SimRNAweb v2.0: a web server for RNA folding simulations and 3D structure modeling, with optional restraints and enhanced analysis of folding trajectories.

Research on ribonucleic acid (RNA) structures and functions benefits from easy-to-use tools for computational prediction and analyses of RNA three-dimensional (3D) structure. The SimRNAweb server version 2.0 offers an enhanced, user-friendly platform for RNA 3D structure prediction and analysis of RNA folding trajectories based on the SimRNA method. SimRNA employs a coarse-grained model, Monte Carlo sampling and statistical potentials to explore RNA conformational space, optionally guided by spatial restraints. Recognized for its accuracy in RNA 3D structure prediction in RNA-Puzzles and CASP competitions, SimRNA is particularly useful for incorporating restraints based on experimental data. The new server version introduces performance optimizations and extends user control over simulations and the processing of results. It allows the application of various hard and soft restraints, accommodating alternative structures involving canonical and noncanonical base pairs and unpaired residues, while also integrating data from chemical probing methods. Enhanced features include an improved analysis of folding trajectories, offering advanced clustering options and multiple analyses of the generated trajectories. These updates provide comprehensive tools for detailed RNA structure analysis. SimRNAweb v2.0 significantly broadens the scope of RNA modeling, emphasizing flexibility and user-defined parameter control. The web server is available at https://genesilico.pl/SimRNAweb.

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

E3 ubiquitin ligases recognize substrates through their short linear motifs termed degrons. While degron-signaling has been a subject of extensive study, resources for its systematic screening are limited. To bridge this gap, we developed DEGRONOPEDIA, a web server that searches for degrons and maps them to nearby residues that can undergo ubiquitination and disordered regions, which may act as protein unfolding seeds. Along with an evolutionary assessment of degron conservation, the server also reports on post-translational modifications and mutations that may modulate degron availability. Acknowledging the prevalence of degrons at protein termini, DEGRONOPEDIA incorporates machine learning to assess N-/C-terminal stability, supplemented by simulations of proteolysis to identify degrons in newly formed termini. An experimental validation of a predicted C-terminal destabilizing motif, coupled with the confirmation of a post-proteolytic degron in another case, exemplifies its practical application. DEGRONOPEDIA can be freely accessed at degronopedia.com.

MODOMICS: a database of RNA modifications and related information. 2023 update.

The MODOMICS database was updated with recent data and now includes new data types related to RNA modifications. Changes to the database include an expanded modification catalog, encompassing both natural and synthetic residues identified in RNA structures. This addition aids in representing RNA sequences from the RCSB PDB database more effectively. To manage the increased number of modifications, adjustments to the nomenclature system were made. Updates in the RNA sequences section include the addition of new sequences and the reintroduction of sequence alignments for tRNAs and rRNAs. The protein section was updated and connected to structures from the RCSB PDB database and predictions by AlphaFold. MODOMICS now includes a data annotation system, with 'Evidence' and 'Estimated Reliability' features, offering clarity on data support and accuracy. This system is open to all MODOMICS entries, enhancing the accuracy of RNA modification data representation. MODOMICS is available at https://iimcb.genesilico.pl/modomics/.

RNA tertiary structure prediction in CASP15 by the GeneSilico group: Folding simulations based on statistical potentials and spatial restraints.

Ribonucleic acid (RNA) molecules serve as master regulators of cells by encoding their biological function in the ribonucleotide sequence, particularly their ability to interact with other molecules. To understand how RNA molecules perform their biological tasks and to design new sequences with specific functions, it is of great benefit to be able to computationally predict how RNA folds and interacts in the cellular environment. Our workflow for computational modeling of the 3D structures of RNA and its interactions with other molecules uses a set of methods developed in our laboratory, including MeSSPredRNA for predicting canonical and non-canonical base pairs, PARNASSUS for detecting remote homology based on comparisons of sequences and secondary structures, ModeRNA for comparative modeling, the SimRNA family of programs for modeling RNA 3D structure and its complexes with other molecules, and QRNAS for model refinement. In this study, we present the results of testing this workflow in predicting RNA 3D structures in the CASP15 experiment. The overall high score of the computational models predicted by our group demonstrates the robustness of our workflow and its individual components in terms of predicting RNA 3D structures of acceptable quality that are close to the target structures. However, the variance in prediction quality is still quite high, and the results are still too far from the level of protein 3D structure predictions. This exercise led us to consider several improvements, especially to better predict and enforce stacking interactions and non-canonical base pairs.

