Accelerated weight histogram method for exploring free energy landscapes
Viveca Lindahl, Jack Lidmar, Berk Hess

TL;DR
The paper introduces the accelerated weight histogram (AWH) method, an efficient adaptive sampling technique for exploring free energy landscapes in molecular simulations, demonstrated on complex biological systems.
Contribution
It presents the AWH method as a general, adaptive, and efficient approach for free energy calculations, with practical guidelines and broad applicability.
Findings
Efficient free energy calculations for complex molecular systems.
Demonstrated applicability on peptide folding and solution simulations.
Provides practical setup guidelines for AWH simulations.
Abstract
Calculating free energies is an important and notoriously difficult task for molecular simulations. The rapid increase in computational power has made it possible to probe increasingly complex systems, yet extracting accurate free energies from these simulations remains a major challenge. Fully exploring the free energy landscape of, say, a biological macromolecule typically requires sampling large conformational changes and slow transitions. Often, the only feasible way to study such a system is to simulate it using an enhanced sampling method. The accelerated weight histogram (AWH) method is a new, efficient extended ensemble sampling technique which adaptively biases the simulation to promote exploration of the free energy landscape. The AWH method uses a probability weight histogram which allows for efficient free energy updates and results in an easy discretization procedure. A…
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