About

Joseph A. Piccirilli is a Professor of Biochemistry and Molecular Biology at the University of Chicago within the Department of Biochemistry & Molecular Biology. His research focuses on the structural and mechanistic understanding of RNA molecules, including their conformational dynamics, modifications, and interactions with small molecules. His work involves studying RNA's role in mitochondrial pathology, RNA structure prediction, and ligand recognition, contributing to the broader understanding of RNA biology and its implications in health and disease. Professor Piccirilli's research integrates structural biology, biochemistry, and molecular biology techniques to elucidate the fundamental principles governing RNA function and its potential therapeutic applications.

Research topics

• Chemistry
• Aerospace engineering
• Biochemistry
• Astrobiology
• Computational biology
• Genetics
• Biology
• Combinatorics
• Cell biology
• Mathematics
• Materials science
• Epistemology
• Crystallography

Selected publications

• Functional Relevance of <scp>CASP16</scp> Nucleic Acid Predictions as Evaluated by Structure Providers

  Proteins Structure Function and Bioinformatics · 2025-09-04 · 11 citations

  articleOpen access

  Accurate biomolecular structure prediction enables the prediction of mutational effects, the speculation of function based on predicted structural homology, the analysis of ligand binding modes, experimental model building, and many other applications. Such algorithms to predict essential functional and structural features remain out of reach for biomolecular complexes containing nucleic acids. Here, we report a quantitative and qualitative evaluation of nucleic acid structures for the CASP16 blind prediction challenge by 12 of the experimental groups who provided nucleic acid targets. Blind predictions accurately model secondary structure and some aspects of tertiary structure, including reasonable global folds for some complex RNAs; however, predictions often lack accuracy in the regions of highest functional importance. All models have inaccuracies in non-canonical regions where, for example, the nucleic-acid backbone bends, deviating from an A-form helix geometry, or a base forms a non-standard hydrogen bond (not a Watson-Crick base pair). These bends and non-canonical interactions are integral to forming functionally important regions such as RNA enzymatic active sites. Additionally, the modeling of conserved and functional interfaces between nucleic acids and ligands, proteins, or other nucleic acids remains poor. For some targets, the experimental structures may not represent the only structure the biomolecular complex occupies in solution or in its functional life cycle, posing a future challenge for the community.

  PublisherOA PDFDOI

• Genome-wide profiling of tRNA modifications by Induro-tRNAseq reveals coordinated changes

  Nature Communications · 2025-01-26 · 19 citations

  articleOpen access

  While all native tRNAs undergo extensive post-transcriptional modifications as a mechanism to regulate gene expression, mapping these modifications remains challenging. The critical barrier is the difficulty of readthrough of modifications by reverse transcriptases (RTs). Here we use Induro-a new group-II intron-encoded RT-to map and quantify genome-wide tRNA modifications in Induro-tRNAseq. We show that Induro progressively increases readthrough over time by selectively overcoming RT stops without altering the misincorporation frequency. In a parallel analysis of Induro vs. a related RT, we provide comparative datasets to facilitate the prediction of each modification. We assess tRNA modifications across five human cell lines and three mouse tissues and show that, while the landscape of modifications is highly variable throughout the tRNA sequence framework, it is stabilized for modifications that are required for reading of the genetic code. The coordinated changes have fundamental importance for development of tRNA modifications in protein homeostasis.

  PublisherOA PDFDOI

• Author response for "Functional Relevance of CASP16 Nucleic Acid Predictions as Evaluated by Structure Providers"

  2025-08-04 · 2 citations

  peer-review
  PublisherDOI

• Functional Relevance of CASP16 Nucleic Acid Predictions as Evaluated by Structure Providers

  Maryland Shared Open Access Repository (USMAI Consortium) · 2025-08-14

  articleOpen access

  Accurate biomolecular structure prediction enables the prediction of mutational effects, the speculation of function based on predicted structural homology, the analysis of ligand binding modes, experimental model building, and many other applications. Such algorithms to predict essential functional and structural features remain out of reach for biomolecular complexes containing nucleic acids. Here, we report a quantitative and qualitative evaluation of nucleic acid structures for the CASP16 blind prediction challenge by 12 of the experimental groups who provided nucleic acid targets. Blind predictions accurately model secondary structure and some aspects of tertiary structure, including reasonable global folds for some complex RNAs; however, predictions often lack accuracy in the regions of highest functional importance. All models have inaccuracies in non-canonical regions where, for example, the nucleic-acid backbone bends, deviating from an A-form helix geometry, or a base forms a non-standard hydrogen bond (not a Watson-Crick base pair). These bends and non-canonical interactions are integral to forming functionally important regions such as RNA enzymatic active sites. Additionally, the modeling of conserved and functional interfaces between nucleic acids and ligands, proteins, or other nucleic acids remains poor. For some targets, the experimental structures may not represent the only structure the biomolecular complex occupies in solution or in its functional life cycle, posing a future challenge for the community.

