AIMC Topic: Protein Binding

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MambaTransDTA: A Hybrid Mamba-Transformer Architecture for Accurate Drug-Target Binding Affinity Prediction.

Journal of chemical information and modeling Dec 17, 2025
In recent years, deep learning techniques have made significant advances in drug-target affinity (DTA) prediction. However, existing models still have considerable room for improvement in prediction accuracy, robustness, and generalization ability. T...
Pharmaceutical Preparations Deep Learning Protein Binding Drug Discovery
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SSIF-Affinity: Multimodal Deep Learning of Sequence-Structure Features for Precise Protein-Protein Binding Affinity Prediction.

Journal of chemical information and modeling Dec 15, 2025
Quantitative prediction of binding affinity in protein-protein interactions is critical for deciphering biological mechanisms and advancing therapeutic antibody development. While experimental methods for measuring binding affinity remain limited by ...
Deep Learning Models, Molecular Binding Sites Protein Binding Proteins
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Can AI-Predicted Complexes Teach Machine Learning to Compute Drug Binding Affinity?

Journal of chemical information and modeling Dec 10, 2025
We evaluate the feasibility of using co-folding models for synthetic data augmentation in training machine learning-based scoring functions (MLSFs) for binding affinity prediction. Our results show that performance gains depend critically on the stru...
Machine Learning Protein Binding Pharmaceutical Preparations
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Uncertainty quantification enables reliable deep learning for protein-ligand binding affinity prediction.

Scientific reports Dec 4, 2025
Deep learning (DL) algorithms have increasingly been applied to predict protein-ligand binding affinity, a critical step in drug design. Yet, many models still struggle to generalize to unseen data, and when coupled with the absence of confidence est...
Neural Networks, Computer Deep Learning Protein Binding Algorithms Drug Design Ligands Uncertainty Proteins Bayes Theorem
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Hybrid AI/physics pipeline for miniprotein binder prioritization: application to the BRD3 ET domain.

Chemical communications (Cambridge, England) Nov 27, 2025
AI-based protein design can rapidly generate thousands of candidate binders, but most fail to fold or bind productively, creating a critical need for robust prioritization. We present a generalizable hybrid pipeline that integrates deep-learning desi...
Deep Learning Protein Binding Protein Domains
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Mechanistic Disruption of the TREM2-DAP12 Transmembrane Complex by Alzheimer's Disease Mutations: A Multiscale Simulation Study.

Journal of chemical information and modeling Nov 26, 2025
Triggering receptor expressed on myeloid cell 2 (TREM2) is an immunomodulatory receptor that plays a critical role in microglial activation through its association with the adaptor protein DNAX-activation protein 12 (DAP12). Variants in TREM2 have be...
Lipid Bilayers Receptors, Immunologic Cell Membrane Adaptor Proteins, Signal Transducing Mutation Molecular Dynamics Simulation Alzheimer Disease Membrane Proteins Membrane Glycoproteins Humans Protein Binding
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Covalent: Interpretable and Discriminative Collective Variables Reveal Ligand-Dependent Switching in Human Cellular Retinol-Binding Protein 2.

Journal of chemical theory and computation Nov 25, 2025
Identifying collective variables (CVs) that are both discriminative and interpretable remains a central challenge for enhanced sampling and mechanistic analysis of biomolecular systems. We present (), a supervised machine learning-based CV discovery...
Molecular Dynamics Simulation Ligands Vitamin A Retinol-Binding Proteins, Cellular Machine Learning Protein Binding Humans
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Accurate prediction of protein-ATP binding sites based on a protein pretrained large language model and a fractional-order convolutional neural network.

Scientific reports Nov 25, 2025
ATP, a high-energy phosphate compound also known as adenosine triphosphate, serves as a direct energy source for living organisms. Proteins, composed of amino acids, are fundamental macromolecules and essential building blocks of life. The interactio...
Computational Biology Proteins Adenosine Triphosphate Binding Sites Convolutional Neural Networks Protein Binding Algorithms Deep Learning Large Language Models Neural Networks, Computer
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Benchmarking Sequence-Based Compound-Protein Interaction Prediction through Constructing a Debiased Data Set CDPN.

Journal of chemical information and modeling Nov 20, 2025
Accurate prediction of compound-protein interactions (CPIs) is critical for drug discovery, but existing data sets often suffer from biases that hinder model generalization. Here, we first highlighted that over-represented molecular scaffolds and imb...
Drug Discovery Benchmarking Deep Learning Protein Binding Proteins
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A multi-geometric graph fusion network for protein-ligand affinity prediction.

Physical chemistry chemical physics : PCCP Nov 19, 2025
Protein-ligand binding affinity prediction plays a crucial role in drug discovery. While recent works use two-dimensional graph neural networks to improve affinity prediction, we find that the three-dimensional geometric information of proteins and l...
Neural Networks, Computer Protein Conformation Protein Binding Binding Sites Proteins Ligands
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