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Updating README #5

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8 changes: 4 additions & 4 deletions AlphaFlex/README.md
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Expand Up @@ -40,13 +40,13 @@ Augments the `AlphaFlex_database_Jul2024.json` file with additional information

Using this information, an `idr_type_summary.txt` file will be given that outlines the distribution of each protein into AlphaFlex defined categories.

Usage: `python step_1_case_label.py`
Usage: `python Step_1_case_label.py`

## Step 1B: Subset Label `(Output Directory: Step_1_Labeling)`

Creates an `id_lists` directory containing a list of proteins in each category within a specified length subset. The lists will contain the IDs of each protein for subsequent processing.

Usage: `python step_1B_subset_label.py`
Usage: `python Step_1B_subset_label.py`

## Step 2: Template Creation `(Output Directory: Step_2_Templates)`

Expand All @@ -56,15 +56,15 @@ Tails and Loops have templates made by `mk_ldr_template.py` which keeps all regi

Linkers have templates made by `mk_flex_template.py` which designates the 2 adjacent folded domains as separate objects and randomly shifts them within a certain distance of one another (mimicking the flexibility of non-interacting folded domains).

Usage: `python step_2_mk_ldr_template.py`
Usage: `python Step_2_mk_ldr_template.py`

## Step 3: IDR Conformer Generation `(Output Directory: Step_3_Raw_Conformers)`

Generates `X` conformers (Default `X` = 10) for each previously created template. Each IDR region is diffused upon individually, so proteins containing multiple IDRs will have multiple templates, leading to the creation of individual 10-conformer ensembles unique to each IDR. Conformers are minimized with their folded domains restrained to minimize structural shifts.

Generation of IDR conformers is done through the use of `sample_ldr.py`.

Usage: `python step_3_sample_conformer.py`.
Usage: `python Step_3_sample_conformer.py`.

## Step 4: Stitching and Minimization `(Output Directory: Step_4_Final_Models)`

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12 changes: 12 additions & 0 deletions README.md
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Expand Up @@ -62,6 +62,8 @@ Then proceed into `openfold/` activate the OpenFold environment using the follow
mamba env create -n openfold_env -f environment.yml
```

> Note: This can also be run with `conda env create -n openfold_env -f environment.yml`

Install other dependencies required by IDPForge using the following command:

``` bash
Expand All @@ -70,6 +72,16 @@ conda install einops mdtraj -c conda-forge

It is also recommended to uninstall flash-attn via `pip uninstall flash-attn` when starting out if this installation pathway is chosen.

Once flash-attn is uninstalled, proceed into `IDPForge/` and `openfold/` and install IDPForge and openfold as modules in the environment using the following commands:

``` bash
cd IDPForge/
pip install -e .
cd openfold/
pip install -e .
```
> Note: If `pip install -e .` does not work, proceed with `pip install . --no-build-isolation` instead.

This makes the environment fully ready for use.

> Note: For more information on OpenFold installation, please refer to the installation guide. https://openfold.readthedocs.io/en/latest/Installation.html
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