Nanobody engineering: computational modelling and design for biomedical and therapeutic applications
Nanobodies, the smallest functional antibody fragment derived from camelid heavy‐chain‐
only antibodies, have emerged as powerful tools for diverse biomedical applications. In this …
only antibodies, have emerged as powerful tools for diverse biomedical applications. In this …
[HTML][HTML] Unified Sampling and Ranking for Protein Docking with DFMDock
Diffusion models have shown promise in addressing the protein docking problem.
Traditionally, these models are used solely for sampling docked poses, with a separate …
Traditionally, these models are used solely for sampling docked poses, with a separate …
On Machine Learning Approaches for Protein-Ligand Binding Affinity Prediction
Binding affinity optimization is crucial in early-stage drug discovery. While numerous
machine learning methods exist for predicting ligand potency, their comparative efficacy …
machine learning methods exist for predicting ligand potency, their comparative efficacy …
[HTML][HTML] PAbFold: Linear Antibody Epitope Prediction using AlphaFold2
J DeRoo, JS Terry, N Zhao, TJ Stasevich, CD Snow… - bioRxiv, 2024 - ncbi.nlm.nih.gov
Defining the binding epitopes of antibodies is essential for understanding how they bind to
their antigens and perform their molecular functions. However, while determining linear …
their antigens and perform their molecular functions. However, while determining linear …
Loop-Diffusion: an equivariant diffusion model for designing and scoring protein loops
K Borisiak, GM Visani, A Nourmohammad - arXiv preprint arXiv …, 2024 - arxiv.org
Predicting protein functional characteristics from structure remains a central problem in
protein science, with broad implications from understanding the mechanisms of disease to …
protein science, with broad implications from understanding the mechanisms of disease to …
Rosetta Energy Approximation Using a Machine Learning Approach
S Wei - 2024 - jscholarship.library.jhu.edu
The advent of AlphaFold2 has significantly accelerated advancements in protein structure
prediction using deep learning. Despite its monumental success, the AlphaFold2-like …
prediction using deep learning. Despite its monumental success, the AlphaFold2-like …