Structural interaction fingerprints and machine learning for predicting and explaining binding of small molecule ligands to RNA.

Ribonucleic acids (RNAs) play crucial roles in living organisms and some of them, such as bacterial ribosomes and precursor messenger RNA, are targets of small molecule drugs, whereas 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 and encodes them as structural interaction fingerprint (SIFt). Here, we present the application of SIFts accompanied by machine learning methods for binding prediction of small molecules to RNA. We show that SIFt-based models outperform the classic, general-purpose scoring functions in virtual screening. We also employed Explainable Artificial Intelligence (XAI)-the SHapley Additive exPlanations, Local Interpretable Model-agnostic Explanations and other methods to help understand the decision-making process behind the predictive models. We conducted a case study in which we applied XAI on a predictive model of ligand binding to human immunodeficiency virus type 1 trans-activation response element RNA to distinguish between residues and interaction types important for binding. We also used XAI to indicate whether an interaction has a positive or negative effect on binding prediction and to quantify its impact. Our results obtained using all XAI methods were consistent with the literature data, demonstrating the utility and importance of XAI in medicinal chemistry and bioinformatics.

Design, Synthesis, and Development of pyrazolo[1,5-a]pyrimidine Derivatives as a Novel Series of Selective PI3Kδ Inhibitors: Part I-Indole Derivatives.

Phosphoinositide 3-kinase δ (PI3Kδ), a member of the class I PI3K family, is an essential signaling biomolecule that regulates the differentiation, proliferation, migration, and survival of immune cells. The overactivity of this protein causes cellular dysfunctions in many human disorders, for example, inflammatory and autoimmune diseases, including asthma or chronic obstructive pulmonary disease (COPD). In this work, we designed and synthesized a new library of small-molecule inhibitors based on indol-4-yl-pyrazolo[1,5-a]pyrimidine with IC50 values in the low nanomolar range and high selectivity against the PI3Kδ isoform. CPL302253 (54), the most potent compound of all the structures obtained, with IC50 = 2.8 nM, is a potential future candidate for clinical development as an inhaled drug to prevent asthma.

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 fingerprint-based similarity as an alternative measure to RMSD to recapitulate complexes with similar interactions but different folding. We present an application of interaction 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. The fingeRNAt software is freely available at https://github.com/n-szulc/fingeRNAt.

MODOMICS: a database of RNA modification pathways. 2021 update.

The MODOMICS database has been, since 2006, a manually curated and centralized resource, storing and distributing comprehensive information about modified ribonucleosides. Originally, it only contained data on the chemical structures of modified ribonucleosides, their biosynthetic pathways, the location of modified residues in RNA sequences, and RNA-modifying enzymes. Over the years, prompted by the accumulation of new knowledge and new types of data, it has been updated with new information and functionalities. In this new release, we have created a catalog of RNA modifications linked to human diseases, e.g., due to mutations in genes encoding modification enzymes. MODOMICS has been linked extensively to RCSB Protein Data Bank, and sequences of experimentally determined RNA structures with modified residues have been added. This expansion was accompanied by including nucleotide 5'-monophosphate residues. We redesigned the web interface and upgraded the database backend. In addition, a search engine for chemically similar modified residues has been included that can be queried by SMILES codes or by drawing chemical molecules. Finally, previously available datasets of modified residues, biosynthetic pathways, and RNA-modifying enzymes have been updated. Overall, we provide users with a new, enhanced, and restyled tool for research on RNA modification. MODOMICS is available at https://iimcb.genesilico.pl/modomics/.

AnnapuRNA: A scoring function for predicting RNA-small molecule binding poses.

