AI-ACCELERATED DRUG DISCOVERY

Runt-related transcription factor 2

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

Runt-related transcription factor 2 - Focused Library Design

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 Runt-related transcription factor 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 Runt-related transcription factor 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 Runt-related transcription factor 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 Runt-related transcription factor 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 Runt-related transcription factor 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 Runt-related transcription factor 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.

Runt-related transcription factor 2

partner:

Reaxense

upacc:

Q13950

UPID:

RUNX2_HUMAN

Alternative names:

Acute myeloid leukemia 3 protein; Core-binding factor subunit alpha-1; Oncogene AML-3; Osteoblast-specific transcription factor 2; Polyomavirus enhancer-binding protein 2 alpha A subunit; SL3-3 enhancer factor 1 alpha A subunit; SL3/AKV core-binding factor alpha A subunit

Alternative UPACC:

Q13950; O14614; O14615; O95181

Background:

Runt-related transcription factor 2 (RUNX2) is a pivotal transcription factor involved in osteoblastic differentiation and skeletal morphogenesis. It plays a crucial role in the maturation of osteoblasts and is essential for both intramembranous and endochondral ossification. RUNX2's ability to bind to various enhancers and promoters facilitates the transcription of genes critical for bone development and homeostasis.

Therapeutic significance:

RUNX2's involvement in diseases such as Cleidocranial dysplasia 1 and Metaphyseal dysplasia with maxillary hypoplasia underscores its therapeutic significance. Understanding the role of RUNX2 could open doors to potential therapeutic strategies for these skeletal disorders, highlighting the importance of targeted research in uncovering novel treatments.

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