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 DNA-binding protein SMUBP-2 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 DNA-binding protein SMUBP-2 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 DNA-binding protein SMUBP-2, 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 DNA-binding protein SMUBP-2. 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 DNA-binding protein SMUBP-2. 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 DNA-binding protein SMUBP-2 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.
DNA-binding protein SMUBP-2
partner:
Reaxense
upacc:
P38935
UPID:
SMBP2_HUMAN
Alternative names:
ATP-dependent helicase IGHMBP2; Glial factor 1; Immunoglobulin mu-binding protein 2
Alternative UPACC:
P38935; A0PJD2; Q00443; Q14177
Background:
DNA-binding protein SMUBP-2, also known as ATP-dependent helicase IGHMBP2, plays a crucial role in unwinding RNA and DNA duplexes in an ATP-dependent manner. It specifically targets 5'-phosphorylated single-stranded guanine-rich sequences, indicating a specialized function in nucleic acid metabolism. This protein is implicated in various cellular processes including RNA metabolism, ribosome biogenesis, and potentially in the initiation of translation and regulation of transcription.
Therapeutic significance:
DNA-binding protein SMUBP-2 is linked to two significant neuromuscular disorders: Neuronopathy, distal hereditary motor, 6, and Charcot-Marie-Tooth disease, axonal, 2S. Both diseases are characterized by progressive muscle weakness and atrophy, attributed to mutations affecting the gene encoding this protein. Understanding the role of DNA-binding protein SMUBP-2 could open doors to potential therapeutic strategies for these debilitating conditions.
