Acta Medica Medianae
Vol. 53, No 1, March, 2014
UDC 61
ISSN 0365-4478(Printed version)
ISSN 1821-2794(Online)
 

Correspondence to:

Jadranka Odović

Faculty of Pharmacy

Department of Analytical Chemistry

Vojvode Stepe 450

11221 Belgrade, Serbia

E-mail: jodovic@pharmacy.bg.ac.rs

Original article                                                                                  UDK: 615.363

                                                                                                            doi:10.5633/amm.2014.0104

IN SILICO EVALUATION OF ANGIOTENSIN II RECEPTOR ANTAGONIST’S PLASMA PROTEIN BINDING USING COMPUTED MOLECULAR DESCRIPTORS

Jadranka Odović¹, Jasna Trbojević-Stanković²

University of Belgrade Faculty of Pharmacy, Department of Analytical Chemistry, Belgrade, Serbia¹

Clinical Center "Dr Dragiša Mišović", Clinic of Urology, Department of Hemodialysis, Belgrade, Serbia²

The discovery of new pharmacologically active substances and drugs modeling led to necessity of predicting drugs properties and its ADME data. Angiotensin II receptor antagonists are a group of pharmaceuticals which modulate the renin-angiotensin-aldosterone system and today represent the most commonly prescribed anti-hypertensive drugs. The aim of this study was to compare different molecular properties of seven angiotensin II receptor antagonists / blockers (ARBs), (eprosartan, irbesartan, losartan, olmesartan, telmisartan, valsartan) and their plasma protein binding (PPB) data. Several ARBs molecular descriptors were calculated using software package Molinspiration Depiction Software as well as Virtual Computational Chemistry Laboratory (electronic descriptor – PSA, constitutional parameter – Mw, geometric descriptor – Vol, lipophilicity descriptors - logP values, aqueous solubility data – logS). The correlations between all collected descriptors and plasma protein binding data obtained from relevant literature were established. In the simple linear regression poor correlations were obtained in relationships between PPB data and all calculated molecular descriptors.  In the next stage of the study multiple linear regression (MLR) was used for correlation of PPB data with two different descriptors as independent variables. The best correlation (R²=0.70 with P<0.05) was established between PPB data and molecular weight with addition of volume values as independent variables. The possible application of computed molecular descriptors in drugs protein binding evaluation can be of great importance in drug research. Acta Medica Medianae 2014;53(1):19-24.

Key words: molecular descriptor, angiotensin II receptor antagonists, plasma protein binding