Recent developments in deep learning, coupled with an increasing number of sequenced
proteins, have led to a breakthrough in life science applications, in particular in protein …

Abstract Protein Structure Prediction is a central topic in Structural Bioinformatics. Since
the'60s statistical methods, followed by increasingly complex Machine Learning and recently …

Molecule docking has been regarded as a routine tool for drug discovery, but its accuracy
highly depends on the reliability of scoring functions (SFs). With the rapid development of …

Worldwide, heart disease is the leading cause of mortality. By providing proper therapy,
early identification of heart disease can lower the likelihood of the illness advancing to a …

We present DescribePROT, the database of predicted amino acid-level descriptors of
structure and function of proteins. DescribePROT delivers a comprehensive collection of 13 …

Abstract Na+/H+ exchangers (NHEs) are ancient membrane‐bound nanomachines that
work to regulate intracellular pH, sodium levels and cell volume. NHE activities contribute to …

Because of the increase in different types of diseases in human habitats, demands for
designing various types of drugs are also increasing. Protein and its structure play a very …

Motivation Protein structures provide basic insight into how they can interact with other
proteins, their functions and biological roles in an organism. Experimental methods (eg X …

The recent emergence of deep learning to characterize complex patterns of protein big data
reveals its potential to address the classic challenges in the field of protein data mining …

This paper aims to provide a comprehensive review of the trends and challenges of deep
neural networks for protein secondary structure prediction (PSSP). In recent years, deep …