title: Proteochemometric modeling of the antigen-antibody interaction: new fingerprints for antigen, antibody and epitope-paratope interaction.
abstract: Despite the high specificity between antigen and antibody binding, similar epitopes can be recognized or cross-neutralized by paratopes of antibody with different binding affinities. How to accurately characterize this slight variation which may or may not change the antigen-antibody binding affinity is a key issue in this area. In this report, by combining cylinder model with shell structure model, a new fingerprint was introduced to describe both the structural and physical-chemical features of the antigen and antibody protein. Furthermore, beside the description of individual protein, the specific epitope-paratope interaction fingerprint (EPIF) was developed to reflect the bond and the environment of the antigen-antibody interface. Finally, Proteochemometric Modeling of the antigen-antibody interaction was established and evaluated on 429 antigen-antibody complexes. By using only protein descriptors, our model achieved the best performance (R2 = 0.91, Qtest(2) = 0.68) among peers. Further, together with EPIF as a new cross-term, our model (R2 = 0.92, Qtest(2) = 0.74) can significantly outperform peers with multiplication of ligand and protein descriptors as a cross-term (R2 ≤ 0.81, Qtest(2) ≤ 0.44). Results illustrated that: 1) our newly designed protein fingerprints and EPIF can better describe the antigen-antibody interaction; 2) EPIF is a better and specific cross-term in Proteochemometric Modeling for antigen-antibody interaction. The fingerprints designed in this study will provide assistance to the description of antigen-antibody binding, and in future, it may be valuable help for the high-throughput antibody screening. The algorithm is freely available on request.
authors.affiliation: Department of Bioinformatics, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.
authors.forename: Tianyi
authors.initials: T
authors.lastname: Qiu
authors.affiliation: Department of Computer Science, University of Helsinki, Helsinki, FI-00014, Finland.
authors.forename: Han
authors.initials: H
authors.lastname: Xiao
authors.affiliation: Department of Bioinformatics, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.
authors.forename: Qingchen
authors.initials: Q
authors.lastname: Zhang
authors.affiliation: Department of Bioinformatics, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.
authors.forename: Jingxuan
authors.initials: J
authors.lastname: Qiu
authors.affiliation: Department of Bioinformatics, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.
authors.forename: Yiyan
authors.initials: Y
authors.lastname: Yang
authors.affiliation: Department of Bioinformatics, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.
authors.forename: Dingfeng
authors.initials: D
authors.lastname: Wu
authors.affiliation: Department of Bioinformatics, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China; Shanghai Center for Bioinformation Technology, Shanghai 201203, China.
authors.forename: Zhiwei
authors.initials: Z
authors.lastname: Cao
authors.affiliation: Department of Bioinformatics, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China; School of Pharmacy, Liaoning University of Traditional Chinese Medicine, Dalian 116600, Liaoning, China.
authors.forename: Ruixin
authors.initials: R
authors.lastname: Zhu
mesh_terms: D000818:Animals; D000906:Antibodies / Q000737:chemistry* / Q000276:immunology; D000936:Antigen-Antibody Complex / Q000737:chemistry*; D000941:Antigens / Q000737:chemistry* / Q000276:immunology; D000939:Epitopes / Q000737:chemistry / Q000378:metabolism; D006801:Humans; D008958:Models, Molecular; D010449:Peptide Mapping
chemical_list: D000906:Antibodies; D000936:Antigen-Antibody Complex; D000941:Antigens; D000939:Epitopes