Web-based platform for analysis of RNA folding from high throughput chemical probing data

RNA structures play critical roles in regulating gene expression across all domains of life and viruses. Chemical probing methods coupled with massively parallel sequencing have revolutionized the RNA structure field by enabling the assessment of many structures in their native, physiological context. Previously, we developed Dimethyl-Sulfate-based Mutational Profiling and Sequencing (DMS-MaPseq), which uses DMS to label the Watson-Crick face of open and accessible adenine and cytosine bases in the RNA. We used this approach to determine the genome-wide structures of HIV-1 and SARS-CoV-2 in infected cells, which permitted uncovering new biology and identifying therapeutic targets. Due to the simplicity and ease of the experimental procedure, DMS-MaPseq has been adopted by labs worldwide. However, bioinformatic analysis remains a substantial hurdle for labs that often lack the necessary infrastructure and computational expertise. Here we present a modern web-based interface that automates the analysis of chemical probing profiles from raw sequencing files (http://rnadreem.org). The availability of a simple web-based platform for DMSMaPseq analysis will dramatically expand studies of RNA structure and aid in the design of structurebased therapeutics

Assessing the quality of absolute hydration free energies among CHARMM‐compatible ligand parameterization schemes

Multipurpose atom‐typer for CHARMM (MATCH), an atom‐typing toolset for molecular mechanics force fields, was recently developed in our laboratory. Here, we assess the ability of MATCH‐generated parameters and partial atomic charges to reproduce experimental absolute hydration free energies for a series of 457 small neutral molecules in GBMV2, Generalized Born with a smooth SWitching (GBSW), and fast analytical continuum treatment of solvation (FACTS) implicit solvent models. The quality of hydration free energies associated with small molecule parameters obtained from ParamChem, SwissParam, and Antechamber are compared. Given optimized surface tension coefficients for scaling the surface area term in the nonpolar contribution, these automated parameterization schemes with GBMV2 and GBSW demonstrate reasonable agreement with experimental hydration free energies (average unsigned errors of 0.9–1.5 kcal/mol and R 2 of 0.63–0.87). GBMV2 and GBSW consistently provide slightly more accurate estimates than FACTS, whereas Antechamber parameters yield marginally more accurate estimates than the current generation of MATCH, ParamChem, and SwissParam parameterization strategies. Modeling with MATCH libraries that are derived from different CHARMM topology and parameter files highlights the importance of having sufficient coverage of chemical space within the underlying databases of these automated schemes and the benefit of targeting specific functional groups for parameterization efforts to maximize both the breadth and the depth of the parameterized space. © 2013 Wiley Periodicals, Inc. Ligand parameterization for molecular mechanics simulations is computationally intensive, requiring long multistep optimization procedures. Recently there has been an influx of automated parameterization tools for the CHARMM force field. These tools radically speed up the process, but it remains unclear whether accuracy is sacrificed to a significant extent. The research presented in this article uses a set of 457 small molecules to quantify the accuracy of four automated parameterization tools by computing absolute hydration free energies.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/97284/1/23199_ftp.pd

Development of Methods for the Investigation of RNA-Ligand Interactions.

Three critical features of RNA make it a unique challenge for drug discovery: a) it is highly negatively charged, increasing non-specific binding, b) it can be highly dynamic, adopting different conformations upon binding varying ligands, and c) it has solvent exposed shallow binding pockets. All these properties represent distinct problems in the advancement of RNA-drug discovery. To address this first problem, MATCH was developed to rapidly, accurately, and universally parameterize small molecules for docking. MATCH accomplishes this by deconstructing a force field into a set of fundamental rules which best replicates existing parameters and permits extension to new molecules. MATCH is not only necessary to study RNA-ligand interactions en masse but will also contribute to understanding the charge-charge consequences of ligand binding. To address RNA flexibility, a method to combine NMR chemical shifts and Molecular Dynamics (MD) was developed to generate dynamic ensembles. To benchmark this technique, a set of 26 RNA structures with experimentally determined chemical shift was selected. An ensemble of structures was optimized to match the chemical shifts of each system. These ensembles were also shown to be consistent with of NMR NOE and RDCs constraints. To further demonstrate the utility of this method a large pool of structures (~350,000) was used to generate an ensemble for a prominent RNA target – the ribosomal decoding site. The conformations within this ensemble were found on favorable areas of the free energy landscape, independently indicating the validity of these structures. Finally to address the solvent exposed binding pocket of RNA and its flexible ligands, a new docking approach for RNA was developed, which performs an enhanced sampling technique by fragmenting the ligand and independently optimizing the conformation of each fragment. To properly benchmark this novel algorithm, a large set of 230 nucleic acid-ligand complexes was compiled. Utilizing this large set of this enhanced sampling technique was compared to ICM – a leading docking program. ICM produced native-like conformations 45% of the time, while our approach yields native-like conformations 55% of the time. Demonstrating the effectiveness of this novel sampling procedure.PHDBiophysicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/102297/1/jyesselm_1.pd

Predicting extreme p K a shifts in staphylococcal nuclease mutants with constant pH molecular dynamics

