M. I. Zimmerman

Apolipoprotein E4 has extensive conformational heterogeneity in lipid free and bound forms

This study uses single-molecule spectroscopy and molecular dynamics simulations to show that ApoE4 has extensive conformational heterogeneity in both lipid-free and lipid-bound states, differing from previous models.

SARS-CoV-2 Nsp16 activation mechanism and a cryptic pocket with pan-coronavirus antiviral potential

This paper investigates how Nsp10 activates Nsp16 and identifies a cryptic pocket in SARS-CoV-2 Nsp16 that could be targeted for pan-coronavirus antivirals.

DiffNets: Self-supervised deep learning to identify the mechanistic basis for biochemical differences between protein variants

DiffNets identifies structural features predicting biochemical differences between protein variants using self-supervised learning.

SARS-CoV-2 Simulations Go Exascale to Capture Spike Opening and Reveal Cryptic Pockets Across the Proteome

The paper uses exascale simulations to study SARS-CoV-2 protein dynamics, revealing cryptic epitopes and conformational changes that inform antiviral target design.

The SARS-CoV-2 nucleocapsid protein is dynamic, disordered, and phase separates with RNA

This study investigates the SARS-CoV-2 nucleocapsid protein's dynamics, disorder, and RNA phase separation using single-molecule spectroscopy and simulations, revealing its multivalent RNA binding properties and phase separation behavior.

A cryptic pocket in Ebola VP35 allosterically controls RNA binding

This study identifies a cryptic pocket in Ebola VP35 that allosterically controls RNA binding, validated through simulations, experiments, and drug-like modifications.

Spatial and temporal alterations in protein structure by EGF regulate cryptic cysteine oxidation

This study identifies three spatiotemporal patterns of cysteine oxidation in response to EGF stimulation, revealing that cryptic cysteines become redox regulated through structural changes induced by EGF.

Conformational distributions of isolated myosin motor domains encode their mechanochemical properties

The paper models conformational distributions of myosin motor domains using molecular dynamics simulations to predict mechanochemical properties better than sequence or structure alone.

Enspara: Modeling molecular ensembles with scalable data structures and parallel computing

Enspara improves the scalability of Markov state models by introducing novel algorithms and data structures for efficient computation.

Cooperative changes in solvent exposure identify cryptic pockets, conformational switches, and allosteric coupling

The paper introduces a method to identify functionally-relevant conformational changes in proteins by analyzing cooperative solvent exposure changes, demonstrating its utility in discovering cryptic allosteric sites.