AI-ACCELERATED DRUG DISCOVERY
Available from Reaxense
This protein is integrated into the Receptor.AI ecosystem as a prospective target with high therapeutic potential. We performed a comprehensive characterization of U1 small nuclear ribonucleoprotein A including:
1. LLM-powered literature research
Our custom-tailored LLM extracted and formalized all relevant information about the protein from a large set of structured and unstructured data sources and stored it in the form of a Knowledge Graph. This comprehensive analysis allowed us to gain insight into U1 small nuclear ribonucleoprotein A therapeutic significance, existing small molecule ligands, relevant off-targets, and protein-protein interactions.
Fig. 1. Preliminary target research workflow
2. AI-Driven Conformational Ensemble Generation
Starting from the initial protein structure, we employed advanced AI algorithms to predict alternative functional states of U1 small nuclear ribonucleoprotein A, including large-scale conformational changes along "soft" collective coordinates. Through molecular simulations with AI-enhanced sampling and trajectory clustering, we explored the broad conformational space of the protein and identified its representative structures. Utilizing diffusion-based AI models and active learning AutoML, we generated a statistically robust ensemble of equilibrium protein conformations that capture the receptor's full dynamic behavior, providing a robust foundation for accurate structure-based drug design.
Fig. 2. AI-powered molecular dynamics simulations workflow
3. Binding pockets identification and characterization
We employed the AI-based pocket prediction module to discover orthosteric, allosteric, hidden, and cryptic binding pockets on the protein’s surface. Our technique integrates the LLM-driven literature search and structure-aware ensemble-based pocket detection algorithm that utilizes previously established protein dynamics. Tentative pockets are then subject to AI scoring and ranking with simultaneous detection of false positives. In the final step, the AI model assesses the druggability of each pocket enabling a comprehensive selection of the most promising pockets for further targeting.
Fig. 3. AI-based binding pocket detection workflow
4. AI-Powered Virtual Screening
Our ecosystem is equipped to perform AI-driven virtual screening on U1 small nuclear ribonucleoprotein A. With access to a vast chemical space and cutting-edge AI docking algorithms, we can rapidly and reliably predict the most promising, novel, diverse, potent, and safe small molecule ligands of U1 small nuclear ribonucleoprotein A. This approach allows us to achieve an excellent hit rate and to identify compounds ready for advanced lead discovery and optimization.
Fig. 4. The screening workflow of Receptor.AI
Receptor.AI, in partnership with Reaxense, developed a next-generation technology for on-demand focused library design to enable extensive target exploration.
The focused library for U1 small nuclear ribonucleoprotein A includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.
U1 small nuclear ribonucleoprotein A
partner:
Reaxense
upacc:
P09012
UPID:
SNRPA_HUMAN
Alternative names:
-
Alternative UPACC:
P09012
Background:
U1 small nuclear ribonucleoprotein A (U1 snRNP A) plays a pivotal role in the pre-mRNA splicing process. It is a key component of the spliceosomal U1 snRNP complex, essential for the recognition of the pre-mRNA 5' splice-site and subsequent spliceosome assembly. This protein's interaction with pre-mRNA is crucial for the binding of U2 snRNP and the U4/U6/U5 tri-snRNP, facilitating the splicing process. Additionally, U1 snRNP A binds to stem loop II of U1 snRNA and may engage in the coupled pre-mRNA splicing and polyadenylation process, showing preference for the 5'-UGCAC-3' RNA motif.
Therapeutic significance:
Understanding the role of U1 small nuclear ribonucleoprotein A could open doors to potential therapeutic strategies, offering insights into the regulation of gene expression and the development of novel treatments.
