Active Site Prediction Service
The functionality of proteins and other biomolecules often depends on their active sites. Accurately predicting and analyzing these active sites is critical to advancing research and accelerating the drug discovery process. CD ComputaBio understands the complexity of active site prediction and is committed to providing researchers with advanced computational biology solutions. Our active site prediction services use cutting-edge computational methods to help clients accurately and efficiently identify drug targets, thereby promoting new drug development and deepening the understanding of biological processes.
Introduction to Drug's Active Site Prediction
Active sites refer to key regions in biological macromolecules, such as proteins, enzymes, nucleic acids, etc., that can bind to specific ligands or substrates and exert biological functions. Accurate prediction of active sites can accelerate the drug design process, reduce R&D costs, and improve the success rate. Traditional identification of active sites mainly relies on experimental methods, such as X-ray crystallography, nuclear magnetic resonance (NMR), and mass spectrometry. However, these methods are often time-consuming, expensive, and technically difficult.
Fig. 1 Active site prediction for protein tyrosine phosphatase. (Wang X, et al.; 2024)
With the rapid development of computer technology and bioinformatics, computational-based methods have become an effective way to predict active sites. These methods can quickly and efficiently predict potential active sites, thereby helping to:
Drug Design and Development
In the process of drug development, accurate active site prediction helps identify potential drug targets because it can reveal where small molecules or inhibitors can bind to proteins and regulate their activity.
Disease Mechanism Research
By identifying the active sites of disease-related proteins, researchers can conduct in-depth research on how their dysfunction leads to the occurrence and development of diseases, providing a basis for the development of new treatment strategies.
Biological Function Research
Active site prediction helps to analyze the functional mechanisms of biological macromolecules such as proteins and nucleic acids, understand their roles in biological processes, and provide important clues for basic scientific research.
Our Services
Relying on advanced AI algorithms and high-precision computing models, CD ComputaBio provides highly credible active site prediction solutions for global customers. Our computing platform integrates multi-scale molecular simulation with 3D protein structure databases and chemical databases, allowing efficient prediction of functional regions of biological macromolecules such as proteins and nucleic acids, supporting customers' new drug development process.
Active Site Prediction
Our highly qualified computational biology experts use bioinformatics algorithms and computational tools to predict the location of active sites in proteins or enzymes and identify regions that may interact with substrates, small molecules, or other proteins.
Key Amino Acid Identification
In addition to predicting active sites, we also identify key amino acid residues that play key roles in catalytic activity, ligand binding or protein-protein interaction. This key information helps customers understand the functional mechanism and mode of action of proteins.
Protein-Ligand Docking
Once possible active sites are predicted, our scientists perform molecular docking simulations to predict how small molecule ligands bind to the active sites of these proteins and assess binding affinity and stability.
Mutation Impact Analysis
Furthermore, our scientists also simulate the effects of amino acid mutations on the structure and function of active sites, predicting potential loss or enhancement of function or other property changes due to these mutations.
Our Solutions
Protein Active Site Prediction
- Proteins with known structures - For proteins with known 3D structures, we use algorithms based on physicochemical properties to identify potential active sites, such as ligand binding pockets and functional key residues.
- Proteins lacking structural information - For proteins that lack 3D structures, our scientists first perform homology modeling to generate their 3D structural models and then predict their active sites.
Enzyme Active Site Prediction
- Catalytic (active) site identification - Our scientists identify the catalytic site and cofactor binding site of the enzyme through sequence and structure comparison.
- Substrate specificity analysis - We also provide enzyme interaction prediction services with different substrates, which allows the identification of key binding sites and provides a theoretical basis for your enzyme engineering.
Small Molecule Drug Target Prediction
- Potential target screening - As a complementary service to our active site prediction, our scientists will assist you in analyzing the possible protein binding sites of small molecule compounds, predicting their potential drug targets, and accelerating the new drug discovery process.
- Binding affinity assessment - If necessary, we will also evaluate the binding affinity of small molecules to the active sites of target proteins to provide key information for the structural optimization of your lead compounds.
Methods for Active Site Prediction
Structure-Based Prediction
Utilizing the known three-dimensional structure of the molecule to predict possible active sites by identifying grooves, pockets, and surface features on the structure.
Machine Learning
Extract features from a large amount of known active site data and train machine learning models, such as support vector machines, random forests, or deep learning models to predict new active sites.
Homology Modeling
Predicting the active site of the target protein based on the active sites of homologous proteins with known structures and similar sequences.
If you are looking for breakthroughs in drug development, CD ComputaBio's active site prediction service will be your wise choice. We use cutting-edge AI algorithms and sophisticated computational models to deeply explore potential active sites in protein and nucleic acid structures. Please don't hesitate to contact us to learn how we can help you locate potential drug targets faster and more accurately through active site prediction.
Reference:
- Wang X, et al. Multi-modal deep learning enables efficient and accurate annotation of enzymatic active sites. Nat Commun. 2024;15(1):7348.
* For Research Use Only.
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