AIMC Topic: Molecular Structure

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Cyanobacteria Join the Kahalalide Conversation: Genome and Metabolite Evidence for Structurally Related Peptides.

Journal of the American Chemical Society
Kahalalide F is a cyclic depsipeptide with notable anticancer properties, initially discovered from the green alga sp. and its molluscan predator . Recent studies have pinpointed a bacterial endosymbiont of the green alga, Endobryopsis kahalalidefa...

PairReg: A method for enhancing the learning of molecular structure representation in equivariant graph neural networks.

PloS one
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...

A dual-view deep learning-driven discovery of cinnamoyl anthranilic acid derivatives against orthopoxvirus through targeting host ITGB3.

European journal of medicinal chemistry
The orthopoxvirus genus, particularly the monkeypox virus (MPXV), continues to pose a significant global public health threat. Therefore, the development of novel anti-orthopoxvirus agents remains an urgent priority. Machine learning has proven to be...

In Silico Design and Analysis of Cyanobacterial Pseudo Natural Products.

Journal of natural products
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...

MASSISTANT: A deep learning model for De Novo molecular structure prediction from EI‑MS spectra via SELFIES encoding.

Journal of chromatography. A
Gas chromatography coupled with electron impact mass spectrometry (GC‑EI‑MS) is a widely used analytical technique for identifying volatile and semi‑volatile compounds in applications ranging from pharmaceutical research to material science. However,...

Unlocking the Potential: The Structural Wonders and Diverse Applications of Triazoles in Contemporary Science.

Topics in current chemistry (Cham)
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
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...

1,3-Thiazole nucleus as promising molecular platform against antimicrobial resistance: a recent overview in drug discovery.

European journal of medicinal chemistry
Antimicrobial resistance (AMR) has emerged as one of the foremost public health threats of the 21st century. The progressive decline in the efficacy of conventional antibiotics, combined with a scarcity of new drug classes approved in recent decades,...

CSU-MS: A Contrastive Learning Framework for Cross-Modal Compound Identification from MS/MS Spectra to Molecular Structures.

Analytical chemistry
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
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...