AI Medical Compendium Topic:
Amino Acid Sequence

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MEGA-GO: functions prediction of diverse protein sequence length using Multi-scalE Graph Adaptive neural network.

Bioinformatics (Oxford, England)
MOTIVATION: The increasing accessibility of large-scale protein sequences through advanced sequencing technologies has necessitated the development of efficient and accurate methods for predicting protein function. Computational prediction models hav...

[AcidBasePred: a protein acid-base tolerance prediction platform based on deep learning].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology
The structures and activities of enzymes are influenced by pH of the environment. Understanding and distinguishing the adaptation mechanisms of enzymes to extreme pH values is of great significance for elucidating the molecular mechanisms and promoti...

SAMP: Identifying antimicrobial peptides by an ensemble learning model based on proportionalized split amino acid composition.

Briefings in functional genomics
It is projected that 10 million deaths could be attributed to drug-resistant bacteria infections in 2050. To address this concern, identifying new-generation antibiotics is an effective way. Antimicrobial peptides (AMPs), a class of innate immune eff...

Examining the Influenza A Virus Sialic Acid Binding Preference Predictions of a Sequence-Based Convolutional Neural Network.

Influenza and other respiratory viruses
BACKGROUND: Though receptor binding specificity is well established as a contributor to host tropism and spillover potential of influenza A viruses, determining receptor binding preference of a specific virus still requires expensive and time-consumi...

EFG-CS: Predicting chemical shifts from amino acid sequences with protein structure prediction using machine learning and deep learning models.

Protein science : a publication of the Protein Society
Nuclear magnetic resonance (NMR) crystallography is one of the main methods in structural biology for analyzing protein stereochemistry and structure. The chemical shift of the resonance frequency reflects the effect of the protons in a molecule prod...

Knot or not? Identifying unknotted proteins in knotted families with sequence-based Machine Learning model.

Protein science : a publication of the Protein Society
Knotted proteins, although scarce, are crucial structural components of certain protein families, and their roles continue to be a topic of intense research. Capitalizing on the vast collection of protein structure predictions offered by AlphaFold (A...

DEAttentionDTA: protein-ligand binding affinity prediction based on dynamic embedding and self-attention.

Bioinformatics (Oxford, England)
MOTIVATION: Predicting protein-ligand binding affinity is crucial in new drug discovery and development. However, most existing models rely on acquiring 3D structures of elusive proteins. Combining amino acid sequences with ligand sequences and bette...

AttABseq: an attention-based deep learning prediction method for antigen-antibody binding affinity changes based on protein sequences.

Briefings in bioinformatics
The optimization of therapeutic antibodies through traditional techniques, such as candidate screening via hybridoma or phage display, is resource-intensive and time-consuming. In recent years, computational and artificial intelligence-based methods ...

TemStaPro: protein thermostability prediction using sequence representations from protein language models.

Bioinformatics (Oxford, England)
MOTIVATION: Reliable prediction of protein thermostability from its sequence is valuable for both academic and industrial research. This prediction problem can be tackled using machine learning and by taking advantage of the recent blossoming of deep...

Enhancing cryo-EM structure prediction with DeepTracer and AlphaFold2 integration.

Briefings in bioinformatics
Understanding the protein structures is invaluable in various biomedical applications, such as vaccine development. Protein structure model building from experimental electron density maps is a time-consuming and labor-intensive task. To address the ...