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1. Molecular interactions between a diphenyl scaffold and PED/PEA15: Implications for type II diabetes therapeutics targeting PED/PEA15 – Phospholipase D1 interaction

Author

Mercurio, Ivan, D’Abrosca, Gianluca, della Valle, Maria, Malgieri, Gaetano, Fattorusso, Roberto, Isernia, Carla, Russo, Luigi, Di Gaetano, Sonia, Pedone, Emilia Maria, Pirone, Luciano, Del Gatto, Annarita, Zaccaro, Laura, Alberga, Domenico, Saviano, Michele, and Mangiatordi, Giuseppe Felice

Published
2024
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4. Comparative molecular dynamics study of neuromyelitis optica-immunoglobulin G binding to aquaporin-4 extracellular domains

Author

Alberga, Domenico, Trisciuzzi, Daniela, Lattanzi, Gianluca, Bennett, Jeffrey L, Verkman, Alan S, Mangiatordi, Giuseppe Felice, and Nicolotti, Orazio

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Autoimmune Disease, Eye Disease and Disorders of Vision, Neurosciences, Amino Acid Motifs, Aquaporin 4, Autoantibodies, Binding Sites, Epitopes, Humans, Hydrogen Bonding, Immunoglobulin G, Lipid Bilayers, Models, Molecular, Molecular Dynamics Simulation, Mutation, Neuromyelitis Optica, Phosphatidylcholines, Protein Binding, Protein Conformation, alpha-Helical, Protein Interaction Domains and Motifs, Protein Multimerization, Thermodynamics, Aquaporin-4, Molecular Dynamics, Mutations, Biochemistry and Cell Biology, Other Biological Sciences, Chemical Engineering, Biochemistry & Molecular Biology, Biophysics, Biochemistry and cell biology
Abstract

Neuromyelitis optica (NMO) is an inflammatory demyelinating disease of the central nervous system in which most patients have serum autoantibodies (called NMO-IgG) that bind to astrocyte water channel aquaporin-4 (AQP4). A potential therapeutic strategy in NMO is to block the interaction of NMO-IgG with AQP4. Building on recent observation that some single-point and compound mutations of the AQP4 extracellular loop C prevent NMO-IgG binding, we carried out comparative Molecular Dynamics (MD) investigations on three AQP4 mutants, TP137-138AA, N153Q and V150G, whose 295-ns long trajectories were compared to that of wild type human AQP4. A robust conclusion of our modeling is that loop C mutations affect the conformation of neighboring extracellular loop A, thereby interfering with NMO-IgG binding. Analysis of individual mutations suggested specific hydrogen bonding and other molecular interactions involved in AQP4-IgG binding to AQP4.

Published
2017

13. Erratum: CATMoS: Collaborative Acute Toxicity Modeling Suite

Author

Mansouri, Kamel, primary, Karmaus, Agnes L., additional, Fitzpatrick, Jeremy, additional, Patlewicz, Grace, additional, Pradeep, Prachi, additional, Alberga, Domenico, additional, Alepee, Nathalie, additional, Allen, Timothy E.H., additional, Allen, Dave, additional, Alves, Vinicius M., additional, Andrade, Carolina H., additional, Auernhammer, Tyler R., additional, Ballabio, Davide, additional, Bell, Shannon, additional, Benfenati, Emilio, additional, Bhattacharya, Sudin, additional, Bastos, Joyce V., additional, Boyd, Stephen, additional, Brown, J. B., additional, Capuzzi, Stephen J., additional, Chushak, Yaroslav, additional, Ciallella, Heather, additional, Clark, Alex M., additional, Consonni, Viviana, additional, Daga, Pankaj R., additional, Ekins, Sean, additional, Farag, Sherif, additional, Fedorov, Maxim, additional, Fourches, Denis, additional, Gadaleta, Domenico, additional, Gao, Feng, additional, Gearhart, Jeffery M., additional, Goh, Garett, additional, Goodman, Jonathan M., additional, Grisoni, Francesca, additional, Grulke, Christopher M., additional, Hartung, Thomas, additional, Hirn, Matthew, additional, Karpov, Pavel, additional, Korotcov, Alexandru, additional, Lavado, Giovanna J., additional, Lawless, Michael, additional, Li, Xinhao, additional, Luechtefeld, Thomas, additional, Lunghini, Filippo, additional, Mangiatordi, Giuseppe F., additional, Marcou, Gilles, additional, Marsh, Dan, additional, Martin, Todd, additional, Mauri, Andrea, additional, Muratov, Eugene N., additional, Myatt, Glenn J., additional, Nguyen, Dac-Trung, additional, Nicolotti, Orazio, additional, Note, Reine, additional, Pande, Paritosh, additional, Parks, Amanda K., additional, Peryea, Tyler, additional, Polash, Ahsan H., additional, Rallo, Robert, additional, Roncaglioni, Alessandra, additional, Rowlands, Craig, additional, Ruiz, Patricia, additional, Russo, Daniel P., additional, Sayed, Ahmed, additional, Sayre, Risa, additional, Sheils, Timothy, additional, Siegel, Charles, additional, Silva, Arthur C., additional, Simeonov, Anton, additional, Sosnin, Sergey, additional, Southall, Noel, additional, Strickland, Judy, additional, Tang, Yun, additional, Teppen, Brian, additional, Tetko, Igor V., additional, Thomas, Dennis, additional, Tkachenko, Valery, additional, Todeschini, Roberto, additional, Toma, Cosimo, additional, Tripodi, Ignacio, additional, Trisciuzzi, Daniela, additional, Tropsha, Alexander, additional, Varnek, Alexandre, additional, Vukovic, Kristijan, additional, Wang, Zhongyu, additional, Wang, Liguo, additional, Waters, Katrina M., additional, Wedlake, Andrew J., additional, Wijeyesakere, Sanjeeva J., additional, Wilson, Dan, additional, Xiao, Zijun, additional, Yang, Hongbin, additional, Zahoranszky-Kohalmi, Gergely, additional, Zakharov, Alexey V., additional, Zhang, Fagen F., additional, Zhang, Zhen, additional, Zhao, Tongan, additional, Zhu, Hao, additional, Zorn, Kimberley M., additional, Casey, Warren, additional, and Kleinstreuer, Nicole C., additional

