AIMC Topic: Molecular Structure
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PairReg: A method for enhancing the learning of molecular structure representation in equivariant graph neural networks.
PloS one
Jul 31, 2025
The 3D structure of molecules contains a wealth of important information, but traditional 3DCNN-based methods fail to adequately address the transformations of rigid motions (rotation, translation, and mapping). Equivariant graph neural networks (EGN...
In Silico Design and Analysis of Cyanobacterial Pseudo Natural Products.
Journal of natural products
Jul 16, 2025
Marine cyanobacteria produce natural products (NPs) with potent and selective bioactivity against a broad range of diseases. However, like many NPs, most exhibit poor drug-like physicochemical properties, and the discovery of structurally novel NPs i...
Unlocking the Potential: The Structural Wonders and Diverse Applications of Triazoles in Contemporary Science.
Topics in current chemistry (Cham)
Jul 4, 2025
Triazoles, a captivating class of nitrogen-containing heterocyclic compounds, have emerged as pivotal players in contemporary chemistry, drawing significant attention for their exceptional versatility and wide-ranging applications. They have become e...
DCGCN: Dual-Channel Graph Convolutional Network-Based Drug-Target Interaction Prediction Method with 3D Molecular Structure.
Journal of chemical information and modeling
Jul 2, 2025
Exploring drug-target interactions (DTIs) is crucial for drug discovery. Most existing methods for predicting DTIs rely solely on the linear structures of molecules, such as SMILES or the amino acid sequence. However, these linear features fail to re...
CSU-MS: A Contrastive Learning Framework for Cross-Modal Compound Identification from MS/MS Spectra to Molecular Structures.
Analytical chemistry
Jun 20, 2025
Tandem mass spectrometry (MS/MS) is a cornerstone for compound identification in complex mixtures, but conventional spectral matching approaches face critical limitations due to limited library coverage and matching algorithms. To address this, we pr...
Developing Pharmaceutically Relevant Pd-Catalyzed C-N Coupling Reactivity Models Leveraging High-Throughput Experimentation.
Journal of the American Chemical Society
May 29, 2025
This manuscript presents machine learning models for Pd-catalyzed C-N couplings constructed using a large, pharmaceutically relevant, structurally diverse dataset (4204 unique products) generated using high-throughput experimentation. The dataset ge...
Recent research frontiers of heterocycles as antifungal Agents: Insights from the past five years.
European journal of medicinal chemistry
May 23, 2025
This review explores the growing global concern of fungal infections, particularly in immunocompromised individuals, and highlights the critical need for improved antifungal therapies. With the rise of multidrug-resistant strains, such as Candida aur...
Sculpting molecules in text-3D space: a flexible substructure aware framework for text-oriented molecular optimization.
BMC bioinformatics
May 7, 2025
The integration of deep learning, particularly AI-Generated Content, with high-quality data derived from ab initio calculations has emerged as a promising avenue for transforming the landscape of scientific research. However, the challenge of designi...
Bioactive structures for inhibitors of polymerase enzyme by artificial intelligence.
Future medicinal chemistry
Apr 17, 2025
AIMS: Present new bioactive compounds, created by De novo Drug Design and artificial intelligence (AI), as possible inhibitors of polymerase.
Design and Synthesis of Magnolol Derivatives Using Integrated CNNs and Pharmacophore Approaches for Enhanced Parasiticidal Activity in Aquaculture.
Journal of agricultural and food chemistry
Apr 16, 2025
Aquaculture is a rapidly growing sector of global food production, playing a vital role in poverty alleviation, food security, and income generation. However, it faces substantial challenges, particularly due to infections caused by the protozoan , l...
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