AIMC Topic: Single-Domain Antibodies

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Nanobodies targeting ion channels: advancing therapeutics through precision and structural insights.

Chemical communications (Cambridge, England)
Ion channels, which are integral to cellular signaling and homeostasis, are implicated in a variety of diseases, including neurological disorders, cardiovascular conditions, and cancers. Despite their importance, targeting ion channels therapeuticall...

Nanobodies targeting cytokines for the amelioration of autoimmune diseases.

International immunopharmacology
Autoimmune diseases are driven by dysregulated cytokine networks, where excessive cytokines such as TNF-α, IL-6, IL-17, and IL-23 promote chronic inflammation and tissue damage. While monoclonal antibodies effectively neutralise these cytokines, they...

An iterative strategy to design 4-1BB agonist nanobodies de novo with generative AI models.

Scientific reports
The 4-1BB receptor, a key member of the tumor necrosis factor receptor (TNFR) family, represents a highly promising target for cancer immunotherapy. In this study, we developed a novel in silico pipeline to design VHH domain antibodies targeting 4-1B...

Design of nanobody targeting SARS-CoV-2 spike glycoprotein using CDR-grafting assisted by molecular simulation and machine learning.

PLoS computational biology
The design of proteins capable effectively binding to specific protein targets is crucial for developing therapies, diagnostics, and vaccine candidates for viral infections. Here, we introduce a complementarity-determining region (CDR) grafting appro...

Unveiling the new chapter in nanobody engineering: advances in traditional construction and AI-driven optimization.

Journal of nanobiotechnology
Nanobodies (Nbs), miniature antibodies consisting solely of the variable region of heavy chains, exhibit unique properties such as small size, high stability, and strong specificity, making them highly promising for disease diagnosis and treatment. T...

Nanobody screening and machine learning guided identification of cross-variant anti-SARS-CoV-2 neutralizing heavy-chain only antibodies.

PLoS pathogens
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to persist, demonstrating the risks posed by emerging infectious diseases to national security, public health, and the economy. Development of new vaccines and antibodies for emer...

Prediction of protein biophysical traits from limited data: a case study on nanobody thermostability through NanoMelt.

mAbs
In-silico prediction of protein biophysical traits is often hindered by the limited availability of experimental data and their heterogeneity. Training on limited data can lead to overfitting and poor generalizability to sequences distant from those ...

ParaAntiProt provides paratope prediction using antibody and protein language models.

Scientific reports
Efficiently predicting the paratope holds immense potential for enhancing antibody design, treating cancers and other serious diseases, and advancing personalized medicine. Although traditional methods are highly accurate, they are often time-consumi...

Advancements in nanobody generation: Integrating conventional, in silico, and machine learning approaches.

Biotechnology and bioengineering
Nanobodies, derived from camelids and sharks, offer compact, single-variable heavy-chain antibodies with diverse biomedical potential. This review explores their generation methods, including display techniques on phages, yeast, or bacteria, and comp...

Accurate prediction of CDR-H3 loop structures of antibodies with deep learning.

eLife
Accurate prediction of the structurally diverse complementarity determining region heavy chain 3 (CDR-H3) loop structure remains a primary and long-standing challenge for antibody modeling. Here, we present the H3-OPT toolkit for predicting the 3D st...