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 Cyclic AMP-dependent transcription factor ATF-1 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 Cyclic AMP-dependent transcription factor ATF-1 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 Cyclic AMP-dependent transcription factor ATF-1, 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 Cyclic AMP-dependent transcription factor ATF-1. 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 Cyclic AMP-dependent transcription factor ATF-1. 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 Cyclic AMP-dependent transcription factor ATF-1 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.
Cyclic AMP-dependent transcription factor ATF-1
partner:
Reaxense
upacc:
P18846
UPID:
ATF1_HUMAN
Alternative names:
Activating transcription factor 1; Protein TREB36
Alternative UPACC:
P18846; B4DRF9; P25168; Q9H4A8
Background:
Cyclic AMP-dependent transcription factor ATF-1, also known as Activating transcription factor 1 and Protein TREB36, plays a pivotal role in cellular processes. It binds the cAMP response element (CRE), a sequence found in many viral and cellular promoters, and the Tax-responsive element (TRE) of HTLV-I. ATF-1 is crucial in mediating PKA-induced stimulation of CRE-reporter genes and represses the expression of FTH1 and other antioxidant detoxification genes, thereby triggering cell proliferation and transformation.
Therapeutic significance:
Angiomatoid fibrous histiocytoma, a distinct variant of malignant fibrous histiocytoma, is associated with ATF-1. Chromosomal aberrations involving ATF1, such as translocations with FUS and EWSR1, result in chimeric proteins linked to the disease. Understanding the role of ATF-1 could open doors to potential therapeutic strategies for this and related conditions.
