AIMC Topic: Databases, Protein

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A large language model for predicting neurotoxic peptides and neurotoxins.

Protein science : a publication of the Protein Society
The accurate prediction of neurotoxicity in peptides and proteins is essential for the safety evaluation of therapeutic proteins and genetically modified (GM) organisms. Existing tools, including our earlier method NTxPred, typically use a single pre...

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 ...

InDeepNet: a web platform for predicting functional binding sites in proteins using InDeep.

Nucleic acids research
Predicting functional binding sites in proteins is crucial for understanding protein-protein interactions (PPIs) and identifying drug targets. While various computational approaches exist, many fail to assess PPI ligandability, which often involves c...

GOBeacon: An ensemble model for protein function prediction enhanced by contrastive learning.

Protein science : a publication of the Protein Society
Accurate prediction of protein function is fundamental to understanding biological processes, with computational methods becoming increasingly essential as experimental methods struggle to keep pace with the rate of newly discovered proteins. Despite...

Predicting Protein Function in the AI and Big Data Era.

Biochemistry
It is an exciting time for researchers working to link proteins to their functions. Most techniques for extracting functional information from genomic sequences were developed several years ago, with major progress driven by the availability of big d...

DeepAllo: allosteric site prediction using protein language model (pLM) with multitask learning.

Bioinformatics (Oxford, England)
MOTIVATION: Allostery, the process by which binding at one site perturbs a distant site, is being rendered as a key focus in the field of drug development with its substantial impact on protein function. The identification of allosteric pockets (site...

DRBP-EDP: classification of DNA-binding proteins and RNA-binding proteins using ESM-2 and dual-path neural network.

NAR genomics and bioinformatics
Regulation of DNA or RNA at the transcriptional, post-transcriptional, and translational levels are key steps in the central dogma of molecular biology. DNA-binding proteins (DBPs) and RNA-binding proteins (RBPs) play pivotal roles in the precise reg...

Predicting Mutation-Disease Associations Through Protein Interactions Via Deep Learning.

IEEE journal of biomedical and health informatics
Disease is one of the primary factors affecting life activities, with complex etiologies often influenced by gene expression and mutation. Currently, wet lab experiments have analyzed the mechanisms of mutations, but these are usually limited by the ...

Protein function prediction using GO similarity-based heterogeneous network propagation.

Scientific reports
Protein function prediction is a fundamental cornerstone in bioinformatics, providing critical insights into biological processes and disease mechanisms. Despite significant advances, challenges persist due to data sparsity and functional ambiguity. ...

AbSet: A Standardized Data Set of Antibody Structures for Machine Learning Applications.

Journal of chemical information and modeling
Machine learning algorithms have played a fundamental role in the development of therapeutic antibodies by being trained on data sets of sequences and/or structures. However, structural data sets remain limited, especially those that include antibody...