AIMC Topic: Models, Molecular

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The continuous evolution of biomolecular force fields.

Structure (London, England : 1993) Jun 16, 2025
Biomolecular force fields have continuously evolved to improve their accuracy and broaden their applications in biological and therapeutic discoveries. The rapid adaptation of advanced computational technology, in particular the recent deep learning ...
Proteins Models, Molecular Molecular Dynamics Simulation Machine Learning Deep Learning
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AbEpiTope-1.0: Improved antibody target prediction by use of AlphaFold and inverse folding.

Science advances Jun 13, 2025
B cell epitope prediction tools are crucial for designing vaccines and disease diagnostics. However, predicting which antigens a specific antibody binds to and their exact binding sites (epitopes) remains challenging. Here, we present AbEpiTope-1.0, ...
Antibodies Antigens Protein Folding Epitopes, B-Lymphocyte Antigen-Antibody Complex Software Computational Biology Models, Molecular Humans Machine Learning
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The Highly Conserved Cys95 Residue of Fructose-1,6-Bisphosphatase 1 Mediates the pH-Driven Structure and Activity of the Enzyme and Photosynthesis.

Plant, cell & environment Jun 8, 2025
In Arabidopsis, exposure to microbial volatile compounds promotes thiol reduction of the Cys95 residue of the photosynthetic enzyme fructose-1,6-bisphosphatase (cFBP1). Although highly conserved in plants, the Cys95 function still remains unknown. We...
Fructose-Bisphosphatase Plants, Genetically Modified Conserved Sequence Amino Acid Sequence Models, Molecular Arabidopsis Arabidopsis Proteins Cysteine Hydrogen-Ion Concentration Photosynthesis
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MlCOFSyn: A Machine Learning Framework To Facilitate the Synthesis of 2D Covalent Organic Frameworks.

Journal of chemical information and modeling Jun 5, 2025
Two-dimensional covalent organic frameworks (2D COFs) have been historically synthesized empirically, often resulting in uncontrolled crystallization and inferior crystal sizes, which limit their performance in various applications. Recently, crystal...
Crystallization Chemistry Techniques, Synthetic Models, Molecular Metal-Organic Frameworks Machine Learning
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Amortized template matching of molecular conformations from cryoelectron microscopy images using simulation-based inference.

Proceedings of the National Academy of Sciences of the United States of America Jun 4, 2025
Characterizing the conformational ensemble of biomolecular systems is key to understand their functions. Cryoelectron microscopy (cryo-EM) captures two-dimensional snapshots of biomolecular ensembles, giving in principle access to thermodynamics. How...
Models, Molecular Bayes Theorem Cryoelectron Microscopy Molecular Conformation Deep Learning Image Processing, Computer-Assisted Neural Networks, Computer Computer Simulation
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Comparing models and experimental structures of the GPR101 receptor: Artificial intelligence yields highly accurate models.

Journal of molecular graphics & modelling Jun 3, 2025
Experimental structures solved through cryo-electron microscopy have recently been published for GPR101, a G protein-coupled receptor (GPCR) implicated in the genetic condition X-linked acrogigantism (X-LAG). Here, we compared these experimental stru...
Artificial Intelligence Protein Binding Receptors, G-Protein-Coupled Humans Amino Acid Sequence Protein Conformation Cryoelectron Microscopy Models, Molecular Molecular Dynamics Simulation
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Modeling Active-State Conformations of G-Protein-Coupled Receptors Using AlphaFold2 via Template Bias and Explicit Protein Constrains.

Journal of chemical information and modeling May 29, 2025
AlphaFold2 and other deep learning tools represent the state of the art for protein structure prediction; however, they are still limited in their ability to model multiple protein conformations. Since the function of many proteins depends on their a...
Deep Learning Humans Receptors, G-Protein-Coupled Ligands Models, Molecular Protein Conformation
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Automating the Analysis of Substrate Reactivity through Environment Interaction Mapping.

Journal of chemical information and modeling May 28, 2025
Exploring the interaction configurations between substrates and atomic or molecular systems is crucial for various scientific and technological applications, such as characterizing catalytic reactions, solvation structures, and molecular interactions...
Automation Cluster Analysis Models, Molecular Machine Learning
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EMOCPD: Efficient Attention-Based Models for Computational Protein Design Using Amino Acid Microenvironment.

Journal of chemical information and modeling May 26, 2025
Computational protein design (CPD) refers to the use of computational methods to design proteins. Traditional methods relying on energy functions and heuristic algorithms for sequence design are inefficient and do not meet the demands of the big data...
Computational Biology Proteins Protein Conformation Models, Molecular Amino Acids Protein Engineering
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Cyclic peptide structure prediction and design using AlphaFold2.

Nature communications May 21, 2025
Small cyclic peptides have gained significant traction as a therapeutic modality; however, the development of deep learning methods for accurately designing such peptides has been slow, mostly due to the lack of sufficiently large training sets. Here...
Proto-Oncogene Proteins c-mdm2 Models, Molecular Deep Learning Crystallography, X-Ray Amino Acid Sequence Humans Protein Conformation Kelch-Like ECH-Associated Protein 1 Computational Biology Peptides, Cyclic Drug Design
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