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V.I. Ivashchenko, P.E.A. Turchi, V.I. Shevchenko, N.R. Mediukh, Leonid Gorb, Jerzy Leszczynski Phase diagram, electronic, mechanical and thermodynamic properties of TiB2–ZrB2 solid solutions: A first-principles study Journal Article Mater. Chem. Phys., 263 , pp. 124340, 2021. Abstract | Links | BibTeX | Tags: BSE, DSSC, Elastic properties, Electronic properties, Exciton, First-principles, GW, Optical properties, Ti-Zr-B2 @article{Ivashchenko2021, title = {Phase diagram, electronic, mechanical and thermodynamic properties of TiB2\textendashZrB2 solid solutions: A first-principles study}, author = {V.I. Ivashchenko, P.E.A. Turchi, V.I. Shevchenko, N.R. Mediukh, Leonid Gorb, Jerzy Leszczynski}, doi = {https://doi.org/10.1016/j.matchemphys.2021.124340}, year = {2021}, date = {2021-04-15}, journal = {Mater. Chem. Phys.}, volume = {263}, pages = {124340}, abstract = {The stability, electronic and phonon structures, mechanical and thermodynamic properties as well optical spectra of the Ti1−xZrxB2 solid solutions were investigated in the framework of a first-principles approach. The miscibility gap was predicted with the consolute temperature TC = 1973 K and composition xC = 0.4. The negative deviation of the calculated bulk, shear, Young moduli, Debye temperature, Vickers hardness and fracture toughness from the mixing rule is observed. The ideal shear stress of 41.1 GPa for Ti0.5Zr0.5B2 was found to be lower compared to that for TiB2 (43.5 GPa) and ZrB2 (43.1 GPa). The calculated elastic moduli and Poisson ratio exhibit the spatial anisotropy inherent to hexagonal structures. It was shown that the thermodynamic characteristics of the Zr-rich solid solutions could be well reproduced in a temperature range up to 1000\textendash1400 K using the harmonic approximation. The calculated dielectric constants and , and optical reflectivity spectra for Ti1−xZrxB2 were analyzed in comparison with available optical spectra of parent diborides from other authors.}, keywords = {BSE, DSSC, Elastic properties, Electronic properties, Exciton, First-principles, GW, Optical properties, Ti-Zr-B2}, pubstate = {published}, tppubtype = {article} } The stability, electronic and phonon structures, mechanical and thermodynamic properties as well optical spectra of the Ti1−xZrxB2 solid solutions were investigated in the framework of a first-principles approach. The miscibility gap was predicted with the consolute temperature TC = 1973 K and composition xC = 0.4. The negative deviation of the calculated bulk, shear, Young moduli, Debye temperature, Vickers hardness and fracture toughness from the mixing rule is observed. The ideal shear stress of 41.1 GPa for Ti0.5Zr0.5B2 was found to be lower compared to that for TiB2 (43.5 GPa) and ZrB2 (43.1 GPa). The calculated elastic moduli and Poisson ratio exhibit the spatial anisotropy inherent to hexagonal structures. It was shown that the thermodynamic characteristics of the Zr-rich solid solutions could be well reproduced in a temperature range up to 1000–1400 K using the harmonic approximation. The calculated dielectric constants and , and optical reflectivity spectra for Ti1−xZrxB2 were analyzed in comparison with available optical spectra of parent diborides from other authors. | |
Iryna O. Borysenko, Liudmyla K. Sviatenko, Sergiy I. Okovytyy, Jerzy Leszczynski Struct. Chem., 32 , pp. 581 - 589, 2021. Abstract | Links | BibTeX | Tags: DFT, Epoxide ring opening reaction @article{Borysenko2021, title = {Efficient approach for exploring the multiple-channel bimolecular interactions of conformationally flexible reagents. Epoxide ring opening reaction}, author = {Iryna O. Borysenko, Liudmyla K. Sviatenko, Sergiy I. Okovytyy, Jerzy Leszczynski}, doi = {https://doi.org/10.1007/s11224-020-01663-0}, year = {2021}, date = {2021-04-15}, journal = {Struct. Chem.}, volume = {32}, pages = {581 - 589}, abstract = {Algorithm for generation and assessment of probability of possible reaction pathways for multiple-channel bimolecular interactions is presented. The proposed algorithm comprises a combination of few steps. They include conformational search for reaction intermediate using the molecular mechanics (MMX) approach, based on the obtained conformation construction of structures of transition states and pre-reaction complexes, and calculation activation energies to further determine the probable reaction pathways. The proposed algorithm could be adopted for investigation of chemical and biochemical reactions of different types. Here, we have considered the reaction of bicyclo[2.2.1]hept-5-en-endo-2-ylmethylamine (1) with glycidyl ether (2) in a neutral environment that proceeds through SN2-like mechanism forming bipolar ion (3) which is a good starting point for identification of the reaction channels. Conformational properties of intermediate (3) have been investigated using stochastic conformational search. From the 95 localized conformations within 10 kcal/mol of global minimum that have been obtained, 63 unique transition state conformations were generated and optimized by using the PM7 and M062X/6-31G(d) methods for accurate estimation of overall rate constant of reaction. The most energetically favorable pathways have been investigated at the M062X/6-31G(d) level of theory taking into account the influence of solvent.}, keywords = {DFT, Epoxide ring opening reaction}, pubstate = {published}, tppubtype = {article} } Algorithm for generation and assessment of probability of possible reaction pathways for multiple-channel bimolecular interactions is presented. The proposed algorithm comprises a combination of few steps. They include conformational search for reaction intermediate using the molecular mechanics (MMX) approach, based on the obtained conformation construction of structures of transition states and pre-reaction complexes, and calculation activation energies to further determine the probable reaction pathways. The proposed algorithm could be adopted for investigation of chemical and biochemical reactions of different types. Here, we have considered the reaction of bicyclo[2.2.1]hept-5-en-endo-2-ylmethylamine (1) with glycidyl ether (2) in a neutral environment that proceeds through SN2-like mechanism forming bipolar ion (3) which is a good starting point for identification of the reaction channels. Conformational properties of intermediate (3) have been investigated using stochastic conformational search. From the 95 localized conformations within 10 kcal/mol of global minimum that have been obtained, 63 unique transition state conformations were generated and optimized by using the PM7 and M062X/6-31G(d) methods for accurate estimation of overall rate constant of reaction. The most energetically favorable pathways have been investigated at the M062X/6-31G(d) level of theory taking into account the influence of solvent. | |
