Focused On-demand Libraries - Receptor.AI 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 Reaxense.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


Our top-notch dedicated system is used to design specialised libraries for enzymes.


 

Fig. 1. The screening 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
Receptor.AI
 
UPACC
Q86SQ9

UPID:
DHDDS_HUMAN

ALTERNATIVE NAMES:
Cis-isoprenyltransferase; Cis-prenyltransferase subunit hCIT; Epididymis tissue protein Li 189m

ALTERNATIVE UPACC:
Q86SQ9; B7Z4B9; B7ZB20; D3DPK7; D3DPK8; D3DPK9; E9KL43; Q5T0A4; Q8NE90; Q9BTG5; Q9BTK3; Q9H905

BACKGROUND:
The protein Dehydrodolichyl diphosphate synthase complex subunit DHDDS, known alternatively as Cis-prenyltransferase subunit hCIT, is integral to the dolichol monophosphate biosynthetic machinery. It collaborates with NUS1 to produce dehydrodolichyl diphosphate, a precursor for dolichol phosphate, essential for glycosylation and protein stability in the endoplasmic reticulum.

THERAPEUTIC SIGNIFICANCE:
Linked to diseases such as Retinitis pigmentosa 59 and developmental disorders with seizures, DHDDS's function in glycosylation and lipid metabolism suggests its potential as a target for therapeutic intervention. Exploring DHDDS's role further could unveil novel treatment avenues for these debilitating conditions.

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