[HTML][HTML] On the potential of machine learning to examine the relationship between sequence, structure, dynamics and function of intrinsically disordered proteins

K Lindorff-Larsen, BB Kragelund - Journal of Molecular Biology, 2021 - Elsevier
Intrinsically disordered proteins (IDPs) constitute a broad set of proteins with few uniting and
many diverging properties. IDPs—and intrinsically disordered regions (IDRs) interspersed …

Enhancing efficiency of protein language models with minimal wet-lab data through few-shot learning

Z Zhou, L Zhang, Y Yu, B Wu, M Li, L Hong… - Nature …, 2024 - nature.com
Accurately modeling the protein fitness landscapes holds great importance for protein
engineering. Pre-trained protein language models have achieved state-of-the-art …

Invertebrate models untangle the mechanism of neurodegeneration in Parkinson's disease

A Surguchov - Cells, 2021 - mdpi.com
Parkinson's disease (PD) is the second most common neurodegenerative disease,
afflicting~ 10 million people worldwide. Although several genes linked to PD are currently …

[HTML][HTML] Proteingym: Large-scale benchmarks for protein design and fitness prediction

P Notin, AW Kollasch, D Ritter, L van Niekerk, S Paul… - bioRxiv, 2023 - ncbi.nlm.nih.gov
Predicting the effects of mutations in proteins is critical to many applications, from
understanding genetic disease to designing novel proteins that can address our most …

Scalable approaches for generating, validating and incorporating data from high-throughput functional assays to improve clinical variant classification

SR Padigepati, DA Stafford, CA Tan, MR Silvis… - Human Genetics, 2024 - Springer
As the adoption and scope of genetic testing continue to expand, interpreting the clinical
significance of DNA sequence variants at scale remains a formidable challenge, with a high …

Plasticity of membrane binding by the central region of α-synuclein

C Navarro-Paya, M Sanz-Hernandez… - Frontiers in Molecular …, 2022 - frontiersin.org
Membrane binding by α-synuclein (αS), an intrinsically disordered protein whose
aggregation is associated with Parkinson's disease, is a key step in determining its …

Spiers Memorial Lecture: Analysis and de novo design of membrane-interactive peptides

HT Kratochvil, RW Newberry, B Mensa, M Mravic… - Faraday …, 2021 - pubs.rsc.org
Membrane–peptide interactions play critical roles in many cellular and organismic functions,
including protection from infection, remodeling of membranes, signaling, and ion transport …

Integrating deep mutational scanning and low-throughput mutagenesis data to predict the impact of amino acid variants

Y Fu, J Bedő, AT Papenfuss, AF Rubin - GigaScience, 2023 - academic.oup.com
Background Evaluating the impact of amino acid variants has been a critical challenge for
studying protein function and interpreting genomic data. High-throughput experimental …

Deep generative models for biology: represent, predict, design

P Notin - 2023 - ora.ox.ac.uk
Deep generative models have revolutionized the field of artificial intelligence, fundamentally
changing how we generate novel objects that imitate or extrapolate from training data, and …

Enhancing the efficiency of protein language models with minimal wet-lab data through few-shot learning

P Tan, Z Zhou, L Zhang, Y Yu, M Li, L Hong - 2024 - researchsquare.com
Accurately modeling the protein fitness landscapes holds great importance for protein
engineering. Recently, due to their capacity and representation ability, pre-trained protein …