AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Ras/Rap GTPase-activating protein SynGAP

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.

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.

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.

Our top-notch dedicated system is used to design specialised 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 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

Q96PV0

UPID:

SYGP1_HUMAN

Alternative names:

Neuronal RasGAP; Synaptic Ras GTPase-activating protein 1

Alternative UPACC:

Q96PV0; A2AB17; A2BEL6; A2BEL7; A8MQC4; Q8TCS2; Q9UGE2

Background:

Ras/Rap GTPase-activating protein SynGAP, also known as Neuronal RasGAP and Synaptic Ras GTPase-activating protein 1, plays a pivotal role in postsynaptic signaling. It is a major constituent of the PSD, essential for synaptic plasticity, and acts as an inhibitory regulator of the Ras-cAMP pathway. SynGAP's involvement in NMDAR signaling complex at excitatory synapses contributes to the control of AMPAR potentiation and membrane trafficking.

Therapeutic significance:

SynGAP is linked to Intellectual developmental disorder, autosomal dominant 5, characterized by developmental delays, intellectual disability, and possible epilepsy and autism. Understanding the role of SynGAP could open doors to potential therapeutic strategies for these conditions.

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