Biology subjects

Bogetti, A. T.

Publications and source records attributed to Bogetti, A. T..

4 recordsLinked to original sources

bioRxiv2026

Generation of Pathway Signatures by Combining Normal Modes with Weighted Ensemble Simulations

Molecular dynamics simulations provide a "computational microscope" by which molecular phenomena can be studied at atomic resolution. However, such simulations are often expensive, usually due to a combination of system size and timescale. Various enhanced sampling methods have been proposed to overcome these challenges. Despite their effectiveness, many suffer from artifacts from energetic biases guiding the simulations, or lack of effective progress coordinates. Proteins normal modes uniquely defined by their 3D fold capture their intrinsic dynamics and could provide unbiased guidance, but how to combine these modes with molecular dynamics to generate continuous, energetically unbiased pathways has been challenging. In this study, we demonstrate that conformations generated along from normal modes using adaptive anisotropic network model provide a physical, intuitive, and generalizable progress coordinate for weighted ensemble simulations, providing a boost in efficiency and a means to generate pathways for any protein system without prior knowledge.

biophysics↗

bioRxiv2025

Lessons Learned from a Ligand-Unbinding Stress Test for Weighted Ensemble Simulations

The weighted ensemble (WE) path sampling strategy has pushed the boundaries of molecular simulation by enabling the generation of rates and atomistic pathways for biological processes beyond the ms timescale. However, the WE strategy has not yet reached its full potential and much can be gained from pursuing "stress tests." Here we have explored a stress test involving the seconds-timescale unbinding of a highly charged ligand from a protein receptor: the release of the ADP ligand from the Eg5 protein receptor, which functions as a motor protein in cell division. From this stress test we learned valuable lessons regarding the choice of progress coordinate and improvements to the WE resampling procedure. Based on the latter, we have developed a WE method referred to as the Minimal Adaptive BinLess (MABL) method. The MABL method is in the same spirit as our previously developed Minimal Adaptive Binning (MAB) scheme for surmounting large energetic barriers, but is "binless", i.e., does not require the use of rectilinear bins along a progress coordinate. This minimal version of a binless method is >50% more efficient than the corresponding binned version and provides a framework for implementing more complex binless methods.

biophysics↗

bioRxiv2021

A glycan gate controls opening of the SARS-CoV-2 spike protein

SARS-CoV-2 infection is controlled by the opening of the spike protein receptor binding domain (RBD), which transitions from a glycan-shielded "down" to an exposed "up" state in order to bind the human ACE2 receptor and infect cells. While snapshots of the "up" and "down" states have been obtained by cryoEM and cryoET, details of the RBD opening transition evade experimental characterization. Here, over 130 s of weighted ensemble (WE) simulations of the fully glycosylated spike ectodomain allow us to characterize more than 300 continuous, kinetically unbiased RBD opening pathways. Together with ManifoldEM analysis of cryo-EM data and biolayer interferometry experiments, we reveal a gating role for the N-glycan at position N343, which facilitates RBD opening. Residues D405, R408, and D427 also participate. The atomic-level characterization of the glycosylated spike activation mechanism provided herein achieves a new high-water mark for ensemble pathway simulations and offers a foundation for understanding the fundamental mechanisms of SARS-CoV-2 viral entry and infection.

biophysics↗

bioRxiv2020

A Minimal, Adaptive Binning Scheme for Weighted Ensemble Simulations

A promising approach for simulating rare events with rigorous kinetics is the weighted ensemble path sampling strategy. One challenge of this strategy is the division of configurational space into bins for sampling. Here we present a minimal adaptive binning (MAB) scheme for the automated, adaptive placement of bins along a progress coordinate within the framework of the weighted ensemble strategy. Results reveal that the MAB binning scheme, despite its simplicity, is more efficient than a manual, fixed binning scheme in generating transitions over large free energy barriers, generating a diversity of pathways, estimating rate constants, and sampling conformations. The scheme is general and extensible to any rare-events sampling strategy that employs progress coordinates.

biophysics↗