AIMC Topic: Amino Acid Sequence

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mACPpred 2.0: Stacked Deep Learning for Anticancer Peptide Prediction with Integrated Spatial and Probabilistic Feature Representations.

Journal of molecular biology Jun 25, 2024
Anticancer peptides (ACPs), naturally occurring molecules with remarkable potential to target and kill cancer cells. However, identifying ACPs based solely from their primary amino acid sequences remains a major hurdle in immunoinformatics. In the pa...
Deep Learning Computational Biology Amino Acid Sequence Software Peptides Antineoplastic Agents Humans Neural Networks, Computer
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RAIN: machine learning-based identification for HIV-1 bNAbs.

Nature communications Jun 24, 2024
Broadly neutralizing antibodies (bNAbs) are promising candidates for the treatment and prevention of HIV-1 infections. Despite their critical importance, automatic detection of HIV-1 bNAbs from immune repertoires is still lacking. Here, we develop a ...
HIV Envelope Protein gp120 CD4 Antigens Cryoelectron Microscopy HIV Antibodies Humans Machine Learning HIV Infections Antibodies, Neutralizing Amino Acid Sequence HIV-1
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Protein-Protein Interaction Prediction via Structure-Based Deep Learning.

Proteins Jun 23, 2024
Protein-protein interactions (PPIs) play an essential role in life activities. Many artificial intelligence algorithms based on protein sequence information have been developed to predict PPIs. However, these models have difficulty dealing with vario...
Databases, Protein Amino Acid Sequence Protein Interaction Mapping Computational Biology Proteins Humans Neural Networks, Computer Algorithms Animals Deep Learning Protein Interaction Maps
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TriplEP-CPP: Algorithm for Predicting the Properties of Peptide Sequences.

International journal of molecular sciences Jun 22, 2024
Advancements in medicine and pharmacology have led to the development of systems that deliver biologically active molecules inside cells, increasing drug concentrations at target sites. This improves effectiveness and duration of action and reduces s...
Humans Machine Learning Algorithms Amino Acid Sequence Animals Cell-Penetrating Peptides Proteome Wasp Venoms
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Improved prediction of anti-angiogenic peptides based on machine learning models and comprehensive features from peptide sequences.

Scientific reports Jun 22, 2024
Angiogenesis is a key process for the proliferation and metastatic spread of cancer cells. Anti-angiogenic peptides (AAPs), with the capability of inhibiting angiogenesis, are promising candidates in cancer treatment. We propose AAPL, a sequence-base...
Humans Angiogenesis Inhibitors Amino Acid Sequence Machine Learning Algorithms Peptides
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Enhancing Machine-Learning Prediction of Enzyme Catalytic Temperature Optima through Amino Acid Conservation Analysis.

International journal of molecular sciences Jun 6, 2024
Enzymes play a crucial role in various industrial production and pharmaceutical developments, serving as catalysts for numerous biochemical reactions. Determining the optimal catalytic temperature () of enzymes is crucial for optimizing reaction cond...
Machine Learning Enzyme Stability Conserved Sequence Catalysis Phosphoric Monoester Hydrolases Algorithms Amino Acids Temperature Amino Acid Sequence
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PTransIPs: Identification of Phosphorylation Sites Enhanced by Protein PLM Embeddings.

IEEE journal of biomedical and health informatics Jun 6, 2024
Phosphorylation is pivotal in numerous fundamental cellular processes and plays a significant role in the onset and progression of various diseases. The accurate identification of these phosphorylation sites is crucial for unraveling the molecular me...
Humans A549 Cells Amino Acid Sequence Sequence Analysis, Protein Deep Learning Proteins Phosphorylation
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RhoMax: Computational Prediction of Rhodopsin Absorption Maxima Using Geometric Deep Learning.

Journal of chemical information and modeling Jun 3, 2024
Microbial rhodopsins (MRs) are a diverse and abundant family of photoactive membrane proteins that serve as model systems for biophysical techniques. Optogenetics utilizes genetic engineering to insert specialized proteins into specific neurons or br...
Rhodopsin Rhodopsins, Microbial Protein Conformation Optogenetics Deep Learning Models, Molecular Amino Acid Sequence
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Application of artificial intelligence and machine learning techniques to the analysis of dynamic protein sequences.

Proteins May 29, 2024
We apply methods of Artificial Intelligence and Machine Learning to protein dynamic bioinformatics. We rewrite the sequences of a large protein data set, containing both folded and intrinsically disordered molecules, using a representation developed ...
Databases, Protein Amino Acid Sequence Intrinsically Disordered Proteins Algorithms Fourier Analysis Artificial Intelligence Protein Folding Computational Biology Machine Learning Sequence Analysis, Protein Proteins
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A multimodal Transformer Network for protein-small molecule interactions enhances predictions of kinase inhibition and enzyme-substrate relationships.

PLoS computational biology May 20, 2024
The activities of most enzymes and drugs depend on interactions between proteins and small molecules. Accurate prediction of these interactions could greatly accelerate pharmaceutical and biotechnological research. Current machine learning models des...
Deep Learning Protein Binding Protein Kinase Inhibitors Computational Biology Proteins Substrate Specificity Humans Amino Acid Sequence Machine Learning Small Molecule Libraries Protein Kinases
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