RNA is considered as an attractive target for new small molecule drugs. Designing active compounds can be facilitated by computational modeling. Most of the available tools developed for these prediction purposes, such as molecular docking or scoring functions, are parametrized for protein targets. The performance of these methods, when applied to RNA-ligand systems, is insufficient. To overcome these problems, we developed AnnapuRNA, a new knowledge-based scoring function designed to evaluate RNA-ligand complex structures, generated by any computational docking method. We also evaluated three main factors that may influence the structure prediction, i.e., the starting conformer of a ligand, the docking program, and the scoring function used. We applied the AnnapuRNA method for a post-hoc study of the recently published structures of the FMN riboswitch. Software is available at https://github.com/filipspl/AnnapuRNA.

Luciferase reporter assay for small-molecule inhibitors of MIR92b-3p function: Screening cyanopeptolins produced by Nostoc from the Baltic Sea.

We developed a cell sensor that detects the liver cancer-specific microRNA MIR92b-3p, involved in hepatocellular carcinoma development and hepatitis C virus infection. To validate our small-molecule screen that employs a Huh7 human hepatoma cell line stably transfected with a pmirGLO vector containing dual luciferase reporters, we used i) a MIR92b-3p antisense or a MIR92b-3p mimicking agent (concentrations from 0.1 pM to 100 nM), ii) expression of XIST, a long non-coding RNA that is a cellular target of MIR92b, and iii) ectopic expression of Luc2 luciferase. This reporter system was used to test four cyanopeptolins from a de novo library of peptides that were isolated from the Baltic Sea cyanobacteria Nostoc edaphicum strain CCNP1411. Exposure of the Huh7-pmirGLO-MIR92b-3p cells to increasing concentrations (from 10 nM to 100 µM) of the cyanopeptolins and microcystin-LR (MC-LR; a treatment control) did not lead to a dose-dependent restoration of the luciferase signal. Instead, when the reporter cells were treated with MC-LR, the luciferase signal decreased markedly, most likely due to non-target, toxic effects of MC-LR on the cells. Although the first use of this reporter system to screen selected Nostoc peptides did not identify inhibitors of MIR92b, this method provides a means to identify functional miRNA regulators and could be readily extended to other compounds.

Benzoxazepine-Derived Selective, Orally Bioavailable Inhibitor of Human Acidic Mammalian Chitinase.

Human acidic mammalian chitinase (hAMCase) is one of two true chitinases in humans, the function of which remains elusive. In addition to the defense against highly antigenic chitin and chitin-containing pathogens in the gastric and intestinal contents, AMCase has been implicated in asthma, allergic inflammation, and ocular pathologies. Potent and selective small-molecule inhibitors of this enzyme have not been identified to date. Here we describe structural modifications of compound OAT-177, a previously developed inhibitor of mouse AMCase, leading to OAT-1441, which displays high activity and selectivity toward hAMCase. Significantly reduced off-target activity toward the human ether-à-go-go-related gene (hERG) and a good pharmacokinetic profile make OAT-1441 a potential candidate for further preclinical development as well as a useful tool compound to study the physiological role of hAMCase.

RNAProbe: a web server for normalization and analysis of RNA structure probing data.

RNA molecules play key roles in all living cells. Knowledge of the structural characteristics of RNA molecules allows for a better understanding of the mechanisms of their action. RNA chemical probing allows us to study the susceptibility of nucleotides to chemical modification, and the information obtained can be used to guide secondary structure prediction. These experimental results can be analyzed using various computational tools, which, however, requires additional, tedious steps (e.g., further normalization of the reactivities and visualization of the results), for which there are no fully automated methods. Here, we introduce RNAProbe, a web server that facilitates normalization, analysis, and visualization of the low-pass SHAPE, DMS and CMCT probing results with the modification sites detected by capillary electrophoresis. RNAProbe automatically analyzes chemical probing output data and turns tedious manual work into a one-minute assignment. RNAProbe performs normalization based on a well-established protocol, utilizes recognized secondary structure prediction methods, and generates high-quality images with structure representations and reactivity heatmaps. It summarizes the results in the form of a spreadsheet, which can be used for comparative analyses between experiments. Results of predictions with normalized reactivities are also collected in text files, providing interoperability with bioinformatics workflows. RNAProbe is available at https://rnaprobe.genesilico.pl.

Development of Dual Chitinase Inhibitors as Potential New Treatment for Respiratory System Diseases.

