PIONEER: Protein-protein InteractiON IntErfacE pRediction

PIONEER is a deep learning-based machine learning framework for partner- specific protein interface prediction.

• Web server: https://pioneer.yulab.org
• Software and documentation: https://github.com/hyulab/PIONEER

Related paper: Dapeng X et al. A structurally informed human protein–protein interactome reveals proteome-wide perturbations caused by disease mutations
Nature Biotechnology 2024. [PDF]

NetFlow3D:

NetFlow3D is a computational tool aiming at deciphering how somatic mutations function in cancer. It specifically focuses on protein-altering mutations. By combining the insights from protein structure and protein-protein interaction network, NetFlow3D nominates potential driver mutations and map their functional effects on multiple scales. NetFlow3D web server allows the users to (i) browse and download the results generated from TCGA pan-cancer data, and (ii) run NetFlow3D on their own data.

• Web server: http://netflow3d.yulab.org/#/
• Software and documentation: https://github.com/hyulab/NetFlow3D

Relevant paper: Zhang Y et al. A multiscale functional map of somatic mutations in cancer integrating protein structure and network topology
Nature Communications 2025. [PDF]

PINTS: Peak Identifier for Nascent Transcript Starts.

PINTS is a tool to explore distal transcriptional regulatory elements (TREs) identified from nascent-transcript sequencing.

• Web server: https://pints.yulab.org
• Software and documentation: https://github.com/hyulab/PINTS

Related paper: Yao et al. A comparison of experimental assays and analytical methods for genome-wide identification of active enhancers.

Nature Biotechnology 2022. [PDF]

3D SARS-CoVID-2-Human Interactome:

To facilitate broader exploration of how pathogen–host interactions might impact transmission and virulence in the ongoing COVID-19 pandemic, we performed state-of-the-art interface prediction followed by molecular docking to construct a three-dimensional structural interactome between SARS-CoV-2 and human. We additionally carried out downstream meta-analyses to investigate enrichment of sequence divergence between SARS-CoV-1 and SARS-CoV-2 or human population variants along viral–human protein-interaction interfaces, predict changes in binding affinity by these mutations/variants and further prioritize drug repurposing candidates predicted to competitively bind human targets.

• Web server: https://3d-sars2.yulab.org/
• Software and documentation: https://github.com/hyulab/3D_SARS2

Related paper: Wierbowski, S.D., Liang, S., Liu, Y. et al. A 3D structural SARS-CoV-2–human interactome to explore genetic and drug perturbations

Nature Methods 2022. [PDF]

MaXLinker:

MaXLinker is a software designed to identify cross-links from cross-linking massspectrometry (XL-MS) data. More specifically it can identify cross-links from samples cross-linked by any cleavable cross-linker using MS2-MS3 XL-MS fragmentation strategy.

• Web server: https://yulab.org/resources/MaxLinker/
• Software and documentation: http://hint.yulab.org/about/

Related paper: Kumar et al. MaXLinker: Proteome-wide Cross-link Identifications with High Specificity and Sensitivity
Molecular & cellular proteomics 2020. [PDF]

Interactome INSIDER: INtegrated Structural Interactome and genomic Data browsER

Interactome INSIDER is a tool for functional exploration of human disease on a genomic scale.

• Web server: http://interactomeinsider.yulab.org
• Software and documentation: http://interactomeinsider.yulab.org/about.html

Related paper: Meyer et al. Interactome INSIDER: a structural interactome browser for genomic studies.
Nature Methods 2018. [PDF]

Mutation3D:

mutation3D is a functional prediction and visualization tool for studying the spatial arrangement of amino acid substitutions on protein models and structures. It can be used to identify clusters of amino acid substitutions arising from somatic cancer mutations across many patients in order to identify functional hotspots and fuel downstream hypotheses. It is also useful for clustering other kinds of mutational data, or simply as a tool to quickly assess relative locations of amino acids in proteins.

• Web server: http://mutation3d.org/index.shtml
• Software and documentation: http://mutation3d.org/about.shtml#overview

Related paper: Meyer et al. mutation3D: Cancer Gene Prediction Through Atomic Clustering of Coding Variants in the Structural Proteome
Human mutation 2016. [PDF]

BISQUE: The BIological SeQUence Exchange

BISQUE is a bioinformatics tool enabling locus and variant-specific conversion among human gene, transcript, and protein identifiers from several popular databases. BISQUE implements a graph-traversal algorithm to allow conversion between any two database identifiers, including biologically downstream (gene -> transcript -> protein) and upstream conversions (protein -> transcript -> gene). All major functionality of BISQUE is available via this web interface, a URL-based web service, and a downloadable command-line tool, which includes a python module and deployable MySQL database.

• Web server: http://bisque.yulab.org/index.html
• Software and documentation: https://github.com/hyulab/BISQUE

Related paper: Meyer et al. BISQUE: locus- and variant-specific conversion of genomic, transcriptomic and proteomic database identifiers
Bioinformatics 2016. [PDF]

HINT: High-quality INTeractomes

HINT is a curated compilation of high-quality protein-protein interactions from 8 interactome resources (BioGRID, MINT, iRefWeb, DIP, IntAct, HPRD, MIPS, and the PDB). Interactions are filtered both systematically and manually to remove erroneous and low-quality interactions, and is updated every night. HINT can be used for individual queries as well as for batch downloads.
HINT has been updated in August, 2021.

• Web server: http://hint.yulab.org/
• Software and documentation: http://hint.yulab.org/about/

Related paper: Das J et al. HINT: High-quality protein interactomes and their applications in understanding human disease
BMC systems biology 2012. [PDF]

ClusterONEClustering with Overlapping Neighborhood Expansion:

ClusterONE is a graph clustering algorithm that is able to handle weighted graphs and readily generates overlapping clusters. Owing to these properties, it is especially useful for detecting protein complexes in protein-protein interaction networks with associated confidence values. ClusterONE is available as a standalone command-line application, or as a plugin to Cytoscape or ProCope.
ClusterONE is maintained by collaborators at the Paccanaro Lab.

• Web server: https://paccanarolab.org/cluster-one/
• Software and documentation: https://paccanarolab.org/static_content/clusterone/cl1-cytoscape3-1.0.html

Related paper: Nepusz et al. Detecting overlapping protein complexes in protein-protein interaction networks
Nature Methods 2012. [PDF]