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QSAR and Molecular Modeling Studiesof Factor Xa and Thrombin Inhibitors

  • Dimitra Hadjipavlou-LitinaEmail author
Chapter
Part of the Topics in Heterocyclic Chemistry book series (TOPICS, volume 4)

Abstract

Thrombotic disorders remain the major cause of death and disability in Western society. Many approaches to develop antithrombotic drugs that interfere with enzymes in the coagulation system have been pursued over the past few decades. Factor FXa and thrombin are both bound to and are enzymatically active in blood clots. In this article, a brief review is presented on the QSAR and molecular modelling studies on FXa and thrombin inhibitors reported during the last decade. The results from the widely used CoMFA and CoMSIA methods have been included. Analogues with various heterocyclic rings, isoquinoline derivatives, five- or six-membered heteroaryl derivatives, benzoxazinones, and tetrazoles are included in the discussion. Hydrophobic property of molecules is shown to play a significant role. In most of the cases, CMR/MR as well as Sterimol parameters have been shown to be important. Electronic factors, with the exception of the Hammett's constant, have not been found to be of much importance.

Serine proteases Thrombin and Factor FXa QSAR Molecular modeling Heterocycles 

Abbreviations

AFMoC

Adaptation of fields for molecular comparison

Å

Angstrom

AVRES

Average of absolute values of residuals

C log P

Lipophilicity values calculated theoretically according to Hansch and Leo

CoMSIA

Comparative molecular similarity index analysis

CoMFA

Comparative molecular field analysis

COMBINE

Comparative binding energy

Df

Degrees of freedom

LFER

Free energy related

LMWS

Low molecular weight heparins

GA-MLR

Genetic algorithm multiple linear regression

MLR

Multiple linear regression

PLS

Partial least squares

PDB

Protein data bank

QSAR

Quantitative structure activity relationships

QSPR

Quantitative structure property relationships

PRESS

Sum of the squared errors of prediction

r2a

Adjusted correlation coefficient

r2bs

Bootstrapped correlation coefficient

r2pred

(SD-PRESS)/SD

RMS

Root mean square

RMSE

Root mean square error

Spress

Standard deviation sum of the squared errors of prediction

SDEP

Standard deviation sum of the error of prediction

SlogP

Program for the estimation of logP using the atom – weighted solvent accessible surface areas

tPA

Tissue-type plasminogen activator

TScore

Tailored scored function

uPA

Urokinase-type plasminogen activator

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Authors and Affiliations

  1. 1.Department of Pharmaceutical Chemistry, School of PharmacyAristotle University of ThessalonikiThessalonikiGreece

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