Hi everyone,

I am a 3rd year medical student from Romania, working on structural bioinformatics projects in oncology. I recently developed an open-source Python tool designed to help with the early stages of PROTAC drug design, specifically for finding viable linker exit vectors in "undruggable" pockets.

The Problem: Designing PROTACs for targets like KRAS G12C or p53 Y220C is difficult because finding a collision-free path for the linker to exit the binding pocket is often a trial-and-error process.

The Solution: I built a lightweight "Universal Engine" that uses Monte Carlo simulations to stochastically explore the 3D space around a bound ligand.

Key Features:

Automated Ligand Detection: The script parses PDB files and automatically identifies the ligand (no need to specify residue codes like LIG or EFZ).

"Smart Jiggle" Algorithm: Runs 50,000+ random vector simulations to find pathways that satisfy steric clearance (Van der Waals radii).

Validated on: KRAS G12C (Switch-II pocket), p53 Y220C (surface crevice), BRD4, and Cereblon.

Availability: The code is open-source (MIT License) and available on GitHub: https://github.com/edy487/Project-Universal-KRAS-PROTAC

I would really appreciate any feedback or suggestions from the community!