The Experts below are selected from a list of 8427 Experts worldwide ranked by ideXlab platform
Andrea Volkamer - One of the best experts on this subject based on the ideXlab platform.
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TeachOpenCADD-KNIME: A Teaching Platform for Computer-Aided Drug Design Using KNIME Workflows.
Journal of chemical information and modeling, 2019Co-Authors: Dominique Sydow, Michele Wichmann, Jaime Rodríguez-guerra, Daria Goldmann, Gregory A. Landrum, Andrea VolkamerAbstract:Open-source workflows have become more and more an integral part of Computer-Aided Drug Design (CADD) projects since they allow reproducible and shareable research that can be easily transferred to other projects. Setting up, understanding, and applying such workflows involves either coding or using workflow managers that offer a graphical user interface. We previously reported the TeachOpenCADD teaching platform that provides interactive Jupyter Notebooks (talktorials) on central CADD topics using open-source data and Python packages. Here we present the conversion of these talktorials to KNIME workflows that allow users to explore our teaching material without any line of code. TeachOpenCADD KNIME workflows are freely available on the KNIME Hub: https://hub.knime.com/volkamerlab/space/TeachOpenCADD .
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TeachOpenCADD: a teaching platform for Computer-Aided Drug Design using open source packages and data.
Journal of cheminformatics, 2019Co-Authors: Dominique Sydow, Andrea Morger, Maximilian Driller, Andrea VolkamerAbstract:Owing to the increase in freely available software and data for cheminformatics and structural bioinformatics, research for Computer-Aided Drug Design (CADD) is more and more built on modular, reproducible, and easy-to-share pipelines. While documentation for such tools is available, there are only a few freely accessible examples that teach the underlying concepts focused on CADD, especially addressing users new to the field. Here, we present TeachOpenCADD, a teaching platform developed by students for students, using open source compound and protein data as well as basic and CADD-related Python packages. We provide interactive Jupyter notebooks for central CADD topics, integrating theoretical background and practical code. TeachOpenCADD is freely available on GitHub: https://github.com/volkamerlab/TeachOpenCADD .
Marcus Tullius Scotti - One of the best experts on this subject based on the ideXlab platform.
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Computer-Aided Drug Design Applied to Secondary Metabolites as Anticancer Agents.
Current topics in medicinal chemistry, 2020Co-Authors: Rodrigo Santos Aquino De Araújo, Hamilton Mitsugu Ishiki, Marcus Tullius Scotti, Luciana Scotti, Edeildo Ferreira Da Silva-júnior, Thiago Mendonça De Aquino, Francisco Jaime Bezerra Mendonça-juniorAbstract:Computer-Aided Drug Design (CADD) techniques have garnered a great deal of attention in academia and industry because of their great versatility, low costs, possibilities of cost reduction in in vitro screening and in the development of synthetic steps; these techniques are compared with highthroughput screening, in particular for candidate Drugs. The secondary metabolism of plants and other organisms provide substantial amounts of new chemical structures, many of which have numerous biological and pharmacological properties for virtually every existing disease, including cancer. In oncology, compounds such as vimblastine, vincristine, taxol, podophyllotoxin, captothecin and cytarabine are examples of how important natural products enhance the cancer-fighting therapeutic arsenal. In this context, this review presents an update of Ligand-Based Drug Design and Structure-Based Drug Design techniques applied to flavonoids, alkaloids and coumarins in the search of new compounds or fragments that can be used in oncology. A systematical search using various databases was performed. The search was limited to articles published in the last 10 years. The great diversity of chemical structures (coumarin, flavonoids and alkaloids) with cancer properties, associated with infinite synthetic possibilities for obtaining analogous compounds, creates a huge chemical environment with potential to be explored, and creates a major difficulty, for screening studies to select compounds with more promising activity for a selected target. CADD techniques appear to be the least expensive and most efficient alternatives to perform virtual screening studies, aiming to selected compounds with better activity profiles and better "Drugability".
