The trRosetta server for fast and accurate protein structure prediction
The trRosetta (transform-restrained Rosetta) server is a web-based platform for fast and
accurate protein structure prediction, powered by deep learning and Rosetta. With the input …
accurate protein structure prediction, powered by deep learning and Rosetta. With the input …
Hot spots-making directed evolution easier
Directed evolution has emerged as a powerful strategy to engineer various properties of
proteins. Traditional methods to construct libraries such as error-prone PCR and DNA …
proteins. Traditional methods to construct libraries such as error-prone PCR and DNA …
Accurate prediction of protein structures and interactions using a three-track neural network
DeepMind presented notably accurate predictions at the recent 14th Critical Assessment of
Structure Prediction (CASP14) conference. We explored network architectures that …
Structure Prediction (CASP14) conference. We explored network architectures that …
Independent se (3)-equivariant models for end-to-end rigid protein docking
Protein complex formation is a central problem in biology, being involved in most of the cell's
processes, and essential for applications, eg drug design or protein engineering. We tackle …
processes, and essential for applications, eg drug design or protein engineering. We tackle …
Improved AlphaFold modeling with implicit experimental information
Abstract Machine-learning prediction algorithms such as AlphaFold and RoseTTAFold can
create remarkably accurate protein models, but these models usually have some regions …
create remarkably accurate protein models, but these models usually have some regions …
Deep transfer learning for inter-chain contact predictions of transmembrane protein complexes
Membrane proteins are encoded by approximately a quarter of human genes. Inter-chain
residue-residue contact information is important for structure prediction of membrane protein …
residue-residue contact information is important for structure prediction of membrane protein …
Protein language-model embeddings for fast, accurate, and alignment-free protein structure prediction
Advanced protein structure prediction requires evolutionary information from multiple
sequence alignments (MSAs) from evolutionary couplings that are not always available …
sequence alignments (MSAs) from evolutionary couplings that are not always available …
Improved protein structure prediction using a new multi‐scale network and homologous templates
The accuracy of de novo protein structure prediction has been improved considerably in
recent years, mostly due to the introduction of deep learning techniques. In this work …
recent years, mostly due to the introduction of deep learning techniques. In this work …
MoDAFold: a strategy for predicting the structure of missense mutant protein based on AlphaFold2 and molecular dynamics
Protein structure prediction is a longstanding issue crucial for identifying new drug targets
and providing a mechanistic understanding of protein functions. To enhance the progress in …
and providing a mechanistic understanding of protein functions. To enhance the progress in …
Automatic design of machine learning via evolutionary computation: A survey
Abstract Machine learning (ML), as the most promising paradigm to discover deep
knowledge from data, has been widely applied to practical applications, such as …
knowledge from data, has been widely applied to practical applications, such as …