Despite considerable improvements by deep learning methods for general protein complex prediction, prediction of antibody-antigen binding remains a challenge. Even the recent AlphaFold-Multimer model, which can accurately predict the interactions of many proteins, is still unable to predict how or whether...
et al. (2013) Prediction of site-specific interactions in antibody-antigen complexes: the proABC method and server. Bioinformatics, 29, 2285-2291.Olimpieri,P.P. et al. (2013) Prediction of site-specific interactions in antibody- antigen complexes: the proABC method and server. Bioinformatics,...
Machine learning (ML) is a key technology for accurate prediction of antibody–antigen binding. Two orthogonal problems hinder the application of ML to antibody-specificity prediction and the benchmarking thereof: the lack of a unified ML formalization of immunological antibody-specificity prediction prob...
We offer some final points regarding specificity. First, the interactions between molecules such as CD4 (Chapter 9) andmajor histocompatibility complex(MHC) class II (Chapter 5), which are not clonally distributed, are often described as nonspecific, meaning “not specific for an antigen under cons...
To better evaluate our model, we also tested other well-known structure-based antigen–antibody affinity prediction model (e.g. CSM-AB and AREA-AFFINITY). We input the 26 complex structures from the independent set into their online prediction website and manually calculated the R, R2, RMSD ...
(HERN) forparatopedocking and design by predicting the atomic forces and using them to refine an antibody-antigen complex in an iterative, equivariant fashion. Where both RefineGNN and AbDockGen suffer is the incurred computing cost and memory overhead due to unraveling the CDR sequence in an ...
适用物种:Human 寄主物种:Humanized 形式:Liquid 纯度:>95% 克隆性:Monoclonal 同种型:IgG4-kappa 应用:Research Grade Biosimilar UniProt:P26715 靶点:KLRC1, NKG2-A/NKG2-B type II integral membrane protein, NKG2-A/B-activating NK receptor, CD159 antigen-like family member A, CD159a, NK cell rec...
This mouse monoclonal antibody was generated against a ΦX174 bacteriophage-derived synthetic DNA–RNA antigen and recognizes RNA-DNA hybrids of various lengths.
diversity of the generated sequences and their similarity to natural sequences. Additionally, we employed the SOTA antibody-antigen complex structure prediction method, tFold47, to generate complexes between the modeled antibodies and the target antigen, following the benchmark protocol. We then ...
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