AIMC Topic: Drug Discovery

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A diagnostic model for sepsis using an integrated machine learning framework approach and its therapeutic drug discovery.

BMC infectious diseases Feb 14, 2025
BACKGROUND: Sepsis remains a life-threatening condition in intensive care units (ICU) with high morbidity and mortality rates. Some biomarkers commonly used in clinic do not have the characteristics of rapid and specific growth and rapid decline afte...
Nomograms Drug Discovery Algorithms Gene Expression Profiling Humans Biomarkers Sepsis Machine Learning Gene Regulatory Networks
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metaCDA: A Novel Framework for CircRNA-Driven Drug Discovery Utilizing Adaptive Aggregation and Meta-Knowledge Learning.

Journal of chemical information and modeling Feb 12, 2025
In the emerging field of RNA drugs, circular RNA (circRNA) has attracted much attention as a novel multifunctional therapeutic target. Delving deeper into the intricate interactions between circRNA and disease is critical for driving drug discovery e...
RNA, Circular Humans Machine Learning Drug Discovery
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A novel neural network-based nearest neighbor approach for drug function prediction from chemical structures.

European journal of pharmacology Feb 11, 2025
Drug function prediction is a crucial task in drug discovery, design, and development, which involves the prediction of the biological functions of a drug molecule based on its chemical structure. Misleading drug function is a common reason for adver...
Neural Networks, Computer Drug Discovery Humans Molecular Structure Pharmaceutical Preparations
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AGDIFF: Attention-Enhanced Diffusion for Molecular Geometry Prediction.

Journal of chemical information and modeling Feb 11, 2025
Accurate prediction of molecular geometries is crucial for drug discovery and materials science. Existing fast conformer prediction algorithms often rely on approximate empirical energy functions, resulting in low accuracy. More accurate methods like...
Molecular Dynamics Simulation Algorithms Diffusion Drug Discovery Machine Learning Molecular Conformation
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Single-Cell Array Enhanced Cell Damage Recognition Using Artificial Intelligence for Anticancer Drug Discovery.

Analytical chemistry Feb 10, 2025
This work developed a cell damage recognition method based on single-cell arrays using an artificial intelligence tool. The method uses micropatterns (single-cell micropatches and microwells) to isolate each cell in an ordered array to minimize cell ...
Reactive Oxygen Species Antineoplastic Agents Humans Doxorubicin Artificial Intelligence Single-Cell Analysis Neural Networks, Computer Drug Discovery
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Modeling Boltzmann-weighted structural ensembles of proteins using artificial intelligence-based methods.

Current opinion in structural biology Feb 8, 2025
This review highlights recent advances in AI-driven methods for generating Boltzmann-weighted structural ensembles, which are crucial for understanding biomolecular dynamics and drug discovery. With the rise of deep learning models such as AlphaFold2...
Molecular Dynamics Simulation Protein Conformation Proteins Models, Molecular Drug Discovery Deep Learning Artificial Intelligence
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Machine Learning-Based Bioactivity Classification of Natural Products Using LC-MS/MS Metabolomics.

Journal of natural products Feb 7, 2025
The rediscovery of known drug classes represents a major challenge in natural products drug discovery. Compound rediscovery inhibits the ability of researchers to explore novel natural products and wastes significant amounts of time and resources. Th...
Molecular Structure Tandem Mass Spectrometry Chromatography, Liquid Liquid Chromatography-Mass Spectrometry Machine Learning Software Metabolomics Biological Products Drug Discovery
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Machine Learning-Driven Discovery of Structurally Related Natural Products as Activators of the Cardiac Calcium Pump SERCA2a.

ChemMedChem Feb 6, 2025
A key molecular dysfunction in heart failure is the reduced activity of the cardiac sarcoplasmic reticulum Ca-ATPase (SERCA2a) in cardiac muscle cells. Reactivating SERCA2a improves cardiac function in heart failure models, making it a validated targ...
Machine Learning Mice Dose-Response Relationship, Drug Molecular Structure Animals Calcium Drug Discovery Sarcoplasmic Reticulum Calcium-Transporting ATPases Biological Products Structure-Activity Relationship
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Artificial Intelligence in Natural Product Drug Discovery: Current Applications and Future Perspectives.

Journal of medicinal chemistry Feb 6, 2025
Drug discovery, a multifaceted process from compound identification to regulatory approval, historically plagued by inefficiencies and time lags due to limited data utilization, now faces urgent demands for accelerated lead compound identification. I...
Machine Learning Drug Discovery Deep Learning Humans Artificial Intelligence Biological Products
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CaBind_MCNN: Identifying Potential Calcium Channel Blocker Targets by Predicting Calcium-Binding Sites in Ion Channels and Ion Transporters Using Protein Language Models and Multiscale Feature Extraction.

Journal of chemical information and modeling Feb 6, 2025
Calcium ions (Ca) are crucial for various physiological processes, including neurotransmission and cardiac function. Dysregulation of Ca homeostasis can lead to serious health conditions such as cardiac arrhythmias and hypertension. Ion channels and ...
Calcium Neural Networks, Computer Calcium Channel Blockers Humans Drug Discovery Binding Sites Ion Channels
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