Modeling-based RNA Screening Subset

The importance of RNA in normal and abnormal cellular processes is usually attributed to protein translation and transcription, regulation of protein and enzyme functions. RNA-targeted drugs mainly include antisense oligonucleotides (ASOs), small interfering RNA (siRNA), micro RNA (miRNA), messenger RNA (mRNA), RNA adaptors (Aptamer), short activated RNA ( saRNA), single-guided RNA (sgRNA, used in the CRISPR/Cas9 system), and RNA-targeted small molecule drugs. Currently, antisense oligonucleotides (ASOs) and small interfering RNAs (siRNAs) are the main forms of RNA-targeted drugs developed in the clinic.

At BOC Sciences, our scientists have taken the structural features of RNAs into full consideration, and designed a modeling and docking-based RNA-targeted library, which are special screening libraries containing compounds with predicted RNA interaction activity based on different types of secondary structures.

Figure 1. Pri- and pre-miRNAs as therapeutic targets for small-molecule compounds. (Yu, A. M.; et al. 2020)

Modeling-based RNA Screening Subset Design

BOC Sciences has focused on 15 binding motifs in different RNAs associated with bacterial and viral infections. We select these compounds from the screening compound collection using a ligand and target-based approach. Compounds similar to known RNA binders are then scored using molecular docking, and only those with high predictive activity can be selected.

1. Firstly, we analyze all recorded in PDB RNA-ligand complex
2. The following four structures represent the most common types of RNA-ligand interactions that have been selected for molecular docking and query generation:
   1lvj, 1q8n, 4lvy, 6fz0 pdb entries
• All query models are validated using a small set of known active and non-active ligands, and subsequently corrected
• The same training set of known RNA-binding compounds are used to construct Bayesian models to distinguish between "good" molecules from the compounds with known activity
3. Then, two models are developed for each training set. The first one is based on FCFP6 fingerprints, and the second one on ECFP6. A diversity of molecular descriptors such as LogP, molecular weight, number of hydrogen donors and acceptors, number of rotatable bonds, number of rings and molecular polar surface area are involved in the construction of the models to improve accuracy
4. Finally, the well-established model is applied to BOC Sciences HTS compound collection to select screening compounds that target RNAs with top-scoring

Modeling-based RNA Screening Subset Characteristics

• High diversity over the screening set: mean Tanimoto > 0.85
• Favorable physicochemical parameters and solubility requirements
• No PAINS or toxic substances/unwanted functions: filtered by strict ‘Ro5-like’ physicochemical and most stringent in-house structural filters
• Bioactivity and safety confirmed by preclinical studies and clinical trials
• Structural diversity, medicinal activity, and cellular penetration
• Structural document, IC₅₀, and other chemical and biological data are provided
• All compounds are continually updated
• Compound cherry-picking service is provided

Figure 2. Common approaches for the formulation and delivery of RNA therapeutics. (Yu, A. M.; et al. 2020)

What We Deliver

• Delivered within 2 weeks in any customer-preferred format
• Powders, dry films or DMSO solutions formatted in vials, 96 or 384-well plates
• All compounds have a minimum purity of 90% assessed by ¹H NMR and HPLC
• Analytical data is provided

BOC Sciences provides professional, rapid and high-quality services of Modeling-based RNA Screening Subset design at competitive prices for global customers. Personalized and customized services of Modeling-based RNA Screening Subset design can satisfy any innovative scientific study demands. Our clients have direct access to our staff and prompt feedback to their inquiries. If you are interested in our services, please contact us immediately!