Surface Properties Modeling Services
Surface properties are key factors used to characterize molecules and to display and quantify their interactions, allowing researchers to gain insight into how molecules behave in different environments. CD ComputaBio excels in using advanced computational analysis technologies to model and analyze the surface properties of your target molecules, thereby promoting the development of innovative drugs.
Introduction to Molecular Surface Properties
Molecular surface properties refer to the physical and chemical properties of molecules' external surfaces, including charge distribution, hydrophobic and hydrophilic regions, surface shape, polarity, and energy state. These properties determine how molecules interact with other molecules in the surrounding environment, such as binding, recognition, and reaction.
Fig.1 Molecular surface properties of human (P)RR. (Ebihara A, et al.; 2023)
In biological systems and drug development, molecular surface properties have an important influence on protein-ligand binding, enzyme catalytic activity, signal transduction, and the mechanism of action of drugs. As a typical example, the ability of a drug molecule to penetrate the cell membrane is typically influenced by its lipophilicity. Accurately describing and predicting molecular surface properties helps to understand the nature of biological processes, promoting the development and design of new drugs. At present, machine learning and computer analysis have become powerful tools for managing large-scale data and identifying statistical relationships, allowing in-depth analysis of molecular surface properties and obtaining key features of the corresponding molecules, such as protein images and surface features.
Our Services
At CD ComputaBio, our scientists combine high-performance computing and deep learning technologies to perform detailed quantification and visualization of molecular surface properties, helping you understand the interaction mechanisms of molecules under different conditions. Our services include but are not limited to:
Thanks to our expertise and rich experience, CD ComputaBio provides customized solutions based on the characteristics of your molecules. Our scientists can handle a variety of molecule types, including but not limited to:
Surface Properties Modeling for Small Molecules
Surface Properties Modeling for Carbohydrate Molecules
Surface Properties Modeling for Nucleotide Molecules
Service Highlights
CD ComputaBio's service advantages are based on deep expertise and innovative technologies in the field of biomolecular surface property modeling. Here are the unique values we provide to you:
Advanced Technology Platform
Our platform integrates high-performance computing, advanced algorithms and artificial intelligence technology, and can accurately simulate and predict the surface structure and physical and chemical properties of biological macromolecules such as proteins and nucleic acids.
Customized Solutions
We provide customized surface property modeling solutions. By working closely with your team, we gain a deep understanding of your research background and needs and customize the most suitable modeling strategies and simulation methods.
Fast Delivery Cycle
We use efficient project management processes and automated modeling tools to ensure that high-quality simulation and analysis results are delivered as quickly as possible. We promise to meet your research needs as quickly as possible while ensuring the accuracy of the results.
CD ComputaBio's surface properties modeling services offer customized solutions to meet the unique needs of each client. Please feel free to contact us to discuss your project requirements and how we can leverage our expertise and resources to support your research and development efforts.
References:
- Ebihara A, et al. Mapping the protein binding site of the (pro)renin receptor using in silico 3D structural analysis. Hypertens Res. 2023 Apr;46(4):959-971.
- Guanghao Hu, et al. Protein Classes Predicted by Molecular Surface Chemical Features: Machine Learning-Assisted Classification of Cytosol and Secreted Proteins. The Journal of Physical Chemistry B. 2024 128 (35): 8423-8436
* For Research Use Only.
Related Services
