How Can Network-Pharmacology Contribute to Antiepileptic Drug Development?

Network-pharmacology is a field of pharmacology emerging from the observation that most clinical drugs have multiple targets, contrasting with the previously dominant magic bullet paradigm which proposed the search of exquisitely selective drugs. What is more, drug targets are often involved in multiple diseases and frequently present co-expression patterns. Therefore, useful therapeutic information can be drawn from network representations of drug targets. Here, we discuss potential applications of drug-target networks in the field of antiepileptic drug development.Fil: Di Ianni, Mauricio Emiliano. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Ciencias Biológicas. Cátedra de Química Medicinal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaFil: Talevi, Alan. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Ciencias Biológicas. Cátedra de Química Medicinal; Argentin

How Can Network-Pharmacology Contribute to Antiepileptic Drug Development?

Network-pharmacology is a field of pharmacology emerging from the observation that most clinical drugs have multiple targets, contrasting with the previously dominant magic bullet paradigm which proposed the search of exquisitely selective drugs. What is more, drug targets are often involved in multiple diseases and frequently present co-expression patterns. Therefore, useful therapeutic information can be drawn from network representations of drug targets. Here, we discuss potential applications of drug-target networks in the field of antiepileptic drug development.Facultad de Ciencias Exacta

Topología molecular aplicada a la búsqueda de nuevos fármacos para el tratamiento de la epilepsia refractaria

La epilepsia es un desorden crónico del cerebro que afecta a alrededor de 50 millones de personas en todo el mundo. Esta enfermedad no tiene una preferencia etaria, afectando a personas de cualquier edad, sino una regional: el 80% de los pacientes epilépticos pertenecen a países en vías de desarrollo (Organización Mundial de la Salud, 2015). La epilepsia en la mayoría de los casos se caracteriza por la presencia de convulsiones recurrentes, las cuales son breves episodios de contracciones musculares involuntarias de alguna parte del cuerpo (convulsión parcial) o del cuerpo entero (convulsión generalizada). Estos episodios en ocasiones se acompañan por perdida de la conciencia, así como también del control de esfínteres. Las convulsiones son el resultado de una descarga eléctrica excesiva de un grupo neuronal que puede situarse en partes del cerebro muy diversas. Estas cubren un rango de intensidad que va desde breves lapsos de pérdida de atención o espasmos musculares, a severos episodios de contracciones musculares de larga duración. La frecuencia con la que aparecen los episodios epilépticos también es variable, siendo en ocasiones menos de una por año hasta varias por día (Organización Mundial de la Salud, 2015). La batería de tratamientos destinados a hacer frente a esta enfermedad comprende desde sofisticadas técnicas quirúrgicas de resección del foco epileptogénico, pasando por un arsenal de fármacos de diversas familias químicas, hasta llegar a dietas específicas y terapia basada en deportes (Laxer et al., 2014; Löscher, 2011; Arida, 2011). A pesar de los muchos esfuerzos realizados para encontrar un tratamiento exitoso para este mal, actualmente existe un 30% de la población de epilépticos que no logra controlar la aparición de convulsiones, condición conocida como epilepsia refractaria o intratable (Organización Mundial de la Salud, 2015). Además, las terapias farmacológicas actuales, presentan efectos adversos graves y comprometen seriamente la calidad de vida y la adherencia al tratamiento de los pacientes epilépticos (Löscher, 2011; Talevi & Bruno-Blanch, 2013). El impacto de la epilepsia, es multifacético y posee un amplio espectro de efectos. El carácter impredecible y peligroso de las convulsiones eleva el riesgo de lesiones, hospitalización y mortalidad y afecta negativamente la salud mental de los pacientes, que con frecuencia, deriva en ansiedad, depresión y deterioro cognitivo (Kerr, 2012). El presente trabajo de tesis persigue el objetivo general de descubrir nuevos fármacos anticonvulsivos, capaces de controlar la sintomatología de la epilepsia refractaria asociada a regulación hacia arriba de la glicoproteina-P (P-gp), una proteína transportadora que restringe la biodistribución y promueve la eliminación de una gran diversidad de compuestos exógenos desde el organismo (Fromm, 2004; Taft, 2009) entre otras funciones. Abundante evidencia científica relaciona la sobre-expresión de esta glicoproteina con el fenómeno de resistencia múltiple a fármacos en varias enfermedades, entre ellas la epilepsia (Thomas, 2003; Kim, 1998; Löscher, 2005; Chengyun, 2006; Brandt, 2006; Marchi, 2004; Lazarowski, 2007; Robey, 2008). La afinidad de las sustancias por esta macromolécula es una propiedad relacionada con los procesos ADME/Tox (Administración, Distribución, Metabolismo, Excreción y Toxicidad) a tener en cuenta al momento de iniciar un proyecto de descubrimiento de nuevos fármacos. La incorporación de filtros ADME/Tox in vitro e in silico en las etapas iniciales del proceso de desarrollo de nuevos fármacos ha logrado reducir considerablemente el porcentaje de proyectos que fracasan a nivel preclínico o clínico debido a problemas en la distribución de la droga en el organismo (Kola, 2004; Hop, 2004). Tales filtros descartan en las fases tempranas del proyecto de investigación de nuevos agentes terapéuticos aquellas estructuras que potencialmente podrían presentar características ADME/Tox desfavorables.Facultad de Ciencias Exacta

