AIMC Topic: Proteins

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Exploring Protein Conformational Changes Using a Large-Scale Biophysical Sampling Augmented Deep Learning Strategy.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Oct 10, 2024
Inspired by the success of deep learning in predicting static protein structures, researchers are now actively exploring other deep learning algorithms aimed at predicting the conformational changes of proteins. Currently, a major challenge in the de...
Proteins Molecular Dynamics Simulation Algorithms Deep Learning Protein Conformation Humans
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Drug-Target Binding Affinity Prediction in a Continuous Latent Space Using Variational Autoencoders.

IEEE/ACM transactions on computational biology and bioinformatics Oct 9, 2024
Accurate prediction of Drug-Target binding Affinity (DTA) is a daunting yet pivotal task in the sphere of drug discovery. Over the years, a plethora of deep learning-based DTA models have emerged, rendering promising results in predicting the binding...
Computational Biology Proteins Pharmaceutical Preparations Deep Learning Protein Binding Algorithms Drug Discovery Humans Neural Networks, Computer
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AI Prediction of Structural Stability of Nanoproteins Based on Structures and Residue Properties by Mean Pooled Dual Graph Convolutional Network.

Interdisciplinary sciences, computational life sciences Oct 5, 2024
The structural stability of proteins is an important topic in various fields such as biotechnology, pharmaceuticals, and enzymology. Specifically, understanding the structural stability of protein is crucial for protein design. Artificial design, whi...
Artificial Intelligence Algorithms Neural Networks, Computer Protein Stability Protein Conformation Thermodynamics Proteins Models, Molecular
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Stacking based ensemble learning framework for identification of nitrotyrosine sites.

Computers in biology and medicine Oct 3, 2024
Protein nitrotyrosine is an essential post-translational modification that results from the nitration of tyrosine amino acid residues. This modification is known to be associated with the regulation and characterization of several biological function...
Tyrosine Algorithms Machine Learning Humans Computational Biology Software Proteins Databases, Protein Protein Processing, Post-Translational
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Protein representations: Encoding biological information for machine learning in biocatalysis.

Biotechnology advances Oct 2, 2024
Enzymes offer a more environmentally friendly and low-impact solution to conventional chemistry, but they often require additional engineering for their application in industrial settings, an endeavour that is challenging and laborious. To address th...
Machine Learning Proteins Biocatalysis Neural Networks, Computer Enzymes
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Revolutionizing Molecular Design for Innovative Therapeutic Applications through Artificial Intelligence.

Molecules (Basel, Switzerland) Sep 29, 2024
The field of computational protein engineering has been transformed by recent advancements in machine learning, artificial intelligence, and molecular modeling, enabling the design of proteins with unprecedented precision and functionality. Computati...
Computational Biology Machine Learning Models, Molecular Proteins Drug Design Protein Engineering Humans Artificial Intelligence
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Dataset from a human-in-the-loop approach to identify functionally important protein residues from literature.

Scientific data Sep 27, 2024
We present a novel system that leverages curators in the loop to develop a dataset and model for detecting structure features and functional annotations at residue-level from standard publication text. Our approach involves the integration of data fr...
Proteins Databases, Protein Humans Machine Learning
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SSR-DTA: Substructure-aware multi-layer graph neural networks for drug-target binding affinity prediction.

Artificial intelligence in medicine Sep 17, 2024
Accurate prediction of drug-target binding affinity (DTA) is essential in the field of drug discovery. Recently, scientists have been attempting to utilize artificial intelligence prediction to screen out a significant number of ineffective compounds...
Drug Discovery Protein Binding Proteins Humans Neural Networks, Computer
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Combined Physics- and Machine-Learning-Based Method to Identify Druggable Binding Sites Using SILCS-Hotspots.

Journal of chemical information and modeling Sep 16, 2024
Identifying druggable binding sites on proteins is an important and challenging problem, particularly for cryptic, allosteric binding sites that may not be obvious from X-ray, cryo-EM, or predicted structures. The Site-Identification by Ligand Compet...
Ligands Protein Conformation Proteins Drug Discovery Binding Sites Machine Learning Protein Binding Molecular Dynamics Simulation
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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 ...
Proteins Databases, Protein Protein Structure, Secondary Machine Learning Amino Acids Computational Biology Amino Acid Sequence
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