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Updated: Aug 11, 2026
22:10
Multi-target Parallel Processing Approach for Gene-to-structure Determination of the Influenza Polymerase PB2 Subunit
Published on: June 28, 2013
PSGS-Drug: Generation-Time Dual-Pocket Guidance for Non-Symmetric Dual-Target Molecular Design
Yuchen Zhou1, Tianhe Gu1, Liang Tian1
1College of Computer Science and Technology, Shenyang University of Chemical Technology, Liaoning Key Laboratory of Intelligent Technology for Chemical Process Industry, Shenyang110142, China.
Journal of Chemical Information and Modeling
|August 10, 2026
Summary
We developed PSGS-Drug, a computational framework for designing molecules targeting multiple proteins simultaneously. This approach aids in developing new cancer therapies by prioritizing potential drug candidates.
Area of Science:
- Computational chemistry and drug discovery
- Molecular modeling and simulation
- Oncology and cancer research
Background:
- Designing molecules for multiple protein targets simultaneously is complex.
- Understanding cross-talk between MEK1 and mTOR pathways is crucial for NRAS mutant melanoma treatment.
- Existing computational methods face challenges in dual-target drug design.
Purpose of the Study:
- To present PSGS-Drug, a novel dual-pocket framework for computational dual-target drug design.
- To fuse protein binding site information for enhanced molecule generation.
- To prioritize drug candidates for pathway-linked dual-context hypotheses.
Main Methods:
- PSGS-Drug framework integrates localized token priors from MEK1 (PDB: 7PQV) and mTOR (PDB: 3FAP) binding sites.
- Contact-guided prefix initialization is used for rank-head exploration.
- Generated molecules were evaluated using summed two-context docking scores (docksum) and dual-hit coverage criteria.
Main Results:
- PSGS-Drug achieved a mean docksum of -17.700 ± 0.242 and 29.00 ± 2.98% dual-hit coverage.
- Outperformed Pocket2Mol and PCMol comparators in docksum and dual-hit coverage.
- Validation on a kinase-nuclear-receptor pair demonstrated transferability of the fused-prior effect.
Conclusions:
- PSGS-Drug is an effective computational prioritization framework for dual-target drug design.
- The framework supports candidate selection for pathway-linked dual-context hypotheses.
- Further biochemical and cellular testing is required for candidate validation.
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