Published
2021
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16. CATMoS: Collaborative Acute Toxicity Modeling Suite

Author

Mansouri, K, Karmaus, A, Fitzpatrick, J, Patlewicz, G, Pradeep, P, Alberga, D, Alepee, N, Allen, T, Allen, D, Alves, V, Andrade, C, Auernhammer, T, Ballabio, D, Bell, S, Benfenati, E, Bhattacharya, S, Bastos, J, Boyd, S, Brown, J, Capuzzi, S, Chushak, Y, Ciallella, H, Clark, A, Consonni, V, Daga, P, Ekins, S, Farag, S, Fedorov, M, Fourches, D, Gadaleta, D, Gao, F, Gearhart, J, Goh, G, Goodman, J, Grisoni, F, Grulke, C, Hartung, T, Hirn, M, Karpov, P, Korotcov, A, Lavado, G, Lawless, M, Li, X, Luechtefeld, T, Lunghini, F, Mangiatordi, G, Marcou, G, Marsh, D, Martin, T, Mauri, A, Muratov, E, Myatt, G, Nguyen, D, Nicolotti, O, Note, R, Pande, P, Parks, A, Peryea, T, Polash, A, Rallo, R, Roncaglioni, A, Rowlands, C, Ruiz, P, Russo, D, Sayed, A, Sayre, R, Sheils, T, Siegel, C, Silva, A, Simeonov, A, Sosnin, S, Southall, N, Strickland, J, Tang, Y, Teppen, B, Tetko, I, Thomas, D, Tkachenko, V, Todeschini, R, Toma, C, Tripodi, I, Trisciuzzi, D, Tropsha, A, Varnek, A, Vukovic, K, Wang, Z, Wang, L, Waters, K, Wedlake, A, Wijeyesakere, S, Wilson, D, Xiao, Z, Yang, H, Zahoranszky-Kohalmi, G, Zakharov, A, Zhang, F, Zhang, Z, Zhao, T, Zhu, H, Zorn, K, Casey, W, Kleinstreuer, N, Mansouri, Kamel, Karmaus, Agnes L, Fitzpatrick, Jeremy, Patlewicz, Grace, Pradeep, Prachi, Alberga, Domenico, Alepee, Nathalie, Allen, Timothy E H, Allen, Dave, Alves, Vinicius M, Andrade, Carolina H, Auernhammer, Tyler R, Ballabio, Davide, Bell, Shannon, Benfenati, Emilio, Bhattacharya, Sudin, Bastos, Joyce V, Boyd, Stephen, Brown, J B, Capuzzi, Stephen J, Chushak, Yaroslav, Ciallella, Heather, Clark, Alex M, Consonni, Viviana, Daga, Pankaj R, Ekins, Sean, Farag, Sherif, Fedorov, Maxim, Fourches, Denis, Gadaleta, Domenico, Gao, Feng, Gearhart, Jeffery M, Goh, Garett, Goodman, Jonathan M, Grisoni, Francesca, Grulke, Christopher M, Hartung, Thomas, Hirn, Matthew, Karpov, Pavel, Korotcov, Alexandru, Lavado, Giovanna J, Lawless, Michael, Li, Xinhao, Luechtefeld, Thomas, Lunghini, Filippo, Mangiatordi, Giuseppe F, Marcou, Gilles, Marsh, Dan, Martin, Todd, Mauri, Andrea, Muratov, Eugene N, Myatt, Glenn J, Nguyen, Dac-Trung, Nicolotti, Orazio, Note, Reine, Pande, Paritosh, Parks, Amanda K, Peryea, Tyler, Polash, Ahsan H, Rallo, Robert, Roncaglioni, Alessandra, Rowlands, Craig, Ruiz, Patricia, Russo, Daniel P, Sayed, Ahmed, Sayre, Risa, Sheils, Timothy, Siegel, Charles, Silva, Arthur C, Simeonov, Anton, Sosnin, Sergey, Southall, Noel, Strickland, Judy, Tang, Yun, Teppen, Brian, Tetko, Igor V, Thomas, Dennis, Tkachenko, Valery, Todeschini, Roberto, Toma, Cosimo, Tripodi, Ignacio, Trisciuzzi, Daniela, Tropsha, Alexander, Varnek, Alexandre, Vukovic, Kristijan, Wang, Zhongyu, Wang, Liguo, Waters, Katrina M, Wedlake, Andrew J, Wijeyesakere, Sanjeeva J, Wilson, Dan, Xiao, Zijun, Yang, Hongbin, Zahoranszky-Kohalmi, Gergely, Zakharov, Alexey V, Zhang, Fagen F, Zhang, Zhen, Zhao, Tongan, Zhu, Hao, Zorn, Kimberley M, Casey, Warren, Kleinstreuer, Nicole C, Mansouri, K, Karmaus, A, Fitzpatrick, J, Patlewicz, G, Pradeep, P, Alberga, D, Alepee, N, Allen, T, Allen, D, Alves, V, Andrade, C, Auernhammer, T, Ballabio, D, Bell, S, Benfenati, E, Bhattacharya, S, Bastos, J, Boyd, S, Brown, J, Capuzzi, S, Chushak, Y, Ciallella, H, Clark, A, Consonni, V, Daga, P, Ekins, S, Farag, S, Fedorov, M, Fourches, D, Gadaleta, D, Gao, F, Gearhart, J, Goh, G, Goodman, J, Grisoni, F, Grulke, C, Hartung, T, Hirn, M, Karpov, P, Korotcov, A, Lavado, G, Lawless, M, Li, X, Luechtefeld, T, Lunghini, F, Mangiatordi, G, Marcou, G, Marsh, D, Martin, T, Mauri, A, Muratov, E, Myatt, G, Nguyen, D, Nicolotti, O, Note, R, Pande, P, Parks, A, Peryea, T, Polash, A, Rallo, R, Roncaglioni, A, Rowlands, C, Ruiz, P, Russo, D, Sayed, A, Sayre, R, Sheils, T, Siegel, C, Silva, A, Simeonov, A, Sosnin, S, Southall, N, Strickland, J, Tang, Y, Teppen, B, Tetko, I, Thomas, D, Tkachenko, V, Todeschini, R, Toma, C, Tripodi, I, Trisciuzzi, D, Tropsha, A, Varnek, A, Vukovic, K, Wang, Z, Wang, L, Waters, K, Wedlake, A, Wijeyesakere, S, Wilson, D, Xiao, Z, Yang, H, Zahoranszky-Kohalmi, G, Zakharov, A, Zhang, F, Zhang, Z, Zhao, T, Zhu, H, Zorn, K, Casey, W, Kleinstreuer, N, Mansouri, Kamel, Karmaus, Agnes L, Fitzpatrick, Jeremy, Patlewicz, Grace, Pradeep, Prachi, Alberga, Domenico, Alepee, Nathalie, Allen, Timothy E H, Allen, Dave, Alves, Vinicius M, Andrade, Carolina H, Auernhammer, Tyler R, Ballabio, Davide, Bell, Shannon, Benfenati, Emilio, Bhattacharya, Sudin, Bastos, Joyce V, Boyd, Stephen, Brown, J B, Capuzzi, Stephen J, Chushak, Yaroslav, Ciallella, Heather, Clark, Alex M, Consonni, Viviana, Daga, Pankaj R, Ekins, Sean, Farag, Sherif, Fedorov, Maxim, Fourches, Denis, Gadaleta, Domenico, Gao, Feng, Gearhart, Jeffery M, Goh, Garett, Goodman, Jonathan M, Grisoni, Francesca, Grulke, Christopher M, Hartung, Thomas, Hirn, Matthew, Karpov, Pavel, Korotcov, Alexandru, Lavado, Giovanna J, Lawless, Michael, Li, Xinhao, Luechtefeld, Thomas, Lunghini, Filippo, Mangiatordi, Giuseppe F, Marcou, Gilles, Marsh, Dan, Martin, Todd, Mauri, Andrea, Muratov, Eugene N, Myatt, Glenn J, Nguyen, Dac-Trung, Nicolotti, Orazio, Note, Reine, Pande, Paritosh, Parks, Amanda K, Peryea, Tyler, Polash, Ahsan H, Rallo, Robert, Roncaglioni, Alessandra, Rowlands, Craig, Ruiz, Patricia, Russo, Daniel P, Sayed, Ahmed, Sayre, Risa, Sheils, Timothy, Siegel, Charles, Silva, Arthur C, Simeonov, Anton, Sosnin, Sergey, Southall, Noel, Strickland, Judy, Tang, Yun, Teppen, Brian, Tetko, Igor V, Thomas, Dennis, Tkachenko, Valery, Todeschini, Roberto, Toma, Cosimo, Tripodi, Ignacio, Trisciuzzi, Daniela, Tropsha, Alexander, Varnek, Alexandre, Vukovic, Kristijan, Wang, Zhongyu, Wang, Liguo, Waters, Katrina M, Wedlake, Andrew J, Wijeyesakere, Sanjeeva J, Wilson, Dan, Xiao, Zijun, Yang, Hongbin, Zahoranszky-Kohalmi, Gergely, Zakharov, Alexey V, Zhang, Fagen F, Zhang, Zhen, Zhao, Tongan, Zhu, Hao, Zorn, Kimberley M, Casey, Warren, and Kleinstreuer, Nicole C

