3D-QSAR refers to the application of force field calculations, requiring the three-dimensional structure of a given set of small molecules (training set) with known activities. The training set needs to be superimposed (aligned) by experimental data (based on ligand-protein crystallography) or molecular superposition software. It uses calculated potentials, such as Lennard-Jones potentials rather than experimental constants, but related to the entire molecule, rather than individual substituents. It studies the spatial field (the shape of the molecule) and the electrostatic field related to each other through partial least squares regression (PLS).

Figure 1.3D-QSAR.

Overall solutions

• Data mining approach

Molecule mining approaches is a special case of structured data mining approaches. It applies a similarity matrix based prediction or an automatic fragmentation scheme into molecular substructures. There are also other approaches using maximum common subgraph searches or graph kernels.

• Matched molecular pair analysis

Typical QSAR models derived from nonlinear machine learning are seen as a "black box," which fails to guide medicinal chemists. There is a relatively new concept of matched molecular pair analysis or prediction driven MMPA that is coupled with QSAR model to identify activity cliffs.

Our services

For validation of QSAR models, usually various strategies are adopted:

• Internal validation or cross-validation (actually, while extracting data, cross validation is a measure of model robustness, the more a model is robust (higher q2) the less data extraction perturb the original model).
• External validation by splitting the available data set into training set for model development and prediction set for model predictivity check.
• Blind external validation by application of model on new external data.
• Data randomization or Y-scrambling for verifying the absence of chance correlation between the response and the modeling descriptors.

Our advantages

• CD ComputaBio has prepared several databases for pharmacophore screening and molecular docking.
• The user can specify the required database for us to prepare.
• CD ComputaBio can customize a service plan that meets your scientific research needs accordingly.

CD ComputaBio can offer you but not limited to:

• Structure-based Virtual Screening (SBVS) Service
• Reverse Virtual Screening
• 2D-QSAR Service

CD ComputaBio' 3D-QSAR service can significantly reduce the cost and labor of subsequent experiments. 3D-QSAR service is a personalized and customized innovative scientific research service. Each project needs to be evaluated before the corresponding analysis plan and price can be determined. If you want to know more service prices or technical details, please feel free to contact us.

3D-QSAR Service FAQs

• • Q: What is QSAR?

    • A: Quantitative Structure-Activity Relationship (QSAR) is an active research field at home and abroad. It is mainly based on various molecular descriptors and modeling algorithms to establish the qualitative/quantitative relationship between the structure of a compound and its physicochemical properties, biological activity, toxicological effects, environmental behavior and convergence. With the rapid development of computer technology, QSAR has stepped into a new level of academic research in many fields such as chemistry, drugs, environment and health. At the same time, QASR is playing an increasingly important role in the research and development, risk assessment, registration and management of industrial chemicals, pesticides, disinfectants, cosmetics, food contact materials and additives, and pharmaceuticals, as its acceptance by regulatory agencies increases.

  • Q: What are the activity parameters in QSAR?

    • A: The activity parameters are one of the elements constituting the two-dimensional quantitative constitutive relationship, people choose different activity parameters according to the system under study, the common activity parameters are: half effective amount, half effective concentration, half inhibition concentration, half lethal amount, minimum inhibition concentration, etc. All activity parameters must use the amount of the substance as the unit of measurement in order to eliminate the influence of molecular weight, so as to truly reflect the molecular level of physiological activity at the molecular level. In order to obtain a better mathematical model, the activity parameters are generally taken as negative logarithms in the two-dimensional quantitative constitutive relationships and then statistically analyzed.

  • Q: What is the comparative molecular field analysis method?

    • A: This method analyzes the hydrophobic, electrostatic and steric field distributions of molecules in three-dimensional space and regresses the drug activity on these parameters as variables. The basic principle is that if a group of similar compounds act in the same way on the same target, their biological activity depends on the difference of the molecular field around each compound, which reflects the non-bonded interaction properties between the drug molecule and the target.

  • Q: What is the 5 rules that QSAR model needs to follow?

    • A:

      Determined endpoint

      Define the operation method

      Define the scope of application

      Appropriate validation of model fit, robustness and predictive capability

      If possible, to explain the mechanism.
  • Q: What is the purpose of QSAR model?

    • A: The purpose of QSAR models is usually to:

      Predict the biological activity of unassayed or new compounds and determine which molecular structural properties determine the biological activity of a compound, e.g., in pharmacological studies, QSAR studies can be used to modify the molecular structure of a drug to improve efficacy or to further understand the biological mechanism.