Development of Conformation Independent Computational Models for the Early Recognition of Breast Cancer Resistance Protein Substrates

ABC efflux transporters are polyspecific members of the ABC superfamily that, acting as drug and metabolite carriers, provide a biochemical barrier against drug penetration and contribute to detoxification. Their overexpression is linked tomultidrug resistance issues in a diversity of diseases. Breast cancer resistance protein (BCRP) is the most expressed ABC efflux transporter throughout the intestine and the blood-brain barrier, limiting oral absorption and brain bioavailability of its substrates. Early recognition of BCRP substrates is thus essential to optimize oral drug absorption, design of novel therapeutics for central nervous systemconditions, and overcome BCRP-mediated cross-resistance issues. We present the development of an ensemble of ligand-based machine learning algorithms for the early recognition of BCRP substrates, from a database of 262 substrates and nonsubstrates compiled from the literature. Such dataset was rationally partitioned into training and test sets by application of a 2-step clustering procedure. The models were developed through application of linear discriminant analysis to randomsubsamples ofDragonmolecular descriptors. Simple data fusion and statistical comparison of partial areas under the curve of ROC curves were applied to obtain the best 2-model combination, which presented 82% and 74.5% of overall accuracy in the training and test set, respectively.Facultad de Ciencias Exacta

Development of Conformation Independent Computational Models for the Early Recognition of Breast Cancer Resistance Protein Substrates

ABC efflux transporters are polyspecific members of the ABC superfamily that, acting as drug and metabolite carriers, provide a biochemical barrier against drug penetration and contribute to detoxification. Their overexpression is linked tomultidrug resistance issues in a diversity of diseases. Breast cancer resistance protein (BCRP) is the most expressed ABC efflux transporter throughout the intestine and the blood-brain barrier, limiting oral absorption and brain bioavailability of its substrates. Early recognition of BCRP substrates is thus essential to optimize oral drug absorption, design of novel therapeutics for central nervous systemconditions, and overcome BCRP-mediated cross-resistance issues. We present the development of an ensemble of ligand-based machine learning algorithms for the early recognition of BCRP substrates, from a database of 262 substrates and nonsubstrates compiled from the literature. Such dataset was rationally partitioned into training and test sets by application of a 2-step clustering procedure. The models were developed through application of linear discriminant analysis to randomsubsamples ofDragonmolecular descriptors. Simple data fusion and statistical comparison of partial areas under the curve of ROC curves were applied to obtain the best 2-model combination, which presented 82% and 74.5% of overall accuracy in the training and test set, respectively.Facultad de Ciencias Exacta

Development of Conformation Independent Computational Models for the Early Recognition of Breast Cancer Resistance Protein Substrates

ABC efflux transporters are polyspecific members of the ABC superfamily that, acting as drug and metabolite carriers, provide a biochemical barrier against drug penetration and contribute to detoxification. Their overexpression is linked tomultidrug resistance issues in a diversity of diseases. Breast cancer resistance protein (BCRP) is the most expressed ABC efflux transporter throughout the intestine and the blood-brain barrier, limiting oral absorption and brain bioavailability of its substrates. Early recognition of BCRP substrates is thus essential to optimize oral drug absorption, design of novel therapeutics for central nervous systemconditions, and overcome BCRP-mediated cross-resistance issues. We present the development of an ensemble of ligand-based machine learning algorithms for the early recognition of BCRP substrates, from a database of 262 substrates and nonsubstrates compiled from the literature. Such dataset was rationally partitioned into training and test sets by application of a 2-step clustering procedure. The models were developed through application of linear discriminant analysis to randomsubsamples ofDragonmolecular descriptors. Simple data fusion and statistical comparison of partial areas under the curve of ROC curves were applied to obtain the best 2-model combination, which presented 82% and 74.5% of overall accuracy in the training and test set, respectively.Facultad de Ciencias Exacta

Interaction of Solid Lipid Nanoparticles and Specific Proteins of the Corona Studied by Surface Plasmon Resonance

