Cluster Analysis Service

Cluster analysis

QSAR is to quantitatively establish the relationship between molecular structure and properties. Through the analysis of existing active molecules, the structure and physical chemical parameters of the compound are used as independent variables, and the biological activity is the dependent variable. The chemical structure and chemical structure of the compound are established by mathematical statistics. The purpose of establishing QSAR is to explain how the biological activity of the compound changes with the structure of the compound (such as topological structure, steric hindrance, etc.) and its physical and chemical parameters (solubility, hydrophobicity, polarity, etc.), so as to infer its possible mechanism of action, and then predict its activity based on the structure data of the new compound or change the structure of the existing compound to improve its activity, and use molecular parameters to study the absorption, distribution, metabolism, and excretion of small molecules in organisms by mathematical and statistical means.

Overall solutions

CD ComputaBio has developed a variety of QSAR technologies to help you obtain the best QSAR model to achieve leading processes.

  • Comparative Molecular Field Analysis (CoMFA)
    CoMFA is the earliest used 3D-QSAR method and has been a well-deserved tool for decades. According to the position of the lattice point, use the cutoff value (±30 kcal/mol) to modify the space and electrostatic value. CoMFA generates an equation that relates the biological activity to the contribution of the interactive energy field at each grid point.
    3D-QSAR Models

    Figure 1. Template CoMFA Generates Single 3D-QSAR Models.(Cramer R D,et al.2015)

  • Comparative Molecular Surface Analysis (CoMSA)
    CoMSA is a non-grid 3D-QSAR method that uses the average electrostatic potential of the molecular surface to mark specific areas defined on the molecular surface. In this method, the geometry of the data set is optimized for the molecules and part of the atomic charge is assigned to them.
  • Hologram QSAR (HQSAR)
    HQSAR is a two-dimensional QSAR method that uses the known PPB to conduct a series of molecular studies with diverse structures. This model is used to predict the structure-activity relationship based on fragments, which has powerful predictive power.

Our service process

CD ComputaBio provides a 3D-QSAR pipeline, which can effectively perform force field calculations that require a three-dimensional structure of the training set (measured through experiments with known activities). Then use feature extraction and the following machine learning methods to reduce the created data space. Our workflow includes biological data analysis, optimizing the 3D structure of biomolecules, determining the bioactive conformation of biomolecules, calculating the molecular interaction energy field, 3D QSAR model generation and verification, etc. This one-step 3D-QSAR workflow is designed to help researchers determine the determinants of the biological activity of small molecules, optimize existing lead to improve activity, and predict the biological activity of untested compounds.

Services items

Project name 3D-QSAR service
Our services
  • We can provide automatic 3D-QSAR workflow.
  • Powerful statistical techniques that we can build models.
  • Our 3D-QSAR service can improve the biological activity of existing leading compounds.
  • 3D-QSAR service can be used for prediction of unknown compound activities.
Cycle Depends on the time you need to simulate and the time required for the system to reach equilibrium.
Product delivery mode The simulation results provide you with the raw data and analysis results of molecular dynamics.
Price Inquiry

Our 3D-QSAR analysis represents a valuable medicinal chemistry tool, and the growing information from structural biology will surely provide valuable feedback on the assumptions that form the basis of the 3D-QSAR method. The generated QSAR model will be thoroughly verified internally and externally (in cooperation with customers) using strict cross-validation techniques. If you have any needs in this regard, please feel free to contact us.


  • Cramer R D . Template CoMFA Generates Single 3D-QSAR Models that, for Twelve of Twelve Biological Targets, Predict All ChEMBL-Tabulated Affinities. Plos One, 2015, 10.


Online Inquiry

CD ComputaBio

Copyright © 2024 CD ComputaBio Inc. All Rights Reserved.