Fusion Protein Modeling Service
CD ComputaBio provides comprehensive fusion protein modeling services covering a variety of advanced methods to optimize and select models. The fusion proteins modeling services include structural modeling, stability prediction, thermodynamic property prediction, etc. Our methods are holistic and customizable, ensuring that we meet the unique needs of each client while providing strong customer support, competitive pricing, and fast turnaround time.
Introduction to Fusion Protein Modeling
Fusion protein modeling is a relatively fast computational method that can predict the structure and biological function of fusion proteins. Fusion protein modeling has obvious advantages. Fusion protein modeling combines various bioinformatics, structural biology and molecular modeling strategies to understand how these modified proteins behave and their biological activity in biological systems. Computational modeling enables researchers to quickly generate and evaluate multiple fusion protein designs, thereby accelerating the initial design stage.
Fig 1. An open source in silico workflow to assist in the design of fusion proteins. (Lalaurie C J, et al., 2024)
Our Services
By leveraging advanced modeling platforms and the expertise of a dedicated team, CD ComputaBio provides researchers with services for studying fusion proteins, which is critical for drug discovery, biochemistry, and biological research.
Modeling Types of Fusion Protein
- Thermodynamics Analysis
- Stability Analysis
- More
Software for Fusion Protein Modeling
GROMACS
It is an open-source molecular dynamics simulation software that supports the simulation of various biomolecular systems, has good performance optimization, and is suitable for large-scale parallel computing
APBS (Adaptive Poisson-Boltzmann Solver)
A tool for calculating the electrostatic potential and surface properties of biomolecules, suitable for analyzing protein-protein and protein-ligand interactions
MDAnalysis
A Python library for molecular dynamics trajectory analysis that supports stability assessment and dynamics analysis. MDAnalysis also provides powerful atom selection functions and analysis tools and can access atomic coordinates in the form of NumPy arrays to achieve efficient data processing
PyMOL
PyMOL is a powerful molecular visualization software that is widely used in biomedicine, chemistry, and other fields. It supports the display and editing of various molecular structures such as proteins, nucleic acids, and small molecules, and provides rich visualization tools and operation functions.
Workflow of Our Services
- 01Customer Inquiry
The customer service team collects basic customer needs, including project background, goals, and expected modeling types (such as structural modeling, dynamic simulation, stability analysis, surface property analysis, etc.).
- 02Project Design
Our project design phase includes developing a detailed project plan, designing a solution architecture, determining resource requirements, setting a timeline and budget, etc. This phase aims to provide a clear blueprint for project implementation.
- 03Project Execution
Use appropriate tools (GROMACS, AMBER, APBS, etc.) to model fusion proteins, and use multiple verification strategies to ensure the rationality and accuracy of the model.
- 04Result Delivery
Integrate all modeling data, analysis methods, and optimization suggestions to form a complete project report.
CD ComputaBio is proud to offer a structured, efficient workflow for our fusion protein modeling services. Our team of computational biology experts excels in fusion protein modeling method selection, model optimization, model evaluation, and more. Our approach is designed to ensure that each client's specific needs are met while delivering high-quality, reliable results on time. For more information or to discuss your project, please contact us today!
Reference:
- Lalaurie C J, Zhang C, Liu S M, et al. An open source in silico workflow to assist in the design of fusion proteins[J]. Computational Biology and Chemistry, 2024, 113: 108209.
* For Research Use Only.
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