Molecular characterization based on prediction of protein affinity and application thereof

A protein and affinity technology, applied in the analysis of two-dimensional or three-dimensional molecular structure, molecular design, instruments, etc., can solve the problems of incomplete, false negative and incomplete links between molecules and biological activities, and achieve superior skeleton transition performance , Build robust and accurate effects with a wide range of applications

Pending Publication Date: 2020-06-16
CENT SOUTH UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The disadvantage of this incomplete data matrix is ​​passed on to the molecule through the characterization, making the link between the molecule and the biological activity incomplete
Some studies will default the missing value to 0, that is, the molecule has no binding force with the protein of the test or the molecule has no such biological activity. This processing method leads to false negatives

Method used

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  • Molecular characterization based on prediction of protein affinity and application thereof
  • Molecular characterization based on prediction of protein affinity and application thereof
  • Molecular characterization based on prediction of protein affinity and application thereof

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0064] A computational target spectrum, its construction process see figure 1 , the specific construction steps are:

[0065] (1) Data collection: collect target protein and its activity data.

[0066] Collect multiple protein targets from the database and literature, and then download the activity data of each protein target from the ChEMBL database. The activity data includes: IC50 (half maximal inhibitory concentration, half inhibitory concentration), which refers to the half maximal inhibitory concentration when the specified biological process is inhibited required drug or inhibitor concentration), EC50 (halfmaximal effective concentration, half maximum effect concentration), refers to the concentration of drug or inhibitor that can reach 50% of the maximum biological effect after a specific exposure time), inhibition constant (Ki value, the half-dissociation concentration of the drug) in the data of any activity value. The final activity data value in this embodiment i...

Embodiment 2

[0084] An application of the calculated target spectrum of embodiment 1 in the skeleton transition, its application process can be found in figure 2 , the specific construction steps are:

[0085] (1) Active molecule database: used from the literature: Vogt, M.; Stumpfe, D.; Geppert, H.; Bajorath, J. Scaffold Hopping Using Two-Dimensional Fingerprints: True Potential, Black Magic, or a Hopeless Endeavor? Guidelines for VirtualScreening.J Med Chem 2010,53,(15),5707-5715. The constructed database includes active molecules of 17 targets, and only select Ki or IC50 less than 1μm, the number of heavy atoms within 10-50 and side A molecule in which the number of non-hydrogen atoms in the chain group is less than the number of non-hydrogen atoms in the backbone. Each target has at least 10 different Bemis-Murcko frameworks (proposed by Bemis and Murcko, defined as a scaffold extracted from a molecule that removes the R-group but retains the linker between the ring systems), and eac...

Embodiment 3

[0094] An application of the computational target profile of Example 1 to predict protein targets, the construction process of which is as follows:

[0095] (1) The drug bromocriptine is input into the consensus model, and the calculated target spectrum of bromocriptine is output to form a molecular characterization.

[0096] (2) We will calculate the predicted probability value in the target spectrum as the binding affinity value between the compound and the protein target, and rank the targets according to the binding affinity value.

[0097] (3) Bromocriptine was shown in computational target profiling to potentially interact with a novel protein D(1A) dopamine receptor (UniprotID: Q95136). Bromocriptine mesylate is a semisynthetic ergot alkaloid derivative with strong dopaminergic activity and is indicated for the treatment of Parkinson's disease. By consulting relevant literature, it was found that the binding affinity between bromocriptine and D(1A) dopamine receptors (...

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Abstract

The invention discloses molecular characterization based on prediction of protein affinity. The molecular characterization is constructed by adopting the following method: collecting a protein targetand activity data thereof; selecting and calculating a plurality of different descriptors of each protein target, and selecting a plurality of different machine learning algorithms; combining the calculated descriptors with a machine learning algorithm in pairs to form a plurality of different single models; calculating an average probability value of a single model, and forming a consensus modelby taking the average probability value as a binding strength value of a molecule and a protein target; and in the consensus model, inputting a to-be-detected molecule, outputting and calculating a target spectrum, and forming molecular characterization. Molecular characterization is described from the perspective of biological space, binding affinity between a compound and a target is integratedinto the molecular characterization, and new activity or biological information is obtained through integrity prediction of an organism; a result is quickly obtained by utilizing a computer, and is quicker and more efficient compared with test-based bioactive molecule characterization.

Description

technical field [0001] The invention relates to the field of computer-aided drug design, in particular to a molecular characterization based on predicted protein affinity and its application. Background technique [0002] In the current drug design process, in order to shorten the drug research cycle and control the cost of drug development, computer-aided molecular design has become an indispensable tool in the drug development process. Computer-aided molecular design can be divided into ligand-based and receptor-based methods. Ligand-based methods are mostly based on the assumption that compounds with similar structures have similar biological activities, and the key point is how to characterize the relationship between molecules and biological activities. [0003] Existing solutions and disadvantages: Existing molecular characterization can be divided into two types based on chemical structure and based on biological activity. Traditional molecular characterization of c...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16B15/30G16C20/50G16C20/70
CPCG16B15/30G16C20/50G16C20/70
Inventor 曹东升刘璐
Owner CENT SOUTH UNIV
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