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Related Concept Videos

2D NMR: Overview of Homonuclear Correlation Techniques01:16

2D NMR: Overview of Homonuclear Correlation Techniques

Homonuclear correlation spectroscopy (COSY) is a powerful technique used in Nuclear Magnetic Resonance (NMR) spectroscopy to study the correlations between nuclei of the same type within a molecule. It provides information about scalar couplings between adjacent nuclei, which helps determine connectivity and structural information. There are several COSY variants, each with its unique strengths and experimental parameters.
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Homonuclear correlation spectroscopy, or COSY, is a 2-dimensional NMR technique that provides information about coupled protons. Typically, the geminal and vicinal coupling are observed. For example, consider the COSY spectrum of ethyl acetate, where its 1D proton NMR spectrum is plotted along the vertical and horizontal axes with their corresponding chemical shift scale. Three spots on the diagonal corresponding to the three peaks in the 1D proton spectrum are called diagonal peaks. The COSY...
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Related Experiment Video

Updated: May 16, 2026

Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
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Published on: June 9, 2023

Conformer Generation Workflows for COSMO-RS Calculations: Are They All the Same?

André M M Gomes1,2,3, José F O Granjo3, Paulo J Costa1,2

  • 1BioISI-Instituto de Biossistemas e Ciências Integrativas, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisbon, Portugal.

Journal of Chemical Information and Modeling
|May 14, 2026
PubMed
Summary
This summary is machine-generated.

Choosing the right molecular conformation method significantly impacts drug solubility predictions using COSMO-RS. Our study shows various methods offer similar accuracy, but solvent-aware approaches show promise for improved drug formulation predictions.

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Last Updated: May 16, 2026

Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
07:59

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Published on: June 9, 2023

Cryo-EM and Single-Particle Analysis with Scipion
09:06

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Published on: May 29, 2021

Area of Science:

  • Computational chemistry
  • Drug discovery and development
  • Physical chemistry

Background:

  • Accurate prediction of drug solubility is crucial for pharmaceutical formulation and bioavailability.
  • The Conductor-like Screening Model for Real Solvents (COSMO-RS) is a key tool for estimating solubility, but its accuracy depends heavily on input molecular conformations.
  • Previous studies lacked a systematic evaluation of different conformer generation methods' impact on COSMO-RS solubility predictions across diverse datasets.

Purpose of the Study:

  • To systematically evaluate the influence of various conformer generation workflows on the accuracy of COSMO-RS solubility predictions.
  • To compare the performance of different computational approaches, from simple to advanced, using a large, curated dataset.
  • To assess the benefits of using conformer ensembles versus single-conformer pipelines and explore solvent-aware methods.

Main Methods:

  • Assessed four distinct conformer generation workflows: RDKit-based, semiempirical, and DFT-based.
  • Utilized a curated dataset of 926 experimental solubility values and 405 free energies of solvation.
  • Compared conformer ensembles against solvent-aware single-conformer pipelines for selected molecules.

Main Results:

  • All evaluated conformer generation workflows demonstrated comparable accuracy, with mean absolute errors around one logarithmic unit.
  • A consistent underperformance was observed in the low-solubility regime across all methods, highlighting a persistent challenge.
  • Conformer ensembles offered moderate improvements but did not consistently outperform solvent-aware lowest-energy conformer selection.
  • Incorporating solvent information during lowest-energy conformer identification enhanced accuracy for molecules with intramolecular interactions.

Conclusions:

  • Practical guidance is provided for selecting conformer generation strategies in high-throughput COSMO-RS applications.
  • Solvent-aware workflows are identified as a promising avenue for improving predictive accuracy and robustness without sacrificing computational efficiency.
  • Further research into optimizing conformer generation, especially for low-solubility compounds, is warranted.