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Computer-Aided Drug Design for the Identification of Novel Antischistosomal Compounds.
Methods in molecular biology (Clifton N.J.), 2020Co-Authors: Jéssika De Oliveira Viana, Marcus Tullius Scotti, Luciana ScottiAbstract:Schistosomiasis is a chronic neglected tropical disease, highlighted by the presence of Schistosoma worms, which presents in advanced cases in approximately 80 countries, affecting almost 300 million people. The treatment is based on only one Drug, praziquantel, a Drug discovered in the 1970s that shows moderate efficacy against the adult parasite, but low efficacy against the larval stages of the parasite. Therefore, the use of only one Drug has brought concerns and losses on Drug-resistance cases, necessitating the development of new effective chemotherapeutic agents against Schistosoma species. One of the strategies that have been implemented in Drug development is the Computer-Aided Drug Design (CADD), investigating the structural characteristics of the compounds and targets in order to understand their actions and biological activities through 3D virtual manipulation, as the QSAR applied to ligands and molecular docking applied to a respective biological target. These studies help to extract information and characteristics relevant to the activity, as well as to predict potential applications and activity. Therefore, this chapter will present the main validated biological targets of the genus Schistosoma, as thioredoxin glutathione reductase (TGR), histone deacetylases (HDAC 1, HDAC 8), dihydroorotate dehydrogenase, sirtuin protein and cathepsin L1, as well as reports of CADD in literature applied to the development of Drugs against schistosomiasis, providing compounds with high pharmacological potential and high specificity.
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Computer-Aided Drug Design Applied to Parkinson Targets.
Current neuropharmacology, 2018Co-Authors: Hamilton Mitsugu Ishiki, José Maria Barbosa Filho, Marcelo Sobral Da Silva, Marcus Tullius Scotti, Luciana ScottiAbstract:Background Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by debilitating motor deficits, as well as autonomic problems, cognitive declines, changes in affect and sleep disturbances. Although the scientific community has performed great efforts in the study of PD, and from the most diverse points of view, the disease remains incurable. The exact mechanism underlying its progression is unclear, but oxidative stress, mitochondrial dysfunction and inflammation are thought to play major roles in the etiology. Objective Current pharmacological therapies for the treatment of Parkinson's disease are mostly inadequate, and new therapeutic agents are much needed. Methods In this review, recent advances in Computer-Aided Drug Design for the rational Design of new compounds against Parkinson disease; using methods such as Quantitative Structure-Activity Relationships (QSAR), molecular docking, molecular dynamics and pharmacophore modeling are discussed. Results In this review, four targets were selected: the enzyme monoamine oxidase, dopamine agonists, acetylcholine receptors, and adenosine receptors. Conclusion Computer aided-Drug Design enables the creation of theoretical models that can be used in a large database to virtually screen for and identify novel candidate molecules.
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Computer-Aided Drug Design Studies in Food Chemistry
Natural and Artificial Flavoring Agents and Food Dyes, 2018Co-Authors: Luciana Scotti, Hamilton Mitsugu Ishiki, Francisco Jaime Bezerra Mendonça Junior, Frederico F. Ribeiro, Marcelo Cavalcante Duarte, Gracielle S. Santana, Tiago Branquinho Oliveira, Margareth De Fátima Formiga Melo Diniz, Lucindo J. Quintans-júnior, Marcus Tullius ScottiAbstract:In silico methods or Computer-Aided Drug Design (CADD) studies, which involve an understanding of molecular interactions from both a qualitative and quantitative point of view, are increasingly being used in both industrial and academic settings. Analysis of the molecular structure of a given system allows relevant information to be extracted, and the potential of bioactive compounds to be predicted. In silico tools used in medicinal chemistry include chemometric methods, structure–activity relationships (SAR), mole cular modeling, and quantitative structure–activity relationships (QSAR), which correlate the structural or property descriptors of compounds to several types of biological activities. This chapter will report some studies to show how computational chemistry can be used to predict important chemical structure information and how these techniques can be applied in food research.