The applications of pharmaceutical and medical nanosystems are among the most intensively investigated fields in nanotechnology. A relevant point to be considered in the design and development of nanovehicles intended for medical use is the formation of the "protein corona" around the nanoparticle, that is, a complex biomolecular layer formed when the nanovehicle is exposed to biological fluids. The chemical nature of the protein corona determines the biological identity of the nanoparticle and influences, among others, the recognition of the nanocarrier by the mononuclear phagocytic system and, thus, its clearance from the blood. Recent works suggest that Surface Plasmon Resonance (SPR), extensively employed for the analysis of biomolecular interactions, can shed light on the formation of the protein corona and its interaction with the surroundings. The synthesis and characterization of solid lipid nanoparticles (SLN) coated with polymers of different chemical nature (e.g., polyvinyl alcohol, chitosans) are reported. The proof-of-concept for the use of SPR technique in characterizing protein-nanoparticle interactions of surface-immobilized proteins (immunoglobulin G and bovine serum albumin, both involved in the formation of the corona) subjected to flowing SLN is demonstrated for non-chitosan-coated nanoparticles. All assayed nanosystems show more preference for IgG than for BSA, such preference being more pronounced in the case of polyvinyl-alcohol-coated SLN.Facultad de Ciencias ExactasCentro de Investigación y Desarrollo en Fermentaciones IndustrialesInstituto de Investigaciones Fisicoquímicas Teóricas y Aplicada

Computer-aided identification of anticonvulsant effect of natural nonnutritive sweeteners stevioside and rebaudioside A

Steviol glycosides are natural constituents of Stevia rebaudiana (Bert.) Bert. (Asteraceae) that have recently gained worldwide approval as nonnutritive sweeteners by the Joint Food and Agriculture Organization/World Organization Expert Committee on Food Additives. Cheminformatic tools suggested that the aglycone steviol and several of its phase I metabolites were predicted as potential anticonvulsant agents effective in the seizure animal model maximal electroshock seizure (MES) test. Thus, aqueous infusion from S. rebaudiana was tested in the MES test (mice, intraperitoneal administration), confirming dose-dependent anticonvulsant effect. Afterward, isolated stevioside and rebaudioside A were tested in the MES test, with positive results. Though drug repositioning most often focuses on known therapeutics, this article illustrates the possibilities of this strategy to find new functionalities and therapeutic indications for food constituents and natural products.Fil: Di Ianni, Mauricio Emiliano. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: del Valle, Maria Eugenia. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Enrique, Andrea Verónica. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Rosella, Maria Adelaida. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Ciencias Biológicas; ArgentinaFil: Bruno, Fiorella. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Ciencias Biológicas; ArgentinaFil: Bruno Blanch, Luis Enrique. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Talevi, Alan. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Interaction of Solid Lipid Nanoparticles and Specific Proteins of the Corona Studied by Surface Plasmon Resonance

The applications of pharmaceutical and medical nanosystems are among the most intensively investigated fields in nanotechnology. A relevant point to be considered in the design and development of nanovehicles intended for medical use is the formation of the "protein corona" around the nanoparticle, that is, a complex biomolecular layer formed when the nanovehicle is exposed to biological fluids. The chemical nature of the protein corona determines the biological identity of the nanoparticle and influences, among others, the recognition of the nanocarrier by the mononuclear phagocytic system and, thus, its clearance from the blood. Recent works suggest that Surface Plasmon Resonance (SPR), extensively employed for the analysis of biomolecular interactions, can shed light on the formation of the protein corona and its interaction with the surroundings. The synthesis and characterization of solid lipid nanoparticles (SLN) coated with polymers of different chemical nature (e.g., polyvinyl alcohol, chitosans) are reported. The proof-of-concept for the use of SPR technique in characterizing protein-nanoparticle interactions of surface-immobilized proteins (immunoglobulin G and bovine serum albumin, both involved in the formation of the corona) subjected to flowing SLN is demonstrated for non-chitosan-coated nanoparticles. All assayed nanosystems show more preference for IgG than for BSA, such preference being more pronounced in the case of polyvinyl-alcohol-coated SLN.Facultad de Ciencias ExactasCentro de Investigación y Desarrollo en Fermentaciones IndustrialesInstituto de Investigaciones Fisicoquímicas Teóricas y Aplicada

Computer-Aided Recognition of ABC Transporters Substrates and Its Application to the Development of New Drugs for Refractory Epilepsy

Despite the introduction of more than 15 third generation antiepileptic drugs to the market from 1990 to the moment, about one third of the epileptic patients still suffer from refractory to intractable epilepsy. Several hypotheses seek to explain the failure of drug treatments to control epilepsy symptoms in such patients. The most studied one proposes that drug resistance might be related with regional overactivity of efflux transporters from the ATP-Binding Cassette (ABC) superfamily at the blood-brain barrier and/or the epileptic foci in the brain. Different strategies have been conceived to address the transporter hypothesis, among them inhibiting or down-regulating the efflux transporters or bypassing them through a diversity of artifices. Here, we review scientific evidence supporting the transporter hypothesis along with its limitations, as well as computer-assisted early recognition of ABC transporter substrates as an interesting strategy to develop novel antiepileptic drugs capable of treating refractory epilepsy linked to ABC transporters overactivity.Laboratorio de Investigación y Desarrollo de Bioactivo