Juganta K. Roy, Henry P. Pinto, Jerzy Leszczynski Interaction of epoxy-based hydrogels and water: A molecular dynamics simulation study Journal Article J MOL GRAPH MODEL, 106 , pp. 107915, 2021. Abstract | Links | BibTeX | Tags: Atomistic MD simulation, Biomaterials, Epoxy-based hydrogel, Gibbs dividing surface, Surface roughness, Swelling behavior @article{Roy2021, title = {Interaction of epoxy-based hydrogels and water: A molecular dynamics simulation study}, author = {Juganta K. Roy, Henry P. Pinto, Jerzy Leszczynski}, doi = {https://doi.org/10.1016/j.jmgm.2021.107915}, year = {2021}, date = {2021-04-13}, journal = {J MOL GRAPH MODEL}, volume = {106}, pages = {107915}, abstract = {Biomaterials play a crucial role in tissue engineering as a functional replacement, regenerative medicines, supportive scaffold for guided tissue growth, and drug delivery devices. The term biomaterial refers to metals, ceramics, and polymers account for the vast majority. In the case of polymers, hydrogels have emerged as active materials for an immense variety of applications. Epoxy-based hydrogels possess a unique network structure that enables very high levels of hydrophilicity and biocompatibility. Hydrogel such as Medipacs Epoxy Polymers (MEPs) models were constructed to understand water’s behavior at the water/hydrogel interface and hydrogel network. We computed the Gibbs dividing surface (GDS) to define the MEP/water interface, and all the physicochemical properties were computed based on GDS. We calculated the radial distribution function (RDF), the 2D surface roughness of the immersed MEPs. RDF analysis confirmed that the first hydration shell is at a distance of 1.86 r{A}, and most of the water molecules are near the hydroxyl group of the MEPs network. Hydrogen bonds (H-bonds) analysis was performed, and the observation suggested that the disruption of the H-bonds between MEP chains leads to an increase in the polymer matrix’s void spaces. These void spaces are filled with diffused water molecules, leading to swelling of the MEP hydrogel. The swelling parameter was estimated from the fitted curve of the yz-lattice of the simulation cell. The MEP/water interface simulation results provide insightful information regarding the design strategy of epoxy-based hydrogel and other hydrogels vital for biomedical applications.}, keywords = {Atomistic MD simulation, Biomaterials, Epoxy-based hydrogel, Gibbs dividing surface, Surface roughness, Swelling behavior}, pubstate = {published}, tppubtype = {article} } Biomaterials play a crucial role in tissue engineering as a functional replacement, regenerative medicines, supportive scaffold for guided tissue growth, and drug delivery devices. The term biomaterial refers to metals, ceramics, and polymers account for the vast majority. In the case of polymers, hydrogels have emerged as active materials for an immense variety of applications. Epoxy-based hydrogels possess a unique network structure that enables very high levels of hydrophilicity and biocompatibility. Hydrogel such as Medipacs Epoxy Polymers (MEPs) models were constructed to understand water’s behavior at the water/hydrogel interface and hydrogel network. We computed the Gibbs dividing surface (GDS) to define the MEP/water interface, and all the physicochemical properties were computed based on GDS. We calculated the radial distribution function (RDF), the 2D surface roughness of the immersed MEPs. RDF analysis confirmed that the first hydration shell is at a distance of 1.86 Å, and most of the water molecules are near the hydroxyl group of the MEPs network. Hydrogen bonds (H-bonds) analysis was performed, and the observation suggested that the disruption of the H-bonds between MEP chains leads to an increase in the polymer matrix’s void spaces. These void spaces are filled with diffused water molecules, leading to swelling of the MEP hydrogel. The swelling parameter was estimated from the fitted curve of the yz-lattice of the simulation cell. The MEP/water interface simulation results provide insightful information regarding the design strategy of epoxy-based hydrogel and other hydrogels vital for biomedical applications. | |
S. Kar, J. Leszczynski Chapter: Drug Databases for Development of Therapeutics Against Coronaviruses Book Chapter K. Roy, Ed (Ed.): pp. 761-780, Springer, New York, NY, 2021, ISBN: 978-1-0716-1366-5. Abstract | Links | BibTeX | Tags: Antiviral, COVID-19, Database Repurposing, SARS-CoV-2, Virtual screening @inbook{Kar2021b, title = {Chapter: Drug Databases for Development of Therapeutics Against Coronaviruses}, author = {S. Kar, J. Leszczynski}, editor = {K. Roy, Ed}, doi = {https://doi.org/10.1007/7653_2020_66}, isbn = {978-1-0716-1366-5}, year = {2021}, date = {2021-04-06}, pages = {761-780}, publisher = {Springer, New York, NY}, series = {In Silico Modeling of Drugs Against Coronaviruses. Methods in Pharmacology and Toxicology. }, abstract = {Within a span of 11 months starting from December 2019, around 47.6 million people have been infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), including the number of deaths touching 1,215,601 on November 3, 2020. The number increases at an alarming rate with a possible second wave of Coronavirus Disease 2019 (COVID-19) throughout the world. A clear threat of another lockdown is looming over the social life and economy. Thus, scientists worldwide are running against the time to find small drug molecules as therapeutics and possible vaccines to relieve the world. Over the past months, computational chemistry and computer-aided drug design (CADD) have shown encouraging promises in generating multiple lead/hit compounds by employing powerful virtual screening techniques (VS) and drug repurposing of various approved and experimental drugs. The present chapter has enlisted and discussed the top 25 small molecule databases, including both synthetic as well as natural compounds. Most of the databases are freely available for research purposes, which can be strategically screened employing multiple computational techniques to discover therapeutics for COVID-19.