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Computational Approaches for the Discovery of Novel Hepatitis C Virus NS3/4A and NS5B Inhibitors
protease inhibitors. This gave rise to some problems. The first thing is, too much pharmacophore key features were generated; another is that the research used MOEdock, which is not a highly reliable docking algorithms. Pharmacophore, however, remains a reliable method employed to strengthen QSAR model due to its ability to discard a large amount of inactive compounds.
We have already carried out a research to build a reliable model, and have obtained prominent results. Initially, we started by building a pharmacophore model that includes five key features. Then, based on 110 active compounds, a QSAR model was generated by SVM and GA algorithms. We continued our study by searching on ChemDiv databases with more than 6000 compounds match­ing the resultant pharmacophore model. After that, self-organization maps were built to identify which compounds are in the chemical space capable of being predicted by our QSAR model with high magnitude of reliability. Finally, we performed docking research, using LeadIT, to evaluate potential compounds predicted by QSAR that have high inhibitory activity against NS3/4A protease.
Generally, docking and pharmacophore are all suitable in combining with QSAR model with an aim of identifying a novel active compound inhibiting HCV NS3/4A protease. Especially, a novel scaffold was targeted to synthesize derivatives with simpler structure than original peptidomimetic compounds like danoprevir or simeprevir. In case of a high level of structural complexity such as NS3/4A protease, combining these virtual screening methods has significantly strengthened our QSAR approach.
CONCLUSION
In brief, in the scope of this chapter we have discussed some successful applications of QSAR in devel­oping novel HCV antivirals. More importantly, not only two main promising targets in HCV viral cycle, NS3/4A protease and NS5B reverse transcriptase are taken into account, but also how to discover their novel inhibitor agents such as QSAR, 3D-QSAR, HQSAR, fragment-based QSAR, QSAR integrated into structure-based drug design is concerned. Although further assessment is required, they remain appealing and helpful tools in drug design and the battle against HCV in particular.
FUTURE DIRECTION
Although several potent HCV inhibitors have been suggested, it remains crucial to make more endeavors to find more effective and less toxic chemothepapeutic agents for HCV treatment. In the battle against HCV, computational approaches have been proven powerful tools to assist drug design in the time–con­suming process of identifying new active lead compounds. Both structure-based and ligand-based drug design, namely, QSAR, docking studies, library searching and in silico screening, are exploited to replace conventional experimental screening protocols in drug discovery. However, challenges still remain when a variety of library of compounds makes it unfeasible to control the quality of database. Moreover, reliable methods need to be employed to assure the integrity and quality of models, similarity search, data mining as well as docking in virtual screening process. These problems have to be tackled to achieve the final goal of proposing potential HCV inhibitor structures to synthesize with an aid of computational studies.
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Computational Approaches for the Discovery of Novel Hepatitis C Virus NS3/4A and NS5B Inhibitors
ACKNOWLEDGMENT
This work was supported by the Vietnam’s National Foundation for Science and Technology Devel­opment - NAFOSTED (Grant # 106.99-2012.106 to Khac-Minh Thai and Grant # 104.01.2012.78 to Thanh-Dao Tran).
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Computational Approaches for the Discovery of Novel Hepatitis C Virus NS3/4A and NS5B Inhibitors
KEY TERMS AND DEFINITIONS
Docking: A computational method used to simulate interactions between protein and ligand and to
calculate free energy if interacting process.
HCV Inhibitors: Which have diverse targets including viral attachment, NS3/4A protease, NS5A,
NS5B polymerase, are significant components in Hepatitis C treatment.
Hepatitis C Virus: Positive-sense single-stranded RNA virus belonging to the family Flaviviridae.
Hepatitis C virus is the cause of hepatitis C, which coulds lead to Cirrhosis or Hepatitis cancer, in humans.
NS3/4A Protease: Another protein of Hepatitis C virus, involves in cleaving process in which a poly-
protein is split into many nonstructural proteins, namely NS3, NS4A, NS4B, NS5A, and NS5B protein.
NS5B Polymerase: A protein of Hepatitis C virus, plays an important role in replicating process of
RNA virus.
Pharmacophore: The ensemble of steric and electronic features that is necessary to ensure the optimal
supramolecular interactions with a specific biological target and to trigger or block its biological response.
QSAR: A computational method which uses diverse statistical and mathematical methods to identify
the correlation between bioactivity and molecular descriptors.
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Chapter 10
QSAR Models towards
Cholinesterase Inhibitors
for the Treatment of
Alzheimer’s Disease
C. Gopi Mohan
Amrita Institute of Medical Sciences and Research Centre, India
Shikhar Gupta
National Institute of Pharmaceutical Education and Research, India
ABSTRACT
Alzheimer’s Disease (AD) is a multifactorial neurological syndrome with the combination of aging, genetic, and environmental factors triggering the pathological decline. Interestingly, the importance of the Acetylcholinesterase (AChE) enzyme has increased due to its involvement in the β-amyloid pep­tide fibril formation during AD pathogenesis. In silico technique, QSAR has proven its usefulness in pharmaceutical research for the design/optimization of new chemical entities. Further, QSAR method advanced the scope of rational drug design and the search for the mechanism of drug action. It is a well­established fact that the chemical and pharmaceutical effects of a compound are closely related to its physico-chemical properties, which can be calculated by various methods from the compound structure. This chapter focuses on different Quantitative Structure-Activity Relationship (QSAR) studies carried out for a variety of cholinesterase inhibitors for the treatment of AD. These predictive models will be potentially used for further designing better and safer drugs against AD.