Abstract

Background: Humans are exposed to tens of thousands of chemical substances that need to be assessed for their potential toxicity. Acute systemic toxicity testing serves as the basis for regulatory hazard classification, labeling, and risk management. However, it is cost- and time-prohibitive to evaluate all new and existing chemicals using traditional rodent acute toxicity tests. In silica models built using existing data facilitate rapid acute tox- icity predictions without using animals. Objkctivks: The U.S. Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM) Acute Toxicity Workgroup organ- ized an international collaboration to develop in silica models for predicting acute oral toxicity based on five different end points: Lethal Dose 50 (LD50 value, U.S. Environmental Protection Agency hazard (four) categories, Globally Harmonized System for Classification and Labeling hazard (five) categories, very toxic chemicals [LD50 (LD50 ≤ 50 mg/kg)], and nontoxic chemicals (LD50 > 2,000 mg/kg). Mkthods: An acute oral toxicity data inventory for 11,992 chemicals was compiled, split into training and evaluation sets, and made available to 35 participating international research groups that submitted a total of 139 predictive models. Predictions that fell within the applicability domains of the submitted models were evaluated using external validation sets. These were then combined into consensus models to leverage strengths of individual approaches. Results: The resulting consensus predictions, which leverage the collective strengths of each individual model, form the Collaborative Acute Toxicity Modeling Suite (CATMoS). CATMoS demonstrated high performance in terms of accuracy and robustness when compared with in viva results. Discussion: CATMoS is being evaluated by regulatory agencies for its utility and applicability as a potential replacement for in viva rat acute oral toxicity studies. CATMoS predictions for more than 800,000 chemica

