Biology subjects

Szulc, N. A.

Publications and source records attributed to Szulc, N. A..

7 recordsLinked to original sources

bioRxiv2023

Lysine-deficient proteome can be regulated through non-canonical ubiquitination and ubiquitin-independent proteasomal degradation

The ubiquitin-proteasome system (UPS) removes damaged and unwanted proteins by attaching ubiquitin to lysines in a process termed ubiquitination. Little is known how functional components of the UPS, often exposed to erroneous labeling by ubiquitin during functioning, avoid premature proteolysis. An extensive lysine-less region (lysine desert) in the yeast E3 ligase Slx5 was shown to counteract its ubiquitin-dependent turnover. We conducted bioinformatic screens among prokaryotes and eukaryotes to describe the scope and conservation of this phenomenon. We found that lysine deserts are widespread among bacteria using pupylation-dependent proteasomal degradation, an analog of the UPS. In eukaryotes, lysine deserts appear with increasing organismal complexity, and the most evolutionarily conserved are enriched in the UPS members. Using VHL and SOCS1 E3 ligases, which elongate their lysine desert in the course of evolution, we established that they are non-lysine ubiquitinated, which does not influence their stability, and can be subject to proteasome turnover irrespective of ubiquitination. Our data suggest that a combination of non-lysine ubiquitination and ubiquitin-independent degradation may control the function and fate of the lysine-deficient proteome, as the presence of lysine deserts does not correlate with the half-life.

molecular biology↗

bioRxiv2023

Structural Interaction Fingerprints and Machine Learning for predicting and explaining binding of small molecule ligands to RNA

Ribonucleic acids (RNA) play crucial roles in living organisms as they are involved in key processes necessary for proper cell functioning. Some RNA molecules, such as bacterial ribosomes and precursor messenger RNA, are targets of small molecule drugs, while others, e.g., bacterial riboswitches or viral RNA motifs are considered as potential therapeutic targets. Thus, the continuous discovery of new functional RNA increases the demand for developing compounds targeting them and for methods for analyzing RNA--small molecule interactions. We recently developed fingeRNAt - a software for detecting non-covalent bonds formed within complexes of nucleic acids with different types of ligands. The program detects several non-covalent interactions, such as hydrogen and halogen bonds, ionic, Pi, inorganic ion-and water-mediated, lipophilic interactions, and encodes them as computational-friendly Structural Interaction Fingerprint (SIFt). Here we present the application of SIFts accompanied by machine learning methods for binding prediction of small molecules to RNA targets. We show that SIFt-based models outperform the classic, general-purpose scoring functions in virtual screening. We discuss the aid offered by Explainable Artificial Intelligence in the analysis of the binding prediction models, elucidating the decision-making process, and deciphering molecular recognition processes. Key PointsO_LIStructural Interaction fingerprints (SIFts), combined with machine learning, were successfully used to develop activity models for ligands binding to RNA. C_LIO_LISIFt-based models outperformed the classic, general-purpose scoring functions in virtual screening. C_LIO_LIExplainable Artificial Intelligence allowed us to understand the decision-making process and decipher molecular recognition processes in the analysis of RNA--ligand binding activity models. C_LIO_LIWe provide a benchmark dataset based on ligands with known or putative binding activity toward six RNA targets. It can be readily used by the scientific community to test new algorithms of virtual screening on RNA--ligand complexes. C_LI

