Focused On-demand Library for Helicase-like transcription factor

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

We employ our advanced, specialised process to create targeted libraries for enzymes.

Fig. 1. The sreening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance activity and selectivity.

Our library is unique due to several crucial aspects:

Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

Q14527

UPID:

HLTF_HUMAN

Alternative names:

DNA-binding protein/plasminogen activator inhibitor 1 regulator; HIP116; RING finger protein 80; RING-type E3 ubiquitin transferase HLTF; SWI/SNF-related matrix-associated actin-dependent regulator of chromatin subfamily A member 3; Sucrose nonfermenting protein 2-like 3

Alternative UPACC:

Q14527; D3DNH3; Q14536; Q16051; Q7KYJ6; Q86YA5; Q92652; Q96KM9

Background:

The Helicase-like transcription factor (HLTF) is a multifunctional protein with helicase and E3 ubiquitin ligase activities. It plays a crucial role in DNA repair and genomic stability by facilitating error-free postreplication repair (PRR) and polyubiquitination of chromatin-bound PCNA. HLTF's ability to remodel nucleosomes and regulate transcription of specific promoters, including those of SERPINE1, HIV-1, and the SV40 enhancer, underscores its significance in cellular processes.

Therapeutic significance:

Understanding the role of Helicase-like transcription factor could open doors to potential therapeutic strategies. Its involvement in DNA repair and transcriptional regulation presents opportunities for targeting in cancer therapy and viral infections, where genomic stability and transcriptional control are compromised.