Published
2021

17. CATMoS: Collaborative Acute Toxicity Modeling Suite

Author

Mansouri, Kamel, primary, Karmaus, Agnes L., additional, Fitzpatrick, Jeremy, additional, Patlewicz, Grace, additional, Pradeep, Prachi, additional, Alberga, Domenico, additional, Alepee, Nathalie, additional, Allen, Timothy E.H., additional, Allen, Dave, additional, Alves, Vinicius M., additional, Andrade, Carolina H., additional, Auernhammer, Tyler R., additional, Ballabio, Davide, additional, Bell, Shannon, additional, Benfenati, Emilio, additional, Bhattacharya, Sudin, additional, Bastos, Joyce V., additional, Boyd, Stephen, additional, Brown, J.B., additional, Capuzzi, Stephen J., additional, Chushak, Yaroslav, additional, Ciallella, Heather, additional, Clark, Alex M., additional, Consonni, Viviana, additional, Daga, Pankaj R., additional, Ekins, Sean, additional, Farag, Sherif, additional, Fedorov, Maxim, additional, Fourches, Denis, additional, Gadaleta, Domenico, additional, Gao, Feng, additional, Gearhart, Jeffery M., additional, Goh, Garett, additional, Goodman, Jonathan M., additional, Grisoni, Francesca, additional, Grulke, Christopher M., additional, Hartung, Thomas, additional, Hirn, Matthew, additional, Karpov, Pavel, additional, Korotcov, Alexandru, additional, Lavado, Giovanna J., additional, Lawless, Michael, additional, Li, Xinhao, additional, Luechtefeld, Thomas, additional, Lunghini, Filippo, additional, Mangiatordi, Giuseppe F., additional, Marcou, Gilles, additional, Marsh, Dan, additional, Martin, Todd, additional, Mauri, Andrea, additional, Muratov, Eugene N., additional, Myatt, Glenn J., additional, Nguyen, Dac-Trung, additional, Nicolotti, Orazio, additional, Note, Reine, additional, Pande, Paritosh, additional, Parks, Amanda K., additional, Peryea, Tyler, additional, Polash, Ahsan H., additional, Rallo, Robert, additional, Roncaglioni, Alessandra, additional, Rowlands, Craig, additional, Ruiz, Patricia, additional, Russo, Daniel P., additional, Sayed, Ahmed, additional, Sayre, Risa, additional, Sheils, Timothy, additional, Siegel, Charles, additional, Silva, Arthur C., additional, Simeonov, Anton, additional, Sosnin, Sergey, additional, Southall, Noel, additional, Strickland, Judy, additional, Tang, Yun, additional, Teppen, Brian, additional, Tetko, Igor V., additional, Thomas, Dennis, additional, Tkachenko, Valery, additional, Todeschini, Roberto, additional, Toma, Cosimo, additional, Tripodi, Ignacio, additional, Trisciuzzi, Daniela, additional, Tropsha, Alexander, additional, Varnek, Alexandre, additional, Vukovic, Kristijan, additional, Wang, Zhongyu, additional, Wang, Liguo, additional, Waters, Katrina M., additional, Wedlake, Andrew J., additional, Wijeyesakere, Sanjeeva J., additional, Wilson, Dan, additional, Xiao, Zijun, additional, Yang, Hongbin, additional, Zahoranszky-Kohalmi, Gergely, additional, Zakharov, Alexey V., additional, Zhang, Fagen F., additional, Zhang, Zhen, additional, Zhao, Tongan, additional, Zhu, Hao, additional, Zorn, Kimberley M., additional, Casey, Warren, additional, and Kleinstreuer, Nicole C., additional

Published
2021
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18. Prediction of Acute Oral Systemic Toxicity Using a Multifingerprint Similarity Approach

Author

Alberga, Domenico, Trisciuzzi, Daniela, Mansouri, Kamel, Mangiatordi, Giuseppe Felice, and Nicolotti, Orazio

Subjects
0301 basic medicine, Computer science, Administration, Oral, alternative nontesting methods, predictive toxicology, acute toxicity, Animal Testing Alternatives, Toxicology, Machine learning, computer.software_genre, Hazardous Substances, Lethal Dose 50, 03 medical and health sciences, 0302 clinical medicine, Similarity (network science), multifingerprint, Toxicity Tests, Acute, United States Environmental Protection Agency, Workgroup, Training set, Dose-Response Relationship, Drug, business.industry, k-nearest neighbors, External validation, Computational Biology, Models, Theoretical, United States, Acute toxicity, 030104 developmental biology, Systemic toxicity, Binary classification, Categorization, Government Regulation, Artificial intelligence, business, computer, Algorithms, 030217 neurology & neurosurgery
Abstract

The implementation of nonanimal approaches is of particular importance to regulatory agencies for the prediction of potential hazards associated with acute exposures to chemicals. This work was carried out in the framework of an international modeling initiative organized by the Acute Toxicity Workgroup (ATWG) of the Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM) with the participation of 32 international groups across government, industry, and academia. Our contribution was to develop a multifingerprints similarity approach for predicting five relevant toxicology endpoints related to the acute oral systemic toxicity that are: The median lethal dose (LD 50) point prediction, the "nontoxic" (LD 50 > 2000 mg/kg) and "very toxic" (LD 50

Published
2018
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19. CoMPARA : Collaborative Modeling Project for Androgen Receptor Activity

