AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Septin-2

Available from Reaxense
Predicted by Alphafold

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.

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

Q15019

UPID:

SEPT2_HUMAN

Alternative names:

Neural precursor cell expressed developmentally down-regulated protein 5

Alternative UPACC:

Q15019; B4DGE8; Q14132; Q53QU3; Q8IUK9; Q96CB0

Background:

Septin-2, also known as Neural precursor cell expressed developmentally down-regulated protein 5, is a pivotal filament-forming cytoskeletal GTPase. It collaborates with SEPTIN12, SEPTIN6, SEPTIN2, and SEPTIN4 in sperm tail structure and motility. Beyond reproductive biology, Septin-2 is integral to actin cytoskeleton organization, mitotic progression, and ciliogenesis, underscoring its role in cellular architecture and division.

Therapeutic significance:

Understanding the role of Septin-2 could open doors to potential therapeutic strategies. Its involvement in critical cellular processes such as mitosis and ciliogenesis makes it a compelling target for drug discovery, aiming to address disorders stemming from cellular architecture abnormalities.

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