Computational prediction of anti HIV-1 peptides and in vitro evaluation of anti HIV-1 activity of HIV-1 P24-derived peptides

Journal of Peptide Science

Volumn 21, Issue 1, 2015, Pages 10-16

  Poorinmohammad, Naghmeh ^a   Mohabatkar, Hassan ^a   Behbahani, Mandana ^a   Biria, Davood ^a  

^a UNIVERSITY OF ISFAHAN   (Iran)

Author keywords

Anti HIV 1 peptides; Machine learning approach; P24 protein; Support vector machine

Indexed keywords

ANTI HUMAN IMMUNODEFICIENCY VIRUS AGENT; GAG PROTEIN; PEPTIDE DERIVATIVE; ANTI-HIV AGENTS; HIV CORE PROTEIN P24; MUTAGENS; P24 PROTEIN, HUMAN IMMUNODEFICIENCY VIRUS TYPE 1; PEPTIDE FRAGMENTS;

AMES TEST; AMINO ACID COMPOSITION; ANTIVIRAL ACTIVITY; ARTICLE; CLASSIFICATION ALGORITHM; DRUG SCREENING; IN VITRO STUDY; MATHEMATICAL ANALYSIS; NONHUMAN; PREDICTION; SUPPORT VECTOR MACHINE; AMINO ACID SEQUENCE; CELLS, CULTURED; CHEMISTRY; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; DRUG EFFECTS; GENETICS; HIV-1; HUMANS; MOLECULAR SEQUENCE DATA; SALMONELLA TYPHIMURIUM;

HUMAN IMMUNODEFICIENCY VIRUS; HUMAN IMMUNODEFICIENCY VIRUS 1;

AMINO ACID SEQUENCE; ANTI-HIV AGENTS; CELLS, CULTURED; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; HIV CORE PROTEIN P24; HIV-1; HUMANS; MOLECULAR SEQUENCE DATA; MUTAGENS; PEPTIDE FRAGMENTS; SALMONELLA TYPHIMURIUM;

EID: 84919762192     PISSN: 10752617     EISSN: 10991387     Source Type: Journal    
DOI: 10.1002/psc.2712     Document Type: Article

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