Author

Mansouri, Kamel, Kleinstreuer, Nicole, Abdelaziz, Ahmed M., Alberga, Domenico, Alves, Vinicius M., Andersson, Patrik L., Andrade, Carolina H., Bai, Fang, Balabin, Ilya, Ballabio, Davide, Benfenati, Emilio, Bhhatarai, Barun, Boyer, Scott, Chen, Jingwen, Consonni, Viviana, Farag, Sherif, Fourches, Denis, García-Sosa, Alfonso T., Gramatica, Paola, Grisoni, Francesca, Grulke, Chris M., Hong, Huixiao, Horvath, Dragos, Hu, Xin, Huang, Ruili, Jeliazkova, Nina, Li, Jiazhong, Li, Xuehua, Liu, Huanxiang, Manganelli, Serena, Mangiatordi, Giuseppe F., Maran, Uko, Marcou, Gilles, Martin, Todd, Muratov, Eugene, Nguyen, Dac-Trung, Nicolotti, Orazio, Nikolov, Nikolai G., Norinder, Ulf, Papa, Ester, Petitjean, Michel, Pür, Geven, Pogodin, Pavel, Poroikov, Vladimir, Qiao, Xianliang, Richard, Ann M., Roncaglioni, Alessandra, Ruiz, Patricia, Rupakheti, Chetan, Sakkiah, Sugunadevi, Sangion, Alessandro, Schramm, Karl-Werner, Selvaraj, Chandrabose, Shah, Imran, Sild, Sulev, Sun, Lixia, Taboureau, Olivier, Tang, Yun, Tetko, Igor V., Todeschini, Roberto, Tong, Weida, Trisciuzzi, Daniela, Tropsha, Alexander, Van Den Driessche, George, Varnek, Alexandre, Wang, Zhongyu, Wedebye, Eva B., Williams, Antony J., Xie, Hongbin, Zakharov, Alexey V., Zheng, Ziye, Judson, Richard S., Mansouri, Kamel, Kleinstreuer, Nicole, Abdelaziz, Ahmed M., Alberga, Domenico, Alves, Vinicius M., Andersson, Patrik L., Andrade, Carolina H., Bai, Fang, Balabin, Ilya, Ballabio, Davide, Benfenati, Emilio, Bhhatarai, Barun, Boyer, Scott, Chen, Jingwen, Consonni, Viviana, Farag, Sherif, Fourches, Denis, García-Sosa, Alfonso T., Gramatica, Paola, Grisoni, Francesca, Grulke, Chris M., Hong, Huixiao, Horvath, Dragos, Hu, Xin, Huang, Ruili, Jeliazkova, Nina, Li, Jiazhong, Li, Xuehua, Liu, Huanxiang, Manganelli, Serena, Mangiatordi, Giuseppe F., Maran, Uko, Marcou, Gilles, Martin, Todd, Muratov, Eugene, Nguyen, Dac-Trung, Nicolotti, Orazio, Nikolov, Nikolai G., Norinder, Ulf, Papa, Ester, Petitjean, Michel, Pür, Geven, Pogodin, Pavel, Poroikov, Vladimir, Qiao, Xianliang, Richard, Ann M., Roncaglioni, Alessandra, Ruiz, Patricia, Rupakheti, Chetan, Sakkiah, Sugunadevi, Sangion, Alessandro, Schramm, Karl-Werner, Selvaraj, Chandrabose, Shah, Imran, Sild, Sulev, Sun, Lixia, Taboureau, Olivier, Tang, Yun, Tetko, Igor V., Todeschini, Roberto, Tong, Weida, Trisciuzzi, Daniela, Tropsha, Alexander, Van Den Driessche, George, Varnek, Alexandre, Wang, Zhongyu, Wedebye, Eva B., Williams, Antony J., Xie, Hongbin, Zakharov, Alexey V., Zheng, Ziye, and Judson, Richard S.

Abstract

BACKGROUND: Endocrine disrupting chemicals (EDCs) are xenobiotics that mimic the interaction of natural hormones and alter synthesis, transport, or metabolic pathways. The prospect of EDCs causing adverse health effects in humans and wildlife has led to the development of scientific and regulatory approaches for evaluating bioactivity. This need is being addressed using high-throughput screening (HTS) in vitro approaches and computational modeling. OBJECTIVES: In support of the Endocrine Disruptor Screening Program, the U.S. Environmental Protection Agency (EPA) led two worldwide consortiums to virtually screen chemicals for their potential estrogenic and androgenic activities. Here, we describe the Collaborative Modeling Project for Androgen Receptor Activity (CoMPARA) efforts, which follows the steps of the Collaborative Estrogen Receptor Activity Prediction Project (CERAPP). METHODS: The CoMPARA list of screened chemicals built on CERAPP's list of 32,464 chemicals to include additional chemicals of interest, as well as simulated ToxCast (TM) metabolites, totaling 55,450 chemical structures. Computational toxicology scientists from 25 international groups contributed 91 predictive models for binding, agonist, and antagonist activity predictions. Models were underpinned by a common training set of 1,746 chemicals compiled from a combined data set of 11 ToxCast (TM)/Tox21 HTS in vitro assays. RESULTS: The resulting models were evaluated using curated literature data extracted from different sources. To overcome the limitations of single-model approaches, CoMPARA predictions were combined into consensus models that provided averaged predictive accuracy of approximately 80% for the evaluation set. DISCUSSION: The strengths and limitations of the consensus predictions were discussed with example chemicals; then, the models were implemented into the free and open-source OPERA application to enable screening of new chemicals with a defined applicability domain and accura

Published
2020
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20. CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity

Author

Mansouri, K, Kleinstreuer, N, Abdelaziz, A, Alberga, D, Alves, V, Andersson, P, Andrade, C, Bai, F, Balabin, I, Ballabio, D, Benfenati, E, Bhhatarai, B, Boyer, S, Chen, J, Consonni, V, Farag, S, Fourches, D, García-Sosa, A, Gramatica, P, Grisoni, F, Grulke, C, Hong, H, Horvath, D, Hu, X, Huang, R, Jeliazkova, N, Li, J, Li, X, Liu, H, Manganelli, S, Mangiatordi, G, Maran, U, Marcou, G, Martin, T, Muratov, E, Nguyen, D, Nicolotti, O, Nikolov, N, Norinder, U, Papa, E, Petitjean, M, Piir, G, Pogodin, P, Poroikov, V, Qiao, X, Richard, A, Roncaglioni, A, Ruiz, P, Rupakheti, C, Sakkiah, S, Sangion, A, Schramm, K, Selvaraj, C, Shah, I, Sild, S, Sun, L, Taboureau, O, Tang, Y, Tetko, I, Todeschini, R, Tong, W, Trisciuzzi, D, Tropsha, A, Van Den Driessche, G, Varnek, A, Wang, Z, Wedebye, E, Williams, A, Xie, H, Zakharov, A, Zheng, Z, Judson, R, Mansouri, Kamel, Kleinstreuer, Nicole, Abdelaziz, Ahmed M., Alberga, Domenico, Alves, Vinicius M., Andersson, Patrik L., Andrade, Carolina H., Bai, Fang, Balabin, Ilya, Ballabio, Davide, Benfenati, Emilio, Bhhatarai, Barun, Boyer, Scott, Chen, Jingwen, Consonni, Viviana, Farag, Sherif, Fourches, Denis, García-Sosa, Alfonso T., Gramatica, Paola, Grisoni, Francesca, Grulke, Chris M., Hong, Huixiao, Horvath, Dragos, Hu, Xin, Huang, Ruili, Jeliazkova, Nina, Li, Jiazhong, Li, Xuehua, Liu, Huanxiang, Manganelli, Serena, Mangiatordi, Giuseppe F., Maran, Uko, Marcou, Gilles, Martin, Todd, Muratov, Eugene, Nguyen, Dac-Trung, Nicolotti, Orazio, Nikolov, Nikolai G., Norinder, Ulf, Papa, Ester, Petitjean, Michel, Piir, Geven, Pogodin, Pavel, Poroikov, Vladimir, Qiao, Xianliang, Richard, Ann M., Roncaglioni, Alessandra, Ruiz, Patricia, Rupakheti, Chetan, Sakkiah, Sugunadevi, Sangion, Alessandro, Schramm, Karl-Werner, Selvaraj, Chandrabose, Shah, Imran, Sild, Sulev, Sun, Lixia, Taboureau, Olivier, Tang, Yun, Tetko, Igor V., Todeschini, Roberto, Tong, Weida, Trisciuzzi, Daniela, Tropsha, Alexander, Van Den Driessche, George, Varnek, Alexandre, Wang, Zhongyu, Wedebye, Eva B., Williams, Antony J., Xie, Hongbin, Zakharov, Alexey V., Zheng, Ziye, Judson, Richard S., Mansouri, K, Kleinstreuer, N, Abdelaziz, A, Alberga, D, Alves, V, Andersson, P, Andrade, C, Bai, F, Balabin, I, Ballabio, D, Benfenati, E, Bhhatarai, B, Boyer, S, Chen, J, Consonni, V, Farag, S, Fourches, D, García-Sosa, A, Gramatica, P, Grisoni, F, Grulke, C, Hong, H, Horvath, D, Hu, X, Huang, R, Jeliazkova, N, Li, J, Li, X, Liu, H, Manganelli, S, Mangiatordi, G, Maran, U, Marcou, G, Martin, T, Muratov, E, Nguyen, D, Nicolotti, O, Nikolov, N, Norinder, U, Papa, E, Petitjean, M, Piir, G, Pogodin, P, Poroikov, V, Qiao, X, Richard, A, Roncaglioni, A, Ruiz, P, Rupakheti, C, Sakkiah, S, Sangion, A, Schramm, K, Selvaraj, C, Shah, I, Sild, S, Sun, L, Taboureau, O, Tang, Y, Tetko, I, Todeschini, R, Tong, W, Trisciuzzi, D, Tropsha, A, Van Den Driessche, G, Varnek, A, Wang, Z, Wedebye, E, Williams, A, Xie, H, Zakharov, A, Zheng, Z, Judson, R, Mansouri, Kamel, Kleinstreuer, Nicole, Abdelaziz, Ahmed M., Alberga, Domenico, Alves, Vinicius M., Andersson, Patrik L., Andrade, Carolina H., Bai, Fang, Balabin, Ilya, Ballabio, Davide, Benfenati, Emilio, Bhhatarai, Barun, Boyer, Scott, Chen, Jingwen, Consonni, Viviana, Farag, Sherif, Fourches, Denis, García-Sosa, Alfonso T., Gramatica, Paola, Grisoni, Francesca, Grulke, Chris M., Hong, Huixiao, Horvath, Dragos, Hu, Xin, Huang, Ruili, Jeliazkova, Nina, Li, Jiazhong, Li, Xuehua, Liu, Huanxiang, Manganelli, Serena, Mangiatordi, Giuseppe F., Maran, Uko, Marcou, Gilles, Martin, Todd, Muratov, Eugene, Nguyen, Dac-Trung, Nicolotti, Orazio, Nikolov, Nikolai G., Norinder, Ulf, Papa, Ester, Petitjean, Michel, Piir, Geven, Pogodin, Pavel, Poroikov, Vladimir, Qiao, Xianliang, Richard, Ann M., Roncaglioni, Alessandra, Ruiz, Patricia, Rupakheti, Chetan, Sakkiah, Sugunadevi, Sangion, Alessandro, Schramm, Karl-Werner, Selvaraj, Chandrabose, Shah, Imran, Sild, Sulev, Sun, Lixia, Taboureau, Olivier, Tang, Yun, Tetko, Igor V., Todeschini, Roberto, Tong, Weida, Trisciuzzi, Daniela, Tropsha, Alexander, Van Den Driessche, George, Varnek, Alexandre, Wang, Zhongyu, Wedebye, Eva B., Williams, Antony J., Xie, Hongbin, Zakharov, Alexey V., Zheng, Ziye, and Judson, Richard S.

Abstract

BACKGROUND: Endocrine disrupting chemicals (EDCs) are xenobiotics that mimic the interaction of natural hormones and alter synthesis, transport, or metabolic pathways. The prospect of EDCs causing adverse health effects in humans and wildlife has led to the development of scientific and regulatory approaches for evaluating bioactivity. This need is being addressed using high-throughput screening (HTS) in vitro approaches and computational modeling. OBJECTIVES: In support of the Endocrine Disruptor Screening Program, the U.S. Environmental Protection Agency (EPA) led two worldwide consortiums to virtually screen chemicals for their potential estrogenic and androgenic activities. Here, we describe the Collaborative Modeling Project for Androgen Receptor Activity (CoMPARA) efforts, which follows the steps of the Collaborative Estrogen Receptor Activity Prediction Project (CERAPP). METHODS: The CoMPARA list of screened chemicals built on CERAPP’s list of 32,464 chemicals to include additional chemicals of interest, as well as simulated ToxCastTM metabolites, totaling 55,450 chemical structures. Computational toxicology scientists from 25 international groups contributed 91 predictive models for binding, agonist, and antagonist activity predictions. Models were underpinned by a common training set of 1,746 chemicals compiled from a combined data set of 11 ToxCastTM/Tox21 HTS in vitro assays. RESULTS: The resulting models were evaluated using curated literature data extracted from different sources. To overcome the limitations of single-model approaches, CoMPARA predictions were combined into consensus models that provided averaged predictive accuracy of approximately 80% for the evaluation set. DISCUSSION: The strengths and limitations of the consensus predictions were discussed with example chemicals; then, the models were implemented into the free and open-source OPERA application to enable screening of new chemicals with a defined applicability domain and accuracy ass

