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Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry UPLC-MS

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Metadynamic metainference: Enhanced sampling of the metainference ensemble using metadynamics.

Massimiliano Bonomi¹, Carlo Camilloni^1,2, Michele Vendruscolo¹

¹Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK.

Scientific Reports

|August 27, 2016

Summary

Metainference, a Bayesian method, accurately determines protein structures by integrating data and prior knowledge. Combining it with metadynamics enhances conformational sampling for complex systems, aiding free energy landscape calculations.

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Area of Science:

Computational biology
Biophysics
Structural biology

Background:

Accurate protein structural ensembles are crucial for understanding biological function.
Existing methods like metainference integrate experimental data and prior knowledge but require efficient conformational sampling.
Complex macromolecular systems necessitate extensive sampling for comprehensive structural analysis.

Purpose of the Study:

To combine metainference with metadynamics for efficient and exhaustive generation of structural ensembles.
To address the challenge of extensive conformational sampling in complex macromolecular systems.
To calculate the free energy landscape of the alanine dipeptide as a demonstration.

Main Methods:

Bayesian inference (metainference) for structural ensemble calculation.
Enhanced conformational sampling through the combination with metadynamics.
Free energy landscape calculation applied to alanine dipeptide.

Main Results:

Demonstrated the successful integration of metainference and metadynamics.
Showcased efficient and exhaustive generation of structural ensembles.
Successfully calculated the free energy landscape of alanine dipeptide.

Conclusions:

The combined metainference and metadynamics approach offers a powerful tool for studying complex macromolecular systems.
This integrated method enhances the accuracy and efficiency of structural ensemble determination.
It provides a robust framework for calculating free energy landscapes.