AI-ACCELERATED DRUG DISCOVERY

General transcription factor IIH subunit 3

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

General transcription factor IIH subunit 3 - 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 General transcription factor IIH subunit 3 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 General transcription factor IIH subunit 3 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 General transcription factor IIH subunit 3, 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 General transcription factor IIH subunit 3. 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 General transcription factor IIH subunit 3. 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 General transcription factor IIH subunit 3 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.

General transcription factor IIH subunit 3

partner:

Reaxense

upacc:

Q13889

UPID:

TF2H3_HUMAN

Alternative names:

Basic transcription factor 2 34 kDa subunit; General transcription factor IIH polypeptide 3; TFIIH basal transcription factor complex p34 subunit

Alternative UPACC:

Q13889; B2R819; B4DNZ6; Q7L0G0; Q96AT7

Background:

General transcription factor IIH subunit 3, also known as the 34 kDa subunit, plays a pivotal role in DNA repair and RNA transcription. It is a component of the TFIIH core complex, essential for nucleotide excision repair (NER) and transcription initiation by RNA polymerase II. In NER, it facilitates the opening of DNA around lesions, enabling damaged oligonucleotide excision and replacement. For transcription, it is crucial for promoter opening and escape, with its kinase module CAK phosphorylating RNA polymerase II to initiate transcription.

Therapeutic significance:

Understanding the role of General transcription factor IIH subunit 3 could open doors to potential therapeutic strategies.

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