AIMC Topic: Adenosine Triphosphate

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Dual-Site Targeting by Peptide Inhibitors of the N-Terminal Domain of Hsp90: Mechanism and Design.

Journal of chemical information and modeling May 1, 2025
Heat shock protein 90 (Hsp90) is a pivotal molecular chaperone crucial in the maturation of client proteins, positioning it as a significant target for cancer therapy. However, the design of effective Hsp90 inhibitors presents substantial challenges ...
Peptides Molecular Docking Simulation Drug Design Humans Machine Learning Adenosine Triphosphate Binding Sites HSP90 Heat-Shock Proteins Protein Binding Protein Domains Molecular Dynamics Simulation
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A potential supplemental indication of dipyridamole for contraception: Dipyridamole inhibits mouse sperm fertilization capacity in vitro.

Biochemical and biophysical research communications Apr 11, 2025
The inhibition of sperm cAMP and ATP levels, using an FDA-approved medication, may impair sperm motility and, consequently, fertilization, thus paving the way for the development of a male contraceptive. The objective of this study was to define the ...
Contraception Dipyridamole Spermatozoa Male Female Contraceptive Agents, Male Sperm Motility Mice Adenosine Triphosphate Animals Fertilization in Vitro Cyclic AMP Fertilization
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Residue-Level Multiview Deep Learning for ATP Binding Site Prediction and Applications in Kinase Inhibitors.

Journal of chemical information and modeling Dec 17, 2024
Accurate identification of adenosine triphosphate (ATP) binding sites is crucial for understanding cellular functions and advancing drug discovery, particularly in targeting kinases for cancer treatment. Existing methods face significant challenges d...
Molecular Docking Simulation Drug Discovery Deep Learning Humans Protein Kinase Inhibitors Binding Sites Adenosine Triphosphate Ligands
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ATP_mCNN: Predicting ATP binding sites through pretrained language models and multi-window neural networks.

Computers in biology and medicine Dec 8, 2024
Adenosine triphosphate plays a vital role in providing energy and enabling key cellular processes through interactions with binding proteins. The increasing amount of protein sequence data necessitates computational methods for identifying binding si...
Neural Networks, Computer Computational Biology Databases, Protein Proteins Humans Adenosine Triphosphate Binding Sites
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TopicBERT: A Topic-Enhanced Neural Language Model Fine-Tuned for Sentiment Classification.

IEEE transactions on neural networks and learning systems Jan 5, 2023
Sentiment classification is a form of data analytics where people's feelings and attitudes toward a topic are mined from data. This tantalizing power to "predict the zeitgeist" means that sentiment classification has long attracted interest, but with...
Neural Networks, Computer Language Natural Language Processing Humans Adenosine Triphosphate Sentiment Analysis
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Identification of missing hierarchical relations in the vaccine ontology using acquired term pairs.

Journal of biomedical semantics Aug 13, 2022
BACKGROUND: The Vaccine Ontology (VO) is a biomedical ontology that standardizes vaccine annotation. Errors in VO will affect a multitude of applications that it is being used in. Quality assurance of VO is imperative to ensure that it provides accur...
Biological Ontologies Vaccines Adenosine Triphosphate
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Prediction of protein mononucleotide binding sites using AlphaFold2 and machine learning.

Computational biology and chemistry Jul 23, 2022
In this study, we developed a system that predicts the binding sites of proteins for five mononucleotides (AMP, ADP, ATP, GDP, and GTP). The system comprises two machine learning (ML)-based predictors using a convolutional neural network and a gradie...
Ligands Binding Sites Adenosine Diphosphate Adenosine Monophosphate Protein Binding Proteins Adenosine Triphosphate Machine Learning
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Robotic end-to-end fusion of microtubules powered by kinesin.

Science robotics Nov 3, 2021
The active assembly of molecules by nanorobots has advanced greatly since “molecular manufacturing”—that is, the use of nanoscale tools to build molecular structures—was proposed. In contrast to a catalyst, which accelerates a reaction by smoothing t...
Biochemical Phenomena Animals Adenosine Triphosphate Microtubules Drosophila melanogaster Rhodamines Kinesins Ribosomes Robotic Surgical Procedures Models, Biological Escherichia coli Motion Robotics
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Accurate prediction of protein-ATP binding residues using position-specific frequency matrix.

Analytical biochemistry May 7, 2021
Knowledge of protein-ATP interaction can help for protein functional annotation and drug discovery. Accurately identifying protein-ATP binding residues is an important but challenging task to gain the knowledge of protein-ATP interactions, especially...
Algorithms Protein Binding Computational Biology Proteins Adenosine Triphosphate Humans Neural Networks, Computer
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Prediction of Protein-ATP Binding Residues Based on Ensemble of Deep Convolutional Neural Networks and LightGBM Algorithm.

International journal of molecular sciences Jan 19, 2021
Accurately identifying protein-ATP binding residues is important for protein function annotation and drug design. Previous studies have used classic machine-learning algorithms like support vector machine (SVM) and random forest to predict protein-AT...
Adenosine Triphosphate Proteins Amino Acid Sequence Humans Neural Networks, Computer Computational Biology Support Vector Machine Carrier Proteins Machine Learning Algorithms Protein Binding
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