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

International Journal of Molecular Sciences

Speranta Avram¹  Cătălin Buiu²  Mihai V. Putz³ 

[1] Department of Anatomy, Animal Physiology and Biophysics, Faculty of Biology, University of Bucharest, Bucharest 050095, Romania;Department of Automatic Control and Systems Engineering, Faculty of Automatic Control and Computers, Politehnica University of Bucharest, Bucharest 060042, Romania;Laboratory of Structural and Computational Physical-Chemistry for Nanosciences and QSAR, Biology-Chemistry Department, Faculty of Chemistry-Biology-Geography, West University of Timisoara, Timisoara 300115, Romania;

关键词: HIV-1;    glycoproteins;    antibodies;    neutralization data;    artificial neural network;    regression;   

DOI  :  10.3390/ijms17101710

来源: DOAJ

【 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.

【 授权许可】

Unknown