AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for SEC14-like protein 2

Available from Reaxense
Predicted by Alphafold

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.

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.

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

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.

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

O76054

UPID:

S14L2_HUMAN

Alternative names:

Alpha-tocopherol-associated protein; Squalene transfer protein; Supernatant protein factor

Alternative UPACC:

O76054; B7Z8Q1; F5H3U4; Q53EQ2; Q6PD61; Q9ULN4

Background:

SEC14-like protein 2, also known as Alpha-tocopherol-associated protein, plays a crucial role in cellular processes by acting as a carrier for hydrophobic molecules, facilitating their transfer within cells. It exhibits a high affinity for alpha-tocopherol, a form of Vitamin E, and engages in the transport of other tocopherols and tocotrienols, albeit with lower affinity. This protein is also implicated in cholesterol biosynthesis through its interaction with squalene structures.

Therapeutic significance:

Understanding the role of SEC14-like protein 2 could open doors to potential therapeutic strategies. Its involvement in the transport of vital molecules and potential regulatory role in cholesterol biosynthesis positions it as a key target for research aimed at addressing metabolic disorders and cardiovascular diseases.

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