To identify the lowest (relatively) energy docking sites for a particular ligand using one-dimensional search.
Developed as part of the Lawrence Livermore National Laboratory Data Science Summer Institute 2022 Challenge Problem. Screening molecular inhibitors for SARS-CoV-2 protein targets with Deep Learning Models.
Flexible Artificial Intelligence Docking
A quick and dirty virtual screening task for potential ligands of Flavobacterium johnsoniae Tyrosine Ammonia Lyase (FjTAL)
GPR119 ligand screening using computational techniques. (Jan - Dec 2023)
Web service for scoring protein-ligand complexes
Project in the Durrant Lab at UPitt that wanted to re-use code from a previous neural network ligand-protein interaction software to extract features for ML
Python program to run several PELE simulations in a very authomaticall way
Computational Drug Screening Platform
This pipeline facilitates setting up ligand docking against a protein using AutoDock-GPU. It streamlines the process of docking a ligand library onto a protein structure, leveraging the enhanced performance of AutoDock-GPU for faster results.
Code for an artificial neural net classifier of small molecule GPCR activity
Your one-stop solution for protein-ligand docking. This pipeline simplifies molecular docking, helping researchers study protein-ligand interactions efficiently. It offers clear instructions and customizable options for easy virtual screening. Simplify drug discovery, explore confidently!
🔷 MX pipeline. Refinement and ligand screening.
Flexible Artificial Intelligence Docking
screenlamp is a Python toolkit for hypothesis-driven virtual screening
RxDock is a fork of rDock. Note: the latest code is under development. Please do git checkout patched-rdock after clone if you want patched rDock. [IMPORTANT NOTE: pull requests should be posted on GitLab, this is a read-only source code mirror]
Educational materials for, and related to, UC Irvine's Drug Discovery Computing Techniques course (PharmSci 175/275), currently taught by David Mobley.
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