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@durrantlab

Durrant Lab

The Durrant lab at the University of Pittsburgh develops and applies broadly applicable, innovative techniques for computer-aided drug discovery.

Durrant Lab @ University of Pittsburgh

We develop open-source tools for computer-aided drug discovery (CADD), focusing on molecular docking, dynamics, cheminformatics, and machine learning. Our research helps identify small-molecule ligands, study protein function, and accelerate therapeutic discovery.

Our tools are free to use and built for reproducibility, education, and extensibility. We welcome contributions and scientific collaborations.

Popular repositories Loading

  1. gypsum_dl gypsum_dl Public

    Open-source tool to generate 3D-ready small molecules for virtual screening

    Python 54 16

  2. autogrow4 autogrow4 Public

    AutoGrow4 is an open-source program for semi-automated computer-aided drug discovery. It uses a genetic algorithm to evolve predicted ligands on demand and so is not limited to a virtual library of…

    Python 43 15

  3. dimorphite_dl dimorphite_dl Public

    Adds or removes hydrogen atoms to achieve the appropriate molecular protonation state for a user-specified pH range

    Python 31 10

  4. deepfrag deepfrag Public

    DeepFrag is a deep convolutional neural network that guides ligand optimization by extending a ligand with a molecular fragment, such that the resulting extension is also highly complementary to th…

    Python 25 5

  5. binana binana Public

    BINANA (BINding ANAlyzer) analyzes the geometries of predicted ligand poses to identify molecular interactions that contribute to binding. It is useful because accurately characterizing these inter…

    Jupyter Notebook 19 1

  6. subpex subpex Public

    SubPEx (Sub-Pocket Explorer) is a tool to enhance ensemble (multiple-receptor/relaxed-complex) virtual screening. It uses weighted ensemble path sampling and molecular dynamics simulations to accel…

    Python 16 1

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