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Computer-Aided Drug Design Using Sesquiterpene Lactones as Sources of New Structures with Potential Activity against Infectious Neglected Diseases
Molecules (Basel Switzerland), 2017Co-Authors: Chonny Herrera Acevedo, Margareth De Fátima Formiga Melo Diniz, Luciana Scotti, Mateus Feitosa Alves, Marcus Tullius ScottiAbstract:This review presents an survey to the biological importance of sesquiterpene lactones (SLs) in the fight against four infectious neglected tropical diseases (NTDs)—leishmaniasis, schistosomiasis, Chagas disease, and sleeping sickness—as alternatives to the current chemotherapies that display several problems such as low effectiveness, resistance, and high toxicity. Several studies have demonstrated the great potential of some SLs as therapeutic agents for these NTDs and the relationship between the protozoal activities with their chemical structure. Recently, Computer-Aided Drug Design (CADD) studies have helped increase the knowledge of SLs regarding their mechanisms, the discovery of new lead molecules, the identification of pharmacophore groups and increase the biological activity by employing in silico tools such as molecular docking, virtual screening and Quantitative-Structure Activity Relationship (QSAR) studies.
Luciana Scotti - One of the best experts on this subject based on the ideXlab platform.
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Computer-Aided Drug Design Applied to Secondary Metabolites as Anticancer Agents.
Current topics in medicinal chemistry, 2020Co-Authors: Rodrigo Santos Aquino De Araújo, Hamilton Mitsugu Ishiki, Marcus Tullius Scotti, Luciana Scotti, Edeildo Ferreira Da Silva-júnior, Thiago Mendonça De Aquino, Francisco Jaime Bezerra Mendonça-juniorAbstract:Computer-Aided Drug Design (CADD) techniques have garnered a great deal of attention in academia and industry because of their great versatility, low costs, possibilities of cost reduction in in vitro screening and in the development of synthetic steps; these techniques are compared with highthroughput screening, in particular for candidate Drugs. The secondary metabolism of plants and other organisms provide substantial amounts of new chemical structures, many of which have numerous biological and pharmacological properties for virtually every existing disease, including cancer. In oncology, compounds such as vimblastine, vincristine, taxol, podophyllotoxin, captothecin and cytarabine are examples of how important natural products enhance the cancer-fighting therapeutic arsenal. In this context, this review presents an update of Ligand-Based Drug Design and Structure-Based Drug Design techniques applied to flavonoids, alkaloids and coumarins in the search of new compounds or fragments that can be used in oncology. A systematical search using various databases was performed. The search was limited to articles published in the last 10 years. The great diversity of chemical structures (coumarin, flavonoids and alkaloids) with cancer properties, associated with infinite synthetic possibilities for obtaining analogous compounds, creates a huge chemical environment with potential to be explored, and creates a major difficulty, for screening studies to select compounds with more promising activity for a selected target. CADD techniques appear to be the least expensive and most efficient alternatives to perform virtual screening studies, aiming to selected compounds with better activity profiles and better "Drugability".
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Computer-Aided Drug Design for the Identification of Novel Antischistosomal Compounds.
Methods in molecular biology (Clifton N.J.), 2020Co-Authors: Jéssika De Oliveira Viana, Marcus Tullius Scotti, Luciana ScottiAbstract:Schistosomiasis is a chronic neglected tropical disease, highlighted by the presence of Schistosoma worms, which presents in advanced cases in approximately 80 countries, affecting almost 300 million people. The treatment is based on only one Drug, praziquantel, a Drug discovered in the 1970s that shows moderate efficacy against the adult parasite, but low efficacy against the larval stages of the parasite. Therefore, the use of only one Drug has brought concerns and losses on Drug-resistance cases, necessitating the development of new effective chemotherapeutic agents against Schistosoma species. One of the strategies that have been implemented in Drug development is the Computer-Aided Drug Design (CADD), investigating the structural characteristics of the compounds and targets in order to understand their actions and biological activities through 3D virtual manipulation, as the QSAR applied to ligands and molecular docking applied to a respective biological target. These studies help to extract information and characteristics relevant to the activity, as well as to predict potential applications and activity. Therefore, this chapter will present the main validated biological targets of the genus Schistosoma, as thioredoxin glutathione reductase (TGR), histone deacetylases (HDAC 1, HDAC 8), dihydroorotate dehydrogenase, sirtuin protein and cathepsin L1, as well as reports of CADD in literature applied to the development of Drugs against schistosomiasis, providing compounds with high pharmacological potential and high specificity.