bioinformatics↗

bioRxiv2022

DEGRONOPEDIA - a web server for proteome-wide inspection of degrons

The ubiquitin-proteasome system is a proteolytic pathway that removes damaged and unwanted proteins. Their selective turnover is initiated by ubiquitin (Ub) attachment, mainly by Ub ligases that recognize substrates through their short linear motifs termed degrons. A degradation-targeting degron comprises a nearby Ub-modified residue and an intrinsically disordered region (IDR) involved in interaction with the proteasome. Degron-signaling has been studied over the last decades, yet there are no resources for systematic screening of degron sites to facilitate studies on their biological significance, such as targeted protein degradation approaches. To bridge this gap, we developed DEGRONOPEDIA, a web server that allows exploration of degron motifs in the proteomes of seven model organisms and maps these data to Lys, Cys, Thr, and Ser residues that can undergo ubiquitination and to IDRs proximal to them, both in sequence and structure. The server also reports the post-translational modifications and pathogenic mutations within the degron and its flanking regions, as these can modulate the degrons accessibility. Degrons often occur at the amino or carboxyl end of a protein substrate, acting as initiators of the N-/C-degron pathway, respectively. Therefore, since they may appear following the protease cleavage, DEGRONOPEDIA simulate sequence nicking based on experimental data and theoretical predictions and screen for emerging degron motifs. Moreover, we implemented machine learning to predict the stability of the N-/C-termini, facilitating the identification of substrates of the N-/C-degron pathways. We are confident that our tool will stimulate research on degron-signaling providing output information in a ready-to-validate context. DEGRONOPEDIA can be freely accessed at degronopedia.com.

bioinformatics↗

bioRxiv2022

CHIP ubiquitin ligase is involved in the nucleolar stress management

The nucleolus is a dynamic nuclear biomolecular condensate involved in cellular stress response. Under proteotoxic stress, the nucleolus can store damaged proteins for refolding or degradation. HSP70 chaperone is a well-documented player in the recovery process of proteins accumulated in the nucleolus after heat shock. However, little is known about the involvement of the ubiquitin-proteasome system in the turnover of its nucleolar clients. Here we show that HSP70, independently of its ATPase activity, promotes migration of the CHIP (carboxyl terminus of HSC70-interacting protein) ubiquitin ligase into the granular component of the nucleolus, specifically after heat stress. We show that while in the nucleolus, CHIP retains mobility that depends on its ubiquitination activity. Furthermore, after prolonged exposure to heat stress, CHIP self-organizes into large, intra-nucleolar droplet-like structures whose size is determined by CHIP ubiquitination capacity. Using a heat-sensitive nucleolar protein luciferase, we show that excess CHIP impairs its regeneration, probably through deregulation of HSP70. Our results demonstrate a novel role for CHIP in managing nucleolar proteostasis in response to stress.

cell biology↗

bioRxiv2022

A novel de novo FEM1C variant as a potential cause of neurodevelopmental disorder with absent speech, pyramidal signs, and limb ataxia.

The principal component of the protein homeostasis network is the ubiquitin-proteasome system. Ubiquitination is mediated by an enzymatic cascade involving, i.e., E3 ubiquitin ligases, many of which belong to the cullin-RING ligases family. Genetic defects in the ubiquitin-proteasome system components, including cullin-RING ligases, are known causes of neurodevelopmental disorders. Using exome sequencing to diagnose a pediatric patient with developmental delay, pyramidal signs, and limb ataxia, we identified a de novo missense variant c.376G>C; p.(Asp126His) in the FEM1C gene encoding a cullin-RING ligase substrate receptor. This variant alters a conserved amino acid located within a highly constrained coding region and is predicted as pathogenic by most in silico tools. In addition, a de novo FEM1C mutation of the same residue p.(Asp126Val) was associated with an undiagnosed developmental disorder, and the relevant variant (FEM1CAsp126Ala) was found to be functionally compromised in vitro. Our computational analysis showed that FEM1CAsp126His hampers protein substrate binding. To further assess its pathogenicity, we used the nematode Caenorhabditis elegans. We found that the FEM-1Asp133His animals (expressing variant homologous to the FEM1C p.(Asp126Val)) had normal muscle architecture yet impaired mobility. Mutant worms were sensitive to the acetylcholinesterase inhibitor aldicarb but not levamisole (acetylcholine receptor agonist), showing that their disabled locomotion is caused by synaptic abnormalities and not muscle dysfunction. In conclusion, we provide the first evidence from an animal model suggesting that a mutation in the evolutionarily conserved FEM1C Asp126 position causes a neurodevelopmental disorder in humans.

genetics↗

bioRxiv2021

fingeRNAt - a novel tool for high-throughput analysis of nucleic acid-ligand interactions

