AI Medical Compendium Journal:
Journal of molecular biology

Showing 1 to 10 of 62 articles

TopCysteineDB: A Cysteinome-wide Database Integrating Structural and Chemoproteomics Data for Cysteine Ligandability Prediction.

Journal of molecular biology
Development of targeted covalent inhibitors and covalent ligand-first approaches have emerged as a powerful strategy in drug design, with cysteines being attractive targets due to their nucleophilicity and relative scarcity. While structural biology ...

ENsiRNA: A Multimodality Method for siRNA-mRNA and Modified siRNA Efficacy Prediction Based on Geometric Graph Neural Network.

Journal of molecular biology
With the rise of small interfering RNA (siRNA) as a therapeutic tool, effective siRNA design is crucial. Current methods often emphasize sequence-related features, overlooking structural information. To address this, we introduce ENsiRNA, a multimoda...

PLPTP: A Motif-based Interpretable Deep Learning Framework Based on Protein Language Models for Peptide Toxicity Prediction.

Journal of molecular biology
Peptide toxicity prediction holds significant importance in drug development and biotechnology, as accurately identifying toxic peptide sequences is crucial for designing safer peptide-based drugs. This study proposes a deep learning-based model for ...

Yeast Knowledge Graphs Database for Exploring Saccharomyces Cerevisiae and Schizosaccharomyces Pombe.

Journal of molecular biology
Biomedical literature contains an extensive wealth of information on gene and protein function across various biological processes and diseases. However, navigating this vast and often restricted-access data can be challenging, making it difficult to...

Identifying RNA-small Molecule Binding Sites Using Geometric Deep Learning with Language Models.

Journal of molecular biology
RNAs are emerging as promising therapeutic targets, yet identifying small molecules that bind to them remains a significant challenge in drug discovery. This underscores the crucial role of computational modeling in predicting RNA-small molecule bind...

ERNIE-ac4C: A Novel Deep Learning Model for Effectively Predicting N4-acetylcytidine Sites.

Journal of molecular biology
RNA modifications are known to play a critical role in gene regulation and cellular processes. Specifically, N4-acetylcytidine (ac4C) modification has emerged as a significant marker involved in mRNA translation efficiency, stability, and various dis...

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...

Caps-ac4C: An effective computational framework for identifying N4-acetylcytidine sites in human mRNA based on deep learning.

Journal of molecular biology
N4-acetylcytidine (ac4C) is a crucial post-transcriptional modification in human mRNA, involving the acetylation of the nitrogen atom at the fourth position of cytidine. This modification, catalyzed by N-acetyltransferases such as NAT10, is primarily...

GEMimp: An Accurate and Robust Imputation Method for Microbiome Data Using Graph Embedding Neural Network.

Journal of molecular biology
Microbiome research has increasingly underscored the profound link between microbial compositions and human health, with numerous studies establishing a strong correlation between microbiome characteristics and various diseases. However, the analysis...

iACP-DFSRA: Identification of Anticancer Peptides Based on a Dual-channel Fusion Strategy of ResCNN and Attention.

Journal of molecular biology
Anticancer peptides (ACPs) have been widely applied in the treatment of cancer owing to good safety, rational side effects, and high selectivity. However, the number of ACPs that have been experimentally validated is limited as identification of ACPs...