QSAR and complex network study of the chiral HMGR inhibitor structural diversity

• Published in: Bioorganic & medicinal chemistry Vol. 17; no. 1; pp. 165 - 175
• Main Authors: García, Isela, Munteanu, Cristian Robert, Fall, Yagamare, Gómez, Generosa, Uriarte, Eugenio, González-Díaz, Humberto
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Ltd 2009; Elsevier
• Subjects: 3-Hydroxy-3-methyl-glutaryl coenzyme A reductase; Anti-parasite drug; Antibiotics. Antiinfectious agents. Antiparasitic agents; Antiparasitic agents; Atherosclerotic disease; Biological and medical sciences; Chagas’ disease; Chiral compound; Cholesterol level; Complex network; General and cellular metabolism. Vitamins; Humans; Hydroxymethylglutaryl CoA Reductases; Hydroxymethylglutaryl-CoA Reductase Inhibitors - chemistry; Hydroxymethylglutaryl-CoA Reductase Inhibitors - pharmacology; Lipid-lowering agent; Medical sciences; Models, Molecular; Pharmacology. Drug treatments; QSAR; Quantitative Structure-Activity Relationship; Stereoisomerism; Topological indices; Trypanosoma cruzi; 3-Hydroxy-3-methyl-glutaryl coenzyme A reductase; Atherosclerotic disease; QSAR; Lipid-lowering agent; Complex network; Chagas’ disease; Chiral compound; Cholesterol level; Topological indices; Anti-parasite drug; Trypanosoma cruzi; Chagas'disease; Modeling; Antiprotozoal agent; reductase; 3-Hydroxy-3-methyl-glutaryl coenzyme A; Structure activity relation; Molecular model; Kinetoplastida; Protozoa; Enzyme; Prediction; Enzyme inhibitor; Cholesterol; Topological index; Parasiticide; Hydroxymethylglutaryl-CoA reductase; Oxidoreductases; Antilipemic agent
• ISSN: 0968-0896; 1464-3391
• DOI: 10.1016/j.bmc.2008.11.007

Efficient drugs such as statins or mevinic acids are inhibitors of the rate-limiting enzyme of cholesterol biosynthesis, 3-hydroxy-3-methyl-glutaryl coenzyme A reductase (HMGR), an enzyme responsible for the double reduction of 3-hydroxy-3-methyl-glutaryl coenzyme A into mevalonic acid. These compounds promoted the synthesis and evaluation of new inhibitors for HMGR, named HMGRIs. The high number of possible candidates creates the necessity of Quantitative Structure–Activity Relationship models in order to guide the HMGRI synthesis. There are two main problems of the reported QSAR models: the homogeneous series of the compounds and the chirality of many candidates. In this work, we propose for the first time a QSAR model for a very large and heterogeneous series of HMGRIs. The model is based on the Topological Indices (TIs) of molecular structures. Using the predictions of this model as input, we construct the first complex network that describes the drug–drug similarity relationships for more than 1600 experimentally non-explored chiral HMGRIs isomers. We also presented a reduced version of this network (Giant Component) that contains the most representative set of chiral HMGRI candidates. The work suggests a new mixed application in the QSAR study of relevant aspects of structural diversity by using chiral/non-chiral TIs, combined with complex networks.