Natural antioxidant proteins are mainly found in plants and animals, which interact to eliminate excessive free radicals and protect cells and DNA from damage, prevent and treat some diseases. Therefore, accurate identification of antioxidant protein...
Journal of chemical information and modeling
Aug 4, 2020
Current deep learning methods for structure-based virtual screening take the structures of both the protein and the ligand as input but make little or no use of the protein structure when predicting ligand binding. Here, we show how a relatively simp...
Imaging technology and machine learning algorithms for disease classification set the stage for high-throughput phenotyping and promising new avenues for genome-wide association studies (GWAS). Despite emerging algorithms, there has been no successfu...
The numerous interconnected biochemical pathways that make up the metabolism of a living cell comprise a fuzzy logic system because of its high level of complexity and our inability to fully understand, predict, and model the many activities, how the...
Manually identifying and correcting errors in protein models can be a slow process, but improvements in validation tools and automated model-building software can contribute to reducing this burden. This article presents a new correctness score that ...
Cancer is driven by genomic alterations, but the processes causing this disease are largely performed by proteins. However, proteins are harder and more expensive to measure than genes and transcripts. To catalyze developments of methods to infer pro...
Journal of chemical theory and computation
Jul 16, 2020
Machine learning encompasses tools and algorithms that are now becoming popular in almost all scientific and technological fields. This is true for molecular dynamics as well, where machine learning offers promises of extracting valuable information ...
Journal of chemical theory and computation
Jul 6, 2020
Atom pairwise potential functions make up an essential part of many scoring functions for protein decoy detection. With the development of machine learning (ML) tools, there are multiple ways to combine potential functions to create novel ML models a...
International journal of molecular sciences
Jul 6, 2020
Predicting protein-protein interactions (PPI) represents an important challenge in structural bioinformatics. Current computational methods display different degrees of accuracy when predicting these interactions. Different factors were proposed to h...
Information embedded in ligand-binding residues (LBRs) of proteins is important for understanding protein functions. How to accurately identify the potential ligand-binding residues is still a challenging problem, especially only protein sequence is ...
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