}, keywords = {Antiviral, COVID-19, Database Repurposing, SARS-CoV-2, Virtual screening}, pubstate = {published}, tppubtype = {inbook} } Within a span of 11 months starting from December 2019, around 47.6 million people have been infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), including the number of deaths touching 1,215,601 on November 3, 2020. The number increases at an alarming rate with a possible second wave of Coronavirus Disease 2019 (COVID-19) throughout the world. A clear threat of another lockdown is looming over the social life and economy. Thus, scientists worldwide are running against the time to find small drug molecules as therapeutics and possible vaccines to relieve the world. Over the past months, computational chemistry and computer-aided drug design (CADD) have shown encouraging promises in generating multiple lead/hit compounds by employing powerful virtual screening techniques (VS) and drug repurposing of various approved and experimental drugs. The present chapter has enlisted and discussed the top 25 small molecule databases, including both synthetic as well as natural compounds. Most of the databases are freely available for research purposes, which can be strategically screened employing multiple computational techniques to discover therapeutics for COVID-19. | |
Agnieszka Gajewicz Skretna, Supratik Kar, Magdalena Piotrowska, Jerzy Leszczynski J. Cheminform., 13 (9), pp. 1-20, 2021. Abstract | Links | BibTeX | Tags: kernel weighted local polynomial regression, QSAR @article{Skretna2021, title = {The kernel weighted local polynomial regression (KwLPR) approach: an efficient, novel tool for development of QSAR/QSAAR toxicity extrapolation models.}, author = {Agnieszka Gajewicz Skretna, Supratik Kar, Magdalena Piotrowska, Jerzy Leszczynski}, doi = {https://doi.org/10.1186/s13321-021-00484-5}, year = {2021}, date = {2021-02-12}, journal = {J. Cheminform.}, volume = {13}, number = {9}, pages = {1-20}, abstract = {The ability of accurate predictions of biological response (biological activity/property/toxicity) of a given chemical makes the quantitative structure‐activity/property/toxicity relationship (QSAR/QSPR/QSTR) models unique among the in silico tools. In addition, experimental data of selected species can also be used as an independent variable along with other structural as well as physicochemical variables to predict the response for different species formulating quantitative activity\textendashactivity relationship (QAAR)/quantitative structure\textendashactivity\textendashactivity relationship (QSAAR) approach. Irrespective of the models' type, the developed model's quality, and reliability need to be checked through multiple classical stringent validation metrics. Among the validation metrics, error-based metrics are more significant as the basic idea of a good predictive model is to improve the predictions' quality by lowering the predicted residuals for new query compounds. Following the concept, we have checked the predictive quality of the QSAR and QSAAR models employing kernel-weighted local polynomial regression (KwLPR) approach over the traditional linear and non-linear regression-based approaches tools such as multiple linear regression (MLR) and k nearest neighbors (kNN). Five datasets which were previously modeled using linear and non-linear regression method were considered to implement the KwPLR approach, followed by comparison of their validation metrics outcomes. For all five cases, the KwLPR based models reported better results over the traditional approaches. The present study's focus is not to develop a better or improved QSAR/QSAAR model over the previous ones, but to demonstrate the advantage, prediction power, and reliability of the KwLPR algorithm and establishing it as a novel, powerful cheminformatic tool. To facilitate the use of the KwLPR algorithm for QSAR/QSPR/QSTR/QSAAR modeling, the authors provide an in-house developed KwLPR.RMD script under the open-source R programming language.}, keywords = {kernel weighted local polynomial regression, QSAR}, pubstate = {published}, tppubtype = {article} } The ability of accurate predictions of biological response (biological activity/property/toxicity) of a given chemical makes the quantitative structure‐activity/property/toxicity relationship (QSAR/QSPR/QSTR) models unique among the in silico tools. In addition, experimental data of selected species can also be used as an independent variable along with other structural as well as physicochemical variables to predict the response for different species formulating quantitative activity–activity relationship (QAAR)/quantitative structure–activity–activity relationship (QSAAR) approach. Irrespective of the models' type, the developed model's quality, and reliability need to be checked through multiple classical stringent validation metrics. Among the validation metrics, error-based metrics are more significant as the basic idea of a good predictive model is to improve the predictions' quality by lowering the predicted residuals for new query compounds. Following the concept, we have checked the predictive quality of the QSAR and QSAAR models employing kernel-weighted local polynomial regression (KwLPR) approach over the traditional linear and non-linear regression-based approaches tools such as multiple linear regression (MLR) and k nearest neighbors (kNN). Five datasets which were previously modeled using linear and non-linear regression method were considered to implement the KwPLR approach, followed by comparison of their validation metrics outcomes. For all five cases, the KwLPR based models reported better results over the traditional approaches. The present study's focus is not to develop a better or improved QSAR/QSAAR model over the previous ones, but to demonstrate the advantage, prediction power, and reliability of the KwLPR algorithm and establishing it as a novel, powerful cheminformatic tool. To facilitate the use of the KwLPR algorithm for QSAR/QSPR/QSTR/QSAAR modeling, the authors provide an in-house developed KwLPR.RMD script under the open-source R programming language. | |
