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docktdeep

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therapeutics/docktdeep

CNN-based protein-ligand scoring function.

Machine-generated from the listed sources and not yet reviewed by a human.

docktdeep project image
GitHub preview card for gmmsb-lncc/docktdeep. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Therapeutics
Subcategory
unknown
License
LGPL-3.0(osi)
Status
active
Maturity
deployed
Organization
gmmsb-lncc
Country
unknown
Homepage
unknown
Documentation
unknown
Tags
binding-affinity · molecular-docking · scoring-functions
Regulatory
unknown
built by · 1

Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.

similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

  • docktgridbinding-affinity · molecular-docking · scoring-functions

    Generate customized voxel representations of protein-ligand complexes using GPU.

  • CompassDockbinding-affinity · molecular-docking

    Official Implementation of CompassDock

  • hybridock-pepbinding-affinity · molecular-docking

    Hybrid peptide docking: RAPiDock diffusion sampling + physics-based rescoring (iGEM 2026)

  • gnina-torchscoring-functions

    🔥 PyTorch implementation of GNINA scoring function for molecular docking

  • boltz2-notebookbinding-affinity

    Boltz2 Notebook – A streamlined Colab-based pipeline for protein structure prediction and binding affinity analysis using the Boltz2 deep learning model.

  • KiwiMSbinding-affinity

    Data analysis workflow for proteomics mass spectrometry featuring bayesian deconvolution and various downstream analyses.

sources
  1. api.github.com/repos/gmmsb-lncc/docktdeep
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2026-03-07, 6 stars, license reported as LGPL-3.0. Category and schematic were assigned by keyword heuristics and are unreviewed.

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machine-readable

/v1/entries/40.json→ .entries["docktdeep"]

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