  PublisherDOI

• Functional relevance of CASP16 nucleic acid predictions as evaluated by structure providers

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-04-18 · 10 citations

  preprintOpen access

  Accurate biomolecular structure prediction enables the prediction of mutational effects, the speculation of function based on predicted structural homology, the analysis of ligand binding modes, experimental model building and many other applications. Such algorithms to predict essential functional and structural features remain out of reach for biomolecular. Here, we report quantitative and qualitative evaluation of nucleic acid structures for the CASP16 blind prediction challenge by 12 of the experimental groups who provided nucleic acid targets. Blind predictions accurately model secondary structure and some aspects of tertiary structure, including reasonable global folds for some complex RNAs, however, predictions often lack accuracy in the regions of highest functional importance. All models have inaccuracies in non-canonical regions where, e.g., the nucleic-acid backbone bends or a base forms a non-standard hydrogen bond. These bends and non-canonical interactions are integral to form functionally important regions such as RNA enzymatic active sites. Additionally, the modeling of conserved and functional interfaces between nucleic acids and ligands, proteins, or other nucleic acids remains poor. For some targets, the experimental structures may not represent the only structure the biomolecular complex occupies in solution or in its functional life-cycle, posing a future challenge for the community.

  PublisherOA PDFDOI

• Mechanistic studies of small molecule ligands selective to RNA single G bulges

  Nucleic Acids Research · 2025-06-05 · 2 citations

  articleOpen access

  Small-molecule RNA binders have emerged as an important pharmacological modality. A profound understanding of the ligand selectivity, binding mode, and influential factors governing ligand engagement with RNA targets is the foundation for rational ligand design. Here, we report a novel class of coumarin derivatives exhibiting selective binding affinity towards single G RNA bulges. Harnessing the computational power of all-atom Gaussian accelerated molecular dynamics simulations, we unveiled a rare minor groove binding mode of the ligand with a key interaction between the coumarin moiety and the G bulge. This predicted binding mode is consistent with results obtained from structure-activity relationship studies and transverse relaxation measurements by nuclear magnetic resonance spectroscopy. We further generated 444 molecular descriptors from 69 coumarin derivatives and identified key contributors to the binding events, such as charge state and planarity, by lasso (least absolute shrinkage and selection operator) regression. Our work deepened the understanding of RNA-small molecule interactions and integrated a new framework for the rational design of selective small-molecule RNA binders.

  PublisherOA PDFDOI

• Structural basis for promiscuity in ligand recognition by yjdF riboswitch

  Cell Discovery · 2024-04-02 · 5 citations

  letterOpen accessSenior authorCorresponding

  No abstract

  PublisherOA PDFDOI

• Unraveling RNA Conformation Dynamics in Mitochondrial Encephalomyopathy, Lactic Acidosis, and Stroke-like Episode Syndrome with Solid-State Nanopores

  ACS Nano · 2024-06-21 · 18 citations

  articleOpen access

  This study investigates transfer ribonucleic acid (tRNA) conformational dynamics in the context of MELAS (mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes) using solid-state silicon nitride (SiN) nanopore technology. SiN nanopores in thin membranes with specific dimensions exhibit high signal resolution, enabling real-time and single-molecule electronic detection of tRNA conformational changes. We focus on human mitochondrial tRNALeu(UAA) (mt-Leu(UAA)) that decodes Leu codons UUA/UUG (UUR) during protein synthesis on the mt-ribosome. The single A14G substitution in mt-Leu(UAA) is the major cause of MELAS disease. Measurements of current blockades and dwell times reveal distinct conformational dynamics of the wild-type (WT) and the A14G variant of mt-Leu(UAA) in response to the conserved post-transcriptional m1G9 methylation. While the m1G9-modified WT transcript adopts a more stable structure relative to the unmodified transcript, the m1G9-modified MELAS transcript adopts a less stable structure relative to the unmodified transcript. Notably, these differential features were observed at 0.4 M KCl, but not at 3 M KCl, highlighting the importance of experimental settings that are closer to physiological conditions. This work demonstrates the feasibility of the nanopore platform to discern tRNA molecules that differ by a single-nucleotide substitution or by a single methylation event, providing an important step forward to explore changes in the conformational dynamics of other RNA molecules in human diseases.

