Protein-Protein Interaction in Silico Analysis


Protein-protein interaction (PPI) plays an important role in maintaining cell homeostasis, signal transduction and other important life processes, and is also a vital link in the occurrence and development of many diseases. Therefore, PPI interface has gradually become an important target for new drug discovery. However, the protein-protein interface has the characteristics of large area and relatively flatness, which is not conducive to the binding of drug molecules, especially small molecule drugs, which makes the design of drugs based on protein-protein interface face severe challenges.

At present, a large number of methods for analyzing PPI in vivo and in vitro have been developed, such as yeast two-hybrid, phage display, NMR, etc. However, due to various physical and chemical factors, such as transient dynamics, post-translational modification (PTM) and physiological conditions, moreover, the experimental methods are complex, time-consuming, and labor-intensive. Therefore, the development of PPI in silico prediction methods is very urgent and significant for cell signaling pathway research and rational drug design targeting protein-protein interfaces.

Different methods for detecting protein-protein interactionsFig 1. Different methods for detecting protein-protein interactions (Chang, J.W.; et al. 2016)


Creative Proteomics can provide a variety of protein-protein interaction prediction servers and data analysis services according to customer needs, including but not limited to the following two aspects.

  • Sequence-based PPI prediction methods

They are more versatile and suitable for large-scale PPI prediction. These methods are not suitable for the prediction of transient interactions, because such interactions are poorly conserved across species.

  • Machine learning-based or scoring function-based PPI prediction methods

These methods take into account various characteristics of proteins, such as geometric and electrostatic complementarity, evolutionary conservation, residue interface propensity and solvent accessibility, etc.

Creative Proteomics has accumulated a wealth of practical experience and core technology in the computer prediction of protein-protein interactions. Our bioinformatics analysis experts can provide high-efficiency and high-quality PPI prediction and complete data analysis services for scientific researchers, customers can contact us directly for consultation, and our expert team will provide you with a customized experimental program.


  • Protein-protein interaction research
  • Protein function research
  • Drug design
  • Research on the relationship between conformational changes of drug targets and pharmacological functions
  • Research on the mechanism of disease occurrence and development


  • Effectively identify PPI and PPI sites
  • High throughput
  • Save time and money
  • Unparalleled technology platform
  • Well-trained bioinformatics analysts
  • One-stop service

Protein-protein interaction in silico prediction can be used as an effective substitute for the experimental methods. Creative Proteomics bioinformatics experts are proficient in various prediction servers, and can analyze and revise data in many aspects. We are honored to be your competent research assistant.


  1. Chang, J.W.; et al. Prediction of protein-protein interactions by evidence combining methods. International Journal of Molecular Sciences. 2016, 17(11).
  2. Murakami, Y.; et al. Network analysis and in silico prediction of protein–protein interactions with applications in drug discovery. Current Opinion in Structural Biology. 2017, 44: 134-142.
* This service is for RESEARCH USE ONLY, not intended for any clinical use.