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 focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

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

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your 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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