AIMC Topic: Drug Design

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AlphaFold2 structures guide prospective ligand discovery.

Science (New York, N.Y.) Jun 21, 2024
AlphaFold2 (AF2) models have had wide impact but mixed success in retrospective ligand recognition. We prospectively docked large libraries against unrefined AF2 models of the σ and serotonin 2A (5-HT2A) receptors, testing hundreds of new molecules a...
Ligands Receptor, Serotonin, 5-HT2A Protein Conformation Drug Discovery Deep Learning Humans Molecular Docking Simulation Cryoelectron Microscopy Drug Design Serotonin 5-HT2 Receptor Agonists Small Molecule Libraries Serotonin 5-HT2 Receptor Antagonists Protein Folding Receptors, sigma
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Harnessing machine learning potential for personalised drug design and overcoming drug resistance.

Journal of drug targeting Jun 13, 2024
Drug resistance in cancer treatment presents a significant challenge, necessitating innovative approaches to improve therapeutic efficacy. Integrating machine learning (ML) in cancer research is promising as ML algorithms outrival in analysing comple...
Humans Machine Learning Algorithms Drug Discovery Antineoplastic Agents Bayes Theorem Precision Medicine Neoplasms Drug Design Drug Resistance, Neoplasm
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Synthetically Feasible De Novo Molecular Design of Leads Based on a Reinforcement Learning Model: AI-Assisted Discovery of an Anti-IBD Lead Targeting CXCR4.

Journal of medicinal chemistry Jun 12, 2024
Artificial intelligence (AI) de novo molecular generation provides leads with novel structures for drug discovery. However, the target affinity and synthesizability of the generated molecules present critical challenges for the successful application...
Receptors, CXCR4 Molecular Structure Mice Structure-Activity Relationship Inflammatory Bowel Diseases Humans Animals Artificial Intelligence Male Molecular Docking Simulation Drug Design Drug Discovery
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The Millennia-Long Development of Drugs Associated with the 80-Year-Old Artificial Intelligence Story: The Therapeutic Big Bang?

Molecules (Basel, Switzerland) Jun 7, 2024
The journey of drug discovery (DD) has evolved from ancient practices to modern technology-driven approaches, with Artificial Intelligence (AI) emerging as a pivotal force in streamlining and accelerating the process. Despite the vital importance of ...
Humans Artificial Intelligence Drug Development Drug Design Drug Discovery
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Mining for Potent Inhibitors through Artificial Intelligence and Physics: A Unified Methodology for Ligand Based and Structure Based Drug Design.

Journal of chemical information and modeling Jun 6, 2024
Determining the viability of a new drug molecule is a time- and resource-intensive task that makes computer-aided assessments a vital approach to rapid drug discovery. Here we develop a machine learning algorithm, iMiner, that generates novel inhibit...
Data Mining Ligands Machine Learning Algorithms Molecular Docking Simulation Drug Design Proteins Molecular Dynamics Simulation Artificial Intelligence
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A novel framework based on explainable AI and genetic algorithms for designing neurological medicines.

Scientific reports Jun 4, 2024
The advent of the fourth industrial revolution, characterized by artificial intelligence (AI) as its central component, has resulted in the mechanization of numerous previously labor-intensive activities. The use of in silico tools has become prevale...
Drug Design Deep Learning Neuropeptides Humans Artificial Intelligence Algorithms Computer Simulation
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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...
Models, Molecular Drug Discovery Algorithms Deep Learning Drug Design Computational Biology
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Mechanism-based organization of neural networks to emulate systems biology and pharmacology models.

Scientific reports May 27, 2024
Deep learning neural networks are often described as black boxes, as it is difficult to trace model outputs back to model inputs due to a lack of clarity over the internal mechanisms. This is even true for those neural networks designed to emulate me...
Systems Biology Neural Networks, Computer Pharmacology Artificial Intelligence Pharmacokinetics Deep Learning Machine Learning Computational Biology Algorithms Drug Design
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Machine learning designs new GCGR/GLP-1R dual agonists with enhanced biological potency.

Nature chemistry May 16, 2024
Several peptide dual agonists of the human glucagon receptor (GCGR) and the glucagon-like peptide-1 receptor (GLP-1R) are in development for the treatment of type 2 diabetes, obesity and their associated complications. Candidates must have high poten...
Amino Acid Sequence Glucagon-Like Peptide-1 Receptor Receptors, Glucagon Glucagon-Like Peptide-1 Receptor Agonists Peptides Drug Design Hypoglycemic Agents Humans Machine Learning
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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...
Drug Discovery Humans Deep Learning Neural Networks, Computer Molecular Structure Drug Design
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