Journal of chemical information and modeling
Feb 7, 2022
Nowadays, machine learning and deep learning approaches are widely utilized for generative chemistry and computer-aided drug design and discovery such as de novo peptide and protein design, where target-specific peptide-based/protein-based therapeuti...
DeepMind released AlphaFold 2.0 in 2020, an artificial intelligence model to predict the structure of proteins, which could mean that proteins can be characterized without the need for tedious and costly lab analysis.
IEEE/ACM transactions on computational biology and bioinformatics
Feb 3, 2022
Identifying interactions between compound and protein is a substantial part of the drug discovery process. Accurate prediction of interaction relationships can greatly reduce the time of drug development. The uniqueness of our method lies in three as...
IEEE/ACM transactions on computational biology and bioinformatics
Feb 3, 2022
Antibodies consisting of variable and constant regions, are a special type of proteins playing a vital role in immune system of the vertebrate. They have the remarkable ability to bind a large range of diverse antigens with extraordinary affinity and...
IEEE/ACM transactions on computational biology and bioinformatics
Feb 3, 2022
Since protein 3D structure prediction is very important for biochemical study and drug design, researchers have developed many machine learning algorithms to predict protein 3D structures using the sequence information only. Understanding the sequenc...
IEEE/ACM transactions on computational biology and bioinformatics
Feb 3, 2022
The majority of clinical trials fail due to low efficacy of investigated drugs, often resulting from a poor choice of target protein. Existing computational approaches aim to support target selection either via genetic evidence or by putting potentia...
IEEE/ACM transactions on computational biology and bioinformatics
Feb 3, 2022
The inverse Potts problem to infer a Boltzmann distribution for homologous protein sequences from their single-site and pairwise amino acid frequencies recently attracts a great deal of attention in the studies of protein structure and evolution. We ...
Protein-protein interaction plays an important role in all biological systems. The binding affinity between two protein binding partners reflects the strength of their association, which is crucial to the elucidation of the biological functions of th...
Journal of chemical information and modeling
Feb 1, 2022
Predicting binding affinities between small molecules and the protein target is at the core of computational drug screening and drug target identification. Deep learning-based approaches have recently been adapted to predict binding affinities and th...
Elucidating the mechanisms of Compound-Protein Interactions (CPIs) plays an essential role in drug discovery and development. Many computational efforts have been done to accelerate the development of this field. However, the current predictive perfo...