Biology subjects

Schneekloth, J. S.

Publications and source records attributed to Schneekloth, J. S..

4 recordsLinked to original sources

bioRxiv2022

Machine Learning Informs RNA-Binding Chemical Space

Small molecule targeting of RNA has emerged as a new frontier in medicinal chemistry, but compared to the protein targeting literature our understanding of chemical matter that binds to RNA is limited. In this study, we report Repository Of BInders to Nucleic acids (ROBIN), a new library of nucleic acid binders identified by small molecule microarray (SMM) screening. The complete results of 36 individual nucleic acid SMM screens against a library of 24,572 small molecules are reported (including a total of 1,627,072 interactions assayed). A set of 2,003 RNA-binding small molecules is identified, representing the largest fully public, experimentally derived library of its kind to date. Machine learning is used to develop highly predictive and interpretable models to characterize RNA-binding molecules. This work demonstrates that machine learning algorithms applied to experimentally derived sets of RNA binders are a powerful method to inform RNA-targeted chemical space.

biochemistry↗

bioRxiv2022

Investigating the NRAS 5' UTR as a Target for Small Molecules

Neuroblastoma RAS (NRAS) is an oncogene that is deregulated and highly mutated in cancers including melanomas and acute myeloid leukemias. Constitutively activated NRAS induces the MAPK and AKT signaling pathways and leads to uncontrolled proliferation and cell growth, making it an attractive target for small molecule inhibition. Like all RAS-family proteins, it has proven difficult to identify small molecules that directly inhibit the protein. An alternative approach would involve targeting the NRAS mRNA. The 5' untranslated region (5' UTR) of the NRAS mRNA is reported to contain a G-quadruplex (G4) that regulates translation of NRAS mRNA. Stabilizing the G4 structure with small molecules could reduce NRAS protein expression in cancer cells by impacting translation. Here we report a novel class of small molecule that binds to the G4 structure located in the 5' UTR of the NRAS mRNA. We used a small molecule microarray (SMM) screen to identify molecules that selectively bind to the NRAS-G4. Biophysical studies demonstrated that compound 18 binds reversibly to the NRAS-G4 structure with submicromolar affinity. A Luciferase based reporter assay indicated that 18 inhibits the translation of NRAS via stabilizing the NRAS-G4 in vitro but showed only moderate effects on the NRAS levels in cellulo. Rapid Amplification of cDNA Ends (RACE), RT-PCR analysis on 14 different NRAS-expressing cell lines, coupled with analysis of publicly available CAGE seq experiments, revealed that predominant NRAS transcript does not possess the G4 structure. Further analysis of published rG4 and G4 sequencing data indicated the presence of G4 structure in the promoter region of NRAS gene (DNA) but not in the mRNA. Thus, although many NRAS transcripts lack a G4 in many cell lines the broader concept of targeting folded regions within 5 UTRs to control translation remains a highly attractive strategy and this work represents an intriguing example of transcript heterogeneity impacting targetability.

biochemistry↗

bioRxiv2021

Interrogating RNA-small molecule interactions with structure probing and AI augmented-molecular simulations

While there is increasing interest in the study of RNA as a therapeutic target, efforts to understand RNA-ligand recognition at the molecular level lag far behind our understanding of protein-ligand recognition. This problem is complicated due to the more than ten orders of magnitude in timescales involved in RNA dynamics and ligand binding events, making it not straightforward to design experiments or simulations. Here we make use of artificial intelligence (AI)-augmented molecular dynamics simulations to directly observe ligand dissociation for cognate and synthetic ligands from a riboswitch system. The site-specific flexibility profiles from our simulations are compared with in vitro measurements of flexibility using Selective 2 Hydroxyl Acylation analyzed by Primer Extension and Mutational Profiling (SHAPE-MaP). Our simulations reproduce known relative binding affinities for the cognate and synthetic ligands, and pinpoint how both ligands make use of different aspects of riboswitch flexibility. On the basis of our dissociation trajectories, we also make and validate predictions of pairs of mutations for both the ligand systems that would show differing binding affinities. These mutations are distal to the binding site and could not have been predicted solely on the basis of structure. The methodology demonstrated here shows how molecular dynamics simulations with all-atom force-fields have now come of age in making predictions that complement existing experimental techniques and illuminate aspects of systems otherwise not trivial to understand.

biophysics↗

bioRxiv2021

Dysregulation of Hepatitis B Virus Nucleocapsid Assembly with RNA-directed Small Ligands

RNA sequences/motifs dispersed across the pre-genomic copy of the Hepatitis B Virus genome regulate formation of nucleocapsids in vitro in an epsilon/polymerase independent fashion. These multiple RNA Packaging Signals (PSs) form stem-loops presenting in each loop a core protein recognition motif, -RGAG-. Small, drug-like molecules binding these motifs were identified by screening an immobilized library with a fluorescently-labelled RNA oligonucleotide encompassing the most conserved of these sites. This identified 66 "hits", with affinities ranging from low nanomolar to high micromolar in SPR assays. High affinity ligand binding is dependent on the presence of the -RGAG-motif, which also appears to be the common element in cross-binding to other PS sites. Some of these compounds are potent inhibitors of in vitro core protein assembly around the HBV pre-genome. Mathematical modelling confirms the potential of these novel anti-viral drug targets for disrupting replication of this major human pathogen. Preliminary structure-activity relationships of the highest affinity compound reveal critical functional groups for PS-binding. PS-regulated assembly is easily adapted to high-throughput screening allowing future development of pharmacologically active compounds.

microbiology↗