[HTML][HTML] AlphaFold and implications for intrinsically disordered proteins

KM Ruff, RV Pappu - Journal of molecular biology, 2021 - Elsevier
Accurate predictions of the three-dimensional structures of proteins from their amino acid
sequences have come of age. AlphaFold, a deep learning-based approach to protein …

Protein design: From the aspect of water solubility and stability

R Qing, S Hao, E Smorodina, D Jin, A Zalevsky… - Chemical …, 2022 - ACS Publications
Water solubility and structural stability are key merits for proteins defined by the primary
sequence and 3D-conformation. Their manipulation represents important aspects of the …

Large language models generate functional protein sequences across diverse families

A Madani, B Krause, ER Greene, S Subramanian… - Nature …, 2023 - nature.com
Deep-learning language models have shown promise in various biotechnological
applications, including protein design and engineering. Here we describe ProGen, a …

Evolutionary-scale prediction of atomic-level protein structure with a language model

Z Lin, H Akin, R Rao, B Hie, Z Zhu, W Lu, N Smetanin… - Science, 2023 - science.org
Recent advances in machine learning have leveraged evolutionary information in multiple
sequence alignments to predict protein structure. We demonstrate direct inference of full …

[PDF][PDF] Language models of protein sequences at the scale of evolution enable accurate structure prediction

Z Lin, H Akin, R Rao, B Hie, Z Zhu, W Lu… - BioRxiv, 2022 - biorxiv.org
Large language models have recently been shown to develop emergent capabilities with
scale, going beyond simple pattern matching to perform higher level reasoning and …

Predicting multiple conformations via sequence clustering and AlphaFold2

HK Wayment-Steele, A Ojoawo, R Otten, JM Apitz… - Nature, 2024 - nature.com
Abstract AlphaFold2 (ref.) has revolutionized structural biology by accurately predicting
single structures of proteins. However, a protein's biological function often depends on …

High-resolution de novo structure prediction from primary sequence

R Wu, F Ding, R Wang, R Shen, X Zhang, S Luo, C Su… - BioRxiv, 2022 - biorxiv.org
Recent breakthroughs have used deep learning to exploit evolutionary information in
multiple sequence alignments (MSAs) to accurately predict protein structures. However …

Computed structures of core eukaryotic protein complexes

IR Humphreys, J Pei, M Baek, A Krishnakumar… - Science, 2021 - science.org
INTRODUCTION Protein-protein interactions play critical roles in biology, but the structures
of many eukaryotic protein complexes are unknown, and there are likely many interactions …

Language models enable zero-shot prediction of the effects of mutations on protein function

J Meier, R Rao, R Verkuil, J Liu… - Advances in neural …, 2021 - proceedings.neurips.cc
Modeling the effect of sequence variation on function is a fundamental problem for
understanding and designing proteins. Since evolution encodes information about function …

MSA transformer

RM Rao, J Liu, R Verkuil, J Meier… - International …, 2021 - proceedings.mlr.press
Unsupervised protein language models trained across millions of diverse sequences learn
structure and function of proteins. Protein language models studied to date have been …