INTRODUCTION
Alzheimer’s Disease (AD) is a multi-factorial syndrome with the combination of aging, genetic, non­genetic causes, and environmental factors triggering the pathological decline (Butters, Deliss & Lucas,
1995). It is a most common form of dementia, with chronic, irreversible and progressive neurodegen­erative disorder.
DOI: 10.4018/978-1-4666-8136-1.ch010
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QSAR Models towards Cholinesterase Inhibitors for the Treatment of Alzheimer’s Disease
AD usually begins after the age of 60, and the risk increases as the age progresses. Younger people in their 30s to 50s may get AD, but it is rare. Approximately, 10% of all the cases of AD are believed to be hereditary in nature. In familial cases, symptoms usually appear within the age range of 30-60 years and known as early-onset AD. This type of AD results from specific genetic mutation of the individual. The late-onset sporadic AD, representing 90% of patients result from multifactorial environmental fac­tors and genetic events, caused due to the inheritance of the apolipoprotein Eε4 allele and other acting polymorphic genes (Rosenberg, 2000). The non-genetic factors are also playing an important role in AD, as the only one third of the identical twins is concordant of the disease (Jin, Gatz, Johansson & Pedersen,
2004). Still the role of the environmental risk factors has remained mysterious, but progress in finding genes causes of AD, as well as increasing risk for it has been firm and impressive.
Several evidences showed that reactive oxygen species (ROS) are involved in most of the neurode­generative pathologies. ROS is the most dangerous reactive species, and which can spoil most of the biological molecules. Hence, it is crucial to maintain the oxidative balance and control in the brain. This is known as the oxygen paradox-oxygen, which is an absolute necessity for our energy-economical aerobic life style. However, it is a potential toxin and our brain is most aerobically active organ, which required ~20% of total oxygen in a resting individual. Normally, these free radicals quickly detoxified by the body’s defense mechanism and firmly regulated by antioxidants. Hence, modifications in normal oxidative metabolism as observed in AD brain suggest that oxidative stress has a crucial role in AD pathogenesis. In general, chemical origin of the bulk of ROS is the reaction of the molecular oxygen with the redox active metals Fe and Cu.
Two distinct histological changes occur in the nerve cells of Alzheimer brain are the formation of extracellular amyloid (‘senile’) plaques developed between neurons and intracellular neurofibrillary tangles developed within neurons, which lead to neurotoxicity. Plaques, which are composed of β-amyloid polypeptides (Aβ) formed by the mutations in the amyloid precursor protein (APP) gene on chromosome 21q and of the presenilin 1 (PS1) and presenilin 2 (PS2) genes on chromosomes 14q and 1q, respectively (Tanzi, Kovacs, Kim, Moir, Guenette, & Wasco, 1996). Amyloidogenesis are responsible for almost one half of the early-onset forms of autosomal dominant inherited disease. An increased synthesis of Aβ in the AD brain is a central point in the amyloid hypothesis and suggests that increased amyloido­genesis and/or decreased amyloid clearance with increased amyloid fibrillation are primarily causal of the pathogenesis of AD (Naslund, Haroutunian, Mohs, Davis, Davies, Greengard, & Buxbaum, 2000). Neurofibrillary tangles are secondary important histological abnormalities, which are composed of hy­perphosphorylated tau protein and links together to form filaments. Increased density of tau deposition within neurons in the brain facilitates Aβ toxicity. APP processing involves 3 classes of enzymes: α-, β-, and γ-secretase (Mullan, Crawford, Axelman, Houlden, Lilius, Winblad, & Lannfelt, 1992). APP is first enzymatically cleaved by γ- or β-secretase, and which in turn was cleaved by γ-secretase. The segment of the molecule produced by α- γ cleavage yielded a soluble fragment and a self-aggregating fragment (β amyloid 40–42) from the portion of the molecule produced by the β-γ cleavage.
Cholinergic hypothesis targeting acetylcholinesterase (AChE) enzyme are one of the major therapeutic strategies adopted for symptomatic relief on AD (Bartus, Dean, Beer & Lippa, 1982). It is a substrate­specific essential enzyme in the family of serine hydrolases, and which degrades the neurotransmitter acetylcholine (ACh) in the nerve synapses. An optimum level of ACh should be maintained in the hip­pocampus and the cortex region of the brain for its proper function (Stahl, 1999). This hypothesis is proven to be successful today by the effective use of cholinesterase inhibitors, to augment the surviving cholinergic activity for the treatment of AD.
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