Supratik Kar, Kavitha Pathakoti, Paul B. Tchounwou, Danuta Leszczynska, Jerzy Leszczynski Chemosphere, 264 , pp. 128428, 2021. Abstract | Links | BibTeX | Tags: Classification, in silico, In vitro, Machine learning, Metal oxide, Nanoparticles, Toxicity @article{Kar2021c, title = {Evaluating the cytotoxicity of a large pool of metal oxide nanoparticles to Escherichia coli: Mechanistic understanding through In Vitro and In Silico studies}, author = {Supratik Kar, Kavitha Pathakoti, Paul B. Tchounwou, Danuta Leszczynska, Jerzy Leszczynski}, doi = {https://doi.org/10.1016/j.chemosphere.2020.128428}, year = {2021}, date = {2021-02-11}, journal = {Chemosphere}, volume = {264}, pages = {128428}, abstract = {The toxic effect of eight metal oxide nanoparticles (MONPs) on Escherichia coli was experimentally evaluated following standard bioassay protocols. The obtained cytotoxicity ranking of these studied MONPs is Er2O3, Gd2O3, CeO2, Co2O3, Mn2O3, Co3O4, Fe3O4/WO3 (in descending order). The computed EC50 values from experimental data suggested that Er2O3 and Gd2O3 were the most acutely toxic MONPs to E. coli. To identify the mechanism of toxicity of these 8 MONPs along with 17 other MONPs from our previous study, we employed seven classifications and machine learning (ML) algorithms including linear discriminant analysis (LDA), na\"{i}ve bayes (NB), multinomial logistic regression (MLogitR), sequential minimal optimization (SMO), AdaBoost, J48, and random forest (RF). We also employed 1st and 2nd generation periodic table descriptors developed by us (without any sophisticated computing facilities) along with experimentally analyzed Zeta-potential, to model the cytotoxicity of these MONPs. Based on qualitative validation metrics, the LDA model appeared to be the best among the 7 tested models. The core environment of metal defined by the ratio of the number of core electrons to the number of valence electrons and the electronegativity count of oxygen showed a positive impact on toxicity. The identified properties were important for understanding the mechanisms of nanotoxicity and for predicting the potential environmental risk associated with MONPs exposure. The developed models can be utilized for environmental risk assessment of any untested MONP to E. coli, thereby providing a scientific basis for the design and preparation of safe nanomaterials.}, keywords = {Classification, in silico, In vitro, Machine learning, Metal oxide, Nanoparticles, Toxicity}, pubstate = {published}, tppubtype = {article} } The toxic effect of eight metal oxide nanoparticles (MONPs) on Escherichia coli was experimentally evaluated following standard bioassay protocols. The obtained cytotoxicity ranking of these studied MONPs is Er2O3, Gd2O3, CeO2, Co2O3, Mn2O3, Co3O4, Fe3O4/WO3 (in descending order). The computed EC50 values from experimental data suggested that Er2O3 and Gd2O3 were the most acutely toxic MONPs to E. coli. To identify the mechanism of toxicity of these 8 MONPs along with 17 other MONPs from our previous study, we employed seven classifications and machine learning (ML) algorithms including linear discriminant analysis (LDA), naïve bayes (NB), multinomial logistic regression (MLogitR), sequential minimal optimization (SMO), AdaBoost, J48, and random forest (RF). We also employed 1st and 2nd generation periodic table descriptors developed by us (without any sophisticated computing facilities) along with experimentally analyzed Zeta-potential, to model the cytotoxicity of these MONPs. Based on qualitative validation metrics, the LDA model appeared to be the best among the 7 tested models. The core environment of metal defined by the ratio of the number of core electrons to the number of valence electrons and the electronegativity count of oxygen showed a positive impact on toxicity. The identified properties were important for understanding the mechanisms of nanotoxicity and for predicting the potential environmental risk associated with MONPs exposure. The developed models can be utilized for environmental risk assessment of any untested MONP to E. coli, thereby providing a scientific basis for the design and preparation of safe nanomaterials. | |
Karina Kapusta, Supratik Kar, Jasmine T. Collins, Latasha M. Franklin, Wojciech Kolodziejczyk, Jerzy Leszczynski & Glake A. Hill J. Biomol. Struct. Dyn. , 39 (17), pp. 6810-6827, 2021. Abstract | Links | BibTeX | Tags: Docking, Molecular dynamics, Natural compounds, Protein reliability, SARS-CoV-2, Virtual screening @article{Kapusta2021, title = {Protein reliability analysis and virtual screening of natural inhibitors for SARS-CoV-2 main protease (Mpro) through docking, molecular mechanic & dynamic, and ADMET profiling.}, author = {Karina Kapusta, Supratik Kar, Jasmine T. Collins, Latasha M. Franklin, Wojciech Kolodziejczyk, Jerzy Leszczynski & Glake A. Hill}, doi = {https://doi.org/10.1080/07391102.2020.1806930}, year = {2021}, date = {2021-02-10}, journal = {J. Biomol. Struct. Dyn. }, volume = {39}, number = {17}, pages = {6810-6827}, abstract = {Due to an outbreak of COVID-19, the number of research papers devoted to in-silico drug discovery of potential antiviral drugs is increasing every day exponentially. Still, there is no specific drug to prevent or treat this novel coronavirus (SARS-CoV-2) disease. Thus, the screening for a potential remedy presents a global challenge for scientists. Up to date over a hundred crystallographic structures of SARS-CoV-2 Mpro have been deposited to Protein Data Bank. With many known proteins, the demand for a reliable target has become higher than ever, so as the choice of an efficient computational methods. Therefore, in this study comparative methods have been used for receptor-based virtual screening, targeting 9 selected structures of viral Mpro. Reliability analyses followed by re-docking of the specific co-crystallized ligand provided the best reproductivity for structures with PDB ID 6LU7, 6Y2G and 6Y2F. The influence of crystallographic water on an outcome of a virtual screening against selected targets was also investigated. Once the most reliable targets were selected, the library of easy purchasable natural compounds were retrieved from the MolPort database (10,305 compounds) and docked against the selected Mpro proteins. To ensure the efficiency of the selected compounds, binding energies for top-15 hit ligands were calculated using Molecular Mechanics as well as their absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties were predicted. Based on predicted binding energies and toxicities, top-5 compounds were selected and subjected to Molecular Dynamics simulation and found to be stable in complex to act as possible inhibitors for SARS-CoV-2.