Biology subjects

Arhin, G.

Publications and source records attributed to Arhin, G..

5 recordsLinked to original sources

bioRxiv2026

Mechanism of molecular recognition revealed through dynamic drug binding pathways to SARS-CoV-2 main protease

Characterization of drug-binding pathways remains experimentally limited by transient intermediates and computationally challenging due to long timescales intractable for conventional molecular dynamics. To address these challenges, we combined solution NMR titrations with weighted ensemble (WE) enhanced sampling simulations to resolve atomistic pathways of nirmatrelvir binding to the SARS-CoV-2 main protease. NMR titration revealed residue-dependent heterogeneity spanning fast, intermediate, and slow exchange regimes. WE simulations complement the NMR by providing insights into unassigned residues and adding time-resolved and three-dimensional structural context. We map key interactions along two distinct binding pathways, provide dynamic explanations for residues involved in resistance, and capture unique backbone conformations compared to those sampled in unbound or bound states. Our comprehensive binding model is consistent with a combined conformational selection and induced fit mechanism in which early transient contacts are made with residues E47 and L50 and allosteric motions are centered around residue V204 of the distal domain. This synergistic application of WE and titration NMR enables a more comprehensive characterization of drug binding than either method alone, providing an integrated framework that may have broader applicability to defining structure-kinetic relationships and guiding design of next-generation inhibitors.

biophysics↗

bioRxiv2025

Integrated in silico and experimental screening identifies novel ligands that target precursor microRNA-31 at the Dicer cleavage site

MicroRNAs (miRNAs) regulate gene expression and the dysregulation in mature miRNA levels has been implicated in a wide variety of diseases. In particular, altered levels of mature microRNA-31 (miR-31) has been linked to a variety of different cancers. Targeting functionally relevant sites of the precursor structure of miR-31 with small molecules offer a strategy to regulate miR-31 maturation. Herein we describe a virtual screening approach to explore the druggability of the precursor structure of microRNA-31 (pre-miR-31). We used a structure-guided approach to virtually screen a fragment library and followed up with experimental characterization of top-ranking candidates, leading to the identification of several compounds that bound to pre-miR-31. Further characterization of the RNA-ligand complexes by heteronuclear single quantum coherence (HSQC) NMR spectroscopy revealed three compounds bound pre-miR-31 at the Dicer cleavage site, suggesting that these compounds may function to inhibit Dicer processing. Using these initial hits, we performed chemical structure similarity searches and identified additional binders of pre-miR-31 that had equivalent or enhanced binding relative to the parent compounds. These studies suggest a generalizable approach by which RNA-binding ligands can be identified from large chemical databases. These hits can then be further optimized to improve affinity and specificity for downstream functional assays.

biophysics↗

bioRxiv2025

In silico discovery of compounds targeting NPSL2: a regulatory element in the human oncomiR-1 primary microRNA.

NPSL2 is a stem loop element within the oncomiR-1 polycistronic primary microRNA (miRNA) cluster. NPSL2 is predicted to mediate conformational rearrangements within oncomiR-1 to regulate the biogenesis of certain miRNA elements within the cluster. The regulatory role of NPSL2 makes it a promising target for small molecule ligands, which we explored through structure-based small molecule ligand discovery. Starting with an NMR-derived ensemble of NPSL2 structures, we identified ligandable cavities within NPSL2 using RNACavityMiner. We then used molecular docking to screen the ZINC library against these cavities to identify potential small molecule hits. A sampling of commercially available compounds from the initial hits were purchased for experimental characterization by saturation transfer difference (STD) and heteronuclear single quantum coherence (HSQC) NMR spectroscopy. This approach led to the identification and characterization of at least eight compounds that bind preferentially within the internal loop of NPSL2. Importantly, this workflow, which combined virtual screening and experimental validation, can be used to identify small molecules that bind to any known RNA three-dimensional structure.

biophysics↗

bioRxiv2022

Using Unassigned NMR Chemical Shifts to Model RNA Secondary Structure

NMR-derived chemical shifts are sensitive probes of RNA structure. However, the need to assign NMR spectra hampers their utility as a direct source of structural information. In this report, we describe a simple method that uses unassigned 2D NMR spectra to model the secondary structure of RNAs. Similar to assigned chemical shifts, we could use unassigned chemical shift data to reweight conformational libraries such that the highest weighted structure closely resembles their reference NMR structure. Furthermore, the application of our approach to the 3- and 5-UTR of the SARS-CoV-2 genome yields structures that are, for the most part, consistent with the secondary structure models derived from chemical probing data. Therefore, we expect the framework we describe here will be useful as a general strategy for rapidly generating preliminary structural RNA models directly from unassigned 2D NMR spectra. As we demonstrated for the 337-nt and 472-nt UTRs of SARS-CoV-2, our approach could be especially valuable for modeling the secondary structures of large RNA.

biophysics↗

bioRxiv2021

NMR chemical shift assignments of RNA oligonucleotides to expand the RNA chemical shift database

RNAs play myriad functional and regulatory roles in the cell. Despite their significance, three-dimensional structure elucidation of RNA molecules lags significantly behind that of proteins. NMR-based studies are often rate-limited by the assignment of chemical shifts. Automation of the chemical shift assignment process can greatly facilitate structural studies, however, accurate chemical shift predictions rely on a robust and complete chemical shift database for training. We searched the Biological Magnetic Resonance Data Bank (BMRB) to identify sequences that had no (or limited) chemical shift information. Here, we report the chemical shift assignments for 12 RNA hairpins designed specifically to help populate the BMRB.

biophysics↗