AIMC Topic: Models, Molecular

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Critical Assessment of RNA and DNA Structure Predictions via Artificial Intelligence: The Imitation Game.

Journal of chemical information and modeling Mar 30, 2025
Computational predictions of biomolecular structure via artificial intelligence (AI) based approaches, as exemplified by AlphaFold software, have the potential to model of all life's biomolecules. We performed oligonucleotide structure prediction and...
Nucleic Acid Conformation Artificial Intelligence Models, Molecular DNA RNA
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Fitting Atomic Structures into Cryo-EM Maps by Coupling Deep Learning-Enhanced Map Processing with Global-Local Optimization.

Journal of chemical information and modeling Mar 28, 2025
With the breakthroughs in protein structure prediction technology, constructing atomic structures from cryo-electron microscopy (cryo-EM) density maps through structural fitting has become increasingly critical. However, the accuracy of the construct...
Models, Molecular Protein Conformation Cryoelectron Microscopy Deep Learning Proteins
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Atomic context-conditioned protein sequence design using LigandMPNN.

Nature methods Mar 28, 2025
Protein sequence design in the context of small molecules, nucleotides and metals is critical to enzyme and small-molecule binder and sensor design, but current state-of-the-art deep-learning-based sequence design methods are unable to model nonprote...
Protein Binding Proteins Amino Acid Sequence Ligands Models, Molecular Deep Learning Crystallography, X-Ray Protein Conformation
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Machine learning methods to study sequence-ensemble-function relationships in disordered proteins.

Current opinion in structural biology Mar 12, 2025
Recent years have seen tremendous developments in the use of machine learning models to link amino-acid sequence, structure, and function of folded proteins. These methods are, however, rarely applicable to the wide range of proteins and sequences th...
Amino Acid Sequence Intrinsically Disordered Proteins Computational Biology Models, Molecular Protein Conformation Protein Folding Humans Machine Learning
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Development of DeepPQK and DeepQK sequence-based deep learning models to predict protein-ligand affinity and application in the directed evolution of ferulic esterase DLfae4.

International journal of biological macromolecules Mar 5, 2025
Affinity plays an essential role in the rate and stability of enzyme-catalyzed reactions, thus directly impacting the catalytic activity. In general, the predictive method for protein-ligand binding affinity mainly relies on high-resolution protein c...
Carboxylic Ester Hydrolases Binding Sites Directed Molecular Evolution Neural Networks, Computer Amino Acid Sequence Protein Binding Deep Learning Ligands Models, Molecular
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Skittles: GNN-Assisted Pseudo-Ligands Generation and Its Application for Binding Sites Classification and Affinity Prediction.

Proteins Feb 28, 2025
Nowadays, multiple solutions are known for identifying ligand-protein binding sites. Another important task is labeling each point of a binding site with the appropriate atom type, a process known as pseudo-ligand generation. The number of solutions ...
Neural Networks, Computer Machine Learning Algorithms Models, Molecular Ligands Binding Sites Proteins Databases, Protein Protein Binding Computational Biology
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Enhancing Functional Protein Design Using Heuristic Optimization and Deep Learning for Anti-Inflammatory and Gene Therapy Applications.

Proteins Feb 22, 2025
Protein sequence design is a highly challenging task, aimed at discovering new proteins that are more functional and producible under laboratory conditions than their natural counterparts. Deep learning-based approaches developed to address this prob...
Models, Molecular Anti-Inflammatory Agents Deep Learning Proteins Protein Conformation Genetic Therapy Protein Engineering Amino Acid Sequence Heuristics Humans Algorithms
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Teaching AI to speak protein.

Current opinion in structural biology Feb 21, 2025
Large Language Models for proteins, namely protein Language Models (pLMs), have begun to provide an important alternative to capturing the information encoded in a protein sequence in computers. Arguably, pLMs have advanced importantly to understandi...
Models, Molecular Protein Conformation Computational Biology Proteins Humans Artificial Intelligence
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Toward deep learning sequence-structure co-generation for protein design.

Current opinion in structural biology Feb 20, 2025
Deep generative models that learn from the distribution of natural protein sequences and structures may enable the design of new proteins with valuable functions. While the majority of today's models focus on generating either sequences or structures...
Protein Conformation Proteins Deep Learning Protein Engineering Models, Molecular
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From part to whole: AI-driven progress in fragment-based drug discovery.

Current opinion in structural biology Feb 18, 2025
Fragment-based drug discovery is a technique that finds potent binding fragments to the binding hotspots and makes them a hit compound. The combination of fragments allows us to explore the large chemical space. Thus, it becomes an effective methodol...
Humans Artificial Intelligence Models, Molecular Drug Discovery Deep Learning
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