A. T. Frank

N1-Methylpseudouridine and pseudouridine modifications modulate mRNA decoding during translation

This study investigates how N1-methylpseudouridine and pseudouridine modifications affect mRNA decoding during translation, showing they influence amino acid misincorporation depending on codon position and tRNA context.

Using Unassigned NMR Chemical Shifts to Model RNA Secondary Structure

This paper models RNA secondary structure using unassigned NMR chemical shifts, showing consistency with existing chemical probing data for SARS-CoV-2 UTRs.

Profiling Unbinding Events to Identify Near-Native RNA-Ligand Poses

This study identifies near-native RNA-ligand poses by analyzing unbinding profiles from molecular dynamics simulations and using a regression model to discriminate native-like structures from decoys.

AI-Generated Virtual Libraries Could Help Uncover RNA-Specific Regions of Chemical Space

The paper uses AI-generated virtual libraries to explore RNA-specific chemical space and finds they replicate trends seen in experimentally validated RNA binders.

Navigating Chemical Space By Interfacing Generative Artificial Intelligence and Molecular Docking

The paper designs a framework combining generative AI and molecular docking to create target-specific chemical libraries, identifying potential drug repurposing candidates for SARS-CoV-2 Mpro.

Structural Ensembles of Ribonucleic Acids From Solvent Accessibility Data: Application to the S-Adenosylmethionine (SAM)-Responsive Riboswitch

The paper constructs atomistic ensembles of the SAM-responsive riboswitch in the presence and absence of SAM using solvent accessibility data, revealing structural changes and a hidden binding pocket.

RNAPosers: Machine Learning Classifiers For RNA-Ligand Poses

RNAPosers uses machine learning to classify RNA-ligand poses, improving native pose recovery compared to docking scores.

Accelerating Dissociative Events in Molecular Dynamics Simulations by Selective Potential Scaling

This paper introduces a method to accelerate dissociative events in MD simulations by selectively scaling potential energy terms, demonstrating its effectiveness in ligand unbinding.

Conditional Prediction of RNA Secondary Structure Using NMR Chemical Shifts

The paper develops a method to predict RNA secondary structure using chemical shifts, achieving accurate predictions for 108 RNAs and confirming conditional prediction of miR-20b structures.