AIMC Topic: Proteins

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Generalized biomolecular modeling and design with RoseTTAFold All-Atom.

Science (New York, N.Y.) Apr 19, 2024
Deep-learning methods have revolutionized protein structure prediction and design but are presently limited to protein-only systems. We describe RoseTTAFold All-Atom (RFAA), which combines a residue-based representation of amino acids and DNA bases w...
Deep Learning Proteins Amino Acids Protein Engineering Crystallography DNA Models, Molecular
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Encoding the space of protein-protein binding interfaces by artificial intelligence.

Computational biology and chemistry Apr 18, 2024
The physical interactions between proteins are largely determined by the structural properties at their binding interfaces. It was found that the binding interfaces in distinctive protein complexes are highly similar. The structural properties underl...
Protein Conformation Binding Sites Proteins Artificial Intelligence Models, Molecular Protein Binding
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ProtTrans and multi-window scanning convolutional neural networks for the prediction of protein-peptide interaction sites.

Journal of molecular graphics & modelling Apr 17, 2024
This study delves into the prediction of protein-peptide interactions using advanced machine learning techniques, comparing models such as sequence-based, standard CNNs, and traditional classifiers. Leveraging pre-trained language models and multi-vi...
Peptides Protein Binding Machine Learning Algorithms Databases, Protein Humans Computational Biology Binding Sites Neural Networks, Computer Proteins
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Protein Engineering with Lightweight Graph Denoising Neural Networks.

Journal of chemical information and modeling Apr 17, 2024
Protein engineering faces challenges in finding optimal mutants from a massive pool of candidate mutants. In this study, we introduce a deep-learning-based data-efficient fitness prediction tool to steer protein engineering. Our methodology establish...
Models, Molecular Mutation Protein Conformation Protein Engineering Deep Learning Proteins Neural Networks, Computer
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Genome-scale annotation of protein binding sites via language model and geometric deep learning.

eLife Apr 17, 2024
Revealing protein binding sites with other molecules, such as nucleic acids, peptides, or small ligands, sheds light on disease mechanism elucidation and novel drug design. With the explosive growth of proteins in sequence databases, how to accuratel...
Peptides Deep Learning Protein Binding Proteins Binding Sites
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Apprehensions and emerging solutions in ML-based protein structure prediction.

Current opinion in structural biology Apr 16, 2024
The three-dimensional structure of proteins determines their function in vital biological processes. Thus, when the structure is known, the molecular mechanism of protein function can be understood in more detail and obtained information utilized in ...
Machine Learning Models, Molecular Computational Biology Proteins Protein Conformation
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PT-Finder: A multi-modal neural network approach to target identification.

Computers in biology and medicine Apr 15, 2024
Efficient target identification for bioactive compounds, including novel synthetic analogs, is crucial for accelerating the drug discovery pipeline. However, the process of target identification presents significant challenges and is often expensive,...
Drug Discovery Proteins Ligands Machine Learning Software Humans Neural Networks, Computer
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DEEP-EP: Identification of epigenetic protein by ensemble residual convolutional neural network for drug discovery.

Methods (San Diego, Calif.) Apr 14, 2024
Epigenetic proteins (EP) play a role in the progression of a wide range of diseases, including autoimmune disorders, neurological disorders, and cancer. Recognizing their different functions has prompted researchers to investigate them as potential t...
Algorithms Drug Discovery Humans Neural Networks, Computer Proteins Deep Learning Epigenesis, Genetic
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PeSTo-Carbs: Geometric Deep Learning for Prediction of Protein-Carbohydrate Binding Interfaces.

Journal of chemical theory and computation Apr 11, 2024
The Protein Structure Transformer (PeSTo), a geometric transformer, has exhibited exceptional performance in predicting protein-protein binding interfaces and distinguishing interfaces with nucleic acids, lipids, small molecules, and ions. In this st...
Carbohydrates Binding Sites Deep Learning Protein Binding Proteins
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Emerging structure-based computational methods to screen the exploding accessible chemical space.

Current opinion in structural biology Apr 10, 2024
Structure-based virtual screening can be a valuable approach to computationally select hit candidates based on their predicted interaction with a protein of interest. The recent explosion in the size of chemical libraries increases the chances of hit...
Humans Small Molecule Libraries Computational Biology Proteins Machine Learning Drug Discovery
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