AIMC Topic: Molecular Structure
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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...
A deep learning model for structure-based bioactivity optimization and its application in the bioactivity optimization of a SARS-CoV-2 main protease inhibitor.
European journal of medicinal chemistry
Apr 5, 2025
Bioactivity optimization is a crucial and technical task in the early stages of drug discovery, traditionally carried out through iterative substituent optimization, a process that is often both time-consuming and expensive. To address this challenge...
Discovery and characterization of novel FAK inhibitors for breast cancer therapy via hybrid virtual screening, biological evaluation and molecular dynamics simulations.
Bioorganic chemistry
Mar 26, 2025
Focal adhesion kinase (FAK) is a critical drug target implicated in various disease pathways, including hematological malignancies and breast cancer. Therefore, identifying FAK inhibitors with novel scaffolds could offer new opportunities for develop...
Molecular Dynamics Simulation
Drug Evaluation, Preclinical
Protein Kinase Inhibitors
Structure-Activity Relationship
Humans
Focal Adhesion Kinase 1
Molecular Docking Simulation
Molecular Structure
Cell Proliferation
Female
Focal Adhesion Protein-Tyrosine Kinases
Drug Discovery
Dose-Response Relationship, Drug
Breast Neoplasms
Antineoplastic Agents
Drug Screening Assays, Antitumor
In silico discovery of novel compounds for FAK activation using virtual screening, AI-based prediction, and molecular dynamics.
Computational biology and chemistry
Mar 25, 2025
Focal Adhesion Kinase (FAK) is a non-receptor tyrosine kinase that plays a crucial role in cell proliferation, migration, and signal transduction. FAK is overexpressed in metastatic and advanced-stage cancers, where it is considered a key kinase in c...
DIG-Mol: A Contrastive Dual-Interaction Graph Neural Network for Molecular Property Prediction.
IEEE journal of biomedical and health informatics
Mar 6, 2025
Molecular property prediction is a key component of AI-driven drug discovery and molecular characterization learning. Despite recent advances, existing methods still face challenges such as limited ability to generalize, and inadequate representation...
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