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Computer-Aided Drug Design Applied to Parkinson Targets.
Current neuropharmacology, 2018Co-Authors: Hamilton Mitsugu Ishiki, José Maria Barbosa Filho, Marcelo Sobral Da Silva, Marcus Tullius Scotti, Luciana ScottiAbstract:Background Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by debilitating motor deficits, as well as autonomic problems, cognitive declines, changes in affect and sleep disturbances. Although the scientific community has performed great efforts in the study of PD, and from the most diverse points of view, the disease remains incurable. The exact mechanism underlying its progression is unclear, but oxidative stress, mitochondrial dysfunction and inflammation are thought to play major roles in the etiology. Objective Current pharmacological therapies for the treatment of Parkinson's disease are mostly inadequate, and new therapeutic agents are much needed. Methods In this review, recent advances in Computer-Aided Drug Design for the rational Design of new compounds against Parkinson disease; using methods such as Quantitative Structure-Activity Relationships (QSAR), molecular docking, molecular dynamics and pharmacophore modeling are discussed. Results In this review, four targets were selected: the enzyme monoamine oxidase, dopamine agonists, acetylcholine receptors, and adenosine receptors. Conclusion Computer aided-Drug Design enables the creation of theoretical models that can be used in a large database to virtually screen for and identify novel candidate molecules.
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Computer-Aided Drug Design Studies in Food Chemistry
Natural and Artificial Flavoring Agents and Food Dyes, 2018Co-Authors: Luciana Scotti, Hamilton Mitsugu Ishiki, Francisco Jaime Bezerra Mendonça Junior, Frederico F. Ribeiro, Marcelo Cavalcante Duarte, Gracielle S. Santana, Tiago Branquinho Oliveira, Margareth De Fátima Formiga Melo Diniz, Lucindo J. Quintans-júnior, Marcus Tullius ScottiAbstract:In silico methods or Computer-Aided Drug Design (CADD) studies, which involve an understanding of molecular interactions from both a qualitative and quantitative point of view, are increasingly being used in both industrial and academic settings. Analysis of the molecular structure of a given system allows relevant information to be extracted, and the potential of bioactive compounds to be predicted. In silico tools used in medicinal chemistry include chemometric methods, structure–activity relationships (SAR), mole cular modeling, and quantitative structure–activity relationships (QSAR), which correlate the structural or property descriptors of compounds to several types of biological activities. This chapter will report some studies to show how computational chemistry can be used to predict important chemical structure information and how these techniques can be applied in food research.
-
Computer-Aided Drug Design Using Sesquiterpene Lactones as Sources of New Structures with Potential Activity against Infectious Neglected Diseases
Molecules (Basel Switzerland), 2017Co-Authors: Chonny Herrera Acevedo, Margareth De Fátima Formiga Melo Diniz, Luciana Scotti, Mateus Feitosa Alves, Marcus Tullius ScottiAbstract:This review presents an survey to the biological importance of sesquiterpene lactones (SLs) in the fight against four infectious neglected tropical diseases (NTDs)—leishmaniasis, schistosomiasis, Chagas disease, and sleeping sickness—as alternatives to the current chemotherapies that display several problems such as low effectiveness, resistance, and high toxicity. Several studies have demonstrated the great potential of some SLs as therapeutic agents for these NTDs and the relationship between the protozoal activities with their chemical structure. Recently, Computer-Aided Drug Design (CADD) studies have helped increase the knowledge of SLs regarding their mechanisms, the discovery of new lead molecules, the identification of pharmacophore groups and increase the biological activity by employing in silico tools such as molecular docking, virtual screening and Quantitative-Structure Activity Relationship (QSAR) studies.
