AI-ACCELERATED DRUG DISCOVERY

DNA-directed RNA polymerase III subunit RPC7-like

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

DNA-directed RNA polymerase III subunit RPC7-like - 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 DNA-directed RNA polymerase III subunit RPC7-like 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-directed RNA polymerase III subunit RPC7-like 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-directed RNA polymerase III subunit RPC7-like, 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-directed RNA polymerase III subunit RPC7-like. 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-directed RNA polymerase III subunit RPC7-like. 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-directed RNA polymerase III subunit RPC7-like 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-directed RNA polymerase III subunit RPC7-like

partner:

Reaxense

upacc:

Q9BT43

UPID:

RPC7L_HUMAN

Alternative names:

DNA-directed RNA polymerase III subunit G-like; RNA polymerase III 32 kDa beta subunit

Alternative UPACC:

Q9BT43; B1MVG5

Background:

The DNA-directed RNA polymerase III subunit RPC7-like, also known as DNA-directed RNA polymerase III subunit G-like and RNA polymerase III 32 kDa beta subunit, plays a pivotal role in the transcription of DNA into RNA, focusing on small RNAs such as 5S rRNA and tRNAs. This protein's involvement in the synthesis of these essential components underscores its fundamental importance in cellular processes.

Therapeutic significance:

Understanding the role of DNA-directed RNA polymerase III subunit RPC7-like could open doors to potential therapeutic strategies, especially considering its link to the disease 'Short stature, oligodontia, dysmorphic facies, and motor delay'. This connection highlights the protein's potential impact on developmental and morphological disorders.

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