Prediction of Protein-Protein Interaction Sites

Welcome to CD ComputaBio, your trusted partner in advancing protein research through our cutting-edge computational services. Our Prediction of Protein-Protein Interaction (PPI) Sites is one of our premier offerings, tailored to support researchers and organizations seeking to understand cellular processes and develop innovative therapeutic strategies.

Our Services

• PPI Database Construction: We build tailored databases of protein structures for your target organisms or systems, enhancing the accuracy of our predictions.
• Custom Analysis: Based on your research needs, we design custom pipelines for protein interaction site prediction, accommodating varying protein structures and complexities.

Fig 1. Predicting Protein-Protein Interactions from Matrix-Based Protein Sequence Using Convolution Neural Network and Feature-Selective Rotation Forest. (Wang L, et al., 2019)

• Homology Modeling: Constructing 3D models of proteins based on known structures to identify interaction potentials.
• Molecular Docking Studies: Simulating interactions between proteins to visualize binding sites and affinities.
• Visualization Tools: Providing graphical representations of models and interaction sites using software tools like PyMOL and Chimera.

• Single/Double Mutant Analysis: Assessing the effects of point mutations or multiple mutations on interaction stability.
• Stability Predictions: Utilizing tools like Rosetta and FoldX to forecast how mutations impact protein stability and function.

Services Details

Analysis Methods

• Machine Learning-Based Predictions
  Machine learning algorithms are at the core of our PPI site prediction services. By training our models on large, curated datasets of known PPIs, we can predict interaction sites with high accuracy. Methods we use include:
  • Support Vector Machines (SVM)
  • Random Forests (RF)
  • Deep Learning Models
• Molecular Docking and Dynamics Simulation
  Our structural approach involves molecular docking and dynamics simulations to predict how proteins interact and to identify potential binding sites.
  • Molecular Docking: We utilize software such as AutoDock and HADDOCK to simulate the docking process between proteins, identifying the most probable interaction sites.
  • Molecular Dynamics (MD) Simulations: Using tools like GROMACS and AMBER, we simulate the dynamic behavior of protein complexes to refine our predictions and understand the stability and conformational changes upon bin
• Network-Based Analysis
  Protein interaction networks provide valuable context for individual PPIs. We analyze these networks to predict interaction sites by understanding the overall connectivity and interaction patterns within the cell.
  • Graph Theory Analysis: We use graph theoretical approaches to identify key nodes and edges representing crucial PPIs within the network.
  • Community Detection Algorithms: These algorithms help identify clusters or modules of interacting proteins that participate in specific biological processes.

Data Files and Visualizations

In addition to the report, you will receive all relevant data files:

• Raw and Processed Data Files: Including sequence alignments, interaction predictions, and simulation data.
• 3D Model Files: Structural models in formats compatible with popular visualization tools such as PyMOL and Chimera.

Result Delivery

Each project culminates in a detailed report that includes:

CD ComputaBio is a leading provider of computational biology services, offering a wide range of bioinformatics, cheminformatics, and structural biology solutions. With a team of experienced scientists and cutting-edge technology, we are dedicated to accelerating scientific discovery and innovation. If you are interested in our services or have any questions, please feel free to contact us.