Dominique Sydow - One of the best experts on this subject based on the ideXlab platform.
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TeachOpenCADD-KNIME: A Teaching Platform for Computer-Aided Drug Design Using KNIME Workflows.
Journal of chemical information and modeling, 2019Co-Authors: Dominique Sydow, Michele Wichmann, Jaime Rodríguez-guerra, Daria Goldmann, Gregory A. Landrum, Andrea VolkamerAbstract:Open-source workflows have become more and more an integral part of Computer-Aided Drug Design (CADD) projects since they allow reproducible and shareable research that can be easily transferred to other projects. Setting up, understanding, and applying such workflows involves either coding or using workflow managers that offer a graphical user interface. We previously reported the TeachOpenCADD teaching platform that provides interactive Jupyter Notebooks (talktorials) on central CADD topics using open-source data and Python packages. Here we present the conversion of these talktorials to KNIME workflows that allow users to explore our teaching material without any line of code. TeachOpenCADD KNIME workflows are freely available on the KNIME Hub: https://hub.knime.com/volkamerlab/space/TeachOpenCADD .
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TeachOpenCADD: a teaching platform for Computer-Aided Drug Design using open source packages and data.
Journal of cheminformatics, 2019Co-Authors: Dominique Sydow, Andrea Morger, Maximilian Driller, Andrea VolkamerAbstract:Owing to the increase in freely available software and data for cheminformatics and structural bioinformatics, research for Computer-Aided Drug Design (CADD) is more and more built on modular, reproducible, and easy-to-share pipelines. While documentation for such tools is available, there are only a few freely accessible examples that teach the underlying concepts focused on CADD, especially addressing users new to the field. Here, we present TeachOpenCADD, a teaching platform developed by students for students, using open source compound and protein data as well as basic and CADD-related Python packages. We provide interactive Jupyter notebooks for central CADD topics, integrating theoretical background and practical code. TeachOpenCADD is freely available on GitHub: https://github.com/volkamerlab/TeachOpenCADD .
Bor-sen Chen - One of the best experts on this subject based on the ideXlab platform.
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A New Era for Cancer Target Therapies: Applying Systems Biology and Computer-Aided Drug Design to Cancer Therapies
Current pharmaceutical biotechnology, 2016Co-Authors: Yung Hao Wong, Chia Chiun Chiu, Chih Lung Lin, Ting Shou Chen, Bo Ren Jheng, Yu Ching Lee, Jeremy J.w. Chen, Bor-sen ChenAbstract:In recent years, many systems biology approaches have been used with various cancers. The materials described here can be used to build bases to discover novel cancer therapy targets in connection with Computer-Aided Drug Design (CADD). A deeper understanding of the mechanisms of cancer will provide more choices and correct strategies in the development of multiple target Drug therapies, which is quite different from the traditional cancer single target therapy. Targeted therapy is one of the most powerful strategies against cancer and can also be applied to other diseases. Due to the large amount of progress in computer hardware and the theories of computational chemistry and physics, CADD has been the main strategy for developing novel Drugs for cancer therapy. In contrast to traditional single target therapies, in this review we will emphasize the future direction of the field, i.e., multiple target therapies. Structure-based and ligand-based Drug Designs are the two main topics of CADD. The former needs both 3D protein structures and ligand structures, while the latter only needs ligand structures. Ordinarily it is estimated to take more than 14 years and 800 million dollars to develop a new Drug. Many new CADD software programs and techniques have been developed in recent decades. We conclude with an example where we combined and applied systems biology and CADD to the core networks of four cancers and successfully developed a novel cocktail for Drug therapy that treats multiple targets.