}, keywords = {Docking, Molecular dynamics, Natural compounds, Protein reliability, SARS-CoV-2, Virtual screening}, pubstate = {published}, tppubtype = {article} } Due to an outbreak of COVID-19, the number of research papers devoted to in-silico drug discovery of potential antiviral drugs is increasing every day exponentially. Still, there is no specific drug to prevent or treat this novel coronavirus (SARS-CoV-2) disease. Thus, the screening for a potential remedy presents a global challenge for scientists. Up to date over a hundred crystallographic structures of SARS-CoV-2 Mpro have been deposited to Protein Data Bank. With many known proteins, the demand for a reliable target has become higher than ever, so as the choice of an efficient computational methods. Therefore, in this study comparative methods have been used for receptor-based virtual screening, targeting 9 selected structures of viral Mpro. Reliability analyses followed by re-docking of the specific co-crystallized ligand provided the best reproductivity for structures with PDB ID 6LU7, 6Y2G and 6Y2F. The influence of crystallographic water on an outcome of a virtual screening against selected targets was also investigated. Once the most reliable targets were selected, the library of easy purchasable natural compounds were retrieved from the MolPort database (10,305 compounds) and docked against the selected Mpro proteins. To ensure the efficiency of the selected compounds, binding energies for top-15 hit ligands were calculated using Molecular Mechanics as well as their absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties were predicted. Based on predicted binding energies and toxicities, top-5 compounds were selected and subjected to Molecular Dynamics simulation and found to be stable in complex to act as possible inhibitors for SARS-CoV-2. | |
Probir Kumar Ojha, Supratik Kar, Jillella Gopala Krishna, Kunal Roy, Jerzy Leszczynski Therapeutics for COVID-19: from computation to practices—where we are, where we are heading to. Journal Article Mol. Divers., 25 , pp. 625–659 , 2021, (NSF/CREST HRD-1547754 NSF/RISE HRD-1547836). Abstract | Links | BibTeX | Tags: Computational, Coronavirus, COVID-19, Drug, SARS-CoV-2, Vaccine @article{Ojha2021, title = {Therapeutics for COVID-19: from computation to practices\textemdashwhere we are, where we are heading to.}, author = {Probir Kumar Ojha, Supratik Kar, Jillella Gopala Krishna, Kunal Roy, Jerzy Leszczynski}, url = {https://link.springer.com/article/10.1007/s11030-020-10134-x#Ack1}, doi = {10.1007/s11030-020-10134-x}, year = {2021}, date = {2021-02-01}, journal = {Mol. Divers.}, volume = {25}, pages = {625\textendash659 }, abstract = {After the 1918 Spanish Flu pandemic caused by the H1N1 virus, the recent coronavirus disease 2019 (COVID-19) brought us to the time of serious global health catastrophe. Although no proven therapies are identified yet which can offer a definitive treatment of the COVID-19, a series of antiviral, antibacterial, antiparasitic, immunosuppressant drugs have shown clinical benefits based on repurposing theory. However, these studies are made on small number of patients, and, in majority of the cases, have been carried out as nonrandomized trials. As society is running against the time to combat the COVID-19, we present here a comprehensive review dealing with up-to-date information of therapeutics or drug regimens being utilized by physicians to treat COVID-19 patients along with in-depth discussion of mechanism of action of these drugs and their targets. Ongoing vaccine trials, monoclonal antibodies therapy and convalescent plasma treatment are also discussed. Keeping in mind that computational approaches can offer a significant insight to repurposing based drug discovery, an exhaustive discussion of computational modeling studies is performed which can assist target-specific drug discovery.}, note = {NSF/CREST HRD-1547754 NSF/RISE HRD-1547836}, keywords = {Computational, Coronavirus, COVID-19, Drug, SARS-CoV-2, Vaccine}, pubstate = {published}, tppubtype = {article} } After the 1918 Spanish Flu pandemic caused by the H1N1 virus, the recent coronavirus disease 2019 (COVID-19) brought us to the time of serious global health catastrophe. Although no proven therapies are identified yet which can offer a definitive treatment of the COVID-19, a series of antiviral, antibacterial, antiparasitic, immunosuppressant drugs have shown clinical benefits based on repurposing theory. However, these studies are made on small number of patients, and, in majority of the cases, have been carried out as nonrandomized trials. As society is running against the time to combat the COVID-19, we present here a comprehensive review dealing with up-to-date information of therapeutics or drug regimens being utilized by physicians to treat COVID-19 patients along with in-depth discussion of mechanism of action of these drugs and their targets. Ongoing vaccine trials, monoclonal antibodies therapy and convalescent plasma treatment are also discussed. Keeping in mind that computational approaches can offer a significant insight to repurposing based drug discovery, an exhaustive discussion of computational modeling studies is performed which can assist target-specific drug discovery. | |
2020 |
