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Protein Conformation

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Protein structure prediction with in-cell photo-crosslinking mass spectrometry and deep learning.

Nature biotechnology
While AlphaFold2 can predict accurate protein structures from the primary sequence, challenges remain for proteins that undergo conformational changes or for which few homologous sequences are known. Here we introduce AlphaLink, a modified version of...

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

Science (New York, N.Y.)
Recent advances in machine learning have leveraged evolutionary information in multiple sequence alignments to predict protein structure. We demonstrate direct inference of full atomic-level protein structure from primary sequence using a large langu...

Are Deep Learning Structural Models Sufficiently Accurate for Virtual Screening? Application of Docking Algorithms to AlphaFold2 Predicted Structures.

Journal of chemical information and modeling
Machine learning-based protein structure prediction algorithms, such as RosettaFold and AlphaFold2, have greatly impacted the structural biology field, arousing a fair amount of discussion around their potential role in drug discovery. While there ar...

Real-to-bin conversion for protein residue distances.

Computational biology and chemistry
Protein Structure Prediction (PSP) has achieved significant progress lately. Prediction of inter-residue distances by machine learning and their exploitation during the conformational search is largely among the critical factors behind the progress. ...

Evaluating native-like structures of RNA-protein complexes through the deep learning method.

Nature communications
RNA-protein complexes underlie numerous cellular processes, including basic translation and gene regulation. The high-resolution structure determination of the RNA-protein complexes is essential for elucidating their functions. Therefore, computation...

Assessing protein homology models with docking reproducibility.

Journal of molecular graphics & modelling
Results of the recent Critical Assessment of Protein Structure (CASP) competitions demonstrate that protein backbones can be predicted with very high accuracy. In particular, the artificial intelligence methods of AlphaFold 2 from DeepMind were able ...

Deep learning for reconstructing protein structures from cryo-EM density maps: Recent advances and future directions.

Current opinion in structural biology
Cryo-Electron Microscopy (cryo-EM) has emerged as a key technology to determine the structure of proteins, particularly large protein complexes and assemblies in recent years. A key challenge in cryo-EM data analysis is to automatically reconstruct a...

Smart de novo Macromolecular Structure Modeling from Cryo-EM Maps.

Journal of molecular biology
The study of macromolecular structures has expanded our understanding of the amazing cell machinery and such knowledge has changed how the pharmaceutical industry develops new vaccines in recent years. Traditionally, X-ray crystallography has been th...

Critical Assessment of Methods for Predicting the 3D Structure of Proteins and Protein Complexes.

Annual review of biophysics
Advances in a scientific discipline are often measured by small, incremental steps. In this review, we report on two intertwined disciplines in the protein structure prediction field, modeling of single chains and modeling of complexes, that have ove...

Improving Protein-Ligand Interaction Modeling with cryo-EM Data, Templates, and Deep Learning in 2021 Ligand Model Challenge.

Biomolecules
Elucidating protein-ligand interaction is crucial for studying the function of proteins and compounds in an organism and critical for drug discovery and design. The problem of protein-ligand interaction is traditionally tackled by molecular docking a...