AIMC Topic: Models, Molecular

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Comparative evaluation of the prediction accuracy of AlphaFold and ESMFold for monomeric and dimeric proteins.

NAR genomics and bioinformatics Jan 16, 2026
We have evaluated the prediction accuracy of three different tools, deep-learning-based AlphaFold2, AlphaFold3, and large language model-based ESMFold, utilizing the experimentally derived structures deposited in the Protein Data Bank between 2022 an...
Computational Biology Proteins Software Deep Learning Protein Conformation Databases, Protein Models, Molecular Protein Folding Protein Multimerization
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LMProtein: a protein language model based framework for protein structural property prediction.

Physical chemistry chemical physics : PCCP Jan 14, 2026
Recent advances in machine learning and self-supervised deep language modeling have made it possible to accurately predict protein structural properties. Most existing models and pretraining methods leverage evolutionary information in multiple seque...
Amino Acid Sequence Protein Conformation Protein Structure, Secondary Proteins Models, Molecular Neural Networks, Computer Machine Learning
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Computational design of protein complexes: influence of binding affinity.

Chemical communications (Cambridge, England) Jan 13, 2026
The interaction of proteins with diverse molecular partners, including other proteins, nucleic acids, and carbohydrates, is essential for performing various functions, from signal transduction and gene regulation to immune recognition and cellular tr...
DNA RNA Machine Learning Models, Molecular Protein Binding Deep Learning Proteins
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A Multimodal Drug-Target Affinity Prediction Framework with Pretrained Models and Hierarchical Graph Transformer.

Journal of chemical information and modeling Dec 31, 2025
Drug-target affinity (DTA) prediction is crucial in drug discovery. It enables researchers to elucidate the complex interaction mechanisms between candidate drugs and biological targets. However, current methods have limitations in capturing global s...
Neural Networks, Computer Drug Discovery Binding Sites Proteins Models, Molecular
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AI-driven molecular modeling and design: from property prediction to drug generation.

Journal of computer-aided molecular design Dec 29, 2025
Integrating the techniques of deep learning, particularly graph neural network models, has made a significant advancement in drug discovery by facilitating effective exploration of chemical spaces and precise prediction of molecular properties. This ...
Deep Learning Models, Molecular Drug Design Drug Discovery Quantum Theory Molecular Structure Pharmaceutical Preparations Neural Networks, Computer
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Enhancing the Predictive Power of Macrocyclic Drug Permeability by Knowledge Distillation from Analogous Pretraining Data.

Journal of medicinal chemistry Dec 20, 2025
Macrocyclic drugs offer powerful opportunities for modulating protein-protein interactions, yet their development is limited by poor and unpredictable membrane permeability. Experimental testing is slow, and 3D modeling of macrocycles is computationa...
Deep Learning Macrocyclic Compounds Permeability Models, Molecular Humans Cell Membrane Permeability
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Exploring voltage-gated sodium channel conformations and protein-protein interactions using AlphaFold2.

The Journal of general physiology Dec 18, 2025
Voltage-gated sodium (NaV) channels are vital regulators of electrical activity in excitable cells. Given their importance in physiology, NaV channels are key therapeutic targets for treating numerous conditions, yet developing subtype-selective drug...
Humans Models, Molecular Protein Conformation Calmodulin Ion Channel Gating Voltage-Gated Sodium Channels
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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 ...
Protein Binding Models, Molecular Deep Learning Proteins Binding Sites
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Deep Learning Exploration Expands the Natural Diversity of Metallothioneins in the Archaea Domain.

Journal of agricultural and food chemistry Dec 10, 2025
The diversity and functions of metallothioneins (MTs) in Archaea remain poorly understood. This study identifies 180 archaeal MTs from 406 genomes, revealing distinct evolutionary lineages and structural diversity. Phylogenetic analysis suggests a no...
Metallothionein Archaea Archaeal Proteins Amino Acid Sequence Cadmium Deep Learning Phylogeny Models, Molecular Copper
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Sensitive detection of structural dynamics using a statistical framework for comparative crystallography.

Science advances Dec 3, 2025
Chemical and conformational changes are crucial to protein function and its pharmacological control. X-ray crystallography can reveal these changes in atomic detail, but standard analysis methods, which refine separate datasets, often overlook differ...
Models, Molecular Algorithms Crystallography, X-Ray Deep Learning Protein Conformation Proteins
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