AIMC Topic: Amino Acid Sequence

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Rapid prediction of key residues for foldability by machine learning model enables the design of highly functional libraries with hyperstable constrained peptide scaffolds.

PLoS computational biology Nov 18, 2024
Peptides are an emerging modality for developing therapeutics that can either agonize or antagonize cellular pathways associated with disease, yet peptides often suffer from poor chemical and physical stability, which limits their potential. However,...
Models, Molecular Amino Acid Sequence Disulfides Protein Folding Peptide Library Computational Biology Machine Learning Peptides
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Pred-AHCP: Robust Feature Selection-Enabled Sequence-Specific Prediction of Anti-Hepatitis C Peptides via Machine Learning.

Journal of chemical information and modeling Nov 6, 2024
Every year, an estimated 1.5 million people worldwide contract Hepatitis C, a significant contributor to liver problems. Although many studies have explored machine learning's potential to predict antiviral peptides, very few have addressed the probl...
Algorithms Peptides Humans Machine Learning Hepacivirus Antiviral Agents Amino Acid Sequence
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All-Atom Protein Sequence Design Based on Geometric Deep Learning.

Angewandte Chemie (International ed. in English) Nov 4, 2024
Designing sequences for specific protein backbones is a key step in creating new functional proteins. Here, we introduce GeoSeqBuilder, a deep learning framework that integrates protein sequence generation with side chain conformation prediction to p...
Deep Learning Proteins Protein Conformation Models, Molecular Thioredoxins Amino Acid Sequence
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Machine Learning Framework for Conotoxin Class and Molecular Target Prediction.

Toxins Nov 3, 2024
Conotoxins are small and highly potent neurotoxic peptides derived from the venom of marine cone snails which have captured the interest of the scientific community due to their pharmacological potential. These toxins display significant sequence and...
Conotoxins Amino Acid Sequence Machine Learning Receptors, Nicotinic Animals
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Generative AI Models for the Protein Scaffold Filling Problem.

Journal of computational biology : a journal of computational molecular cell biology Oct 23, 2024
De novo protein sequencing is an important problem in proteomics, playing a crucial role in understanding protein functions, drug discovery, design and evolutionary studies, etc. Top-down and bottom-up tandem mass spectrometry are popular approaches ...
Algorithms Computational Biology Databases, Protein Humans Proteomics Amino Acid Sequence Artificial Intelligence Proteins Sequence Analysis, Protein
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Development of Peptide Identification System for ToF-SIMS Spectra Using Supervised Machine Learning.

Journal of the American Society for Mass Spectrometry Oct 12, 2024
Time-of-flight secondary ion mass spectrometry (ToF-SIMS) data interpretation for organic materials is complicated because of various fragment ions produced from each molecule and the overlapping of certain mass peaks from different molecules. Fragme...
Peptides Amino Acid Sequence Amino Acids Supervised Machine Learning Spectrometry, Mass, Secondary Ion
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PepNet: an interpretable neural network for anti-inflammatory and antimicrobial peptides prediction using a pre-trained protein language model.

Communications biology Sep 28, 2024
Identifying anti-inflammatory peptides (AIPs) and antimicrobial peptides (AMPs) is crucial for the discovery of innovative and effective peptide-based therapies targeting inflammation and microbial infections. However, accurate identification of AIPs...
Antimicrobial Peptides Anti-Inflammatory Agents Neural Networks, Computer Amino Acid Sequence Computational Biology
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Decoding the impact of neighboring amino acids on ESI-MS intensity output through deep learning.

Journal of proteomics Sep 26, 2024
Peptide-level quantification using mass spectrometry (MS) is no trivial task as the physicochemical properties affect both response and detectability. The specific amino acid (AA) sequence affects these properties, however the connection between sequ...
Peptides Amino Acid Motifs Deep Learning Amino Acid Sequence Amino Acids Spectrometry, Mass, Electrospray Ionization
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Impact of Multi-Factor Features on Protein Secondary Structure Prediction.

Biomolecules Sep 13, 2024
Protein secondary structure prediction (PSSP) plays a crucial role in resolving protein functions and properties. Significant progress has been made in this field in recent years, and the use of a variety of protein-related features, including amino ...
Machine Learning Protein Structure, Secondary Databases, Protein Amino Acids Computational Biology Amino Acid Sequence Proteins
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DeepDBS: Identification of DNA-binding sites in protein sequences by using deep representations and random forest.

Methods (San Diego, Calif.) Sep 11, 2024
Interactions of biological molecules in organisms are considered to be primary factors for the lifecycle of that organism. Various important biological functions are dependent on such interactions and among different kinds of interactions, the protei...
Protein Binding Computational Biology DNA Random Forest Databases, Protein Algorithms Binding Sites Deep Learning Neural Networks, Computer Sequence Analysis, Protein DNA-Binding Proteins Amino Acid Sequence
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