Accurate computational methods of determining protein and nucleic acid p K a values are vital to understanding pH‐dependent processes in biological systems. In this article, we use the recently developed method constant pH molecular dynamics (CPHMD) to explore the calculation of highly perturbed p K a values in variants of staphylococcal nuclease (SNase). Simulations were performed using the replica exchange (REX) protocol for improved conformational sampling with eight temperature windows, and yielded converged proton populations in a total sampling time of 4 ns. Our REX‐CPHMD simulations resulted in calculated p K a values with an average unsigned error (AUE) of 0.75 pK units for the acidic residues in Δ + PHS, a hyperstable variant of SNase. For highly p K a ‐perturbed SNase mutants with known crystal structures, our calculations yielded an AUE of 1.5 pK units and for those mutants based on modeled structures an AUE of 1.4 pK units was found. Although a systematic underestimate of pK shifts was observed in most of the cases for the highly perturbed pK mutants, correlations between conformational rearrangement and plasticity associated with the mutation and error in p K a prediction was not evident in the data. This study further extends the scope of electrostatic environments explored using the REX‐CPHMD methodology and suggests that it is a reliable tool for rapidly characterizing ionizable amino acids within proteins even when modeled structures are employed. Proteins 2011; © 2011 Wiley‐Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/88038/1/23195_ftp.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/88038/2/PROT_23195_sm_SuppInfo.pd

Structural conservation in the template/pseudoknot domain of vertebrate telomerase RNA from teleost fish to human

Telomerase synthesizes the telomeric DNA at the 3′ ends of chromosomes and maintains genome integrity. Telomerase RNA (TR) provides the template for telomere-repeat synthesis within a template/pseudoknot (t/PK) domain that is essential for activity. We investigated the structure and dynamics of the t/PK from medaka fish, which contain the smallest vertebrate TR, using NMR and modeling. Despite differences in length, sequence, and predicted secondary structure with human TR, the remarkable similarities between subdomains, including one newly identified in medaka, reveal a conserved architecture for vertebrate t/PK. Combining our model of the full-length pseudoknot and information from the 9-Å structure of Tetrahymena telomerase, we propose models for the interaction of medaka and human t/PK with telomerase reverse transcriptase, providing insight into function

Frequent side chain methyl carbon‐oxygen hydrogen bonding in proteins revealed by computational and stereochemical analysis of neutron structures

The propensity of backbone Cα atoms to engage in carbon‐oxygen (CH···O) hydrogen bonding is well‐appreciated in protein structure, but side chain CH···O hydrogen bonding remains largely uncharacterized. The extent to which side chain methyl groups in proteins participate in CH···O hydrogen bonding is examined through a survey of neutron crystal structures, quantum chemistry calculations, and molecular dynamics simulations. Using these approaches, methyl groups were observed to form stabilizing CH···O hydrogen bonds within protein structure that are maintained through protein dynamics and participate in correlated motion. Collectively, these findings illustrate that side chain methyl CH···O hydrogen bonding contributes to the energetics of protein structure and folding. Proteins 2015; 83:403–410. © 2014 Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/110709/1/prot24724-sup-0001-suppinfo01.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/110709/2/prot24724.pd

Chemical reversible crosslinking enables measurement of RNA 3D distances and alternative conformations in cells

Three-dimensional (3D) structures dictate the functions of RNA molecules in a wide variety of biological processes. However, direct determination of RNA 3D structures in vivo is difficult due to their large sizes, conformational heterogeneity, and dynamics. Here we present a method, Spatial 2′-Hydroxyl Acylation Reversible Crosslinking (SHARC), which uses chemical crosslinkers of defined lengths to measure distances between nucleotides in cellular RNA. Integrating crosslinking, exonuclease (exo) trimming, proximity ligation, and high throughput sequencing, SHARC enables transcriptome-wide tertiary structure contact maps at high accuracy and precision, revealing heterogeneous RNA structures and interactions. SHARC data provide constraints that improves Rosetta-based RNA 3D structure modeling at near-nanometer resolution. Integrating SHARC-exo with other crosslinking-based methods, we discover compact folding of the 7SK RNA, a critical regulator of transcriptional elongation. These results establish a strategy for measuring RNA 3D distances and alternative conformations in their native cellular context

Rapid and accurate determination of atomistic RNA dynamic ensemble models using NMR and structure prediction

Biomolecules form dynamic ensembles of many inter-converting conformations which are key for understanding how they fold and function. However, determining ensembles is challenging because the information required to specify atomic structures for thousands of conformations far exceeds that of experimental measurements. We addressed this data gap and dramatically simplified and accelerated RNA ensemble determination by using structure prediction tools that leverage the growing database of RNA structures to generate a con- formation library. Refinement of this library with NMR residual dipolar couplings provided an atomistic ensemble model for HIV-1 TAR, and the model accuracy was independently sup- ported by comparisons to quantum-mechanical calculations of NMR chemical shifts, com- parison to a crystal structure of a substate, and through designed ensemble redistribution via atomic mutagenesis. Applications to TAR bulge variants and more complex tertiary RNAs support the generality of this approach and the potential to make the determination of atomic-resolution RNA ensembles routine

Amilorides inhibit SARS-CoV-2 replication in vitro by targeting RNA structures

The SARS-CoV-2 pandemic, and the likelihood of future coronavirus pandemics, emphasized the urgent need for development of novel antivirals. Small-molecule chemical probes offer both to reveal aspects of virus replication and to serve as leads for antiviral therapeutic development. Here, we report on the identification of amiloride-based small molecules that potently inhibit OC43 and SARS-CoV-2 replication through targeting of conserved structured elements within the viral 5′-end. Nuclear magnetic resonance–based structural studies revealed specific amiloride interactions with stem loops containing bulge like structures and were predicted to be strongly bound by the lead amilorides in retrospective docking studies. Amilorides represent the first antiviral small molecules that target RNA structures within the 5′ untranslated regions and proximal region of the CoV genomes. These molecules will serve as chemical probes to further understand CoV RNA biology and can pave the way for the development of specific CoV RNA–targeted antivirals