Focused On-demand Library for Zinc finger CCHC domain-containing protein 8

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

The library 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.

We utilise our cutting-edge, exclusive workflow to develop focused libraries.

Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.

Our library distinguishes itself through several key aspects:

The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

upacc

Q6NZY4

UPID:

ZCHC8_HUMAN

Alternative names:

TRAMP-like complex RNA-binding factor ZCCHC8

Alternative UPACC:

Q6NZY4; Q7L2P6; Q8N2K5; Q96SK7; Q9NSS2; Q9NSS3

Background:

Zinc finger CCHC domain-containing protein 8 (ZCCHC8) plays a pivotal role in RNA metabolism as part of the nuclear exosome targeting (NEXT) complex. It is crucial for the degradation of aberrant transcripts and non-coding RNAs, potentially influencing pre-mRNA splicing and telomerase RNA component maturation. This protein's involvement in telomerase function underscores its importance in cellular aging and genome stability.

Therapeutic significance:

Given its critical role in telomerase RNA maturation and function, ZCCHC8's dysfunction is linked to Pulmonary fibrosis and/or bone marrow failure, telomere-related, 5 (PFBMFT5). Understanding the role of ZCCHC8 could open doors to potential therapeutic strategies for diseases associated with telomere dysfunction, including pulmonary fibrosis, aplastic anemia, and increased cancer risk.