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Protein–Protein Interactions Thermodynamic Database (PINT)


                                                                                                                                              Discover more



 

About Us

At PPITD, we are dedicated to advancing the understanding of protein–protein interactions through a rigorous integration of experimental thermodynamic data, structural information, and scientific literature.

Our team is composed of molecular biologists, bioinformaticians, and structural biology experts committed to building a high-quality, reliable, and accessible resource for the global research community. We believe that data-driven insights into protein interactions are essential for accelerating discoveries in molecular biology, drug development, and biotechnology.

We aim to:

Provide a curated, scientifically accurate database for protein–protein thermodynamics.

Offer tools and interfaces that make data analysis simple, fast, and flexible.

Ensure that all entries are linked to major databases like PIR, SWISS-PROT, PDB, and PubMed, supporting comprehensive research workflows.

 

    Key Features of PPITD

1

Comprehensive Data Integration

  • Experimental thermodynamic parameters.
  • Structural and sequence data for precise protein characterization.
  • Literature references for scientific validation.

 

2

Detailed Experimental Conditions

  • Information about buffers, pH, ions, and additives.
  • Experimental temperatures, concentrations, and techniques used.

 

3

Cross-Database Connectivity

  • Linked to PIR, SWISS-PROT, PDB, and PubMed, providing easy access to complementary information.  

Who Can Benefit From PPITD?

Biochemists & Structural Biologists:

Explore detailed interaction profiles and structural properties of protein complexes.

Computational Biologists:

Integrate high-quality thermodynamic data into molecular dynamics, docking, and predictive models.

Pharmaceutical Researchers:

Identify and prioritize drug targets or modulators of protein interactions.

Educators & Students

Access a rich database for teaching, learning, and practical exercises in protein biochemistry.

How It Works

PPITD is designed to be intuitive and researcher-friendly. Here’s how our database works:

  1. Search and Filter
    • Search by protein name, accession codes (PIR, SWISS-PROT, PDB), organism, or thermodynamic property.
    • Filter by interaction type, experimental conditions, or binding strength.
  2. Explore Detailed Protein Profiles
    • Access thermodynamic parameters: ΔG, ΔH, ΔS, ΔCp, Ka/Kd.
    • View structural information, including secondary structures, solvent accessibility, and 3D coordinates.
    • Check experimental conditions and references linked to PubMed.
  3. Download & Integrate
    • Download datasets for offline analysis or import them via API into computational workflows.
    • Use our visualization tools to map protein interactions and binding networks.

Learn more

    Frequently Asked Questions (FAQ)


In this section, we address frequently asked questions about our bioinformatics services.


PPITD stands for Protein–Protein Interactions Thermodynamic Database. It is a curated platform that integrates experimental thermodynamic data, structural information, sequence details, and literature references for thousands of protein–protein complexes. The database helps researchers understand protein binding specificity, interaction strength, and molecular function.

PPITD provides:

  • Thermodynamic parameters: Binding free energy (ΔG), enthalpy (ΔH), entropy (ΔS), heat capacity change (ΔCp), association/dissociation constants (Ka/Kd).
  • Structural information: Secondary structure, solvent accessibility, and 3D coordinates of protein complexes.
  • Sequence data: PIR, SWISS-PROT, and PDB codes.
  • Experimental conditions: Buffers, pH, ions, temperature, and additives used.
  • Literature references: Linked to PubMed for verification and further reading.

PPITD is designed for:

  • Academic researchers and structural biologists analyzing protein interactions.
  • Computational biologists and bioinformaticians integrating data into molecular modeling and simulations.
  • Pharmaceutical and biotech professionals identifying drug targets or designing therapeutic molecules.
  • Educators and students looking for reliable protein interaction datasets for teaching and learning.

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