SPRank - A knowledge-based scoring function for RNA-ligand pose prediction and virtual screening

Platform Requirements (Tested)

The following are tested system settings.

For compiling and running /bin/sprank

• GNU/Linux x86_64 (Ubuntu 22.04 LTS)
• GNU Make 4.3
• gcc/g++ (version 11.4.0)

For running /bin/check_atom_order

• Python 3.9.21
• NumPy 2.0.2

For running /bin/ambertools_prepare_rec and /bin/ambertools_prepare_cpd

• AmberTools22

For running random forest model attached in the Releases

• scikit-learn 1.5.0
• Polars 1.17.1
• NumPy 2.0.2
• Matplotlib 3.9.4

Installation

Compile and install SPRank

Clone this repository on your local machine and run setup script

git clone https://github.com/Vfold-RNA/SPRank.git ${HOME}/SPRank

compile the code

cd ${HOME}/SPRank && make

put the following environment variable to your .bashrc

echo "export SPRANK_HOME=${HOME}/SPRank" >> ${HOME}/.bashrc

and source it

source ${HOME}/.bashrc

Using SPRank and SPRank-RF

Check SPRank options

${SPRANK_HOME}/bin/sprank -h

or check SPRank-RF options

${SPRANK_HOME}/bin/sprank-rf -h

Run SPRank and SPRank-RF for example cases

cd ${SPRANK_HOME}/example && chmod +x ./run_example && ./run_example

The predicted scores will be saved in the corresponding folders as score.dat for sprank and score_random_forest.dat for sprank-rf. By default, the script does not run AmberTools22 to prepare the input receptor and compound. You can remove the comments in ./run_example to prepare the input files using AmberTools22.

Run conversion scripts for example cases

cd ${SPRANK_HOME}/example && chmod +x ./run_conversion_test && ./run_conversion_test

This script will run convert_rdock_pose and convert_vina_pose to convert rDock and AutoDock Vina generated poses to mol2 format compatible with sprank and sprank-rf. After running the script, the predicted scores will be saved in the corresponding folders as *_pose_score.dat for sprank and *_pose_random_forest_score.dat for sprank-rf, where * will be rdock and vina. By default, the script does not run AmberTools22 to prepare the input receptor and compound. You can remove the comments in ./run_conversion_test to prepare the input files using AmberTools22.

SPRank command line arguments

-r <receptor>         # path to target RNA (in amber mol2 format, must contain hydrogens)
-c <target compound>  # path to target compound (in amber mol2 format, must contain hydrogens 
                        and bond table (i.e., "@<TRIPOS>BOND" record))
-p <compound poses>   # path to poses sampled by docking software,
                        to be scored by SPRank (in mol2 format,
                        the order of the heavy atoms should be same as the target compound)

SPRank-RF command line arguments

-r <receptor>         # path to target RNA (in amber mol2 format, must contain hydrogens)
-c <target compound>  # path to target compound (in amber mol2 format, must contain hydrogens 
                        and bond table (i.e., "@<TRIPOS>BOND" record))
-p <compound poses>   # path to poses sampled by docking software,
                        to be scored by SPRank (in mol2 format,
                        the order of the heavy atoms should be same as the target compound)
-o <output>           # path to save the RandomForest predicted scores

Download data

The training set, pose sets, affinity sets, random forest model, amber atom types, potentials, HIV-1 TAR ensemble and compound library can be downloaded from the Releases or through the following commands:

mkdir -p ${SPRANK_HOME}/data/

for name in "checksum.txt" "training-set.tar.gz" "pose-sets.tar.gz" "affinity-sets.tar.gz" "random-forest.tar.gz" "amber-types.tar.gz" "potentials.tar.gz" "HIV-1-TAR.tar.gz"
do
    wget https://github.com/Vfold-RNA/SPRank/releases/download/data/${name} -O ${SPRANK_HOME}/data/${name}
done

Check the integrity of the files:

cd ${SPRANK_HOME}/data/

sha256sum --check checksum.txt

References

[1] Zhou Y, Jiang YW, Chen SJ. SPRank - A Knowledge-Based Scoring Function for RNA-Ligand Pose Prediction and Virtual Screening. Journal of Chemical Theory and Computation. 2024 Aug. doi: 10.1021/acs.jctc.4c00681.