Developability assessment at early-stage discovery to enable development of antibody-derived therapeutics

W Zhang, H Wang, N Feng, Y Li, J Gu… - Antibody …, 2023 - academic.oup.com
Developability refers to the likelihood that an antibody candidate will become a
manufacturable, safe and efficacious drug. Although the safety and efficacy of a drug …

Building representation learning models for antibody comprehension

J Barton, A Gaspariunas… - Cold Spring Harbor …, 2024 - cshperspectives.cshlp.org
Antibodies are versatile proteins with both the capacity to bind a broad range of targets and
a proven track record as some of the most successful therapeutics. However, the …

Large scale paired antibody language models

H Kenlay, FA Dreyer, A Kovaltsuk… - PLOS Computational …, 2024 - journals.plos.org
Antibodies are proteins produced by the immune system that can identify and neutralise a
wide variety of antigens with high specificity and affinity, and constitute the most successful …

How can we discover developable antibody-based biotherapeutics?

J Bauer, N Rajagopal, P Gupta, P Gupta… - Frontiers in Molecular …, 2023 - frontiersin.org
Antibody-based biotherapeutics have emerged as a successful class of pharmaceuticals
despite significant challenges and risks to their discovery and development. This review …

[HTML][HTML] T-cell receptor binding prediction: A machine learning revolution

A Weber, A Pélissier, MR Martínez - ImmunoInformatics, 2024 - Elsevier
Recent advancements in immune sequencing and experimental techniques are generating
extensive T cell receptor (TCR) repertoire data, enabling the development of models to …

Biophysical cartography of the native and human-engineered antibody landscapes quantifies the plasticity of antibody developability

H Bashour, E Smorodina, M Pariset, J Zhong… - Communications …, 2024 - nature.com
Designing effective monoclonal antibody (mAb) therapeutics faces a multi-parameter
optimization challenge known as “developability”, which reflects an antibody's ability to …

Learning immune receptor representations with protein language models

A Dounas, TS Cotet, A Yermanos - arXiv preprint arXiv:2402.03823, 2024 - arxiv.org
Protein language models (PLMs) learn contextual representations from protein sequences
and are profoundly impacting various scientific disciplines spanning protein design, drug …

HELM: Hierarchical Encoding for mRNA Language Modeling

M Yazdani-Jahromi, M Prakash, T Mansi… - arXiv preprint arXiv …, 2024 - arxiv.org
Messenger RNA (mRNA) plays a crucial role in protein synthesis, with its codon structure
directly impacting biological properties. While Language Models (LMs) have shown promise …

Monoclonal antibodies: From magic bullet to precision weapon

H Aboul-Ella, A Gohar, AA Ali, LM Ismail… - Molecular …, 2024 - Springer
Monoclonal antibodies (mAbs) are used to prevent, detect, and treat a broad spectrum of
non-communicable and communicable diseases. Over the past few years, the market for …

Leveraging Artificial Intelligence to Expedite Antibody Design and Enhance Antibody–Antigen Interactions

DN Kim, AD McNaughton, N Kumar - Bioengineering, 2024 - mdpi.com
This perspective sheds light on the transformative impact of recent computational
advancements in the field of protein therapeutics, with a particular focus on the design and …