Biology subjects

Bolotokova, A.

Publications and source records attributed to Bolotokova, A..

10 recordsLinked to original sources

bioRxiv2025

Identification and Characterization of a Small Molecule Ligand for the Huntingtin-HAP40 Complex

Huntingtons disease (HD) is caused by a CAG repeat expansion mutation, giving rise to a polyglutamine expansion in the huntingtin (HTT). However, the explicit molecular functions of HTT and opportunities for direct pharmacological modulation remain incompletely understood. Here, we report the discovery of a small molecule ligand for the full-length HTT protein in complex with its partner, HAP40. Using affinity selection mass spectrometry (AS-MS), we identified a stereoselective binder, whose binding was characterized by surface plasmon resonance, hydrogen-deuterium exchange mass spectrometry, and cryo-electron microscopy at 2.3 [A] resolution. The ligand binds HTT-HAP40 in vitro with single-digit micromolar affinity and one-to-one stoichiometry at a druggable interface previously predicted computationally. In silico studies predicted and experimental analyses confirmed the (R)-enantiomer as the eutomer and initial structure activity relationship was established experimentally. This work details a structurally-validated chemical scaffold and highlights a ligandable pocket which could enable development of chemical probes for probing HTT biology, as well as therapeutics such as degraders and imaging agents for HD.

pharmacology and toxicology↗

bioRxiv2025

Structure-based discovery of inhibitors of Mac1 domain of nonstructural protein-3 of SARS-CoV-2 by machine learning-augmented screening of chemical space

Significant efforts have been recently dedicated to the discovery of small molecule inhibitors against the Macrodomain 1 (Mac1) of nonstructural protein 3 (NSP3) as potential antivirals for SARS-CoV-2. Thus, Mac1 has also been selected as the target for the Critical Assessment of Hit-finding Experiments (CACHE) challenge #3. As contestants in that challenge, we developed a computational strategy that ranked on the top among all 23 participants in the competition and resulted in the discovery of a novel chemical series of non-charged Mac1 inhibitors. Those have been identified through the combination of machine learning-accelerated virtual screening of Enamine REAL Diversity Subset of approximately 25 million compounds and consequent hit expansion into the entire Enamine REAL Space library. In particular, the initially identified hit compound CACHE3-HI_1706_56 (KD = 20 {micro}M) was explored by probing 17 close analogues from a library of 44 billion molecules from the Enamine REAL. All those analogues effectively displaced the Mac1-binding ADP-ribose peptide, and 12 were confirmed to engage with Mac1 by the Surface Plasmon Resonance experiments, revealing a new chemical series of compounds for hit-to-lead optimization. The structure of the CACHE3-HI_1706_56-Mac1 complex was further determined at high resolution with crystallography, confirming initial computational predictions. Our results illustrate the effectiveness of ML-accelerated docking to rapidly identify novel chemical series and provide a strong foundation for the development of SARS-CoV-2 NSP3 Mac1 inhibitors.

biophysics↗

bioRxiv2025

Enantioselective Protein Affinity Selection Mass Spectrometry (EAS-MS)

We report an enantioselective protein affinity selection mass spectrometry screening approach (E-ASMS) that enables the detection of weak binders, informs on selectivity, and generates orthogonal confirmation of binding. After method development with control proteins, we screened 31 human proteins against a designed library of 8,210 chiral compounds. 16 binders to 12 targets, including many proteins predicted to be "challenging to ligand", were discovered and confirmed in orthogonal biophysical assays. 7 binders to 6 targets bound in an enantioselective manner, with KD values ranging from 3 to 20 {micro}M. Binders for four targets (DDB1, WDR91, WDR55, and HAT1) were selected for in-depth characterization using X-ray crystallography. In all four cases, the mechanism for enantioselectivity was readily explained. We conclude E-ASMS can be used to identify and characterize selective and weakly-binding ligands for novel protein targets with unprecedented throughput and sensitivity.

pharmacology and toxicology↗

bioRxiv2024

CACHE Challenge #1: targeting the WDR domain of LRRK2, a Parkinson's Disease associated protein.