Acidic mammalian chitinase (AMCase) and chitotriosidase-1 (CHIT1) are two enzymatically active proteins produced by mammals capable of cleaving the glycosidic bond in chitin. Based on the clinical findings and animal model studies, involvement of chitinases has been suggested in several respiratory system diseases including asthma, COPD, and idiopathic pulmonary fibrosis. Exploration of structure-activity relationships within the series of 1-(3-amino-1H-1,2,4-triazol-5-yl)-piperidin-4-amines, which was earlier identified as a scaffold of potent AMCase inhibitors, led us to discover highly active dual (i.e., AMCase and CHIT1) inhibitors with very good pharmacokinetic properties. Among them, compound 30 was shown to reduce the total number of cells in bronchoalveolar lavage fluid of mice challenged with house dust mite extract after oral administration (50 mg/kg, qd). In addition, affinity toward the hERG potassium channel of compound 30 was significantly reduced when compared to the earlier reported chitinase inhibitors.

Structural bases of peptidoglycan recognition by lysostaphin SH3b domain.

Staphylococcus simulans lysostaphin cleaves pentaglycine cross-bridges between stem peptides in the peptidoglycan of susceptible staphylococci, including S. aureus. This enzyme consists of an N-terminal catalytic domain and a cell wall binding domain (SH3b), which anchors the protein to peptidoglycan. Although structures of SH3bs from lysostaphin are available, the binding modes of peptidoglycan to these domains are still unclear. We have solved the crystal structure of the lysostaphin SH3b domain in complex with a pentaglycine peptide representing the peptidoglycan cross-bridge. The structure identifies a groove between ß1 and ß2 strands as the pentaglycine binding site. The structure suggests that pentaglycine specificity of the SH3b arises partially directly by steric exclusion of Cß atoms in the ligand and partially indirectly due to the selection of main chain conformations that are easily accessible for glycine, but not other amino acid residues. We have revealed further interactions of SH3b with the stem peptides with the support of bioinformatics tools. Based on the structural data we have attempted engineering of the domain specificity and have investigated the relevance of the introduced substitutions on the domain binding and specificity, also in the contexts of the mature lysostaphin and of its bacteriolytic activity.

Human RNA cap1 methyltransferase CMTr1 cooperates with RNA helicase DHX15 to modify RNAs with highly structured 5' termini.

The 5'-cap structure, characteristic for RNA polymerase II-transcribed RNAs, plays important roles in RNA metabolism. In humans, RNA cap formation includes post-transcriptional modification of the first transcribed nucleotide by RNA cap1 methyltransferase (CMTr1). Here, we report that CMTr1 activity is hindered towards RNA substrates with highly structured 5' termini. We found that CMTr1 binds ATP-dependent RNA DHX15 helicase and that this interaction, mediated by the G-patch domain of CMTr1, has an advantageous effect on CMTr1 activity towards highly structured RNA substrates. The effect of DHX15 helicase activity is consistent with the strength of the secondary structure that has to be removed for CMTr1 to access the 5'-terminal residues in a single-stranded conformation. This is, to our knowledge, the first demonstration of the involvement of DHX15 in post-transcriptional RNA modification, and the first example of a molecular process in which DHX15 directly affects the activity of another enzyme. Our findings suggest a new mechanism underlying the regulatory role of DHX15 in the RNA capping process. RNAs with highly structured 5' termini constitute a significant fraction of the human transcriptome. Hence, CMTr1-DHX15 cooperation is likely to be important for the metabolism of RNA polymerase II-transcribed RNAs.This article is part of the theme issue '5' and 3' modifications controlling RNA degradation'.

Synthesis and characterization of novel classes of PDE10A inhibitors - 1H-1,3-benzodiazoles and imidazo[1,2-a]pyrimidines.

New compounds containing [1,2,4]triazolo [1,5-a]pyridine (I), pyrazolo [1,5-a]pyridine (II), 1H-1,3-benzodiazole (III) and imidazo [1,2-a]pyrimidine (IV) backbones were designed and synthesized for PDE10A interaction. Among these compounds, 1H-1,3-benzodiazoles and imidazo [1,2-a]pyrimidines showed the highest affinity for PDE10A enzyme as well as good metabolic stability. Both classes of compounds were identified as selective and potent PDE10A enzyme inhibitors.

