Papers Antibody-antigen binding prediction
“Antibody-antigen binding prediction” 태그가 달린 논문 10편 · 필터 해제
ParaSurf: A Surface-Based Deep Learning Approach for Paratope-Antigen Interaction Prediction
Motivation Identifying antibody binding sites, is crucial for developing vaccines and therapeutic antibodies, processes that are time-consuming and costly. Accurate prediction of the paratope’s binding site can speed up…
Antibody-antigen binding predictionImproving Paratope and Epitope Prediction by Multi-Modal Contrastive Learning and Interaction Informativeness Estimation
Accurately predicting antibody-antigen binding residues, i.e., paratopes and epitopes, is crucial in antibody design. However, existing methods solely focus on uni-modal data (either sequence or structure), disregarding …
Antibody-antigen binding predictionContrastive LearningInformativenessPeSTo: parameter-free geometric deep learning for accurate prediction of protein binding interfaces
Proteins are essential molecular building blocks of life, responsible for most biological functions as a result of their specific molecular interactions. However, predicting their binding interfaces remains a challenge…
Antibody-antigen binding predictionParagraph—antibody paratope prediction using graph neural networks with minimal feature vectors
Summary: The development of new vaccines and antibody therapeutics typically takes several years and requires over $1bn in investment. Accurate knowledge of the paratope (antibody binding site) can speed up and reduce th…
Antibody-antigen binding predictionDeep learning-based rapid generation of broadly reactive antibodies against SARS-CoV-2 and its Omicron variant
The COVID-19 pandemic has been ongoing for nearly two and half years, and new variants of concern (VOCs) of SARS-CoV-2 continue to emerge, which urges the development of broadly neutralizing antibodies. Variants such as …
Antibody-antigen binding predictionDeep LearningProtein Function PredictionA large-scale systematic survey reveals recurring molecular features of public antibody responses to SARS-CoV-2
Global research to combat the COVID-19 pandemic has led to the isolation and characterization of thousands of human antibodies to the SARS-CoV-2 spike protein, providing an unprecedented opportunity to study the antibody…
Antibody-antigen binding predictionLearning context-aware structural representations to predict antigen and antibody binding interfaces
Motivation Understanding how antibodies specifically interact with their antigens can enable better drug and vaccine design, as well as provide insights into natural immunity. Experimental structural characterization ca…
Antibody-antigen binding predictionTransfer LearningAntibody interface prediction with 3D Zernike descriptors and SVM
Motivation Antibodies are a class of proteins capable of specifically recognizing and binding to a virtually infinite number of antigens. This binding malleability makes them the most valuable category of biopharmaceuti…
Antibody-antigen binding predictionBinary ClassificationDiagnosticPredictionAttentive cross-modal paratope prediction
Antibodies are a critical part of the immune system, having the function of directly neutralising or tagging undesirable objects (the antigens) for future destruction. Being able to predict which amino acids belong to th…
Antibody-antigen binding predictionComputational EfficiencyPredictionParapred: antibody paratope prediction using convolutional and recurrent neural networks
Motivation: Antibodies play essential roles in the immune system of vertebrates and are powerful tools in research and diagnostics. While hypervariable regions of antibodies, which are responsible for binding, can be rea…
Antibody-antigen binding prediction