Published
2020

21. Enhancing the Sensitivity of Biotinylated Surfaces by Tailoring the Design of the Mixed Self-Assembled Monolayer Synthesis

Author

Blasi, Davide, primary, Sarcina, Lucia, additional, Tricase, Angelo, additional, Stefanachi, Angela, additional, Leonetti, Francesco, additional, Alberga, Domenico, additional, Mangiatordi, Giuseppe Felice, additional, Manoli, Kyriaki, additional, Scamarcio, Gaetano, additional, Picca, Rosaria Anna, additional, and Torsi, Luisa, additional

Published
2020
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22. CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity

Author

Mansouri, Kamel, primary, Kleinstreuer, Nicole, additional, Abdelaziz, Ahmed M., additional, Alberga, Domenico, additional, Alves, Vinicius M., additional, Andersson, Patrik L., additional, Andrade, Carolina H., additional, Bai, Fang, additional, Balabin, Ilya, additional, Ballabio, Davide, additional, Benfenati, Emilio, additional, Bhhatarai, Barun, additional, Boyer, Scott, additional, Chen, Jingwen, additional, Consonni, Viviana, additional, Farag, Sherif, additional, Fourches, Denis, additional, García-Sosa, Alfonso T., additional, Gramatica, Paola, additional, Grisoni, Francesca, additional, Grulke, Chris M., additional, Hong, Huixiao, additional, Horvath, Dragos, additional, Hu, Xin, additional, Huang, Ruili, additional, Jeliazkova, Nina, additional, Li, Jiazhong, additional, Li, Xuehua, additional, Liu, Huanxiang, additional, Manganelli, Serena, additional, Mangiatordi, Giuseppe F., additional, Maran, Uko, additional, Marcou, Gilles, additional, Martin, Todd, additional, Muratov, Eugene, additional, Nguyen, Dac-Trung, additional, Nicolotti, Orazio, additional, Nikolov, Nikolai G., additional, Norinder, Ulf, additional, Papa, Ester, additional, Petitjean, Michel, additional, Piir, Geven, additional, Pogodin, Pavel, additional, Poroikov, Vladimir, additional, Qiao, Xianliang, additional, Richard, Ann M., additional, Roncaglioni, Alessandra, additional, Ruiz, Patricia, additional, Rupakheti, Chetan, additional, Sakkiah, Sugunadevi, additional, Sangion, Alessandro, additional, Schramm, Karl-Werner, additional, Selvaraj, Chandrabose, additional, Shah, Imran, additional, Sild, Sulev, additional, Sun, Lixia, additional, Taboureau, Olivier, additional, Tang, Yun, additional, Tetko, Igor V., additional, Todeschini, Roberto, additional, Tong, Weida, additional, Trisciuzzi, Daniela, additional, Tropsha, Alexander, additional, Van Den Driessche, George, additional, Varnek, Alexandre, additional, Wang, Zhongyu, additional, Wedebye, Eva B., additional, Williams, Antony J., additional, Xie, Hongbin, additional, Zakharov, Alexey V., additional, Zheng, Ziye, additional, and Judson, Richard S., additional

Published
2020
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28. Single-molecule detection with a millimetre-sized transistor

Author

Macchia, Eleonora, primary, Manoli, Kyriaki, additional, Holzer, Brigitte, additional, Di Franco, Cinzia, additional, Ghittorelli, Matteo, additional, Torricelli, Fabrizio, additional, Alberga, Domenico, additional, Mangiatordi, Giuseppe Felice, additional, Palazzo, Gerardo, additional, Scamarcio, Gaetano, additional, and Torsi, Luisa, additional

Published
2018
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35. Understanding complexity of physiology by combined molecular simulations and experiments: anion channels as a proof of concept

Author

Alberga, Domenico and Mangiatordi, Giuseppe F.

Subjects
Bicarbonates, HEK293 Cells, Receptors, Glycine, Chloride Channels, Nuclear Pore, Cystic Fibrosis Transmembrane Conductance Regulator, Humans, Molecular Dynamics, Anoctamin-1, Permeability, Perspectives, Neoplasm Proteins, Protein Structure, Tertiary
Abstract

Cellular stimuli can modulate the ion selectivity of some anion channels, such as CFTR, ANO1 and the glycine receptor (GlyR), by changing pore size. Ion selectivity of CFTR, ANO1 and GlyR is critically affected by the electric permittivity and diameter of the channel pore. Pore size change affects the energy barriers of ion dehydration as well as that of size-exclusion of anion permeation. Pore dilatation increases the bicarbonate permeability (P HC O3/ Cl ) of CFTR, ANO1 and GlyR. Dynamic change in P HC O3/ Cl may mediate many physiological and pathological processes.Chloride (Cl(-) ) and bicarbonate (HCO3 (-) ) are two major anions and their permeation through anion channels plays essential roles in our body. However, the mechanism of ion selection by the anion channels is largely unknown. Here, we provide evidence that pore dilatation increases the bicarbonate permeability (P HC O3/ Cl ) of anion channels by reducing energy barriers of size-exclusion and ion dehydration of HCO3 (-) permeation. Molecular, physiological and computational analyses of major anion channels, such as cystic fibrosis transmembrane conductance regulator (CFTR), anoctamin-1(ANO1/TMEM16A) and the glycine receptor (GlyR), revealed that the ion selectivity of anion channels is basically determined by the electric permittivity and diameter of the pore. Importantly, cellular stimuli dynamically modulate the anion selectivity of CFTR and ANO1 by changing the pore size. In addition, pore dilatation by a mutation in the pore-lining region alters the anion selectivity of GlyR. Changes in pore size affected not only the energy barriers of size exclusion but that of ion dehydration by altering the electric permittivity of water-filled cavity in the pore. The dynamic increase in P HC O3/ Cl by pore dilatation may have many physiological and pathophysiological implications ranging from epithelial HCO3 (-) secretion to neuronal excitation.

