Learning the Relationship between the Primary Structure of HIV Envelope Glycoproteins and Neutralization Activity of Particular Antibodies by Using Artificial Neural Networks

被引:17
作者
Buiu, Catalin [1 ]
Putz, Mihai V. [2 ,3 ]
Avram, Speranta [4 ]
机构
[1] Univ Politehn Bucuresti, Dept Automat Control & Syst Engn, Fac Automat Control & Comp, Bucharest 060042, Romania
[2] West Univ Timisoara, Biol Chem Dept, Fac Chem Biol Geog, Lab Struct & Computat Phys Chem Nanosci & QSAR, Timisoara 300115, Romania
[3] R&D Natl Inst Electrochem & Condensed Matter, Lab Renewable Energies Photovolta, Timisoara 300569, Romania
[4] Univ Bucharest, Fac Biol, Dept Anat Anim Physiol & Biophys, Bucharest 050095, Romania
关键词
HIV-1; glycoproteins; antibodies; neutralization data; artificial neural network; regression; MONOCLONAL-ANTIBODIES; RATIONAL DESIGN; POTENT; GP120; REGION; BROAD; DESCRIPTORS; PREDICTION; INHIBITORS; ALGORITHM;
D O I
10.3390/ijms17101710
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
The dependency between the primary structure of HIV envelope glycoproteins (ENV) and the neutralization data for given antibodies is very complicated and depends on a large number of factors, such as the binding affinity of a given antibody for a given ENV protein, and the intrinsic infection kinetics of the viral strain. This paper presents a first approach to learning these dependencies using an artificial feedforward neural network which is trained to learn from experimental data. The results presented here demonstrate that the trained neural network is able to generalize on new viral strains and to predict reliable values of neutralizing activities of given antibodies against HIV-1.
引用
收藏
页数:14
相关论文
共 53 条
[1]  
Al-Gharabli Samer I, 2015, Int J Bioinform Res Appl, V11, P153, DOI 10.1504/IJBRA.2015.068090
[2]  
[Anonymous], 1998, Mach Learn, DOI DOI 10.1023/A:1017181826899
[3]   BgN-Score and BsN-Score: Bagging and boosting based ensemble neural networks scoring functions for accurate binding affinity prediction of protein-ligand complexes [J].
Ashtawy, Hossam M. ;
Mahapatra, Nihar R. .
BMC BIOINFORMATICS, 2015, 16
[4]   Drift of the HIV-1 Envelope Glycoprotein gp120 toward Increased Neutralization Resistance over the Course of the Epidemic: a Comprehensive Study Using the Most Potent and Broadly Neutralizing Monoclonal Antibodies [J].
Bouvin-Pley, M. ;
Morgand, M. ;
Meyer, L. ;
Goujard, C. ;
Moreau, A. ;
Mouquet, H. ;
Nussenzweig, M. ;
Pace, C. ;
Ho, D. ;
Bjorkman, P. J. ;
Baty, D. ;
Chames, P. ;
Pancera, M. ;
Kwong, P. D. ;
Poignard, P. ;
Barin, F. ;
Braibant, M. .
JOURNAL OF VIROLOGY, 2014, 88 (23) :13910-13917
[5]   Evidence for a Continuous Drift of the HIV-1 Species towards Higher Resistance to Neutralizing Antibodies over the Course of the Epidemic [J].
Bouvin-Pley, Melanie ;
Morgand, Marion ;
Moreau, Alain ;
Jestin, Pauline ;
Simonnet, Claire ;
Tran, Laurent ;
Goujard, Cecile ;
Meyer, Laurence ;
Barin, Francis ;
Braibant, Martine .
PLOS PATHOGENS, 2013, 9 (07)
[6]  
Bradley T., 2016, EBIOMEDICINE, V16, P30402
[7]  
Buiu C., 2016, NEUTRALIZATION DATA
[8]   Pharmacological descriptors related to the binding of Gp120 to CD4 corresponding to 60 representative HIV-1 strains [J].
Calborean, Octavian ;
Mernea, Maria ;
Avram, Speranta ;
Mihailescu, Dan Florin .
JOURNAL OF ENZYME INHIBITION AND MEDICINAL CHEMISTRY, 2013, 28 (05) :1015-1025
[9]   Covariance of Charged Amino Acids at Positions 322 and 440 of HIV-1 Env Contributes to Coreceptor Specificity of Subtype B Viruses, and Can Be Used to Improve the Performance of V3 Sequence-Based Coreceptor Usage Prediction Algorithms [J].
Cashin, Kieran ;
Sterjovski, Jasminka ;
Harvey, Katherine L. ;
Ramsland, Paul A. ;
Churchill, Melissa J. ;
Gorry, Paul R. .
PLOS ONE, 2014, 9 (10)
[10]   Direct Antibody Access to the HIV-1 Membrane-Proximal External Region Positively Correlates with Neutralization Sensitivity [J].
Chakrabarti, B. K. ;
Walker, L. M. ;
Guenaga, J. F. ;
Ghobbeh, A. ;
Poignard, P. ;
Burton, D. R. ;
Wyatt, R. T. .
JOURNAL OF VIROLOGY, 2011, 85 (16) :8217-8226