{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T17:20:39Z","timestamp":1763140839467},"reference-count":45,"publisher":"Oxford University Press (OUP)","issue":"10","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,5,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Antibodies are an important class of biological drugs, but with limitations, such as inadequate pharmacokinetics, adverse immunogenicity and high production costs. Synthetic peptides for the desired target represent an important alternative to antibodies. However, no computational tool exists to guide the design of these peptides.<\/jats:p>\n               <jats:p>Results: To identify the interacting residues in a given antibody\u2013antigen (Ab\u2013Ag) interface we used Interface Interacting Residue (I2R), a selection method based on computed molecular interactions. The aggregation of all the molecular interactions between epitope and paratope residues allowed us to transform the 3D Ab\u2013Ag complex structures into interface graphs. Based on these data and the probability of molecular interaction we developed EPI-Peptide Designer tool that uses predicted paratope residues for an epitope of interest to generate targeted peptide ligand libraries. EPI-Peptide Designer successfully predicted 301 peptides able to bind to LiD1 target protein (65% of the experimentally tested peptides), an enrichment of 22% compared to randomly generated peptides. This tool should enable the development of a new generation of synthetic interacting peptides that could be very useful in the biosensor, diagnostic and therapeutic fields.<\/jats:p>\n               <jats:p>Availability and implementation: All software developed in this work are available at http:\/\/www.biocomp.icb.ufmg.br\/biocomp\/<\/jats:p>\n               <jats:p>Contact: \u00a0liza@icb.ufmg.br<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btw014","type":"journal-article","created":{"date-parts":[[2016,2,15]],"date-time":"2016-02-15T01:09:07Z","timestamp":1455498547000},"page":"1462-1470","source":"Crossref","is-referenced-by-count":10,"title":["EPI-peptide designer: a tool for designing peptide ligand libraries based on epitope\u2013paratope interactions"],"prefix":"10.1093","volume":"32","author":[{"given":"B.","family":"Viart","sequence":"first","affiliation":[{"name":"1 Departamento de Bioqu\u00edmica e Imunologia, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil,"}]},{"given":"C.","family":"Dias-Lopes","sequence":"additional","affiliation":[{"name":"1 Departamento de Bioqu\u00edmica e Imunologia, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil,"}]},{"given":"E.","family":"Kozlova","sequence":"additional","affiliation":[{"name":"1 Departamento de Bioqu\u00edmica e Imunologia, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil,"}]},{"given":"C. F. B.","family":"Oliveira","sequence":"additional","affiliation":[{"name":"1 Departamento de Bioqu\u00edmica e Imunologia, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil,"}]},{"given":"C.","family":"Nguyen","sequence":"additional","affiliation":[{"name":"2 Sys2Diag, FRE3690-CNRS\/ALCEDIAG, Montpellier, France and"}]},{"given":"G.","family":"Neshich","sequence":"additional","affiliation":[{"name":"3 Computational Biology Research Group, Embrapa Inform\u00e1tica Agropecu\u00e1ria, Campinas, SP, Brazil"}]},{"given":"C.","family":"Ch\u00e1vez-Ol\u00f3rtegui","sequence":"additional","affiliation":[{"name":"1 Departamento de Bioqu\u00edmica e Imunologia, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil,"}]},{"given":"F.","family":"Molina","sequence":"additional","affiliation":[{"name":"2 Sys2Diag, FRE3690-CNRS\/ALCEDIAG, Montpellier, France and"}]},{"given":"L. 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