AIMC Topic: Proteins

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Prediction of Drug-Target Interactions With High- Quality Negative Samples and a Network-Based Deep Learning Framework.

IEEE journal of biomedical and health informatics Mar 6, 2025
Identification of drug-target interactions (DTIs) plays a crucial role in drug discovery. Compared to traditional experimental methods, computer-based methods for predicting DTIs can significantly reduce the time and financial burdens of drug develop...
Deep Learning Computational Biology Pharmaceutical Preparations Gene Ontology Proteins Neural Networks, Computer Drug Discovery Humans
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iScore: A ML-Based Scoring Function for De Novo Drug Discovery.

Journal of chemical information and modeling Mar 4, 2025
In the quest for accelerating de novo drug discovery, the development of efficient and accurate scoring functions represents a fundamental challenge. This study introduces iScore, a novel machine learning (ML)-based scoring function designed to predi...
Ligands Neural Networks, Computer Machine Learning Protein Binding Proteins Drug Discovery
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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 Databases, Protein Models, Molecular Protein Binding Machine Learning Binding Sites Computational Biology Ligands Algorithms Proteins
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Machine Learning Assisted Nanofluidic Array for Multiprotein Detection.

ACS nano Feb 26, 2025
Solid-state nanopore and nanochannel biosensors have revolutionized protein detection by offering label-free, highly sensitive analyses. Traditional sensing systems (1st and 2nd stages) primarily focus on inner wall (IW) interactions, facing challeng...
Nanotechnology Proteins Machine Learning Disulfides Molybdenum Biosensing Techniques Lab-On-A-Chip Devices
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Recent advances in AI-driven protein-ligand interaction predictions.

Current opinion in structural biology Feb 24, 2025
Structure-based drug discovery is a fundamental approach in modern drug development, leveraging computational models to predict protein-ligand interactions. AI-driven methodologies are significantly improving key aspects of the field, including ligan...
Molecular Docking Simulation Drug Discovery Deep Learning Humans Artificial Intelligence Ligands Binding Sites Protein Binding Proteins
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Natural Language Processing Methods for the Study of Protein-Ligand Interactions.

Journal of chemical information and modeling Feb 24, 2025
Natural Language Processing (NLP) has revolutionized the way computers are used to study and interact with human languages and is increasingly influential in the study of protein and ligand binding, which is critical for drug discovery and developmen...
Proteins Natural Language Processing Ligands Drug Discovery Protein Binding Humans Machine Learning
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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...
Proteins Models, Molecular Anti-Inflammatory Agents Algorithms Deep Learning Protein Conformation Genetic Therapy Protein Engineering Amino Acid Sequence Heuristics Humans
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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...
Protein Conformation Computational Biology Humans Proteins Artificial Intelligence Models, Molecular
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Compact Assessment of Molecular Surface Complementarities Enhances Neural Network-Aided Prediction of Key Binding Residues.

Journal of chemical information and modeling Feb 21, 2025
Predicting interactions between proteins is fundamental for understanding the mechanisms underlying cellular processes, since protein-protein complexes are crucial in physiological conditions but also in many diseases, for example by seeding aggregat...
Neural Networks, Computer Hydrophobic and Hydrophilic Interactions Protein Binding Surface Properties Proteins Binding Sites Molecular Docking Simulation ROC Curve
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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 Protein Engineering Proteins Models, Molecular Deep Learning
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