Resources

Proteomics Databases



Metabolomics Databases

• • What Controls Are Needed for Co-IP-MS and In-Cell Crosslinking MS?

  Protein interaction mass spectrometry can reveal binding partners, complex composition, and spatially constrained protein contacts. The main challenge is that interaction MS data can contain both true biology and technical background. A protein may appear in a Co-IP-MS dataset because the protein binds the bait, binds the antibody, binds beads, or survives washing because the protein is abundant.

• • How to Identify Accessory Proteins of Ion Channels by Mass Spectrometry

  Mass spectrometry can solve this problem when the workflow is designed around membrane biology. The goal is not only to identify proteins in the same sample. The goal is to distinguish likely channel-associated partners from background proteins, expression artifacts, and extraction- dependent noise.

• • Co-IP-MS vs XL-MS: Which Protein Interaction Workflow Should You Choose?

  The most useful way to compare Co-IP-MS vs XL-MS is to start with the desired readout. Co-IP-MS is usually stronger for bait-centered partner discovery and complex profiling. XL-MS is usually stronger for mapping spatial proximity within or between proteins. Both workflows can be valuable, but each workflow has different sample requirements, controls, failure modes, and interpretation limits.

• • Hybridoma Monoclonal Antibody Sequencing for Cell Line Transfer and Recombinant Reformatting

  Technical guide for Hybridoma Monoclonal Antibody Sequencing for Cell Line Transfer and Recombinant Reformatting.

• • Monoclonal Antibody Sequencing for Recombinant Recovery: When Should You Sequence an Existing Antibody Asset?

  Technical guide for Monoclonal Antibody Sequencing for Recombinant Recovery: When Should You Sequence an Existing Antibody Asset?.

• • Monoclonal Antibody Sequencing vs De Novo Protein Sequencing: Which Route Fits an Antibody Recovery Project?

  Technical guide for Monoclonal Antibody Sequencing vs De Novo Protein Sequencing: Which Route Fits an Antibody Recovery Project?.

• • Protein Sequencing: Principles, Workflows, and Research Applications

  Protein sequencing determines the amino acid order of a protein or peptide. This information supports cloning, expression design, antibody engineering, biopharmaceutical characterization, and publication of primary structure evidence.

• • Hybridoma Monoclonal Antibody Sequencing: How to Recover VH and VL Sequences from Unstable or Lost-Producing Clones

  Technical guide for Hybridoma Monoclonal Antibody Sequencing: How to Recover VH and VL Sequences from Unstable or Lost-Producing Clones.

• • Studying Membrane Protein Interactions in Native Cells: Why Overexpression Can Mislead and How In-Cell Crosslinking MS Helps

  Membrane protein interactions are difficult to study because the interaction signal depends on more than protein sequence. Local abundance, lipid composition, membrane curvature, compartment identity, trafficking status, and stimulation timing can all shape whether two proteins meet. Many researchers use overexpression to increase signal, simplify antibody capture, or make a weak interaction easier to detect.

• • PhIP-Seq: Methods, Applications and Challenges

  PhIP-Seq, also called phage immunoprecipitation sequencing, was developed for this type of discovery question. The method combines phage display peptide libraries, antibody capture, next- generation sequencing, and enrichment analysis. PhIP-Seq can help researchers identify antibody-reactive peptides, compare serological profiles across groups, and nominate candidate epitope regions.