Drug Discovery and Design for Complex Diseases through QSAR Computational Methods

Munteanu, Cristian R.; Fernández-Blanco, Enrique; Seoane, José A.; Izquierdo-Novo, Pilar; Rodríguez-Fernández, José Ángel; Prieto-Gonzalez, Jose Maria; Rabuñal, Juan R.

doi:10.2174/138161210792389252

Cited by 38 publications

(24 citation statements)

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“…9,10 These techniques have been particularly helpful for ADME/Tox predictions, providing a useful and reliable alternative to in vivo assessments. QSAR modeling has also been helpful in predicting drug distribution/penetration into specific biological compartments such as the blood-brain barrier (BBB); for instance, a highly predictive model of penetration (R 2 = 0.80 in an external validation set of 10 compounds) as well as specific contributors to penetration, such as van der Waals surface area and active transport, was reported recently.…”

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confidence: 99%

Short Communication: Cheminformatics Analysis to Identify Predictors of Antiviral Drug Penetration into the Female Genital Tract

Thompson

Sedykh

Nicol

et al. 2014

AIDS Research and Human Retroviruses

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The exposure of oral antiretroviral (ARV) drugs in the female genital tract (FGT) is variable and almost unpredictable. Identifying an efficient method to find compounds with high tissue penetration would streamline the development of regimens for both HIV preexposure prophylaxis and viral reservoir targeting. Here we describe the cheminformatics investigation of diverse drugs with known FGT penetration using cluster analysis and quantitative structure-activity relationships (QSAR) modeling. A literature search over the 1950-2012 period identified 58 compounds (including 21 ARVs and representing 13 drug classes) associated with their actual concentration data for cervical or vaginal tissue, or cervicovaginal fluid. Cluster analysis revealed significant trends in the penetrative ability for certain chemotypes. QSAR models to predict genital tract concentrations normalized to blood plasma concentrations were developed with two machine learning techniques utilizing drugs' molecular descriptors and pharmacokinetic parameters as inputs. The QSAR model with the highest predictive accuracy had R 2 test = 0.47. High volume of distribution, high MRP1 substrate probability, and low MRP4 substrate probability were associated with FGT concentrations ‡ 1.5-fold plasma concentrations. However, due to the limited FGT data available, prediction performances of all models were low. Despite this limitation, we were able to support our findings by correctly predicting the penetration class of rilpivirine and dolutegravir. With more data to enrich the models, we believe these methods could potentially enhance the current approach of clinical testing.

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confidence: 99%

Short Communication: Cheminformatics Analysis to Identify Predictors of Antiviral Drug Penetration into the Female Genital Tract

Thompson

Sedykh

Nicol

et al. 2014

AIDS Research and Human Retroviruses

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“…Some recent issues guestedited by González-Díaz et al review many of these techniques. See for instance, papers published in Current Topics in Medicinal Chemistry in 2008 [14][15][16][17][18][19][20][21][22][23], Current Proteomics in 2009, and Current Drug Metabolism [24][25][26][27][28][29][30][31] or Current Pharmaceutical Design in 2010 [32][33][34][35][36][37][38][39][40]. In this work we review computational chemistry and bioinformatics methods used to study an interesting class of peptides called conotoxins, and their possible interaction with HERG channels.…”

Section: Introductionmentioning

confidence: 99%

Conotoxins: Review and Docking Studies to determine potentials of Conotoxin as an Anticancer Drug Molecule

Dave

Lahiry²

2012

CTMC

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It is known that potassium channels are important for cell proliferation. HERG, a potassium channel protein, is a transmembrane protein, which increases in concentration on the cell surface of cancer cells. Apart from cancer cells, this protein is found only in the brain & heart tissue, in very low number. The proliferation of cells in cancer is dependent on activation of this protein, and it has been noted that blocking of this protein with drug molecule, helps inhibit the proliferation of the cells further. The current work aims to study the binding potentials of κ-PVIIA, conotoxin isolated from Conus purpurascens venom with HERG K+ channel of tumor cells, where HERG mutation has been noted. The toxin under consideration i.e. κ-conotoxins-PVIIA (κ-PVIIA) is a 27 residue peptide. The docking studies suggest that the conotoxin binds stably to the HERG protein. The study shows that the peptide interacts with the charged extracellular unit of the HERG protein, i.e. the extracellular portion of the S5 domain named S5-P extracellular linker. Study of binding of toxins of similar origin, with normal potassium channels has been studied in silico. Further, wet laboratory work needs to be conducted for development of a drug molecule from this toxin, to treat some number of cancers.

