AIMC Topic: Models, Molecular

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Machine Learning-Enhanced Quantum Chemistry-Assisted Refinement of the Active Site Structure of Metalloproteins.

Inorganic chemistry May 28, 2024
Understanding the fine structural details of inhibitor binding at the active site of metalloenzymes can have a profound impact on the rational drug design targeted to this broad class of biomolecules. Structural techniques such as NMR, cryo-EM, and X...
Models, Molecular Metalloproteins Catalytic Domain Quantum Theory Matrix Metalloproteinase 12 Humans Machine Learning
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Structure-aware machine learning strategies for antimicrobial peptide discovery.

Scientific reports May 25, 2024
Machine learning models are revolutionizing our approaches to discovering and designing bioactive peptides. These models often need protein structure awareness, as they heavily rely on sequential data. The models excel at identifying sequences of a p...
Antimicrobial Peptides Protein Conformation, alpha-Helical Drug Discovery Models, Molecular Machine Learning
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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...
Protein Conformation Proteins Models, Molecular Protein Binding Humans Computational Biology Deep Learning
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Transferable deep generative modeling of intrinsically disordered protein conformations.

PLoS computational biology May 23, 2024
Intrinsically disordered proteins have dynamic structures through which they play key biological roles. The elucidation of their conformational ensembles is a challenging problem requiring an integrated use of computational and experimental methods. ...
Computational Biology Databases, Protein Intrinsically Disordered Proteins Protein Conformation Models, Molecular Algorithms Neural Networks, Computer Deep Learning Machine Learning
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Coordinate-Free and Low-Order Scaling Machine Learning Model for Atomic Partial Charge Prediction for Any Size of Molecules.

Journal of chemical information and modeling May 17, 2024
The atomic partial charge is of great importance in many fields, such as chemistry and drug-target recognition. However, conventional quantum-based computing of atomic charges is relatively slow, limiting further applications of atomic charge analysi...
Models, Molecular Static Electricity Neural Networks, Computer Machine Learning
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Structures, dynamics, complexes, and functions: From classic computation to artificial intelligence.

Current opinion in structural biology May 13, 2024
Computational approaches can provide highly detailed insight into the molecular recognition processes that underlie drug binding, the assembly of protein complexes, and the regulation of biological functional processes. Classical simulation methods c...
Models, Molecular Molecular Dynamics Simulation Humans Artificial Intelligence Computational Biology Proteins
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Predicting Antimicrobial Peptides Using ESMFold-Predicted Structures and ESM-2-Based Amino Acid Features with Graph Deep Learning.

Journal of chemical information and modeling May 13, 2024
Currently, antimicrobial resistance constitutes a serious threat to human health. Drugs based on antimicrobial peptides (AMPs) constitute one of the alternatives to address it. Shallow and deep learning (DL)-based models have mainly been built from a...
Deep Learning Models, Molecular Protein Conformation Antimicrobial Peptides Amino Acids Amino Acid Sequence
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A Survey of Deep Learning Methods for Estimating the Accuracy of Protein Quaternary Structure Models.

Biomolecules May 13, 2024
The quality prediction of quaternary structure models of a protein complex, in the absence of its true structure, is known as the Estimation of Model Accuracy (EMA). EMA is useful for ranking predicted protein complex structures and using them approp...
Deep Learning Proteins Models, Molecular Protein Structure, Quaternary Humans
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Accurate structure prediction of biomolecular interactions with AlphaFold 3.

Nature May 8, 2024
The introduction of AlphaFold 2 has spurred a revolution in modelling the structure of proteins and their interactions, enabling a huge range of applications in protein modelling and design. Here we describe our AlphaFold 3 model with a substantially...
Deep Learning Ligands Nucleic Acids Protein Binding Antibodies Reproducibility of Results Proteins Ions Molecular Docking Simulation Models, Molecular Humans Software Protein Conformation Antigens
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A Multi-view Molecular Pre-training with Generative Contrastive Learning.

Interdisciplinary sciences, computational life sciences May 6, 2024
Molecular representation learning can preserve meaningful molecular structures as embedding vectors, which is a necessary prerequisite for molecular property prediction. Yet, learning how to accurately represent molecules remains challenging. Previou...
Machine Learning Algorithms Models, Molecular
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