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Sajith M. Vijayan, Nicholas Sparks, Juganta K. Roy, Cameron Smith, Christopher Tate, Nathan I. Hammer, Jerzy Leszczynski,; Davita L. Watkins Evaluating Donor Effects in Isoindigo-Based Small Molecular Fluorophores Journal Article J. Phys. Chem. A , 124 (51), pp. 10777-10786, 2020. Abstract | Links | BibTeX | Tags: Computational analyses, electrochemical, Photophysical, Small molecular organic fluorophores, TD-DFT @article{Vijayan2020, title = {Evaluating Donor Effects in Isoindigo-Based Small Molecular Fluorophores}, author = {Sajith M. Vijayan, Nicholas Sparks, Juganta K. Roy, Cameron Smith, Christopher Tate, Nathan I. Hammer, Jerzy Leszczynski, and Davita L. Watkins}, url = {https://pubs.acs.org/doi/abs/10.1021/acs.jpca.0c07796}, doi = {https://doi.org/10.1021/acs.jpca.0c07796}, year = {2020}, date = {2020-12-11}, journal = {J. Phys. Chem. A }, volume = {124}, number = {51}, pages = {10777-10786}, abstract = {Small molecular organic fluorophores have garnered significant interest because of their indispensable use in fluorescence imaging (FI) and optoelectronic devices. Herein, we designed triphenylamine (TPA)-capped donor\textendashacceptor\textendashdonor (D\textendashA\textendashD)-based fluorophores having a variation at the heterocyclic donor (D) units, 3,4-ethylenedioxythiophene (EDOT), furan (FURAN), thiophene (THIO), and 1-methyl-1H-pyrrole (MePyr), with isoindigo as the core electron acceptor (A) unit. Synthesis of these fluorophores (II-X-TPA) resulted in four symmetrical dye molecules: II-EDOT-TPA, II-FURAN-TPA, II-THIO-TPA, and II-MePyr-TPA, where TPA functioned as a terminal unit and a secondary electron donor group. Photophysical, electrochemical, and computational analyses were conducted to investigate the effect of heterocyclic donor units on the II-X-TPA derivatives. Density functional theory (DFT) and time-dependent DFT (TD-DFT) calculations provided insightful features of structural and electronic properties of each fluorophore and correlated well with experimental observations. Electron density distribution maps, overlapping frontier molecular orbital diagrams, and highest occupied molecular orbital (HOMO) to lowest unoccupied molecular orbital (LUMO) electron transfer indicated intramolecular charge transfer (ICT). Theoretical studies confirmed the experimental HOMO energy trend and demonstrated its crucial importance in understanding each heterocycle’s donor ability. Stokes shifts of up to ∼178 nm were observed, whereas absorptions and emissions were shifted deeper into the NIR region, resulting from ICT. Results suggest that this isoindigo fluorophore series has potential as a molecular scaffold for the development of efficient FI agents. The studied fluorophores can be further tuned with different donor fragments to enhance the ICT and facilitate in shifting the optical properties further into the NIR region.}, keywords = {Computational analyses, electrochemical, Photophysical, Small molecular organic fluorophores, TD-DFT}, pubstate = {published}, tppubtype = {article} } Small molecular organic fluorophores have garnered significant interest because of their indispensable use in fluorescence imaging (FI) and optoelectronic devices. Herein, we designed triphenylamine (TPA)-capped donor–acceptor–donor (D–A–D)-based fluorophores having a variation at the heterocyclic donor (D) units, 3,4-ethylenedioxythiophene (EDOT), furan (FURAN), thiophene (THIO), and 1-methyl-1H-pyrrole (MePyr), with isoindigo as the core electron acceptor (A) unit. Synthesis of these fluorophores (II-X-TPA) resulted in four symmetrical dye molecules: II-EDOT-TPA, II-FURAN-TPA, II-THIO-TPA, and II-MePyr-TPA, where TPA functioned as a terminal unit and a secondary electron donor group. Photophysical, electrochemical, and computational analyses were conducted to investigate the effect of heterocyclic donor units on the II-X-TPA derivatives. Density functional theory (DFT) and time-dependent DFT (TD-DFT) calculations provided insightful features of structural and electronic properties of each fluorophore and correlated well with experimental observations. Electron density distribution maps, overlapping frontier molecular orbital diagrams, and highest occupied molecular orbital (HOMO) to lowest unoccupied molecular orbital (LUMO) electron transfer indicated intramolecular charge transfer (ICT). Theoretical studies confirmed the experimental HOMO energy trend and demonstrated its crucial importance in understanding each heterocycle’s donor ability. Stokes shifts of up to ∼178 nm were observed, whereas absorptions and emissions were shifted deeper into the NIR region, resulting from ICT. Results suggest that this isoindigo fluorophore series has potential as a molecular scaffold for the development of efficient FI agents. The studied fluorophores can be further tuned with different donor fragments to enhance the ICT and facilitate in shifting the optical properties further into the NIR region. | |
Alla P.Toropova, Andrey A.Toropov, Danuta Leszczynska, Jerzy Leszczynski How the CORAL software can be used to select compounds for efficient treatment of neurodegenerative diseases? Journal Article Toxicol. Appl. Pharm., 408 , pp. 115276, 2020. Abstract | Links | BibTeX | Tags: Alzheimer's DiseaseParkinson's DiseaseNeuroprotectionNeurodegenerative DiseasesBioinformaticsIn Silico Design @article{P.Toropova2020, title = {How the CORAL software can be used to select compounds for efficient treatment of neurodegenerative diseases?}, author = {Alla P.Toropova, Andrey A.Toropov, Danuta Leszczynska, Jerzy Leszczynski}, doi = {https://doi.org/10.1016/j.taap.2020.115276}, year = {2020}, date = {2020-12-01}, journal = {Toxicol. Appl. Pharm.}, volume = {408}, pages = {115276}, abstract = {Recommendations on the efficient application of CORAL software (http://www.insilico.eu/coral) to establish quantitative structure-property/activity relationships (QSPRs/QSARs) are provided. The predictive potential of the approach has been demonstrated for QSAR models developed for inhibitor concentrations (negative decimal logarithm of IC50) of derivatives of N-methyl-d-aspartate (NMDA) receptor, leucine-rich repeat kinase 2 (LRRK2), and tropomyosin receptor kinase A (TrkA). The above three protein targets are related to various neurodegenerative diseases such as Alzheimer's and Parkinson's. Each model was checked using several splits of the data for the training and the validation sets. The index of ideality of correlation (IIC) represents a tool to improve the predictive potential for an arbitrary model. However, the use of the IIC should be carried out according to rules, described in this work.