Protein secondary structure prediction is extremely important for determining the spatial structure and function of proteins. In this paper, we apply an optimized convolutional neural network and long short-term memory neural network models to protei...
IEEE/ACM transactions on computational biology and bioinformatics
Feb 3, 2021
Improving the accuracy of predicting protein crystallization is very important for protein crystallization projects, which is a critical step for the determination of protein structure by X-ray crystallography. At present, many machine learning metho...
Proteins often exert their function by binding to other cellular partners. The hot spots are key residues for protein-protein binding. Their identification may shed light on the impact of disease associated mutations on protein complexes and help des...
Protein structure prediction is a long-standing unsolved problem in molecular biology that has seen renewed interest with the recent success of deep learning with AlphaFold at CASP13. While developing and evaluating protein structure prediction metho...
The protein disulfide bond is a covalent bond that forms during post-translational modification by the oxidation of a pair of cysteines. In protein, the disulfide bond is the most frequent covalent link between amino acids after the peptide bond. It ...
Journal of chemical information and modeling
Jan 25, 2021
In the world plagued by the emergence of new diseases, it is essential that we accelerate the drug design process to develop new therapeutics against them. In recent years, deep learning-based methods have shown some success in ligand-based drug desi...
Successful biologics must satisfy multiple properties including activity and particular physicochemical features that are globally defined as developability. These multiple properties must be simultaneously optimized in a very broad design space of p...
Journal of chemical information and modeling
Jan 19, 2021
Proteins carry out the most fundamental processes of life such as cellular metabolism, regulation, and communication. Understanding these processes at a molecular level requires knowledge of their three-dimensional structures. Experimental techniques...
International journal of molecular sciences
Jan 19, 2021
Accurately identifying protein-ATP binding residues is important for protein function annotation and drug design. Previous studies have used classic machine-learning algorithms like support vector machine (SVM) and random forest to predict protein-AT...
Structural insight of the protein-protein interaction (PPI) interface can provide knowledge about the kinetics, thermodynamics and molecular functions of the complex while elucidating its role in diseases and further enabling it as a potential therap...
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