AIMC Topic: Protein Binding

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Machine Learning on the Impacts of Mutations in the SARS-CoV-2 Spike RBD on Binding Affinity to Human ACE2 Based on Deep Mutational Scanning Data.

Biochemistry Aug 14, 2025
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to accumulate mutations in the spike receptor-binding domain (RBD) region, leading to the emergence of new variants that potentially change the binding affinity for the human angi...
Machine Learning COVID-19 SARS-CoV-2 Humans Neural Networks, Computer Angiotensin-Converting Enzyme 2 Models, Molecular Mutation Protein Domains Protein Binding Spike Glycoprotein, Coronavirus
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PepPCBench is a Comprehensive Benchmarking Framework for Protein-Peptide Complex Structure Prediction.

Journal of chemical information and modeling Aug 12, 2025
Accurate modeling of protein-peptide interactions is essential for understanding fundamental biological processes and designing peptide-based drugs. However, predicting the complex structures of these interactions remains challenging, primarily due t...
Models, Molecular Benchmarking Protein Conformation Protein Binding Proteins Protein Folding Neural Networks, Computer Peptides
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Predicting Antibody-Antigen Interactions with Structure-Aware LLMs: Insights from SARS-CoV-2 Variants.

Journal of chemical information and modeling Aug 10, 2025
Predicting antibody-antigen interactions is a critical step in developing new therapeutics to defend against viral infections. However, measuring the extent of these interactions is costly and time-consuming. With the increased availability of exper...
Antigen-Antibody Reactions Antibodies, Viral Spike Glycoprotein, Coronavirus Antibodies, Neutralizing Humans Machine Learning COVID-19 SARS-CoV-2 Protein Binding
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Machine Learning-Enhanced Calculation of Quantum-Classical Binding Free Energies.

Journal of chemical theory and computation Aug 5, 2025
Binding free energies are key elements in understanding and predicting the strength of protein-drug interactions. While classical free energy simulations yield good results for many purely organic ligands, drugs, including transition metal atoms, oft...
Humans Thermodynamics Molecular Dynamics Simulation Machine Learning Quantum Theory Protein Binding Ligands
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The EMC acts as a chaperone for membrane proteins.

Nature communications Aug 2, 2025
Structure formation of membrane proteins is error-prone and thus requires chaperones that oversee this essential process in cell biology. The ER membrane protein complex (EMC) is well-defined as a transmembrane domain (TMD) insertase. In this study, ...
Saccharomyces cerevisiae Lipid Bilayers Saccharomyces cerevisiae Proteins Molecular Chaperones Endoplasmic Reticulum Protein Binding Membrane Proteins Protein Domains Humans Machine Learning
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Affinity prediction of inhibitor-kinase based on mixture of experts enhanced by multimodal feature semantic analysis.

International journal of biological macromolecules Jul 28, 2025
Accurate identification of inhibitor-kinase binding affinity is crucial for drug discovery. However, many deep learning models often overlook high-order feature information from biological networks and face challenges related to the cold-start proble...
Humans Drug Discovery Protein Kinases Deep Learning Semantics Protein Interaction Maps Protein Kinase Inhibitors Protein Binding
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Sequence-based virtual screening using transformers.

Nature communications Jul 28, 2025
Protein-ligand interactions play central roles in myriad biological processes and are of key importance in drug design. Deep learning approaches are becoming cost-effective alternatives to high-throughput experimental methods for ligand identificatio...
Deep Learning Protein Binding ErbB Receptors Drug Evaluation, Preclinical Protein Kinase Inhibitors Proto-Oncogene Proteins c-abl Amino Acid Sequence Humans Ligands Protein Conformation Drug Design
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Augmenting MACCS Keys with Persistent Homology Fingerprints for Protein-Ligand Binding Classification.

Journal of chemical information and modeling Jul 25, 2025
Machine learning has become an essential tool in computational drug design, enabling models to uncover patterns in molecular data and predict protein-ligand interactions. This study introduces a novel approach by integrating persistence images with M...
Ligands Cheminformatics Neural Networks, Computer Machine Learning Drug Design Protein Binding Proteins
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An in silico to in vivo approach identifies retinoid-X receptor activating tert-butylphenols used in food contact materials.

Scientific reports Jul 18, 2025
The potential for food contact chemicals to disrupt genetic programs in development and metabolism raises concerns. Nuclear receptors (NRs) control many of these programs, and the retinoid-X receptor (RXR) is a DNA-binding partner for one-third of th...
Signal Transduction Phenols Models, Molecular Xenopus laevis Humans Computer Simulation Retinoid X Receptors Machine Learning Receptors, Thyroid Hormone Animals Protein Binding
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AF3Score: A Score-Only Adaptation of AlphaFold3 for Biomolecular Structure Evaluation.

Journal of chemical information and modeling Jul 16, 2025
Scoring biomolecular complexes remains central to structural modeling efforts. Recent studies suggest that AlphaFold (AF) - a revolutionary deep learning model for biomolecular structure prediction - has implicitly learned an approximate biophysical ...
Models, Molecular Ligands Protein Conformation Protein Folding Deep Learning Protein Binding Proteins
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