Biomedical Chemistry: Research and Methods 2018, 1(4), e00080

Prediction of Progestin Affinity for the Human Progesterone Receptor Based on Corrected RBA Data

A.V. Mikurova*, V.S. Skvortsov

Institute of Biomedical Chemistry, 10 Pogodinskaya str., Moscow, 119121 Russia; *e-mail:

Keywords: progesterone receptor; affinity; molecular docking; molecular dynamics; MM-PBSA

DOI: 10.18097/BMCRM00080

The whole version of this paper is available in Russian.

The modeling of complexes of 3 sets of steroid and nonsteroidal progestins with the ligand-binding domain of the nuclear progesterone receptor was performed. Molecular docking procedure, long-term simulation of molecular dynamics and subsequent analysis by MM-PBSA (MM-GBSA) were used to model the complexes. Using the characteristics obtained by the MM-PBSA method two data sets of steroid compounds obtained in different scientific groups a prediction equation for the value of relative binding activity (RBA) was constructed. The RBA value was adjusted so that in all samples the actual activity was compared with the progesterone activity. The third data set of nonsteroidal compounds was used as a test. The resulted equation showed that the prediction results could be applied to both steroid molecules and nonsteroidal progestins.

Figure 1. The common structure scaffolds of compounds shown at table 1.
Figure 2. Structure of some compounds listed at table 1.
Figure 3. The comparison of predicted RBA values with experimental RBA values in learning and RBI values in prediction (B).

Table 1. The structure and experimental affinity value of the compounds used towards the progesterone receptor (see figs. 1-2). Selection of a particular variant of the ligand-receptor complex after docking.

Table 2. The parameters of the linear regression equations obtained during learning and test results.


This work was performed within the framework of the Program for Basic Research of State Academies of Sciences for 2013-2020. The software tuning on hybrid cluster was supported by the Russian Foundation for Basic Research (project 18-29-03100).


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