dSPRINT

A machine learning framework predicting interaction sites in human protein domains

This repository provides companion code to

A. Etzion-Fuchs, D. Todd and M. Singh (2020) "dSPRINT: predicting DNA, RNA, ion, peptide and small molecule interaction sites within protein domains", Manuscript under review

This repository can be used as a computation pipeline, and uses Snakemake as the underlying engine.

Essentially, given a file input.hmm, with one or multiple domains which follow the syntax of a Pfam-A entry, the following computational graph of rules is run:

Output files are generated in the output folder, with the final result per-position ligand binding score generated in the file output/binding_scores.csv

        ligand_type     binding_score   domain  match_state
0       dna     0.9916359186172485      zf-C2H2 1
1       dna     0.9872528910636902      zf-C2H2 10
2       dna     0.997771143913269       zf-C2H2 11
3       dna     0.997983455657959       zf-C2H2 12
4       dna     0.9957016110420227      zf-C2H2 13
5       dna     0.9956439733505249      zf-C2H2 14

Read the Getting Started guide on how to run dSPRINT.