}, keywords = {Alzheimer's DiseaseParkinson's DiseaseNeuroprotectionNeurodegenerative DiseasesBioinformaticsIn Silico Design}, pubstate = {published}, tppubtype = {article} } Recommendations on the efficient application of CORAL software (http://www.insilico.eu/coral) to establish quantitative structure-property/activity relationships (QSPRs/QSARs) are provided. The predictive potential of the approach has been demonstrated for QSAR models developed for inhibitor concentrations (negative decimal logarithm of IC50) of derivatives of N-methyl-d-aspartate (NMDA) receptor, leucine-rich repeat kinase 2 (LRRK2), and tropomyosin receptor kinase A (TrkA). The above three protein targets are related to various neurodegenerative diseases such as Alzheimer's and Parkinson's. Each model was checked using several splits of the data for the training and the validation sets. The index of ideality of correlation (IIC) represents a tool to improve the predictive potential for an arbitrary model. However, the use of the IIC should be carried out according to rules, described in this work. | |
Qingli Tang, Feng Shi, Kan Li, Wenchao Ji, Jerzy Leszczynski, Armistead G. Russell, Eric G. Eddings, Zhemin Shen, Maohong Fan Unveiling the critical role of p-d hybridization interaction in M13-nGan clusters on CO2 adsorption Journal Article Fuel, 280 , pp. 118446, 2020. Abstract | Links | BibTeX | Tags: 13-Atom clusters, CO2 adsorption, Effects of Ga, Electronic properties @article{Tang2020, title = {Unveiling the critical role of p-d hybridization interaction in M13-nGan clusters on CO2 adsorption}, author = {Qingli Tang, Feng Shi, Kan Li, Wenchao Ji, Jerzy Leszczynski, Armistead G. Russell, Eric G. Eddings, Zhemin Shen, Maohong Fan}, doi = {https://doi.org/10.1016/j.fuel.2020.118446}, year = {2020}, date = {2020-11-15}, journal = {Fuel}, volume = {280}, pages = {118446}, abstract = {Inspired by conclusions of previous studies that Ga has the promoting effect on CO2 conversion, we performed density functional theory (DFT) investigations of CO2 adsorption on forty icosahedral (Ih) symmetry 13-atom clusters. They include M13, Ga-centered M12Ga, M-centered M12Ga, Ga-centered M11Ga2 and M-centered M11Ga2 clusters (M = Fe, Co, Ni, Cu, Ru, Rh, Pd and Ag). Initially, the stabilities of these clusters were studied. The results show that Ga doped Cu, Pd, and Ag clusters are more stable than their pure metal analogues, and except Pd and Ag clusters, M-centered species are more stable than Ga-centered clusters. In addition, the activation of CO2 on these clusters was studied. The results show that most of M-centered M12Ga clusters transfer more electron density to CO2 than other corresponding Ga-doped analogues. The amount of Bader charge transfers has noteworthy linear relationship with the structural parameters of CO2. DOS analyses show that empty σ orbital of CO2 is acceptor of electrons from cluster. It is worth to mention that Ag13−nGan clusters have little interaction with CO2. To explain the effects of Ga on the adsorption of CO2, the electronic properties of clusters were studied. The projected density of states (PDOSs), charge density differences, Bader charge transfers and electron localization functions (ELFs) analyses show that Ga transfers electron density to M atom, and the effective interaction is attributed to the p orbitals of Ga with the d orbitals of M near Fermi level(0), mainly responsible for the activation of CO2.}, keywords = {13-Atom clusters, CO2 adsorption, Effects of Ga, Electronic properties}, pubstate = {published}, tppubtype = {article} } Inspired by conclusions of previous studies that Ga has the promoting effect on CO2 conversion, we performed density functional theory (DFT) investigations of CO2 adsorption on forty icosahedral (Ih) symmetry 13-atom clusters. They include M13, Ga-centered M12Ga, M-centered M12Ga, Ga-centered M11Ga2 and M-centered M11Ga2 clusters (M = Fe, Co, Ni, Cu, Ru, Rh, Pd and Ag). Initially, the stabilities of these clusters were studied. The results show that Ga doped Cu, Pd, and Ag clusters are more stable than their pure metal analogues, and except Pd and Ag clusters, M-centered species are more stable than Ga-centered clusters. In addition, the activation of CO2 on these clusters was studied. The results show that most of M-centered M12Ga clusters transfer more electron density to CO2 than other corresponding Ga-doped analogues. The amount of Bader charge transfers has noteworthy linear relationship with the structural parameters of CO2. DOS analyses show that empty σ orbital of CO2 is acceptor of electrons from cluster. It is worth to mention that Ag13−nGan clusters have little interaction with CO2. To explain the effects of Ga on the adsorption of CO2, the electronic properties of clusters were studied. The projected density of states (PDOSs), charge density differences, Bader charge transfers and electron localization functions (ELFs) analyses show that Ga transfers electron density to M atom, and the effective interaction is attributed to the p orbitals of Ga with the d orbitals of M near Fermi level(0), mainly responsible for the activation of CO2. | |
