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 Transcription intermediary factor 1-alpha 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 Transcription intermediary factor 1-alpha 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 Transcription intermediary factor 1-alpha, 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 Transcription intermediary factor 1-alpha. 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 Transcription intermediary factor 1-alpha. 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 Transcription intermediary factor 1-alpha 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.
Transcription intermediary factor 1-alpha
partner:
Reaxense
upacc:
O15164
UPID:
TIF1A_HUMAN
Alternative names:
E3 ubiquitin-protein ligase TRIM24; RING finger protein 82; RING-type E3 ubiquitin transferase TIF1-alpha; Tripartite motif-containing protein 24
Alternative UPACC:
O15164; A4D1R7; A4D1R8; O95854
Background:
Transcription intermediary factor 1-alpha (TIF1-alpha), also known as E3 ubiquitin-protein ligase TRIM24, plays a pivotal role in cellular processes by interacting with nuclear receptors and coactivators to modulate gene transcription. It exhibits a unique affinity for chromatin modifications and possesses E3 ligase activity, crucial for DNA damage response and cell cycle regulation. Its interaction with TP53 and involvement in innate immunity highlight its multifunctionality.
Therapeutic significance:
Understanding the role of Transcription intermediary factor 1-alpha could open doors to potential therapeutic strategies. Its central role in regulating cell proliferation, apoptosis, and response to DNA damage, alongside its effects on p53/TP53 levels, positions it as a key target for cancer therapy and immune response modulation.
