3Drefine: Consistent protein structure refinement by optimizing hydrogen bonding network and atomic‐level energy minimization
D Bhattacharya, J Cheng - Proteins: Structure, Function, and …, 2013 - Wiley Online Library
One of the major limitations of computational protein structure prediction is the deviation of
predicted models from their experimentally derived true, native structures. The limitations …
predicted models from their experimentally derived true, native structures. The limitations …
Computational protein structure refinement: almost there, yet still so far to go
M Feig - Wiley Interdisciplinary Reviews: Computational …, 2017 - Wiley Online Library
Protein structures are essential in modern biology yet experimental methods are far from
being able to catch up with the rapid increase in available genomic data. Computational …
being able to catch up with the rapid increase in available genomic data. Computational …
Toward high-resolution de novo structure prediction for small proteins
The prediction of protein structure from amino acid sequence is a grand challenge of
computational molecular biology. By using a combination of improved low-and high …
computational molecular biology. By using a combination of improved low-and high …
Critical assessment of methods of protein structure prediction (CASP)—Round XIV
Critical assessment of structure prediction (CASP) is a community experiment to advance
methods of computing three‐dimensional protein structure from amino acid sequence. Core …
methods of computing three‐dimensional protein structure from amino acid sequence. Core …
Protein tertiary structure prediction and refinement using deep learning and Rosetta in CASP14
The trRosetta structure prediction method employs deep learning to generate predicted
residue‐residue distance and orientation distributions from which 3D models are built. We …
residue‐residue distance and orientation distributions from which 3D models are built. We …
High‐accuracy protein structure prediction in CASP14
The application of state‐of‐the‐art deep‐learning approaches to the protein modeling
problem has expanded the “high‐accuracy” category in CASP14 to encompass all targets …
problem has expanded the “high‐accuracy” category in CASP14 to encompass all targets …
De novo protein design by deep network hallucination
There has been considerable recent progress in protein structure prediction using deep
neural networks to predict inter-residue distances from amino acid sequences,–. Here we …
neural networks to predict inter-residue distances from amino acid sequences,–. Here we …
A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction
Ab initio protein secondary structure (SS) predictions are utilized to generate tertiary
structure predictions, which are increasingly demanded due to the rapid discovery of …
structure predictions, which are increasingly demanded due to the rapid discovery of …
Estimation of model accuracy in CASP13
J Cheng, MH Choe, A Elofsson, KS Han… - Proteins: Structure …, 2019 - Wiley Online Library
Methods to reliably estimate the accuracy of 3D models of proteins are both a fundamental
part of most protein folding pipelines and important for reliable identification of the best …
part of most protein folding pipelines and important for reliable identification of the best …
Single-sequence protein structure prediction using supervised transformer protein language models
Significant progress has been made in protein structure prediction in recent years. However,
it remains challenging for AlphaFold2 and other deep learning-based methods to predict …
it remains challenging for AlphaFold2 and other deep learning-based methods to predict …