Published online 6 June 2012 Nucleic Acids Research, 2012, Vol. 40, Web Server issue W521–W524 doi:10.1093/nar/gks480 Paratome: an online tool for systematic identification of antigen-binding regions in antibodies based on sequence or structure Vered Kunik, Shaul Ashkenazi and Yanay Ofran* The Goodman Faculty of Life Sciences, Nanotechnology Building, Bar-Ilan University, Ramat Gan 52900, Israel Received February 2, 2012; Revised April 26, 2012; Accepted May 8, 2012 ABSTRACT Antibodies are capable of specifically recognizing and binding antigens. Identification of the antigen- binding site, commonly dubbed paratope, is of high importance both for medical and biological applica- tions. To date, the identification of antigen-binding regions (ABRs) relies on tools for the identification of complementarity-determining regions (CDRs). However, we have shown that up to 22% of the residues that actually bind the antigen fall outside the traditionally defined CDRs. The Paratome web server predicts the ABRs of an antibody, given its amino acid sequence or 3D structure. It is based on a set of consensus regions derived from a structural alignment of a non-redundant set of all known antibody–antigen complexes. Given a query sequence or structure, the server identifies the regions in the query antibody that correspond to the consensus ABRs. An independent set of antibody–antigen complexes was used to test the server and it was shown to correctly identify at least 94% of the antigen-binding residues. The Paratome web server is freely available at http:// www.ofranlab.org/paratome/. INTRODUCTION One of the most common problems in immunological research is the identiﬁcation of paratopes, namely the residues within an immunoglobulin that recognize and bind the antigen (Ag). The high afﬁnity and speciﬁcity of antibodies (Abs) to their cognate Ag, which allows them to block its activity or to mark it for destruction (1), are at the heart of immunity. They also make Abs powerful tools in numerous molecular applications in research as well as in diagnostics and therapy (2–7). Therefore, to understand immunity (and autoimmunity) and to engineer and improve Ab-based applications, one needs to ﬁrst identify the molecular determinants that mediate Ag recognition and binding. However, currently there is no tool available for providing such prediction. complementarity-determining regions (CDRs) are con- sidered a proxy for the sites that recognize and bind the Ag. CDRs are six hypervariable segments of amino acids, three on each of the light and heavy chains (8–10). Attempts to computationally identify CDRs have been on going for >40 years (10–17). The most commonly used CDR identiﬁcation methods to date are Kabat (10,15), Chothia (12,13,16) and IMGT (16). Each of these methods has devised a unique residue numbering scheme according to which it numbers the hypervariable region residues and the beginning and ending of each of the six CDRs is then determined according to certain key pos- itions. The pressing need in this type of analysis is mani- fested in the citations: in 2010 alone these methods generated over 500 citations. Arguably, many of the users are not interested in the CDRs as such but rather are interested in identifying the residues that mediate Ag binding. However, in a recent analysis we have shown that CDR identiﬁcation methods may miss >20% of the residues that actually bind the Ag (18). Furthermore, we have also shown that the residues that are missed by these methods include some that make crucial energetic contri- bution to Ag binding (18). The Paratome web server implements an algorithm we developed for the identiﬁcation of antigen-binding regions (ABRs) from the amino acid sequence or 3D structure of an Ab (18). The algorithm is based on the premise that the vast majority of antigen-binding residues lie in regions of structural consensus between Abs. These structural con- sensus regions form six sequence stretches along the Ab sequence, roughly corresponding to the six CDRs (18,19). The server uses the structural consensus regions within a multiple structure alignment (MSTA) of a non-redundant set of all antibody–antigen (Ab–Ag) complexes, as a ref- erence according to which the ABRs of unannotated Abs are inferred (18). It is trained to identify binding regions for Abs that bind protein or peptide Ags. To our know- ledge, Paratome is currently the only server aimed at *To whom correspondence should be addressed. Tel: +972 3 531 9772; Fax: +972 3 7384197; Email: yanay@ofranlab.org The Author(s) 2012. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/ by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.