AIMC Topic: Drug Discovery

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Artificial Intelligence in Drug Identification and Validation: A Scoping Review.

Drug research Jun 3, 2024
The end-to-end process in the discovery of drugs involves therapeutic candidate identification, validation of identified targets, identification of hit compound series, lead identification and optimization, characterization, and formulation and devel...
Drug Discovery Pharmaceutical Preparations Humans Artificial Intelligence
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Equivariant score-based generative diffusion framework for 3D molecules.

BMC bioinformatics May 30, 2024
BACKGROUND: Molecular biology is crucial for drug discovery, protein design, and human health. Due to the vastness of the drug-like chemical space, depending on biomedical experts to manually design molecules is exceedingly expensive. Utilizing gener...
Drug Discovery Deep Learning Computational Biology Models, Molecular Algorithms Drug Design
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PfgPDI: Pocket feature-enabled graph neural network for protein-drug interaction prediction.

Journal of bioinformatics and computational biology May 27, 2024
Biomolecular interaction recognition between ligands and proteins is an essential task, which largely enhances the safety and efficacy in drug discovery and development stage. Studying the interaction between proteins and ligands can improve the unde...
Pharmaceutical Preparations Drug Discovery Ligands Deep Learning Protein Binding Proteins Computational Biology Humans Databases, Protein Neural Networks, Computer
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Artificial intelligence for high content imaging in drug discovery.

Current opinion in structural biology May 25, 2024
Artificial intelligence (AI) and high-content imaging (HCI) are contributing to advancements in drug discovery, propelled by the recent progress in deep neural networks. This review highlights AI's role in analysis of HCI data from fixed and live-cel...
Drug Discovery Humans Artificial Intelligence
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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...
Drug Discovery Antimicrobial Peptides Machine Learning Models, Molecular Protein Conformation, alpha-Helical
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Novel drug discovery: Advancing Alzheimer's therapy through machine learning and network pharmacology.

European journal of pharmacology May 23, 2024
Alzheimer's disease (AD), marked by tau tangles and amyloid-beta plaques, leads to cognitive decline. Despite extensive research, its complex etiology remains elusive, necessitating new treatments. This study utilized machine learning (ML) to analyze...
Proto-Oncogene Proteins c-bcl-2 Network Pharmacology Drug Discovery Neuroprotective Agents TOR Serine-Threonine Kinases Alzheimer Disease Machine Learning Molecular Docking Simulation Humans
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Good machine learning practices: Learnings from the modern pharmaceutical discovery enterprise.

Computers in biology and medicine May 21, 2024
Machine Learning (ML) and Artificial Intelligence (AI) have become an integral part of the drug discovery and development value chain. Many teams in the pharmaceutical industry nevertheless report the challenges associated with the timely, cost effec...
Humans Artificial Intelligence Drug Industry Machine Learning Drug Discovery
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Catalyzing innovation in cancer drug discovery through artificial intelligence, machine learning and patency.

Pharmaceutical patent analyst May 21, 2024
Neoplasms Artificial Intelligence Drug Discovery Antineoplastic Agents Humans Machine Learning Patents as Topic
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Best practices for machine learning in antibody discovery and development.

Drug discovery today May 17, 2024
In the past 40 years, therapeutic antibody discovery and development have advanced considerably, with machine learning (ML) offering a promising way to speed up the process by reducing costs and the number of experiments required. Recent progress in ...
Humans Drug Development Antibodies Animals Drug Discovery Machine Learning Reproducibility of Results
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Geometric deep learning methods and applications in 3D structure-based drug design.

Drug discovery today May 16, 2024
3D structure-based drug design (SBDD) is considered a challenging and rational way for innovative drug discovery. Geometric deep learning is a promising approach that solves the accurate model training of 3D SBDD through building neural network model...
Deep Learning Molecular Structure Drug Design Humans Drug Discovery Neural Networks, Computer
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