AIMC Topic: Drug Design
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Advances of deep Neural Networks (DNNs) in the development of peptide drugs.
Future medicinal chemistry
Feb 12, 2025
Peptides are able to bind to difficult disease targets with high potency and specificity, providing great opportunities to meet unmet medical requirements. Nevertheless, the unique features of peptides, such as their small size, high structural flexi...
Deep Learning Combined with Quantitative Structure‒Activity Relationship Accelerates De Novo Design of Antifungal Peptides.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Feb 8, 2025
Novel antifungal drugs that evade resistance are urgently needed for Candida infections. Antifungal peptides (AFPs) are potential candidates due to their specific mechanism of action, which makes them less prone to developing drug resistance. An AFP ...
Deep learning: A game changer in drug design and development.
Advances in pharmacology (San Diego, Calif.)
Feb 6, 2025
The lengthy and costly drug discovery process is transformed by deep learning, a subfield of artificial intelligence. Deep learning technologies expedite the procedure, increasing treatment success rates and speeding life-saving procedures. Deep lear...
Rational design and synthesis of pyrazole derivatives as potential SARS-CoV-2 M inhibitors: An integrated approach merging combinatorial chemistry, molecular docking, and deep learning.
Bioorganic & medicinal chemistry
Feb 3, 2025
The global impact of SARS-CoV-2 has highlighted the urgent need for novel antiviral therapies. This study integrates combinatorial chemistry, molecular docking, and deep learning to design, evaluate and synthesize new pyrazole derivatives as potentia...
Artificial intelligence in peptide-based drug design.
Drug discovery today
Jan 20, 2025
Protein-protein interactions (PPIs) are fundamental to a variety of biological processes, but targeting them with small molecules is challenging because of their large and complex interaction interfaces. However, peptides have emerged as highly promi...
Targeting protein-ligand neosurfaces with a generalizable deep learning tool.
Nature
Jan 15, 2025
Molecular recognition events between proteins drive biological processes in living systems. However, higher levels of mechanistic regulation have emerged, in which protein-protein interactions are conditioned to small molecules. Despite recent advanc...
In silico design of dehydrophenylalanine containing peptide activators of glucokinase using pharmacophore modelling, molecular dynamics and machine learning: implications in type 2 diabetes.
Journal of computer-aided molecular design
Dec 31, 2024
Diabetes represents a significant global health challenge associated with substantial healthcare costs and therapeutic complexities. Current diabetes therapies often entail adverse effects, necessitating the exploration of novel agents. Glucokinase (...
PharmRL: pharmacophore elucidation with deep geometric reinforcement learning.
BMC biology
Dec 31, 2024
BACKGROUND: Molecular interactions between proteins and their ligands are important for drug design. A pharmacophore consists of favorable molecular interactions in a protein binding site and can be utilized for virtual screening. Pharmacophores are ...
AI-directed formulation strategy design initiates rational drug development.
Journal of controlled release : official journal of the Controlled Release Society
Dec 26, 2024
Rational drug development would be impossible without selecting the appropriate formulation route. However, pharmaceutical scientists often rely on limited personal experiences to perform trial-and-error tests on diverse formulation strategies. Such ...
Accelerating antimicrobial peptide design: Leveraging deep learning for rapid discovery.
PloS one
Dec 20, 2024
Antimicrobial peptides (AMPs) are excellent at fighting many different infections. This demonstrates how important it is to make new AMPs that are even better at eliminating infections. The fundamental transformation in a variety of scientific discip...
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