AI-ACCELERATED DRUG DISCOVERY

Dehydrodolichyl diphosphate synthase complex subunit DHDDS

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

Dehydrodolichyl diphosphate synthase complex subunit DHDDS - Focused Library Design

Available from Reaxense

This protein is integrated into the Receptor.AI ecosystem as a prospective target with high therapeutic potential. We performed a comprehensive characterization of Dehydrodolichyl diphosphate synthase complex subunit DHDDS including:

1. LLM-powered literature research

Our custom-tailored LLM extracted and formalized all relevant information about the protein from a large set of structured and unstructured data sources and stored it in the form of a Knowledge Graph. This comprehensive analysis allowed us to gain insight into Dehydrodolichyl diphosphate synthase complex subunit DHDDS therapeutic significance, existing small molecule ligands, relevant off-targets, and protein-protein interactions.

 Fig. 1. Preliminary target research workflow

2. AI-Driven Conformational Ensemble Generation

Starting from the initial protein structure, we employed advanced AI algorithms to predict alternative functional states of Dehydrodolichyl diphosphate synthase complex subunit DHDDS, including large-scale conformational changes along "soft" collective coordinates. Through molecular simulations with AI-enhanced sampling and trajectory clustering, we explored the broad conformational space of the protein and identified its representative structures. Utilizing diffusion-based AI models and active learning AutoML, we generated a statistically robust ensemble of equilibrium protein conformations that capture the receptor's full dynamic behavior, providing a robust foundation for accurate structure-based drug design.

 Fig. 2. AI-powered molecular dynamics simulations workflow

3. Binding pockets identification and characterization

We employed the AI-based pocket prediction module to discover orthosteric, allosteric, hidden, and cryptic binding pockets on the protein’s surface. Our technique integrates the LLM-driven literature search and structure-aware ensemble-based pocket detection algorithm that utilizes previously established protein dynamics. Tentative pockets are then subject to AI scoring and ranking with simultaneous detection of false positives. In the final step, the AI model assesses the druggability of each pocket enabling a comprehensive selection of the most promising pockets for further targeting.

 Fig. 3. AI-based binding pocket detection workflow

4. AI-Powered Virtual Screening

Our ecosystem is equipped to perform AI-driven virtual screening on Dehydrodolichyl diphosphate synthase complex subunit DHDDS. With access to a vast chemical space and cutting-edge AI docking algorithms, we can rapidly and reliably predict the most promising, novel, diverse, potent, and safe small molecule ligands of Dehydrodolichyl diphosphate synthase complex subunit DHDDS. This approach allows us to achieve an excellent hit rate and to identify compounds ready for advanced lead discovery and optimization.

 Fig. 4. The screening workflow of Receptor.AI

Receptor.AI, in partnership with Reaxense, developed a next-generation technology for on-demand focused library design to enable extensive target exploration.

The focused library for Dehydrodolichyl diphosphate synthase complex subunit DHDDS 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.

Dehydrodolichyl diphosphate synthase complex subunit DHDDS

partner:

Reaxense

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:

Dehydrodolichyl diphosphate synthase complex subunit DHDDS, also known as Cis-isoprenyltransferase, plays a pivotal role in the biosynthesis of dolichol phosphate, a carrier molecule for sugar residues in protein glycosylation within the endoplasmic reticulum. This process is crucial for the proper folding and function of many proteins. DHDDS forms the DDS complex with NUS1, catalyzing the synthesis of long-chain polyprenols, vital for cellular functions.

Therapeutic significance:

DHDDS is implicated in Retinitis pigmentosa 59, a retinal dystrophy leading to vision loss, and a neurodevelopmental disorder characterized by developmental delay, seizures, and movement abnormalities. Understanding the role of DHDDS could open doors to potential therapeutic strategies for these conditions, highlighting its significance in medical research.

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