AIMC Topic: Peptides, Cyclic

Clear Filters Showing 1 to 10 of 23 articles

Bulk Measurement of Membrane Permeability for Random Cyclic Peptides in Living Cells to Guide Drug Development.

Angewandte Chemie (International ed. in English) Jun 1, 2025
Cyclic peptides are attractive for drug discovery due to their excellent binding properties and the potential to cross cell membranes. However, by far, not all cyclic peptides are cell permeable, and measuring or predicting their membrane permeabilit...
Peptides, Cyclic Cell Membrane Permeability Humans Drug Development
View on PubMed DOI

Cyclic peptide structure prediction and design using AlphaFold2.

Nature communications May 21, 2025
Small cyclic peptides have gained significant traction as a therapeutic modality; however, the development of deep learning methods for accurately designing such peptides has been slow, mostly due to the lack of sufficiently large training sets. Here...
Proto-Oncogene Proteins c-mdm2 Kelch-Like ECH-Associated Protein 1 Crystallography, X-Ray Protein Conformation Computational Biology Models, Molecular Drug Design Amino Acid Sequence Deep Learning Peptides, Cyclic Humans
View on PubMed DOI

MultiCycPermea: accurate and interpretable prediction of cyclic peptide permeability using a multimodal image-sequence model.

BMC biology Feb 27, 2025
BACKGROUND: Cyclic peptides, known for their high binding affinity and low toxicity, show potential as innovative drugs for targeting "undruggable" proteins. However, their therapeutic efficacy is often hindered by poor membrane permeability. Over th...
Permeability Peptides, Cyclic Deep Learning
View on PubMed DOI

CPconf_score: A Deep Learning Free Energy Function Trained Using Molecular Dynamics Data for Cyclic Peptides.

Journal of chemical theory and computation Jan 13, 2025
Accurate structural feature characterization of cyclic peptides (CPs), especially those with less than 10 residues and -peptide bonds, is challenging but important for the rational design of bioactive peptides. In this study, we performed high-temper...
Peptides, Cyclic Protein Conformation Deep Learning Molecular Dynamics Simulation Thermodynamics
View on PubMed DOI

Investigating Ligand-Mediated Conformational Dynamics of Pre-miR21: A Machine-Learning-Aided Enhanced Sampling Study.

Journal of chemical information and modeling Nov 11, 2024
MicroRNAs (miRs) are short, noncoding RNA strands that regulate the activity of mRNAs by affecting the repression of protein translation, and their dysregulation has been implicated in several pathologies. miR21 in particular has been implicated in t...
Peptides, Cyclic Nucleic Acid Conformation RNA Precursors Ribonuclease III Molecular Dynamics Simulation Ligands MicroRNAs Humans Machine Learning
View on PubMed DOI

CREMP: Conformer-rotamer ensembles of macrocyclic peptides for machine learning.

Scientific data Aug 9, 2024
Computational and machine learning approaches to model the conformational landscape of macrocyclic peptides have the potential to enable rational design and optimization. However, accurate, fast, and scalable methods for modeling macrocycle geometrie...
Protein Conformation Macrocyclic Compounds Machine Learning Peptides Peptides, Cyclic
View on PubMed DOI

PepExplainer: An explainable deep learning model for selection-based macrocyclic peptide bioactivity prediction and optimization.

European journal of medicinal chemistry Jun 25, 2024
Macrocyclic peptides possess unique features, making them highly promising as a drug modality. However, evaluating their bioactivity through wet lab experiments is generally resource-intensive and time-consuming. Despite advancements in artificial in...
Dose-Response Relationship, Drug Structure-Activity Relationship Molecular Structure Peptides, Cyclic Peptides Deep Learning Humans Macrocyclic Compounds
View on PubMed DOI

Multi_CycGT: A Deep Learning-Based Multimodal Model for Predicting the Membrane Permeability of Cyclic Peptides.

Journal of medicinal chemistry Jan 25, 2024
Cyclic peptides are gaining attention for their strong binding affinity, low toxicity, and ability to target "undruggable" proteins; however, their therapeutic potential against intracellular targets is constrained by their limited membrane permeabil...
Deep Learning Chemistry, Pharmaceutical Permeability Cell Membrane Permeability Peptides, Cyclic
View on PubMed DOI

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

Physical chemistry chemical physics : PCCP Aug 23, 2023
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...
Circular Dichroism Peptides, Cyclic Artificial Intelligence
View on PubMed DOI

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

Journal of chemical theory and computation May 26, 2023
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 ...
Molecular Dynamics Simulation Machine Learning Peptides, Cyclic Protein Structure, Tertiary Neural Networks, Computer Models, Molecular
View on PubMed DOI
Popular Topics
Recent Journals