DEPTH: a web server to compute depth and predict small-molecule binding cavities in proteins
KP Tan, R Varadarajan… - Nucleic acids …, 2011 - academic.oup.com
Depth measures the extent of atom/residue burial within a protein. It correlates with
properties such as protein stability, hydrogen exchange rate, protein–protein interaction hot …
properties such as protein stability, hydrogen exchange rate, protein–protein interaction hot …
Real value prediction of solvent accessibility in proteins using multiple sequence alignment and secondary structure
A Garg, H Kaur, GPS Raghava - Proteins: Structure, Function …, 2005 - Wiley Online Library
The present study is an attempt to develop a neural network‐based method for predicting
the real value of solvent accessibility from the sequence using evolutionary information in …
the real value of solvent accessibility from the sequence using evolutionary information in …
DeepDist: real-value inter-residue distance prediction with deep residual convolutional network
Background Driven by deep learning, inter-residue contact/distance prediction has been
significantly improved and substantially enhanced ab initio protein structure prediction …
significantly improved and substantially enhanced ab initio protein structure prediction …
When homologous sequences meet structural decoys: Accurate contact prediction by tFold in CASP14—(tFold for CASP14 contact prediction)
In this paper, we report our tFold framework's performance on the inter‐residue contact
prediction task in the 14th Critical Assessment of protein Structure Prediction (CASP14). Our …
prediction task in the 14th Critical Assessment of protein Structure Prediction (CASP14). Our …
DOMpro: protein domain prediction using profiles, secondary structure, relative solvent accessibility, and recursive neural networks
Protein domains are the structural and functional units of proteins. The ability to parse
protein chains into different domains is important for protein classification and for …
protein chains into different domains is important for protein classification and for …
DeepECA: an end-to-end learning framework for protein contact prediction from a multiple sequence alignment
Background Recently developed methods of protein contact prediction, a crucially important
step for protein structure prediction, depend heavily on deep neural networks (DNNs) and …
step for protein structure prediction, depend heavily on deep neural networks (DNNs) and …
Protein structure prediction: conventional and deep learning perspectives
VA Jisna, PB Jayaraj - The protein journal, 2021 - Springer
Protein structure prediction is a way to bridge the sequence-structure gap, one of the main
challenges in computational biology and chemistry. Predicting any protein's accurate …
challenges in computational biology and chemistry. Predicting any protein's accurate …
Assessment of protein model structure accuracy estimation in CASP13: challenges in the era of deep learning
Scoring model structure is an essential component of protein structure prediction that can
affect the prediction accuracy tremendously. Users of protein structure prediction results also …
affect the prediction accuracy tremendously. Users of protein structure prediction results also …
A deep dilated convolutional residual network for predicting interchain contacts of protein homodimers
Motivation Deep learning has revolutionized protein tertiary structure prediction recently.
The cutting-edge deep learning methods such as AlphaFold can predict high-accuracy …
The cutting-edge deep learning methods such as AlphaFold can predict high-accuracy …
Sequence-based prediction of protein-protein interaction sites by simplified long short-term memory network
Proteins often interact with each other and form protein complexes to carry out various
biochemical activities. Knowledge of the interaction sites is helpful for understanding …
biochemical activities. Knowledge of the interaction sites is helpful for understanding …