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Chemoinformatics in anti-cancer chemotherapy: Multi-target QSAR model for the in silico discovery of anti-breast cancer agents
ArticleAbstract: The discovery of new and more efficient anti-cancer chemotherapies is a field of research in expansiPalabras claves:Anti-BC activity, BC cell lines, In silico design, linear discriminant analysis, mt-QSAR, quantitative contributionsAutores:Alejandro Speck-Planche, Kleandrova V.V., Luan F., Natalia Dias Soeiro Cordeiro M.Fuentes:scopusCell-based multi-target QSAR model for design of virtual versatile inhibitors of liver cancer cell lines
ArticleAbstract: Liver cancers are one of the leading fatal diseases among malignant neoplasms. Current chemotherapeuPalabras claves:ANTICANCER, Artificial Neural Network, Fragment, Liver cancer, multi-target, QSAR, virtual designAutores:Alejandro Speck-Planche, Kleandrova V.V., Nayarisseri A., Scotti L., Scotti M.T.Fuentes:scopusFragment-based QSAR model toward the selection of versatile anti-sarcoma leads
ArticleAbstract: A sarcoma is a type of cancer which is originated from the connective tissue cells. With the time, sPalabras claves:Anti-sarcoma activity, Fragments, linear discriminant analysis, Multi-target QSARAutores:Alejandro Speck-Planche, Kleandrova V.V., Luan F., Natalia Dias Soeiro Cordeiro M.Fuentes:scopusMulti-Condition QSAR Model for the Virtual Design of Chemicals with Dual Pan-Antiviral and Anti-Cytokine Storm Profiles
ArticleAbstract: Respiratory viruses are infectious agents, which can cause pandemics. Although nowadays the danger aPalabras claves:Autores:Alejandro Speck-Planche, Kleandrova V.V.Fuentes:scopusQSAR Modeling for Multi-Target Drug Discovery: Designing Simultaneous Inhibitors of Proteins in Diverse Pathogenic Parasites
ArticleAbstract: Parasitic diseases remain as unresolved health issues worldwide. While for some parasites the treatmPalabras claves:Artificial Neural Network, docking, Fragment, mt-QSAR, multi-target inhibitor, Multilayer Perceptron, parasites, virtual designAutores:Alejandro Speck-Planche, Bezerra Mendonça Junior F.J., Kleandrova V.V., Muratov E., Scotti L., Scotti M.T.Fuentes:scopusQSAR and molecular docking techniques for the discovery of potent monoamine oxidase B inhibitors: Computer-aided generation of new rasagiline bioisosteres
ArticleAbstract: The search for new therapies against neurodegenerative disorders (NDs) such as Alzheimer (AD) and PaPalabras claves:ALZHÉIMER, artificial neural networks, Computer-aided drug design, Molecular docking, Monoamine Oxidase B, Neurodegenerative disorders, Neuroprotective, PÁRKINSON, QSAR, RasagilineAutores:Alejandro Speck-Planche, Kleandrova V.V.Fuentes:scopusQSAR model toward the rational design of new agrochemical fungicides with a defined resistance risk using substructural descriptors
ArticleAbstract: The increasing resistance of several phytopathogenic fungal species to the existing agrochemical funPalabras claves:Agrochemical fungicides, Fragments, linear discriminant analysis, Molecular descriptors, Resistance riskAutores:Alejandro Speck-Planche, Kleandrova V.V., Rojas-Vargas J.A.Fuentes:scopusThe QSAR paradigm in fragment-based drug discovery: From the virtual generation of target inhibitors to multi-scale modeling
ReviewAbstract: Fragment-based drug design (FBDD) has established itself as a promising approach in modern drug discPalabras claves:Artificial Neural Network, docking, FBDD, Molecular fragment, Multi-scale model, Pseudo-linear equation, QSARAutores:Alejandro Speck-Planche, Kleandrova V.V.Fuentes:scopus