gök M, Özcerit AT, Istanbullu A. A New Feature Extraction Technique for HIV-1 Protease Cleavage Site Analysis. Glob. J. Technol 3; PMID:NOT_FOUND
  • Gök M, Özcerit AT, Istanbullu A. A New Feature Extraction Technique for HIV-1 Protease Cleavage Site Analysis. Proc. 3rd World Conf. Inf. Technol. 2013; 3:1-6.
  • Newell NE. Cascade detection for the extraction of localized sequence features; specificity results for HIV-1 protease and structure-function results for the Schellman loop. Bioinformatics 2011; 27:3415-22; PMID:22039211; http://dx.doi.org/10.1093/bioinformatics/btr594
  • Li X, Hu H, Shu L. Predicting human immunodeficiency virus protease cleavage sites in nonlinear projection space. Mol Cell Biochem 2010; 339:127-33; PMID:20054614; http://dx.doi.org/10.1007/s11010-009-0376-y
  • Kim G, Kim Y, Lim H, Kim H. An MLP-based feature subset selection for HIV-1 protease cleavage site analysis. Artif Intell Med 2010; 48:83-9; PMID:19945261; http://dx.doi.org/10.1016/j.artmed.2009.07.010
  • Lasko TA, Bhagwat JG, Zou KH, Ohno-Machado L. The use of receiver operating characteristic curves in biomedical informatics. J Biomed Inform 2005; 38:404-15; PMID:16198999; http://dx.doi.org/10.1016/j.jbi.2005.02.008
  • Jaeger S, Chen S. Information fusion for biological prediction. J Data Sci 2010; 8:269–88.
  • Nanni L, Lumini A. Using ensemble of classifiers for predicting HIV protease cleavage sites in proteins. Amino Acids 2008; 36:409-16; PMID:18401541; http://dx.doi.org/10.1007/s00726-008-0076-z
  • Nanni L, Lumini A. A new encoding technique for peptide classification. Expert Syst Appl 2011; 38:3185-91; http://dx.doi.org/10.1016/j.eswa.2010.09.005
  • Yuan Y, Liu H, Qiu G. A new approach for HIV-1 protease cleavage site prediction combined with feature selection. J Biomed Sci Eng 2013; 06:1155-60; http://dx.doi.org/10.4236/jbise.2013.612144
  • Nanni L, Brahnam S, Lumini A. Artificial intelligence systems based on texture descriptors for vaccine development. Amino Acids 2010; 40:443-51; PMID:20552381; http://dx.doi.org/10.1007/s00726-010-0654-8
  • Nanni L, Lumini A. Coding of amino acids by texture descriptors. Artif Intell Med 2010; 48:43-50; PMID:19892537; http://dx.doi.org/10.1016/j.artmed.2009.10.001
  • Nanni L, Brahnam S, Lumini A. Matrix representation in pattern classification. Expert Syst Appl 2012; 39:3031-6; http://dx.doi.org/10.1016/j.eswa.2011.08.165
  • Oğul H. Variable context Markov chains for HIV protease cleavage site prediction. Biosystems 2009; 96:246-50; PMID:19758550; http://dx.doi.org/10.1016/j.biosystems.2009.03.001
  • Lipman DJ, Pastor RW, Lee B. Local sequence patterns of hydrophobicity and solvent accessibility in soluble globular proteins. Biopolymers 1987; 26:17-26; PMID:3801594; http://dx.doi.org/10.1002/bip.360260106
  • Manning T, Walsh P. Automatic task decomposition for the neuroevolution of augmenting topologies (NEAT) algorithm Berlin, Heidelberg: Springer Berlin Heidelberg; 2012.
  • Jacobs RA, Jordan MI, Nowlan SJ, Hinton GE. Adaptive Mixtures of Local Experts. Neural Comput 1991; 3:79-87; http://dx.doi.org/10.1162/neco.1991.3.1.79
  • Stanley KO, Miikkulainen R. Evolving neural networks through augmenting topologies. Evol Comput 2002; 10:99-127; PMID:12180173; http://dx.doi.org/10.1162/106365602320169811
  • Radcliffe NJ. Genetic set recombination and its application to neural network topology optimisation. Neural Comput Appl 1993; 1:67-90; http://dx.doi.org/10.1007/BF01411376
  • Whitley D, Rana S, Heckendorn R. The island Model Genetic algorithm: On separability, population size and convergence. CIT J Comput Inf Technol 1999; 7:33–47.
  • Hellberg S, Sjoestroem M, Skagerberg B, Wold S. Peptide quantitative structure-activity relationships, a multivariate approach. J Med Chem 1987; 30:1126-35; PMID:3599020; http://dx.doi.org/10.1021/jm00390a003
  • Sandberg M, Eriksson L, Jonsson J, Sjöström M, Wold S. New Chemical Descriptors Relevant for the Design of Biologically Active Peptides. A Multivariate Characterization of 87 Amino Acids. J Med Chem 1998; 41:2481-91; PMID:9651153; http://dx.doi.org/10.1021/jm9700575
  • Wu C, Whitson G, Mclarty J, Ermongkonchai A, Chang T-C. Protein classification artificial neural system. Protein Sci 1992; 1:667-77; PMID:1304365; http://dx.doi.org/10.1002/pro.5560010512
  • Maetschke S, Towsey M, Boden M. BLOMAP: An encoding of amino acids which improves signal peptide cleavage site prediction. In: Chen Y-PP, Wong L, editors. Proceedings Third Asia Pacific Bioinformatics Conference. 2005. page 273-89;
  • Patsopoulos NA. Relative Citation Impact of Various Study Designs in the Health Sciences. JAMA 2005; 293:2362; PMID:15900006; http://dx.doi.org/10.1001/jama.293.19.2362
  • Manning T, Sleator RD, Walsh P. Biologically inspired intelligent decision making: a commentary on the use of artificial neural networks in bioinformatics. Bioengineered 2013; 5:80-95; PMID:24335433; http://dx.doi.org/10.4161/bioe.26997
  • Mazurowski MA, Habas PA, Zurada JM, Lo JY, Baker JA, Tourassi GD. Training neural network classifiers for medical decision making: the effects of imbalanced datasets on classification performance. Neural Netw 2008; 21:427-36; PMID:18272329; http://dx.doi.org/10.1016/j.neunet.2007.12.031
  • Song J, Tan H, Shen H, Mahmood K, Boyd SE, Webb GI, Akutsu T, Whisstock JC. Cascleave: towards more accurate prediction of caspase substrate cleavage sites. Bioinformatics 2010; 26:752-60; PMID:20130033; http://dx.doi.org/10.1093/bioinformatics/btq043
  • Shao J, Xu D, Tsai S-N, Wang Y, Ngai S-M. Computational Identification of Protein Methylation Sites through Bi-Profile Bayes Feature Extraction. PLoS One 2009; 4:e4920; PMID:19290060; http://dx.doi.org/10.1371/journal.pone.0004920

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.