Published
2016
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39. Prediction of Acute Oral Systemic Toxicity Using a Multifingerprint Similarity Approach.

Author

Alberga, Domenico, Trisciuzzi, Daniela, Mansouri, Kamel, Mangiatordi, Giuseppe Felice, and Nicolotti, Orazio

Subjects
*ACUTE toxicity testing, *ALTERNATIVE toxicity testing, *K-nearest neighbor classification, *CHEMICAL accidents & health
Abstract

The implementation of nonanimal approaches is of particular importance to regulatory agencies for the prediction of potential hazards associated with acute exposures to chemicals. This work was carried out in the framework of an international modeling initiative organized by the Acute Toxicity Workgroup (ATWG) of the Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM) with the participation of 32 international groups across government, industry, and academia. Our contribution was to develop a multifingerprints similarity approach for predicting five relevant toxicology endpoints related to the acute oral systemic toxicity that are: the median lethal dose (LD50) point prediction, the "nontoxic" (LD50 > 2000 mg/kg) and "very toxic" (LD50<50 mg/kg) binary classification, and the multiclass categorization of chemicals based on the United States Environmental Protection Agency and Globally Harmonized System of Classification and Labeling of Chemicals schemes. Provided by the ICCVAM's ATWG, the training set used to develop the models consisted of 8944 chemicals having high-quality rat acute oral lethality data. The proposed approach integrates the results coming from a similarity search based on 19 different fingerprint definitions to return a consensus prediction value. Moreover, the herein described algorithm is tailored to properly tackling the so-called toxicity cliffs alerting that a large gap in LD50 values exists despite a high structural similarity for a given molecular pair. An external validation set made available by ICCVAM and consisting in 2896 chemicals was employed to further evaluate the selected models. This work returned high-accuracy predictions based on the evaluations conducted by ICCVAM's ATWG. [ABSTRACT FROM AUTHOR]

Published
2019
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42. Design, synthesis, biological evaluation, NMR and DFT studies of structurally simplified trimethoxy benzamides as selective P-glycoprotein inhibitors: the role of molecular flatness

Author

Stefanachi, Angela, primary, Mangiatordi, Giuseppe Felice, additional, Tardia, Piero, additional, Alberga, Domenico, additional, Leonetti, Francesco, additional, Niso, Mauro, additional, Colabufo, Nicola Antonio, additional, Adamo, Carlo, additional, Nicolotti, Orazio, additional, and Cellamare, Saverio, additional

Published
2016
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45. Multidisciplinary study of a new CIC‐1 mutation causing myotonia congenita: a paradigm to understand and treat ion channelopathies

Author

Imbrici, Paola, primary, Altamura, Concetta, additional, Camerino, Giulia Maria, additional, Mangiatordi, Giuseppe Felice, additional, Conte, Elena, additional, Maggi, Lorenzo, additional, Brugnoni, Raffaella, additional, Musaraj, Kejla, additional, Caloiero, Roberta, additional, Alberga, Domenico, additional, Marsano, Renè Massimiliano, additional, Ricci, Giulia, additional, Siciliano, Gabriele, additional, Nicolotti, Orazio, additional, Mora, Marina, additional, Bernasconi, Pia, additional, Desaphy, Jean‐Francois, additional, Mantegazza, Renato, additional, and Camerino, Diana Conte, additional

Published
2016
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47. Mind the Gap! A Journey towards Computational Toxicology

Author

Mangiatordi, Giuseppe Felice, primary, Alberga, Domenico, additional, Altomare, Cosimo Damiano, additional, Carotti, Angelo, additional, Catto, Marco, additional, Cellamare, Saverio, additional, Gadaleta, Domenico, additional, Lattanzi, Gianluca, additional, Leonetti, Francesco, additional, Pisani, Leonardo, additional, Stefanachi, Angela, additional, Trisciuzzi, Daniela, additional, and Nicolotti, Orazio, additional

Published
2016
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48. Optoeletronic properties of poly( N-alkenyl-carbazole)s driven by polymer stereoregularity.

Author

Botta, Antonio, Costabile, Chiara, Venditto, Vincenzo, Pragliola, Stefania, Liguori, Rosalba, Rubino, Alfredo, Alberga, Domenico, Savarese, Marika, and Adamo, Carlo

Subjects
ELECTRIC properties of polymers, CATALYTIC activity, HOMOGENEOUS catalysis, CARBAZOLE, ZIEGLER-Natta catalysts, ZIRCONIUM catalysts
Abstract

ABSTRACT Stereoregular polymers like isotactic poly( N-butenyl-carbazole) ( i-PBK), isotactic and syndiotactic poly( N-pentenyl-carbazole) ( i-PPK and s-PPK), and poly( N-hexenyl-carbazole) ( i-PHK and s-PHK) are synthesized using the stereospecific homogeneous 'single site' Ziegler-Natta (Z-N) catalysts: rac-dimethylsilylbis(1-indenyl)zirconium dichloride ( 1)/methylaluminoxane (MAO) and diphenylmethylidene(cyclopentadienyl)-(9-fluorenyl)zirconium dichloride ( 2)/MAO. Catalytic activity is rationalized by density functional theory (DFT) calculations. All synthesized polymers are fully characterized by NMR, thermal, wide-angle X-ray diffraction, and fourier transform infrared spectroscopy analysis. Fluorescence measurements on isotactic and syndiotactic polymer films indicate that all polymers give rise to excimers, both 'sandwich-like' and 'partially overlapping.' Excimer formation is essentially driven by the polymer tacticity. Isotactic polymers generate both sandwich-like and partially overlapping excimers, while syndiotactic polymers give rise especially to partially overlapping ones. A theoretical combined molecular dynamics-time dependent DFT approach is also used to support the experimental results. © 2017 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2018, 56, 242-251 [ABSTRACT FROM AUTHOR]

Published
2018
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