AIMC Topic: Databases, Protein

Clear Filters Showing 51 to 60 of 766 articles

Skittles: GNN-Assisted Pseudo-Ligands Generation and Its Application for Binding Sites Classification and Affinity Prediction.

Proteins
Nowadays, multiple solutions are known for identifying ligand-protein binding sites. Another important task is labeling each point of a binding site with the appropriate atom type, a process known as pseudo-ligand generation. The number of solutions ...

Peptide classification landscape: An in-depth systematic literature review on peptide types, databases, datasets, predictors architectures and performance.

Computers in biology and medicine
Peptides are gaining significant attention in diverse fields such as the pharmaceutical market has seen a steady rise in peptide-based therapeutics over the past six decades. Peptides have been utilized in the development of distinct applications inc...

Probing the eukaryotic microbes of ruminants with a deep-learning classifier and comprehensive protein databases.

Genome research
Metagenomics, particularly genome-resolved metagenomics, have significantly deepened our understanding of microbes, illuminating their taxonomic and functional diversity and roles in ecology, physiology, and evolution. However, eukaryotic populations...

Simpler Protein Domain Identification Using Spectral Clustering.

Proteins
The decomposition of a biomolecular complex into domains is an important step to investigate biological functions and ease structure determination. A successful approach to do so is the SPECTRUS algorithm, which provides a segmentation based on spect...

SEGT-GO: a graph transformer method based on PPI serialization and explanatory artificial intelligence for protein function prediction.

BMC bioinformatics
BACKGROUND: A massive amount of protein sequences have been obtained, but their functions remain challenging to discern. In recent research on protein function prediction, Protein-Protein Interaction (PPI) Networks have played a crucial role. Uncover...

DOGpred: A Novel Deep Learning Framework for Accurate Identification of Human O-linked Threonine Glycosylation Sites.

Journal of molecular biology
O-linked glycosylation is a crucial post-translational modification that regulates protein function and biological processes. Dysregulation of this process is associated with various diseases, underscoring the need to accurately identify O-linked gly...

KaMLs for Predicting Protein p Values and Ionization States: Are Trees All You Need?

Journal of chemical theory and computation
Despite its importance in understanding biology and computer-aided drug discovery, the accurate prediction of protein ionization states remains a formidable challenge. Physics-based approaches struggle to capture the small, competing contributions in...

PDB-IHM: A System for Deposition, Curation, Validation, and Dissemination of Integrative Structures.

Journal of molecular biology
Structures of many large biomolecular assemblies are now being determined using integrative approaches. In these approaches, information derived from multiple experimental and computational methods is combined to compute three-dimensional structures ...

MAI-TargetFisher: A proteome-wide drug target prediction method synergetically enhanced by artificial intelligence and physical modeling.

Acta pharmacologica Sinica
Computational target identification plays a pivotal role in the drug development process. With the significant advancements of deep learning methods for protein structure prediction, the structural coverage of human proteome has increased substantial...

Phyre2.2: A Community Resource for Template-based Protein Structure Prediction.

Journal of molecular biology
Template-based modelling, also known as homology modelling, is a powerful approach to predict the structure of a protein from its amino acid sequence. The approach requires one to identify a sequence similarity between the query sequence and that of ...