AIMC Topic: Binding Sites

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Transcription Factor Binding Site Prediction Using CnNet Approach.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Controlling the gene expression is the most important development in a living organism, which makes it easier to find different kinds of diseases and their causes. It's very difficult to know what factors control the gene expression. Transcription Fa...
Humans Computational Biology Transcription Factors Sequence Analysis, DNA Neural Networks, Computer Algorithms Deep Learning Binding Sites
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RGCNPPIS: A Residual Graph Convolutional Network for Protein-Protein Interaction Site Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Accurate identification of protein-protein interaction (PPI) sites is crucial for understanding the mechanisms of biological processes, developing PPI networks, and detecting protein functions. Currently, most computational methods primarily concentr...
Computational Biology Binding Sites Proteins Neural Networks, Computer Humans Databases, Protein Protein Interaction Mapping Algorithms Protein Interaction Maps
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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...
Databases, Protein Adenosine Triphosphate Binding Sites Neural Networks, Computer Computational Biology Proteins Humans
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Small Molecule Inhibitors of Topoisomerase I Identified by Machine Learning and In Vitro Assays.

International journal of molecular sciences Nov 15, 2024
Tuberculosis (TB) caused by is a leading infectious cause of death globally. The treatment of patients becomes much more difficult for the increasingly common multi-drug resistant TB. Topoisomerase I is essential for the viability of and has been v...
Topoisomerase I Inhibitors Humans Machine Learning Molecular Docking Simulation Binding Sites Small Molecule Libraries DNA Topoisomerases, Type I Antitubercular Agents Mycobacterium tuberculosis High-Throughput Screening Assays
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Estimating AChE inhibitors from MCE database by machine learning and atomistic calculations.

Journal of molecular graphics & modelling Nov 14, 2024
Acetylcholinesterase (AChE) is one of the most successful targets for the treatment of Alzheimer's disease (AD). Inhibition of AChE can result in preventing AD. In this context, the machine-learning (ML) model, molecular docking, and molecular dynami...
Molecular Dynamics Simulation Ligands Acetylcholinesterase Cholinesterase Inhibitors Databases, Chemical Binding Sites Machine Learning Molecular Docking Simulation Protein Binding Humans
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Improving drug-target interaction prediction through dual-modality fusion with InteractNet.

Journal of bioinformatics and computational biology Nov 11, 2024
In the drug discovery process, accurate prediction of drug-target interactions is crucial to accelerate the development of new drugs. However, existing methods still face many challenges in dealing with complex biomolecular interactions. To this end,...
Ligands Deep Learning Machine Learning Protein Binding Binding Sites Algorithms Proteins Humans Computational Biology Drug Discovery Databases, Protein Neural Networks, Computer Pharmaceutical Preparations
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LGS-PPIS: A Local-Global Structural Information Aggregation Framework for Predicting Protein-Protein Interaction Sites.

Proteins Nov 9, 2024
Exploring protein-protein interaction sites (PPIS) is of significance to elucidating the intrinsic mechanisms of diverse biological processes. On this basis, recent studies have applied deep learning-based technologies to overcome the high cost of we...
Databases, Protein Protein Binding Binding Sites Humans Protein Interaction Domains and Motifs Protein Interaction Mapping Computational Biology Algorithms Proteins Deep Learning
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An Integrated TCN-CrossMHA Model for Predicting circRNA-RBP Binding Sites.

Interdisciplinary sciences, computational life sciences Nov 6, 2024
Circular RNA (circRNA) has the capacity to bind with RNA binding protein (RBP), thereby exerting a substantial impact on diseases. Predicting binding sites aids in comprehending the interaction mechanism, thereby offering insights for disease treatme...
RNA, Circular Computational Biology RNA-Binding Proteins Binding Sites Algorithms Protein Binding Humans Neural Networks, Computer
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GeoNet enables the accurate prediction of protein-ligand binding sites through interpretable geometric deep learning.

Structure (London, England : 1993) Nov 1, 2024
The identification of protein binding residues is essential for understanding their functions in vivo. However, it remains a computational challenge to accurately identify binding sites due to the lack of known residue binding patterns. Local residue...
Ligands Binding Sites Models, Molecular RNA Deep Learning Protein Binding Computational Biology Proteins DNA
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GraphPBSP: Protein binding site prediction based on Graph Attention Network and pre-trained model ProstT5.

International journal of biological macromolecules Oct 28, 2024
Protein-protein/peptide interactions play crucial roles in various biological processes. Exploring their interactions attracts wide attention. However, accurately predicting their binding sites remains a challenging task. Here, we develop an effectiv...
Computational Biology Proteins Binding Sites Neural Networks, Computer Algorithms Protein Binding
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