AIMC Topic: Amino Acid Sequence

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Predicting Peptide Ionization Efficiencies for Electrospray Ionization Mass Spectrometry Using Machine Learning.

Journal of the American Society for Mass Spectrometry Sep 9, 2024
Mass spectrometry (MS) is inherently an information-rich technique. In this era of big data, label-free MS quantification for nontargeted studies has gained increasing popularity, especially for complex systems. One of the cornerstones of successful ...
Antibodies, Monoclonal Amino Acid Sequence Spectrometry, Mass, Electrospray Ionization Machine Learning Peptides
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StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features.

Methods (San Diego, Calif.) Aug 22, 2024
Host defense or antimicrobial peptides (AMPs) are promising candidates for protecting host against microbial pathogens for example bacteria, virus, fungi, yeast. Defensins are the type of AMPs that act as potential therapeutic drug agent and perform ...
Defensins Amino Acid Sequence Position-Specific Scoring Matrices Computational Biology Principal Component Analysis Machine Learning Algorithms
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Protein Language Models and Machine Learning Facilitate the Identification of Antimicrobial Peptides.

International journal of molecular sciences Aug 14, 2024
Peptides are bioactive molecules whose functional versatility in living organisms has led to successful applications in diverse fields. In recent years, the amount of data describing peptide sequences and function collected in open repositories has s...
Antimicrobial Cationic Peptides Amino Acid Sequence Antimicrobial Peptides Drug Discovery Computational Biology Machine Learning Algorithms
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Deep mutational scanning and machine learning for the analysis of antimicrobial-peptide features driving membrane selectivity.

Nature biomedical engineering Jul 31, 2024
Many antimicrobial peptides directly disrupt bacterial membranes yet can also damage mammalian membranes. It is therefore central to their therapeutic use that rules governing the membrane selectivity of antimicrobial peptides be deciphered. However,...
Amino Acid Sequence Cell Membrane Antimicrobial Peptides Structure-Activity Relationship Mutation Mice Antimicrobial Cationic Peptides Machine Learning Female Animals Microbial Sensitivity Tests
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Context-aware geometric deep learning for protein sequence design.

Nature communications Jul 25, 2024
Protein design and engineering are evolving at an unprecedented pace leveraging the advances in deep learning. Current models nonetheless cannot natively consider non-protein entities within the design process. Here, we introduce a deep learning appr...
Protein Conformation Protein Engineering Models, Molecular Amino Acid Sequence Deep Learning Proteins
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Uncovering substrate specificity determinants of class IIb aminoacyl-tRNA synthetases with machine learning.

Journal of molecular graphics & modelling Jul 14, 2024
Specific amino acid (AA) binding by aminoacyl-tRNA synthetases (aaRSs) is necessary for correct translation of the genetic code. Sequence and structure analyses have revealed the main specificity determinants and allowed a partitioning of aaRSs into ...
Amino Acid Sequence Substrate Specificity Amino Acyl-tRNA Synthetases Machine Learning Models, Molecular
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A CNN-CBAM-BIGRU model for protein function prediction.

Statistical applications in genetics and molecular biology Jul 1, 2024
Understanding a protein's function based solely on its amino acid sequence is a crucial but intricate task in bioinformatics. Traditionally, this challenge has proven difficult. However, recent years have witnessed the rise of deep learning as a powe...
Computational Biology Proteins Algorithms Humans Amino Acid Sequence Deep Learning Databases, Protein Neural Networks, Computer
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APLpred: A machine learning-based tool for accurate prediction and characterization of asparagine peptide lyases using sequence-derived optimal features.

Methods (San Diego, Calif.) Jun 28, 2024
Asparagine peptide lyase (APL) is among the seven groups of proteases, also known as proteolytic enzymes, which are classified according to their catalytic residue. APLs are synthesized as precursors or propeptides that undergo self-cleavage through ...
Support Vector Machine Databases, Protein Software Computational Biology Amino Acid Sequence Machine Learning
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Cracking AlphaFold2: Leveraging the power of artificial intelligence in undergraduate biochemistry curriculums.

PLoS computational biology Jun 27, 2024
AlphaFold2 is an Artificial Intelligence-based program developed to predict the 3D structure of proteins given only their amino acid sequence at atomic resolution. Due to the accuracy and efficiency at which AlphaFold2 can generate 3D structure predi...
Curriculum Protein Conformation Biochemistry Proteins Amino Acid Sequence Computational Biology Universities Software Students Humans Artificial Intelligence
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TransfIGN: A Structure-Based Deep Learning Method for Modeling the Interaction between HLA-A*02:01 and Antigen Peptides.

Journal of chemical information and modeling Jun 26, 2024
The intricate interaction between major histocompatibility complexes (MHCs) and antigen peptides with diverse amino acid sequences plays a pivotal role in immune responses and T cell activity. In recent years, deep learning (DL)-based models have eme...
Humans Peptides Protein Conformation Models, Molecular Amino Acid Sequence HLA-A2 Antigen Deep Learning Protein Binding
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