  PublisherOA PDFDOI

• Structure-guided aminoacylation and assembly of chimeric RNAs

  bioRxiv (Cold Spring Harbor Laboratory) · 2024-03-03 · 1 citations

  preprintOpen access

  Coded ribosomal peptide synthesis could not have evolved unless its sequence and amino acid specific aminoacylated tRNA substrates already existed. We therefore wondered whether aminoacylated RNAs might have served some primordial function prior to their role in protein synthesis. Here we show that specific RNA sequences can be nonenzymatically aminoacylated and ligated to produce amino acid-bridged stem-loop RNAs. We used deep sequencing to identify RNAs that undergo highly efficient glycine aminoacylation followed by loop-closing ligation. The crystal structure of one such glycine-bridged RNA hairpin reveals a compact internally stabilized structure with the same eponymous T-loop architecture found in modern tRNA. We demonstrate that the T-loop assisted amino acid bridging of RNA oligonucleotides enables the rapid template-free assembly of a chimeric version of an aminoacyl-RNA synthetase ribozyme. We suggest that the primordial assembly of such chimeric ribozymes would have allowed the greater functionality of amino acids to contribute to enhanced ribozyme catalysis, providing a driving force for the evolution of sequence and amino acid specific aminoacyl-RNA synthetase enzymes prior to their role in protein synthesis.

  PublisherOA PDFDOI

• The Role of General Acid Catalysis in the Mechanism of an Alkyl Transferase Ribozyme

  ACS Catalysis · 2024-10-02 · 14 citations

  articleOpen access

  MTR1 is an in vitro-selected alkyl transferase ribozyme that transfers an alkyl group from O6-alkylguanine to N1 of the target adenine in the RNA substrate (A63). The structure of the ribozyme suggested a mechanism in which a cytosine (C10) acts as a general acid to protonate O6-alkylguanine N1. Here, we have analyzed the role of the C10 general acid and the A63 nucleophile by atomic mutagenesis and computation. C10 was substituted by n1c and n1c, c5n variants. The n1c variant has an elevated pKa (11.4 as the free nucleotide) and leads to a 104-fold lower activity that is pH-independent. Addition of the second c5n substitution with a lower pKa restored both the rate and pH dependence of alkyl transfer. Quantum mechanical calculations indicate that protonation of O6-alkylguanine lowers the barrier to alkyl transfer and that there is a significantly elevated barrier to proton transfer for the n1c single substitution. The calculated pKa values are in good agreement with the apparent values from measured rates. Increasing the pKa of the nucleophile by A63 n7c substitution led to a 6-fold higher rate. The increased reactivity of the nucleophile corresponds to a βnuc of ∼0.5, indicating significant C–N bond formation in the transition state. Taken together, these results are consistent with a two-step mechanism comprising protonation of the O6-alkylguanine followed by alkyl transfer.

  PublisherDOI

Recent grants

• The VS Ribozyme: Catalytic Mechanism, Transition State Structure, and Evolution

  NIH · $1.4M · 2019–2023

• Chaperone-Assisted RNA Crystallography

  NIH · $380k · 2013–2021

• NIH Grant R56AI081987

  NIH · $385k · 2010

• Chaperone-Assisted RNA Crystallography

  NIH · $2.5M · 2013–2022

• NIH Grant T32GM008720

  NIH · $4.0M · 2021

Frequent coauthors

• Nan‐Sheng Li

  University of Chicago

  111 shared

• Michael E. Harris

  University of Florida

  88 shared

• Darrin M. York

  Quantitative BioSciences

  79 shared

• Qing Dai

  76 shared

• K. Y. Wong

  Prince of Wales Hospital

  53 shared

• Steven A. Benner

  Foundation for Applied Molecular Evolution

  43 shared

• Daniel Herschlag

  40 shared

• Hong Gu

  Peking University

  39 shared

Labs

• Joseph A. Piccirilli LabPI