Xinqiang Ding
xqding.bsky.social
Xinqiang Ding
@xqding.bsky.social
Assistant Professor at Tufts Chemistry, dinglab.io
Reposted by Xinqiang Ding
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"Ensemble docking for intrinsically disordered proteins"

from Dartmouth undergrad Anjali Dhar 24' and grad student Tommy Sisk. We present ensemble docking strategies for IDPs that, remarkably, seem to work!

www.biorxiv.org/content/10.1...

Code: github.com/paulrobustel...
January 31, 2025 at 7:59 PM
Our new method, Coupled BayesMBAR, is published on JCTC! It provides a principled Bayesian approach for computing free energy differences and their uncertainties on perturbation graphs with cycles. pubs.acs.org/doi/full/10..... Source code is available at github.com/DingGroup/Ba...
Bayesian Approach for Computing Free Energy on Perturbation Graphs with Cycles
A common approach for computing free energy differences among multiple states is to build a perturbation graph connecting the states and compute free energy differences on all edges of the graph. Such perturbation graphs are often designed to have cycles. Because free energy is a function of states, the free energy around any cycle is zero, which we refer to as the cycle consistency condition. Since the cycle consistency condition relates free energy differences on the edges of a cycle, it could be used to improve the accuracy of free energy estimates. Here, we propose a Bayesian method called the coupled Bayesian multistate Bennett acceptance ratio (CBayesMBAR) that can properly couple the calculations of free energy differences on the edges of cycles in a principled way. We apply the CBayesMBAR to compute free energy differences among harmonic oscillators and relative protein–ligand binding free energies. In both cases, the CBayesMBAR provides more accurate results compared to methods that do not consider the cycle consistency condition. Additionally, it outperforms the cycle closure correction method that also uses cycle consistency conditions.
pubs.acs.org
November 23, 2024 at 8:54 PM