[HTML][HTML] Advances in computational structure-based antibody design
Antibodies are currently the most important class of biotherapeutics and are used to treat
numerous diseases. Recent advances in computational methods are ushering in a new era …
numerous diseases. Recent advances in computational methods are ushering in a new era …
Third generation antibody discovery methods: in silico rational design
Owing to their outstanding performances in molecular recognition, antibodies are
extensively used in research and applications in molecular biology, biotechnology and …
extensively used in research and applications in molecular biology, biotechnology and …
Unconstrained generation of synthetic antibody–antigen structures to guide machine learning methodology for antibody specificity prediction
Abstract Machine learning (ML) is a key technology for accurate prediction of antibody–
antigen binding. Two orthogonal problems hinder the application of ML to antibody …
antigen binding. Two orthogonal problems hinder the application of ML to antibody …
Specificity of bispecific T cell receptors and antibodies targeting peptide-HLA
CJ Holland, RM Crean, JM Pentier… - The Journal of …, 2020 - Am Soc Clin Investig
Tumor-associated peptide–human leukocyte antigen complexes (pHLAs) represent the
largest pool of cell surface–expressed cancer-specific epitopes, making them attractive …
largest pool of cell surface–expressed cancer-specific epitopes, making them attractive …
Structural aspects of the allergen-antibody interaction
A Pomés, GA Mueller, M Chruszcz - Frontiers in immunology, 2020 - frontiersin.org
The development of allergic disease involves the production of IgE antibodies upon allergen
exposure in a process called sensitization. IgE binds to receptors on the surface of mast …
exposure in a process called sensitization. IgE binds to receptors on the surface of mast …
One billion synthetic 3D-antibody-antigen complexes enable unconstrained machine-learning formalized investigation of antibody specificity prediction
Abstract Machine learning (ML) is a key technology to enable accurate prediction of
antibody-antigen binding, a prerequisite for in silico vaccine and antibody design. Two …
antibody-antigen binding, a prerequisite for in silico vaccine and antibody design. Two …
Protein-protein interactions: insight from molecular dynamics simulations and nanoparticle tracking analysis
Protein-protein interaction plays an essential role in almost all cellular processes and
biological functions. Coupling molecular dynamics (MD) simulations and nanoparticle …
biological functions. Coupling molecular dynamics (MD) simulations and nanoparticle …
Intrinsically Disordered Malaria Antigens: An Overview of Structures, Dynamics and Molecular Simulation Opportunities
PCC Silva, L Martínez - Journal of the Brazilian Chemical Society, 2024 - SciELO Brasil
The proteome of Plasmodium falciparum (Pf) is abundant in intrinsically disordered proteins
(IDPs). Their important roles in the malaria life cycle and the limitations of experimental and …
(IDPs). Their important roles in the malaria life cycle and the limitations of experimental and …
Label‐Free Detection of Transferrin Receptor by a Designed Ligand‐Protein Sensor
Advanced detection of biomarkers in biofluids plays an important role in disease diagnosis
and prognosis. Current techniques with pre‐labelling suffer from high cost and complicated …
and prognosis. Current techniques with pre‐labelling suffer from high cost and complicated …
Communication pathways bridge local and global conformations in an IgG4 antibody
The affinity of an antibody for its antigen is primarily determined by the specific sequence
and structural arrangement of the complementarity-determining regions (CDRs). Recent …
and structural arrangement of the complementarity-determining regions (CDRs). Recent …