The CACHE challenges are a series of prospective benchmarking exercises meant to evaluate progress in the field of computational hit-finding. Here we report the results of the inaugural CACHE #1 challenge in which 23 computational teams each selected up to 100 commercially available compounds that they predicted would bind to the WDR domain of the Parkinsons disease target LRRK2, a domain with no known ligand and only an apo structure in the PDB. The lack of known binding data and presumably low druggability of the target is a challenge to computational hit finding methods. Seventy-three of the 1955 procured molecules bound LRRK2 in an SPR assay with KD lower than 150 M and were advanced to a hit expansion phase where computational teams each selected up to 50 analogs each. Binding was observed in two orthogonal assays with affinities ranging from 18 to 140 M for seven chemically diverse series. The seven successful computational workflows varied in their screening strategies and techniques. Three used molecular dynamics to produce a conformational ensemble of the targeted site, three included a fragment docking step, three implemented a generative design strategy and five used one or more deep learning steps. CACHE #1 reflects a highly exploratory phase in computational drug design where participants sometimes adopted strikingly diverging screening strategies. Machine-learning accelerated methods achieved similar results to brute force (e.g. exhaustive) docking. First-in-class, experimentally confirmed compounds were rare and weakly potent, indicating that recent advances are not sufficient to effectively address challenging targets.

biochemistry↗

bioRxiv2024

A resource to enable chemical biology and drug discovery of WDR Proteins

Protein class-focused drug discovery has a long and successful history in pharmaceutical research, yet most members of druggable protein families remain unliganded, often for practical reasons. Here we combined experiment and computation to enable discovery of ligands for WD40 repeat (WDR) proteins, one of the largest human protein families. This resource includes expression clones, purification protocols, and a comprehensive assessment of the druggability for hundreds of WDR proteins. We solved 21 high resolution crystal structures, and have made available a suite of biophysical, biochemical, and cellular assays to facilitate the discovery and characterization of small molecule ligands. To this end, we use the resource in a hit-finding pilot involving DNA-encoded library (DEL) selection followed by machine learning (ML). This led to the discovery of first-in-class, drug-like ligands for 9 of 20 targets. This result demonstrates the broad ligandability of WDRs. This extensive resource of reagents and knowledge will enable further discovery of chemical tools and potential therapeutics for this important class of proteins.

biochemistry↗

bioRxiv2023

Discovery of a first-in-class small molecule ligand for WDR91 using DNA-encoded chemical library selection followed by machine learning

WD40 repeat-containing protein 91 regulates endosomal phosphatidylinositol 3-phosphate levels at the critical stage of endosome maturation and plays vital roles in endosome fusion, recycling, and transport by mediating protein-protein interactions. Due to its various roles in endocytic pathways, WDR91 has recently been identified as a potential host factor responsible for viral infection. We employed DNA-Encoded Chemical Library (DEL) selection against the WDR domain of WDR91, followed by machine learning to generate a model that was then used to predict ligands from the synthetically accessible Enamine REAL database. Screening of predicted compounds enabled us to identify the hit compound 1, which binds selectively to WDR91 with a KD of 6 {+/-} 2 M by surface plasmon resonance. The co-crystal structure confirmed the binding of 1 to the WDR91 side pocket, in proximity to cysteine 487. Machine learning-assisted structure activity relationship-by-catalog validated the chemotype of 1 and led to the discovery of covalent analogs 18 and 19. Intact mass LC-MS and differential scanning fluorimetry confirmed the formation of a covalent adduct, and thermal stabilization, respectively. The discovery of 1, 18, 19, accompanying SAR, and co-crystal structures will provide valuable insights for designing more potent and selective compounds against WDR91, thus accelerating the development of novel chemical tools to evaluate the therapeutic potential of WDR91 in disease.

molecular biology↗

bioRxiv2021

Pharmacological targeting of a PWWP domain demonstrates cooperative control of NSD2 localization

NSD2 is the primary enzyme responsible for the dimethylation of lysine 36 of histone 3 (H3K36me2), a mark associated with active gene transcription and intergenic DNA methylation. In addition to a methyltransferase domain, NSD2 harbors two PWWP and five PHD domains believed to serve as chromatin reading modules, but their exact function in the regulation of NSD2 activity remains underexplored. Here we report a first-in-class chemical probe targeting the N-terminal PWWP (PWWP1) domain of NSD2. UNC6934 binds potently (Kd of 91 {+/-} 8 nM) to PWWP1, antagonizes its interaction with nucleosomal H3K36me2, and selectively engages endogenous NSD2 in cells. Crystal structures show that UNC6934 occupies the canonical H3K36me2-binding pocket of PWWP1 which is juxtaposed to the DNA-binding surface. In cells, UNC6934 induces accumulation of endogenous NSD2 in the nucleolus, phenocopying the localization defects of NSD2 protein isoforms lacking PWWP1 as a result of translocations prevalent in multiple myeloma. Mutation of other NSD2 chromatin reader domains also increases NSD2 nucleolar localization, and enhances the effect of UNC6934. Finally we identified two C-terminal nucleolar localization sequences in NSD2 that appear to drive nucleolar accumulation when one or more chromatin reader domains are disabled. These data support a model in which NSD2 chromatin engagement is achieved in a cooperative manner and subcellular localization is controlled by multiple competitive structural determinants. This chemical probe and the accompanying negative control, UNC7145, will be useful tools in defining NSD2 biology.

