AI-ACCELERATED DRUG DISCOVERY
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 All trans-polyprenyl-diphosphate synthase PDSS2 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 All trans-polyprenyl-diphosphate synthase PDSS2 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 All trans-polyprenyl-diphosphate synthase PDSS2, 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 All trans-polyprenyl-diphosphate synthase PDSS2. 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 All trans-polyprenyl-diphosphate synthase PDSS2. 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 All trans-polyprenyl-diphosphate synthase PDSS2 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.
All trans-polyprenyl-diphosphate synthase PDSS2
partner:
Reaxense
upacc:
Q86YH6
UPID:
DLP1_HUMAN
Alternative names:
All-trans-decaprenyl-diphosphate synthase subunit 2; Candidate tumor suppressor protein; Decaprenyl pyrophosphate synthase subunit 2; Decaprenyl-diphosphate synthase subunit 2; Solanesyl-diphosphate synthase subunit 2
Alternative UPACC:
Q86YH6; Q33DR4; Q4G158; Q5VU38; Q5VU39; Q9NR58
Background:
All trans-polyprenyl-diphosphate synthase PDSS2, also known as Decaprenyl-diphosphate synthase subunit 2, plays a crucial role in the biosynthesis of coenzyme Q10 (CoQ10). This enzyme catalyzes the condensation of farnesyl diphosphate (FPP) and isopentenyl diphosphate (IPP) to produce prenyl diphosphates, essential for CoQ10 synthesis. CoQ10 is vital for mitochondrial respiratory chain function and cellular energy production.
Therapeutic significance:
Mutations in PDSS2 are linked to Coenzyme Q10 deficiency, primary, 3, a fatal disorder affecting the brain, muscles, and kidneys. Understanding PDSS2's role could lead to novel treatments for this and related mitochondrial diseases, highlighting its potential in therapeutic strategies.