Computational methods play a pivotal role in drug discovery and are widely applied in virtual screening, structure optimization, and compound activity profiling. Over the last decades, almost all the attention in medicinal chemistry has been directed to protein-ligand binding, and computational tools have been created with this target in mind. With novel discoveries of functional RNAs and their possible applications, RNAs have gained considerable attention as potential drug targets. However, the availability of bioinformatics tools for nucleic acids is limited. Here, we introduce fingeRNAt - a software tool for detecting non-covalent interactions formed in complexes of nucleic acids with ligands. The program detects nine types of interactions: (i) hydrogen and (ii) halogen bonds, (iii) cation-anion, (iv) pi-cation, (v) pi-anion, (vi) pi-stacking, (vii) inorganic ion-mediated, (viii) water-mediated, and (ix) lipophilic interactions. However, the scope of detected interactions can be easily expanded using a simple plugin system. In addition, detected interactions can be visualized using the associated PyMOL plugin, which facilitates the analysis of medium-throughput molecular complexes. Interactions are also encoded and stored as a bioinformatics-friendly Structural Interaction Fingerprint (SIFt) - a binary string where the respective bit in the fingerprint is set to 1 if a particular interaction is present and to 0 otherwise. This output format, in turn, enables high-throughput analysis of interaction data using data analysis techniques. We present applications of fingeRNAt-generated interaction fingerprints for visual and computational analysis of RNA-ligand complexes, including analysis of interactions formed in experimentally determined RNA-small molecule ligand complexes deposited in the Protein Data Bank. We propose interaction-based similarity based on fingerprints as an alternative measure to RMSD to recapitulate complexes with similar interactions but different folding. We present an application of molecular fingerprints for the clustering of molecular complexes. This approach can be used to group ligands that form similar binding networks and thus have similar biological properties. AUTHOR SUMMARYWe present a novel bioinformatic tool, fingeRNAt, aiming to support scientists in the analysis of complexes of nucleic acids with various types of ligands. The software automatically detects non-covalent interactions and presents them in a form that is understandable to both humans and computers. Such data can help decipher the nature of interactions between nucleic acids and ligands and determine the main factors responsible for forming such complexes in nature. fingeRNAt finds application in multiple studies, both structure- and drug discovery-oriented. Here, we analyzed the experimentally solved structures of RNA complexes with small molecules to determine which binding features are most prevalent, i.e., most common interactions or their hot spots. The results of this analysis may help elucidate the mechanisms of binding and design new active molecules. Moreover, we propose to use the data generated by our software as a new metric for the quantitative comparison of two molecule complexes. We have shown that it is more reliable than the currently used methods in certain "difficult" cases. We have shown that the results of our program can be used for high-throughput analysis of molecular complexes and the search for active molecules. We are confident that fingeRNAt will be a valuable tool for exploring the complex world of interactions of nucleic acids with ligands.

bioinformatics↗

bioRxiv2021

Heterotypic Assembly Mechanism Regulates CHIP E3 Ligase Activity

The E3 ubiquitin ligases CHIP/CHN-1 and UFD-2 team up to accelerate ubiquitin chain formation. However, it remained largely unclear how the high processivity of this E3 set is achieved. Here we studied the molecular mechanism and function of the CHN-1/UFD-2 complex in Caenorhabditis elegans. Our data show that UFD-2 binding promotes the cooperation between CHN-1 and ubiquitin-conjugating E2 enzymes by stabilizing the CHN-1 U-box dimer. The HSP-1 chaperone outcompetes UFD-2 for CHN-1 binding and promotes the auto-inhibited CHN-1 state by acting on the conserved position of the U-box domain. The interaction with UFD-2 enables CHN-1 to efficiently ubiquitinate S-Adenosylhomocysteinase (AHCY-1), an enzyme crucial for lipid metabolism. Our results define the molecular mechanism underlying the synergistic cooperation of CHN-1 and UFD-2 in substrate ubiquitylation. HIGHLIGHTSO_LIE3 ligase UFD-2 stimulates ubiquitylation activity of CHIP/CHN-1 C_LIO_LIUFD-2 binding promotes dimerization of CHIP/CHN-1 U-box domains and utilization of E2 enzymes C_LIO_LIHSP70/HSP-1 by latching the U-box and TPR domains stabilizes the autoinhibitory state of CHIP/CHN-1, limiting interactions with E2s and UFD-2 C_LIO_LIAssembly with UFD-2 enables CHIP/CHN-1 to regulate lipid metabolism by ubiquitylation of S-Adenosylhomocysteinase C_LI

molecular biology↗