AIMC Topic: Peptides, Cyclic

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Simplified and enhanced VCD analysis of cyclic peptides guided by artificial intelligence.

Physical chemistry chemical physics : PCCP
Cyclic peptides are privileged structures in medicinal chemistry; however, their solution-state structure characterization is difficult. Vibrational circular dichroism (VCD) spectroscopy is a powerful alternative to NMR, but requires challenging calc...

Training Neural Network Models Using Molecular Dynamics Simulation Results to Efficiently Predict Cyclic Hexapeptide Structural Ensembles.

Journal of chemical theory and computation
Cyclic peptides have emerged as a promising class of therapeutics. However, their design remains challenging, and many cyclic peptide drugs are simply natural products or their derivatives. Most cyclic peptides, including the current cyclic peptide ...

RA V-Net: deep learning network for automated liver segmentation.

Physics in medicine and biology
Segmenting liver from CT images is the first step for doctors to diagnose a patient's disease. Processing medical images with deep learning models has become a current research trend. Although it can automate segmenting region of interest of medical ...

A Convolutional Neural Network-Based Approach for the Rapid Annotation of Molecularly Diverse Natural Products.

Journal of the American Chemical Society
This report describes the first application of the novel NMR-based machine learning tool "Small Molecule Accurate Recognition Technology" (SMART 2.0) for mixture analysis and subsequent accelerated discovery and characterization of new natural produc...

Broad-specificity ELISA with a heterogeneous strategy for sensitive detection of microcystins and nodularin.

Toxicon : official journal of the International Society on Toxinology
A highly sensitive and broadly specific competitive indirect enzyme-linked immunosorbent assay (ciELISA) method was developed for the simultaneous detection of nine microcystins (MCs) and nodularin (NOD) using MC-LR-keyhole limpet hemocyanin (KLH) fo...

Computational prediction of plasma protein binding of cyclic peptides from small molecule experimental data using sparse modeling techniques.

BMC bioinformatics
BACKGROUND: Cyclic peptide-based drug discovery is attracting increasing interest owing to its potential to avoid target protein depletion. In drug discovery, it is important to maintain the biostability of a drug within the proper range. Plasma prot...

Automated Whole-Body Bone Lesion Detection for Multiple Myeloma on Ga-Pentixafor PET/CT Imaging Using Deep Learning Methods.

Contrast media & molecular imaging
The identification of bone lesions is crucial in the diagnostic assessment of multiple myeloma (MM). Ga-Pentixafor PET/CT can capture the abnormal molecular expression of CXCR-4 in addition to anatomical changes. However, whole-body detection of doze...

A new cyclic lipopeptide isolated from Bacillus amyloliquefaciens HAB-2 and safety evaluation.

Pesticide biochemistry and physiology
Bacillus is the most widely studied biocontrol agent and has been extensively used in the development of biopesticides and fungicides. In this study, a new cyclic lipopeptide was isolated from Bacillus amyloliquefaciens HAB-2 by column chromatography...

Cyclic Peptide Therapeutic Agents Discovery: Computational and Artificial Intelligence-Driven Strategies.

Journal of medicinal chemistry
Cyclic peptides have emerged as promising modulators of protein-protein interactions due to their unique pharmacological properties and ability to target extensive flat binding interfaces. However, traditional strategies for developing cyclic peptide...

NCPepFold: Accurate Prediction of Noncanonical Cyclic Peptide Structures via Cyclization Optimization with Multigranular Representation.

Journal of chemical theory and computation
Artificial intelligence-based peptide structure prediction methods have revolutionized biomolecular science. However, restricting predictions to peptides composed solely of 20 natural amino acids significantly limits their practical application; as s...