AIMC Topic: Amino Acid Sequence

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SPIN-CGNN: Improved fixed backbone protein design with contact map-based graph construction and contact graph neural network.

PLoS computational biology Dec 7, 2023
Recent advances in deep learning have significantly improved the ability to infer protein sequences directly from protein structures for the fix-backbone design. The methods have evolved from the early use of multi-layer perceptrons to convolutional ...
Neural Networks, Computer Cluster Analysis Diffusion Amino Acid Sequence Amino Acids
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Prediction of interactions between cell surface proteins by machine learning.

Proteins Dec 5, 2023
Cells detect changes in their external environments or communicate with each other through proteins on their surfaces. These cell surface proteins form a complicated network of interactions in order to fulfill their functions. The interactions betwee...
Immunoglobulins Humans Ligands Machine Learning Membrane Proteins Amino Acid Sequence
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MEnTaT: A machine-learning approach for the identification of mutations to increase protein stability.

Proceedings of the National Academy of Sciences of the United States of America Dec 1, 2023
Enhancing protein thermal stability is important for biomedical and industrial applications as well as in the research laboratory. Here, we describe a simple machine-learning method which identifies amino acid substitutions that contribute to thermal...
Machine Learning Protein Stability Proteins Enzyme Stability Mutation Amino Acid Sequence
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MaTPIP: A deep-learning architecture with eXplainable AI for sequence-driven, feature mixed protein-protein interaction prediction.

Computer methods and programs in biomedicine Nov 30, 2023
BACKGROUND AND OBJECTIVE: Protein-protein interaction (PPI) is a vital process in all living cells, controlling essential cell functions such as cell cycle regulation, signal transduction, and metabolic processes with broad applications that include ...
Deep Learning ROC Curve Mice Proteins Neural Networks, Computer Amino Acid Sequence Humans Animals
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PepCNN deep learning tool for predicting peptide binding residues in proteins using sequence, structural, and language model features.

Scientific reports Nov 28, 2023
Protein-peptide interactions play a crucial role in various cellular processes and are implicated in abnormal cellular behaviors leading to diseases such as cancer. Therefore, understanding these interactions is vital for both functional genomics and...
Software Peptides Deep Learning Proteins Amino Acid Sequence
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Ensemble Learning with Supervised Methods Based on Large-Scale Protein Language Models for Protein Mutation Effects Prediction.

International journal of molecular sciences Nov 18, 2023
Machine learning has been increasingly utilized in the field of protein engineering, and research directed at predicting the effects of protein mutations has attracted increasing attention. Among them, so far, the best results have been achieved by r...
Proteins Amino Acid Sequence Linear Models Machine Learning Reproducibility of Results
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Evaluating the chaos game representation of proteins for applications in machine learning models: prediction of antibody affinity and specificity as a case study.

Journal of molecular modeling Nov 15, 2023
CONTEXT: Machine learning techniques are becoming increasingly important in the selection and optimization of therapeutic molecules, as well as for the selection of formulation components and the prediction of long-term stability. Compared to first-p...
Antibody Affinity Proteins Amino Acid Sequence Machine Learning Neural Networks, Computer
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DeepMPSF: A Deep Learning Network for Predicting General Protein Phosphorylation Sites Based on Multiple Protein Sequence Features.

Journal of chemical information and modeling Nov 6, 2023
Phosphorylation, as one of the most important post-translational modifications, plays a key role in various cellular physiological processes and disease occurrences. In recent years, computer technology has been gradually applied to the prediction of...
Protein Processing, Post-Translational Proteins Mice Rats Phosphorylation Amino Acid Sequence Humans Animals Deep Learning
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ProGen2: Exploring the boundaries of protein language models.

Cell systems Oct 30, 2023
Attention-based models trained on protein sequences have demonstrated incredible success at classification and generation tasks relevant for artificial-intelligence-driven protein design. However, we lack a sufficient understanding of how very large-...
Artificial Intelligence Amino Acid Sequence Language Proteins Databases, Factual
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Exploring novel ANGICon-EIPs through ameliorated peptidomics techniques: Can deep learning strategies as a core breakthrough in peptide structure and function prediction?

Food research international (Ottawa, Ont.) Oct 27, 2023
Dairy-derived angiotensin-I-converting enzyme inhibitory peptides (ANGICon-EIPs) have been regarded as a relatively safe supplementary diet-therapy strategy for individuals with hypertension, and short-chain peptides may have more relevant antihypert...
Neural Networks, Computer Amino Acid Sequence Humans Deep Learning Peptides Proteins
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