Antibody H3 structure prediction

Antibody H3 structure prediction

Antibodies are proteins of the immune system that are able to bind to a huge variety of different substances, making them attractive candidates for therapeutic applications. Antibody structures have the potential to be useful during drug development, allowing the implementation of rational design pr...

Full description

Bibliographic Details
Main Authors:	Marks, C, Deane, C
Format:	Journal article
Published:	Research Network of Computational and Structural Biotechnology 2017

Similar Items

Antibody H3 Structure Prediction
by: C. Marks, et al.
Published: (2017-01-01)

The H3 loop of antibodies shows unique structural characteristics
by: Regep, C, et al.
Published: (2017)

Increasing the accuracy of protein loop structure prediction with evolutionary constraints
by: Marks, C, et al.
Published: (2018)

SAbPred: a structure-based antibody prediction server
by: Deane, C, et al.
Published: (2016)

Predicting antibody complementarity determining region structures without classification.
by: Choi, Y, et al.
Published: (2011)

ABodyBuilder3: improved and scalable antibody structure predictions
by: Kenlay, H, et al.
Published: (2024)

Epitope profiling using computational structural modelling demonstrated on coronavirus-binding antibodies
by: Robinson, SA, et al.
Published: (2021)

CoV-AbDab: the coronavirus antibody database
by: Raybould, MIJ, et al.
Published: (2020)

Thera-SAbDab: the Therapeutic Structural Antibody Database
by: Raybould, MIJ, et al.
Published: (2019)

Antibody i-Patch prediction of the antibody binding site improves rigid local antibody-antigen docking.
by: Krawczyk, K, et al.
Published: (2013)

Challenges in antibody structure prediction
by: Monica L. Fernández-Quintero, et al.
Published: (2023-12-01)

Public Baseline and shared response structures support the theory of antibody repertoire functional commonality
by: Raybould, MIJ, et al.
Published: (2021)

ABodyBuilder: automated antibody structure prediction with data-driven accuracy estimation
by: Leem, J, et al.
Published: (2016)

Humanization of antibodies using a machine learning approach on large-scale repertoire data
by: Marks, C, et al.
Published: (2021)

Predicting loop conformational ensembles
by: Marks, C, et al.
Published: (2017)

ABlooper: fast accurate antibody CDR loop structure prediction with accuracy estimation
by: Abanades, B, et al.
Published: (2022)

TCRBuilder: multi-state T-cell receptor structure prediction
by: Wong, WK, et al.
Published: (2020)

Prediction of polyspecificity from antibody sequence data by machine learning
by: Éliás, S, et al.
Published: (2024)

Epitope profiling using computational structural modelling demonstrated on coronavirus-binding antibodies.
by: Sarah A Robinson, et al.
Published: (2021-12-01)

DLAB: deep learning methods for structure-based virtual screening of antibodies
by: Schneider, C, et al.
Published: (2021)

Public Baseline and shared response structures support the theory of antibody repertoire functional commonality.
by: Matthew I J Raybould, et al.
Published: (2021-03-01)

SAbDab: the structural antibody database.
by: Dunbar, J, et al.
Published: (2014)

SAbDab: the structural antibody database
by: Dunbar, J, et al.
Published: (2014)

Investigating the ability of deep learning-based structure prediction to extrapolate and/or enrich the set of antibody CDR canonical forms
by: Alexander Greenshields-Watson, et al.
Published: (2024-02-01)

Protein structure prediction begins well but ends badly.
by: Saunders, R, et al.
Published: (2010)

MP-T: improving membrane protein alignment for structure prediction.
by: Hill, JR, et al.
Published: (2013)

Improving B-cell epitope prediction and its application to global antibody-antigen docking.
by: Krawczyk, K, et al.
Published: (2014)

Five computational developability guidelines for therapeutic antibody profiling
by: Raybould, MIJ, et al.
Published: (2019)

CODA: a combined algorithm for predicting the structurally variable regions of protein models.
by: Deane, C, et al.
Published: (2001)

Prediction of polyspecificity from antibody sequence data by machine learning
by: Szabolcs Éliás, et al.
Published: (2024-04-01)

The role and predicted propensity of conserved proline residues in the 5-HT3 receptor
by: Deane, C, et al.
Published: (2001)

The role and predicted propensity of conserved proline residues in the 5-HT3 receptor.
by: Deane, C, et al.
Published: (2001)

Combining co-evolution and secondary structure prediction to improve fragment library generation
by: de Oliveira, S, et al.
Published: (2018)

Filtering next-generation sequencing of the Ig gene repertoire data using antibody structural information
by: Kovaltsuk, A, et al.
Published: (2018)

Filtering next-generation sequencing of the Ig gene repertoire data using antibody structural information
by: Kovaltsuk, A, et al.
Published: (2018)

Structurally mapping antibody repertoires
by: Krawczyk, K, et al.
Published: (2018)

Biologically inspired de novo protein structure prediction
by: de Oliveira, S, et al.
Published: (2015)

Predicting and validating protein interactions using network structure
by: Chen, P, et al.
Published: (2008)

SCALOP: sequence-based antibody canonical loop structure annotation
by: Wong, W, et al.
Published: (2018)

FREAD revisited: Accurate loop structure prediction using a database search algorithm.
by: Choi, Y, et al.
Published: (2010)