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DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction

Authors: Alex Morehead; Chen Chen; Ada Sedova; Jianlin Cheng;

DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction

Abstract

This dataset contains replication data for the paper titled "DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction". The dataset consists of pickled Pandas DataFrame files that can be used to train and validate protein interface prediction models. This dataset also contains the externally generated residue-level PSAIA and HH-suite3 features for users' convenience (e.g. raw MSAs and profile HMMs for each protein complex). Our GitHub repository linked in the "Additional notes" metadata section below provides more details on how we parsed through these files to create training and validation datasets. The GitHub repository for DIPS-Plus also includes scripts that can be used to impute missing feature values and convert the final "raw" complexes into DGL-compatible graph objects.

This dataset can be updated periodically using the instructions contained in our GitHub repository for DIPS-Plus (https://github.com/amorehead/DIPS-Plus). For data provenance, the complexes curated for DIPS-Plus originate from the RCSB's bound protein complex repository (https://ftp.wwpdb.org/pub/pdb/data/biounit/coordinates/divided/).

Keywords

Computational Biology, Geometric deep learning, Neural networks, Protein interface prediction

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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