Antibody complementarity determining region design using high-capacity machine learning
نویسندگان
چکیده
منابع مشابه
Predicting antibody complementarity determining region structures without classification.
Antibodies are used extensively in medical and biological research. Their complementarity determining regions (CDRs) define the majority of their antigen binding functionality. CDR structures have been intensively studied and classified (canonical structures). Here we show that CDR structure prediction is no different from the standard loop structure prediction problem and predict them without ...
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Protein-protein interactions are critical determinants in biological systems. Engineered proteins binding to specific areas on protein surfaces could lead to therapeutics or diagnostics for treating diseases in humans. But designing epitope-specific protein-protein interactions with computational atomistic interaction free energy remains a difficult challenge. Here we show that, with the antibo...
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Structural restrictions are present even in the most sequence diverse portions of antibodies, the complementary determining region (CDR) loops. Previous studies identified robust rules that define canonical structures for five of the six CDR loops, however the heavy chain CDR 3 (HCDR3) defies standard classification attempts. The HCDR3 loop can be subdivided into two domains referred to as the ...
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In contrast to a number of studies on the humanization of non-human antibodies, the reshaping of a non-human antibody into a chicken antibody has never been attempted. Therefore, nothing is known about the animal species-dependent compatibility of the framework regions (FRs) that sustain the appropriate conformation of the complementarity-determining regions (CDRs). In this study, we attempted ...
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The humanized monoclonal antibody HzKR127 recognizes the preS1 domain of the human hepatitis B virus surface proteins with a broadly neutralizing activity in vivo. We present the crystal structures of HzKR127 Fab and its complex with a major epitope peptide. In the complex structure, the bound peptide forms a type IV beta-turn followed by 3(10) helical turn, the looped-out conformation of which...
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ژورنال
عنوان ژورنال: Bioinformatics
سال: 2019
ISSN: 1367-4803,1460-2059
DOI: 10.1093/bioinformatics/btz895