cell biology↗

bioRxiv2021

Probing the SAM Binding Site of SARS-CoV-2 nsp14 in vitro Using SAM Competitive Inhibitors Guides Developing Selective bi-substrate Inhibitors

The COVID-19 pandemic has clearly brought the healthcare systems world-wide to a breaking point along with devastating socioeconomic consequences. The SARS-CoV-2 virus which causes the disease uses RNA capping to evade the human immune system. Non-structural protein (nsp) 14 is one of the 16 nsps in SARS-CoV-2 and catalyzes the methylation of the viral RNA at N7-guanosine in the cap formation process. To discover small molecule inhibitors of nsp14 methyltransferase (MT) activity, we developed and employed a radiometric MT assay to screen a library of 161 in house synthesized S-adenosylmethionine (SAM) competitive methyltransferase inhibitors and SAM analogs. Among seven identified screening hits, SS148 inhibited nsp14 MT activity with an IC50 value of 70 {+/-} 6 nM and was selective against 20 human protein lysine methyltransferases indicating significant differences in SAM binding sites. Interestingly, DS0464 with IC50 value of 1.1 {+/-} 0.2 M showed a bi-substrate competitive inhibitor mechanism of action. Modeling the binding of this compound to nsp14 suggests that the terminal phenyl group extends into the RNA binding site. DS0464 was also selective against 28 out of 33 RNA, DNA, and protein methyltransferases. The structure-activity relationship provided by these compounds should guide the optimization of selective bi-substrate nsp14 inhibitors and may provide a path towards a novel class of antivirals against COVID-19, and possibly other coronaviruses.

biochemistry↗

bioRxiv2021

A high-throughput radioactivity-based assay for screening SARS-CoV-2 nsp10-nsp16 complex

Frequent outbreaks of novel coronaviruses (CoVs), highlighted by the current SARS-CoV-2 pandemic, necessitate the development of therapeutics that could be easily and effectively administered world-wide. The conserved mRNA-capping process enables CoVs to evade their host immune system and is a target for antiviral development. Nonstructural protein (nsp) 16 in complex with nsp10 catalyzes the final step of coronaviral mRNA-capping through its 2-O-methylation activity. Like other methyltransferases, SARS-CoV-2 nsp10-nsp16 complex is druggable. However, the availability of an optimized assay for high-throughput screening (HTS) is an unmet need. Here, we report the development of a radioactivity-based assay for methyltransferase activity of nsp10-nsp16 complex in a 384-well format, and kinetic characterization, and optimization of the assay for HTS (Z'-factor: 0.83). Considering the high conservation of nsp16 across known CoV species, the potential inhibitors targeting SARS-CoV-2 nsp10-nsp16 complex may also be effective against other emerging pathogenic CoVs.

biochemistry↗

bioRxiv2020

A high throughput RNA displacement assay for screening SARS-CoV-2 nsp10-nsp16 complex towards developing therapeutics for COVID-19

SARS-CoV-2, the coronavirus that causes COVID-19, evades the human immune system by capping its RNA. This process protects the viral RNA and is essential for its replication. Multiple viral proteins are involved in this RNA capping process including the nonstructural protein 16 (nsp16) which is an S-adenosyl-L-methionine (SAM)-dependent 2-O-methyltransferase. Nsp16 is significantly active when in complex with another nonstructural protein, nsp10, which plays a key role in its stability and activity. Here we report the development of a fluorescence polarization (FP)-based RNA displacement assay for nsp10-nsp16 complex in 384-well format with a Z'-Factor of 0.6, suitable for high throughput screening. In this process, we purified the nsp10-nsp16 complex to higher than 95% purity and confirmed its binding to the methyl donor SAM, product of the reaction, SAH, and a common methyltransferase inhibitor, sinefungin using Isothermal Titration Calorimetry (ITC). The assay was further validated by screening a library of 1124 drug-like compounds. This assay provides a cost-effective high throughput method for screening nsp10-nsp16 complex for RNA-competitive inhibitors towards developing COVID-19 therapeutics.

biochemistry↗