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“…This year, another issue [48] has been published, focusing on QSAR/QSPR models and graph theory used to approach Drug ADMET processes and Metabolomics [49][50][51][52][53][54][55][56]. Last, one of the most recent issues published has been devoted to discuss the applications of QSAR in Pharmaceutical Design [57][58][59][60][61][62][63][64][65][66]. In the present work, we firstly review the state-ofthe-art on the design, synthesis, and biological assay ofsecretase inhibitors.…”

Section: Introductionmentioning

confidence: 99%

Review of Synthesis, Biological Assay and QSAR Studies of β-Secretase Inhibitors

Nino¹,

Garcia-Pintos²,

Rodríguez‐Borges³

et al. 2011

CAD

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Alzheimer's disease (AD) is highly complex. While several pathologies characterize this disease, amyloid plaques, composed of the β-amyloid peptide, are hallmark neuropathological lesions in Alzheimer's disease brain. Indeed, a wealth of evidence suggests that β-amyloid is central to the pathophysiology of AD and is likely to play an early role in this intractable neurodegenerative disorder. The BACE-1 enzyme is essential for the generation of β-amyloid. BACE-1 knockout mice do not produce β-amyloid and are free from Alzheimer's associated pathologies, including neuronal loss and certain memory deficits. The fact that BACE-1 initiates the formation of β-amyloid, and the observation that BACE-1 levels are elevated in this disease provide direct and compelling reasons to develop therapies directed at BACE-1 inhibition, thus reducing β-amyloid and its associated toxicities. In this sense, quantitative structure-activity relationships (QSAR) could play an important role in studying these β-secretase inhibitors. QSAR models are necessary in order to guide the β-secretase synthesis. This work is aimed at reviewing different design and synthesis and computational studies for a very large and heterogeneous series of β-secretase inhibitors. First, we review design, synthesis, and Biological assay of β-secretase inhibitors. Next, we review 2D QSAR, 3D QSAR, CoMFA, CoMSIA and Docking with different compounds to find out the structural requirements. Next, we review QSAR studies using the method of Linear Discriminant Analysis (LDA) in order to understand the essential structural requirement for receptor binding for β- secretase inhibitors.

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Drug Discovery and Design for Complex Diseases through QSAR Computational Methods

Cited by 38 publications

References 0 publications

Short Communication: Cheminformatics Analysis to Identify Predictors of Antiviral Drug Penetration into the Female Genital Tract

Short Communication: Cheminformatics Analysis to Identify Predictors of Antiviral Drug Penetration into the Female Genital Tract

Conotoxins: Review and Docking Studies to determine potentials of Conotoxin as an Anticancer Drug Molecule

Review of Synthesis, Biological Assay and QSAR Studies of β-Secretase Inhibitors

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Drug Discovery and Design for Complex Diseases through QSAR Computational Methods

Cited by 38 publications

References 0 publications

Short Communication: Cheminformatics Analysis to Identify Predictors of Antiviral Drug Penetration into the Female Genital Tract

Short Communication: Cheminformatics Analysis to Identify Predictors of Antiviral Drug Penetration into the Female Genital Tract

Conotoxins: Review and Docking Studies to determine potentials of Conotoxin as an Anticancer Drug Molecule

Review of Synthesis, Biological Assay and QSAR Studies of &#946;-Secretase Inhibitors

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Review of Synthesis, Biological Assay and QSAR Studies of β-Secretase Inhibitors