eScholarship
metadata only
CC BY
Mechanistic Dissection of Conformational Transitions in a Bicyclic Peptide via Molecular Modeling and Deep Learning
Abstract Molecular conformations play a critical role in determining molecular properties, such as membrane permeability, binding affinity, and ultimately therapeutic efficacy. Experimental and computational approaches can characterize conformations and provide insight into why certain conformations
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Analyzing Peptide Torsional Dynamics: An Angular-Displacement PCA Pipeline for Short-Horizon Prediction from Molecular Dynamics.#174550
- Deep Learning-based Design of Peptide Binders#236583
- Enriching traditional proteinprotein interaction networks with alternative conformations of proteins#954936
- Comparative Analysis of Deep Learning‐Based Algorithms for Peptide Structure Prediction#1039063
- Predicting most probable conformations of a given peptide sequence in the random coil state#954539
Record · ID 1250103
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive