AIMC Topic: Drug Design

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Identification of hub necroptosis-related targets and discovery of potential natural inhibitors in ulcerative colitis based on bioinformatics and computer-aided drug design.

Journal of computer-aided molecular design Oct 24, 2025
Ulcerative colitis (UC) is a chronic inflammatory bowel disease with a complex pathogenesis and limited treatment options. Recently, necroptosis has been found to play a significant role in UC. This study aimed to investigate necroptosis-related mech...
Machine Learning Molecular Docking Simulation Computer-Aided Design Humans Colitis, Ulcerative Necroptosis Molecular Dynamics Simulation Protein Kinases Single-Cell Analysis Computational Biology Biological Products Drug Design Drug Discovery
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4-Hydroxy-2,5-dihydrothiazole derivatives as a new class of small-molecule antibiotics for MRSA: AI-integrated design, chemical synthesis and biological evaluation.

European journal of medicinal chemistry Oct 16, 2025
Staphylococcus aureus (S. aureus) is one of the most concerned Gram-positive bacteria due to its resistance to the commonly used antibiotics, methicillin. To address the threat of methicillin-resistant S. aureus (MRSA), new classes of antibiotics are...
Microbial Sensitivity Tests Mice Methicillin-Resistant Staphylococcus aureus Anti-Bacterial Agents Animals Drug Design Thiazoles HEK293 Cells Small Molecule Libraries Dose-Response Relationship, Drug Structure-Activity Relationship Molecular Structure Humans Artificial Intelligence
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MolAgent: Biomolecular Property Estimation in the Agentic Era.

Journal of chemical information and modeling Oct 16, 2025
The advent of agentic AI systems is leading to significant transformations across scientific and technological domains. Advances in large language models (LLMs), reasoning capabilities, and integration with external tools have ushered in a new era wh...
Humans Computer-Aided Design Drug Design Drug Discovery
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DLFea4AMPGen de novo design of antimicrobial peptides by integrating features learned from deep learning models.

Nature communications Oct 15, 2025
Deep learning models show promise in accelerating the design and optimization of antimicrobial peptides (AMPs), but current methods face challenges, such as low success rates, or large virtual library scales. In this study, we introduce DLFea4AMPGen,...
Antimicrobial Peptides Microbial Sensitivity Tests Amino Acid Sequence Humans Anti-Bacterial Agents Animals Drug Design Deep Learning
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TEMPL: A Template-Based Protein-Ligand Pose Prediction Baseline.

Journal of chemical information and modeling Oct 14, 2025
Pose prediction of ligands to proteins remains a central challenge of structure-based drug design. Although data leakage and generalizability concerns remain, data-driven methods for pose prediction (i.e., based on deep learning and diffusion) now ro...
Protein Conformation Protein Binding Proteins Ligands Deep Learning Antiviral Agents Humans Algorithms SARS-CoV-2 Molecular Docking Simulation Drug Design
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A meta-learning framework to mitigate negative transfer in transfer learning applicable to drug design.

Scientific reports Oct 9, 2025
Data sparseness is a major limiting factor for deep machine learning. In the natural sciences, data distributions are heterogeneous. For instance, in chemistry and early-phase drug discovery, compound and molecular property data are typically sparse ...
Humans Machine Learning Cheminformatics Drug Discovery Algorithms Drug Design Deep Learning Protein Kinase Inhibitors
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Manifold-constrained nucleus-level denoising diffusion model for structure-based drug design.

Proceedings of the National Academy of Sciences of the United States of America Oct 6, 2025
AI models have shown great potential in structure-based drug design, generating ligands with high binding affinities. However, existing models have often overlooked a crucial physical prior: Atoms must maintain a minimum pairwise distance to avoid at...
Drug Design Antiviral Agents Ligands COVID-19 Drug Treatment Humans COVID-19 SARS-CoV-2
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Manifold Embedding of Quantum Information as Molecule Representation to Predict Blood-Brain Barrier Permeability by Deep Learning.

Molecular pharmaceutics Sep 30, 2025
Neurological disorders continue to be a leading global health challenge, with the blood-brain barrier (BBB) presenting considerable obstacles to effective drug delivery for central nervous system (CNS) therapies. Accurately predicting BBB permeabilit...
Deep Learning Permeability Blood-Brain Barrier Drug Delivery Systems Humans Drug Design
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Unravelling mutation patterns in Extended-Spectrum β-Lactamases for precision drug design against AMR in Enterobacteriaceae.

Molecular genetics and genomics : MGG Sep 29, 2025
Antimicrobial resistance (AMR) presents a critical global challenge, causing over 1.27 million deaths annually, with projections reaching 10 million by 2050. Among the most concerning contributors are Enterobacteriaceae, particularly Escherichia coli...
Escherichia coli Bacterial Proteins Mutation Polymorphism, Single Nucleotide Klebsiella pneumoniae beta-Lactamases Enterobacteriaceae Humans Anti-Bacterial Agents Drug Design
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CNSGT: Generative Transformer for De Novo Drug Design Targeting the Central Nervous System.

Journal of chemical information and modeling Sep 26, 2025
The design of novel central nervous system (CNS) drugs presents formidable challenges due to the restrictive nature of the blood-brain barrier, which imposes stringent physicochemical requirements. Recent advances in deep learning, particularly Trans...
Drug Design Central Nervous System Agents Humans Deep Learning Central Nervous System Molecular Docking Simulation Dopamine Plasma Membrane Transport Proteins Molecular Dynamics Simulation
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