Novel inhibitors of the rRNA ErmC' methyltransferase to block resistance to macrolides, lincosamides, streptogramine B antibiotics.

In erythromycin-resistant bacteria, the N6 position of A2058 in 23S rRNA is mono- or dimethylated by Erm family methyltransferases. This modification results in cross-resistance to macrolides, lincosamides and streptogramin B. Most inhibitors of Erm methyltransferases developed up-to-date target the cofactor-binding pocket, resulting in a lack of selectivity whereas inhibitors that bind the substrate-binding pocket demonstrate low in vitro activity. In this study, a molecular docking approach followed by biochemical screening was applied to search for inhibitors targeting both cofactor- and substrate-binding pockets of ErmC' methyltransferase. Based on the results of the molecular docking-based virtual screening of the clean-leads subset of the ZINC database, 29 compounds were chosen for experimental verification. Among them inhibitor 28 (ZINC code 32747906), with an IC50 of 100 µM, decreased the minimal inhibitory concentration of erythromycin in the Escherichia coli strain overexpressing ErmC'. Docking analysis of 28 to the ErmC' structure and the competitive ligand binding assay revealed a non-competitive model of inhibition. Inhibitor 28 served as a template for similarity-based virtual screening, which resulted in the identification of two derivatives 3s (ZINC code 62022572) and 4s (ZINC code 49032257) with an IC50 of 116 µM and 110 µM, respectively. Our results provide a basis for the development of inhibitors against the Erm-family of enzymes.

Discovery of selective, orally bioavailable inhibitor of mouse chitotriosidase.

This article describes our work towards the identification of a potent and selective inhibitor of mouse chitotriosidase (mCHIT1). A series of small molecule inhibitors of mCHIT1 and mAMCase have been developed from early lead compound 1. Examination of synthetized analogues led to discovery of several novel highly potent compounds. Among them compound 9 (OAT-2068) displays a remarkable 143-fold mCHIT1 vs. mAMCase selectivity. To explain the observed SAR molecular docking experiments were performed, which were in line with the experimental data from the enzymatic assays. Inhibitor 9 (OAT-2068) was found to have an excellent pharmacokinetic profile. This, together with high activity and selectivity, makes the compound an ideal and unique tool for studying the role of CHIT1 in biological models.

RNArchitecture: a database and a classification system of RNA families, with a focus on structural information.

RNArchitecture is a database that provides a comprehensive description of relationships between known families of structured non-coding RNAs, with a focus on structural similarities. The classification is hierarchical and similar to the system used in the SCOP and CATH databases of protein structures. Its central level is Family, which builds on the Rfam catalog and gathers closely related RNAs. Consensus structures of Families are described with a reduced secondary structure representation. Evolutionarily related Families are grouped into Superfamilies. Similar structures are further grouped into Architectures. The highest level, Class, organizes families into very broad structural categories, such as simple or complex structured RNAs. Some groups at different levels of the hierarchy are currently labeled as 'unclassified'. The classification is expected to evolve as new data become available. For each Family with an experimentally determined three-diemsional (3D) structure(s), a representative one is provided. RNArchitecture also presents theoretical models of RNA 3D structure and is open for submission of structural models by users. Compared to other databases, RNArchitecture is unique in its focus on structure-based RNA classification, and in providing a platform for storing RNA 3D structure predictions. RNArchitecture can be accessed at http://iimcb.genesilico.pl/RNArchitecture/.

Molecularly Imprinted Polymer (MIP) Film with Improved Surface Area Developed by Using Metal-Organic Framework (MOF) for Sensitive Lipocalin (NGAL) Determination.

Electropolymerizable functional and cross-linking monomers were used to prepare conducting molecularly imprinted polymer film with improved surface area with the help of a sacrificial metal-organic framework (MOF). Subsequent dissolution of the MOF layer resulted in a surface developed MIP film. This surface enlargement increased the analyte accessibility to imprinted molecular cavities. Application of the porous MIP film as a recognition unit of an extended-gate field effect transistor (EG-FET) chemosensor effectively enhanced analytical current signals of determination of recombinant human neutrophil gelatinase-associated lipocalin (NGAL).