AIMC Topic: Protein Binding

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Protein embeddings predict binding residues in disordered regions.

Scientific reports Jun 12, 2024
The identification of protein binding residues helps to understand their biological processes as protein function is often defined through ligand binding, such as to other proteins, small molecules, ions, or nucleotides. Methods predicting binding re...
Humans Computational Biology Databases, Protein Intrinsically Disordered Proteins Machine Learning Protein Binding Binding Sites
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CENsible: Interpretable Insights into Small-Molecule Binding with Context Explanation Networks.

Journal of chemical information and modeling Jun 7, 2024
We present a novel and interpretable approach for assessing small-molecule binding using context explanation networks. Given the specific structure of a protein/ligand complex, our CENsible scoring function uses a deep convolutional neural network to...
Proteins Ligands Small Molecule Libraries Machine Learning Neural Networks, Computer Protein Binding
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Unveiling Conformational States of CDK6 Caused by Binding of Vcyclin Protein and Inhibitor by Combining Gaussian Accelerated Molecular Dynamics and Deep Learning.

Molecules (Basel, Switzerland) Jun 5, 2024
CDK6 plays a key role in the regulation of the cell cycle and is considered a crucial target for cancer therapy. In this work, conformational transitions of CDK6 were identified by using Gaussian accelerated molecular dynamics (GaMD), deep learning (...
Normal Distribution Cyclin-Dependent Kinase 6 Binding Sites Thermodynamics Protein Binding Principal Component Analysis Protein Conformation Protein Kinase Inhibitors Molecular Dynamics Simulation Humans Deep Learning
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HeteroTCR: A heterogeneous graph neural network-based method for predicting peptide-TCR interaction.

Communications biology Jun 4, 2024
Identifying interactions between T-cell receptors (TCRs) and immunogenic peptides holds profound implications across diverse research domains and clinical scenarios. Unsupervised clustering models (UCMs) cannot predict peptide-TCR binding directly, w...
Protein Binding Humans Peptides Computational Biology Neural Networks, Computer Receptors, Antigen, T-Cell
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SOFB is a comprehensive ensemble deep learning approach for elucidating and characterizing protein-nucleic-acid-binding residues.

Communications biology Jun 3, 2024
Proteins and nucleic-acids are essential components of living organisms that interact in critical cellular processes. Accurate prediction of nucleic acid-binding residues in proteins can contribute to a better understanding of protein function. Howev...
Deep Learning Proteins Nucleic Acids Binding Sites Protein Binding Computational Biology
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Geometry Optimization Algorithms in Conjunction with the Machine Learning Potential ANI-2x Facilitate the Structure-Based Virtual Screening and Binding Mode Prediction.

Biomolecules May 31, 2024
Structure-based virtual screening utilizes molecular docking to explore and analyze ligand-macromolecule interactions, crucial for identifying and developing potential drug candidates. Although there is availability of several widely used docking pro...
Binding Sites Protein Binding Ligands Algorithms Machine Learning Molecular Docking Simulation
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Protein-Protein Interfaces: A Graph Neural Network Approach.

International journal of molecular sciences May 28, 2024
Protein-protein interactions (PPIs) are fundamental processes governing cellular functions, crucial for understanding biological systems at the molecular level. Compared to experimental methods for PPI prediction and site identification, computationa...
Neural Networks, Computer Deep Learning Protein Interaction Maps Algorithms Proteins Protein Binding Databases, Protein Computational Biology Protein Interaction Mapping
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PfgPDI: Pocket feature-enabled graph neural network for protein-drug interaction prediction.

Journal of bioinformatics and computational biology May 27, 2024
Biomolecular interaction recognition between ligands and proteins is an essential task, which largely enhances the safety and efficacy in drug discovery and development stage. Studying the interaction between proteins and ligands can improve the unde...
Ligands Humans Drug Discovery Databases, Protein Neural Networks, Computer Protein Binding Proteins Pharmaceutical Preparations Deep Learning Computational Biology
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Integrative modeling meets deep learning: Recent advances in modeling protein assemblies.

Current opinion in structural biology May 24, 2024
Recent progress in protein structure prediction based on deep learning revolutionized the field of Structural Biology. Beyond single proteins, it also enabled high-throughput prediction of structures of protein-protein interactions. Despite the succe...
Humans Deep Learning Models, Molecular Computational Biology Proteins Protein Conformation Protein Binding
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Prediction of Protein-DNA Interface Hot Spots Based on Empirical Mode Decomposition and Machine Learning.

Genes May 23, 2024
Protein-DNA complex interactivity plays a crucial role in biological activities such as gene expression, modification, replication and transcription. Understanding the physiological significance of protein-DNA binding interfacial hot spots, as well a...
Algorithms Protein Binding Machine Learning Computational Biology DNA-Binding Proteins Binding Sites DNA
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