AIMC Topic: Proteins

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Deep-ProBind: binding protein prediction with transformer-based deep learning model.

BMC bioinformatics Mar 22, 2025
Binding proteins play a crucial role in biological systems by selectively interacting with specific molecules, such as DNA, RNA, or peptides, to regulate various cellular processes. Their ability to recognize and bind target molecules with high speci...
Protein Binding Algorithms Computational Biology Deep Learning Binding Sites Neural Networks, Computer Sequence Analysis, Protein Proteins Databases, Protein
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Current experimental, statistical, and mechanistic approaches to optimizing biomolecule separations in aqueous two-phase systems.

Journal of chromatography. A Mar 17, 2025
Aqueous two-phase systems (ATPS) have been used to purify a range of biomolecules, including small molecules, monoclonal antibodies, viruses, and whole cells. They are known for selective separations, creating a stabilizing, low-shear environment, an...
Water Models, Chemical Thermodynamics Models, Statistical Proteins
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Automation of protein crystallization scaleup via Opentrons-2 liquid handling.

SLAS technology Mar 16, 2025
In this study we present an approach for optimizing protein crystallization trials at the multi-microliter scale utilizing the Opentrons-2 liquid handling robot. Our research demonstrates the robot's capability to automate 24-well sitting drop protei...
Muramidase Automation, Laboratory Crystallization Proteins Robotics Campylobacter jejuni
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DeepMVD: A Novel Multiview Dynamic Feature Fusion Model for Accurate Protein Function Prediction.

Journal of chemical information and modeling Mar 7, 2025
Proteins, as the fundamental macromolecules of life, play critical roles in various biological processes. Recent advancements in intelligent protein function prediction methods leverage sequences, structures, and biomedical literature data. Among the...
Proteins Databases, Protein Deep Learning Computational Biology
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PocketDTA: A pocket-based multimodal deep learning model for drug-target affinity prediction.

Computational biology and chemistry Mar 6, 2025
Drug-target affinity prediction is a fundamental task in the field of drug discovery. Extracting and integrating structural information from proteins effectively is crucial to enhance the accuracy and generalization of prediction, which remains a sub...
Humans Neural Networks, Computer Proteins Pharmaceutical Preparations Drug Discovery Deep Learning
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Multimodal Drug Target Binding Affinity Prediction Using Graph Local Substructure.

IEEE journal of biomedical and health informatics Mar 6, 2025
Predicting the binding affinity of drug target is essential to reduce drug development costs and cycles. Recently, several deep learning-based methods have been proposed to utilize the structural or sequential information of drugs and targets to pred...
Proteins Pharmaceutical Preparations Drug Discovery Deep Learning Protein Binding Computational Biology Humans Algorithms
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BINDTI: A Bi-Directional Intention Network for Drug-Target Interaction Identification Based on Attention Mechanisms.

IEEE journal of biomedical and health informatics Mar 6, 2025
The identification of drug-target interactions (DTIs) is an essential step in drug discovery. In vitro experimental methods are expensive, laborious, and time-consuming. Deep learning has witnessed promising progress in DTI prediction. However, how t...
Drug Discovery Deep Learning Computational Biology Proteins Humans Neural Networks, Computer
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Dual Representation Learning for Predicting Drug-Side Effect Frequency Using Protein Target Information.

IEEE journal of biomedical and health informatics Mar 6, 2025
Knowledge of unintended effects of drugs is critical in assessing the risk of treatment and in drug repurposing. Although numerous existing studies predict drug-side effect presence, only four of them predict the frequency of the side effects. Unfort...
Computational Biology Proteins Humans Deep Learning Drug-Related Side Effects and Adverse Reactions
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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...
Neural Networks, Computer Drug Discovery Humans Gene Ontology Proteins Pharmaceutical Preparations Deep Learning Computational Biology
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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...
Neural Networks, Computer Machine Learning Drug Discovery Protein Binding Proteins Ligands
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