Andrey A. Toropov, Natalia Sizochenko, Alla P. Toropova, Danuta Leszczynska, Jerzy Leszczynski Advancement of predictive modeling of zeta potentials (ζ) in metal oxide nanoparticles with correlation intensity index (CII) Journal Article J. Mol. Liq., 317 , pp. 113929, 2020. Abstract | Links | BibTeX | Tags: Correlation intensity index, Index of ideality of correlation, Metal oxide nanoparticles, Nano-QSPR, Quasi-SMILES, Zeta potential @article{Toropov2020, title = {Advancement of predictive modeling of zeta potentials (ζ) in metal oxide nanoparticles with correlation intensity index (CII)}, author = {Andrey A. Toropov, Natalia Sizochenko, Alla P. Toropova, Danuta Leszczynska, Jerzy Leszczynski}, doi = {https://doi.org/10.1016/j.molliq.2020.113929}, year = {2020}, date = {2020-11-01}, journal = {J. Mol. Liq.}, volume = {317}, pages = {113929}, abstract = {It was expected that index of the ideality of correlation (IIC) and correlation intensity index (CII) could be used as possible tools to improve the predictive power of the quantitative model for zeta potential of nanoparticles. In this paper, we test how the statistical quality of quantitative structure-activity models for zeta potentials (ζ, a common measurement that reflects surface charge and stability of nanomaterial) could be improved with the use of these two indexes. Our hypothesis was tested using the benchmark data set that consists of 87 measurements of zeta potentials in water. We used quasi-SMILES molecular representation to take into consideration the size of nanoparticles in water and calculated optimal descriptors and predictive models based on the Monte Carlo method. We observed that the models developed with utilization of CII are statistically more reliable than models obtained with the IIC. However, the described approach gives an improvement of the statistical quality of these models for the external validation sets to the detriment for the training sets. Nevertheless, this circumstance is rather an advantage than a disadvantage.}, keywords = {Correlation intensity index, Index of ideality of correlation, Metal oxide nanoparticles, Nano-QSPR, Quasi-SMILES, Zeta potential}, pubstate = {published}, tppubtype = {article} } It was expected that index of the ideality of correlation (IIC) and correlation intensity index (CII) could be used as possible tools to improve the predictive power of the quantitative model for zeta potential of nanoparticles. In this paper, we test how the statistical quality of quantitative structure-activity models for zeta potentials (ζ, a common measurement that reflects surface charge and stability of nanomaterial) could be improved with the use of these two indexes. Our hypothesis was tested using the benchmark data set that consists of 87 measurements of zeta potentials in water. We used quasi-SMILES molecular representation to take into consideration the size of nanoparticles in water and calculated optimal descriptors and predictive models based on the Monte Carlo method. We observed that the models developed with utilization of CII are statistically more reliable than models obtained with the IIC. However, the described approach gives an improvement of the statistical quality of these models for the external validation sets to the detriment for the training sets. Nevertheless, this circumstance is rather an advantage than a disadvantage. | |
Iryna O. Borysenko, Liudmyla K. Sviatenko, Sergiy I. Okovytyy, Jerzy Leszczynski Struct. Chem., 32 , pp. 581–589, 2020. Abstract | Links | BibTeX | Tags: Conformational analysis, Epoxide cycle opening, Glycidyl ethers, Multiple-channel bimolecular reaction @article{Borysenko2020, title = {Efficient approach for exploring the multiple-channel bimolecular interactions of conformationally flexible reagents. Epoxide ring opening reaction}, author = {Iryna O. Borysenko, Liudmyla K. Sviatenko, Sergiy I. Okovytyy, Jerzy Leszczynski}, doi = {https://doi.org/10.1007/s11224-020-01663-0}, year = {2020}, date = {2020-10-19}, journal = {Struct. Chem.}, volume = {32}, pages = {581\textendash589}, abstract = {Algorithm for generation and assessment of probability of possible reaction pathways for multiple-channel bimolecular interactions is presented. The proposed algorithm comprises a combination of few steps. They include conformational search for reaction intermediate using the molecular mechanics (MMX) approach, based on the obtained conformation construction of structures of transition states and pre-reaction complexes, and calculation activation energies to further determine the probable reaction pathways. The proposed algorithm could be adopted for investigation of chemical and biochemical reactions of different types. Here, we have considered the reaction of bicyclo[2.2.1]hept-5-en-endo-2-ylmethylamine (1) with glycidyl ether (2) in a neutral environment that proceeds through SN2-like mechanism forming bipolar ion (3) which is a good starting point for identification of the reaction channels. Conformational properties of intermediate (3) have been investigated using stochastic conformational search. From the 95 localized conformations within 10 kcal/mol of global minimum that have been obtained, 63 unique transition state conformations were generated and optimized by using the PM7 and M062X/6-31G(d) methods for accurate estimation of overall rate constant of reaction. The most energetically favorable pathways have been investigated at the M062X/6-31G(d) level of theory taking into account the influence of solvent.}, keywords = {Conformational analysis, Epoxide cycle opening, Glycidyl ethers, Multiple-channel bimolecular reaction}, pubstate = {published}, tppubtype = {article} } Algorithm for generation and assessment of probability of possible reaction pathways for multiple-channel bimolecular interactions is presented. The proposed algorithm comprises a combination of few steps. They include conformational search for reaction intermediate using the molecular mechanics (MMX) approach, based on the obtained conformation construction of structures of transition states and pre-reaction complexes, and calculation activation energies to further determine the probable reaction pathways. The proposed algorithm could be adopted for investigation of chemical and biochemical reactions of different types. Here, we have considered the reaction of bicyclo[2.2.1]hept-5-en-endo-2-ylmethylamine (1) with glycidyl ether (2) in a neutral environment that proceeds through SN2-like mechanism forming bipolar ion (3) which is a good starting point for identification of the reaction channels. Conformational properties of intermediate (3) have been investigated using stochastic conformational search. From the 95 localized conformations within 10 kcal/mol of global minimum that have been obtained, 63 unique transition state conformations were generated and optimized by using the PM7 and M062X/6-31G(d) methods for accurate estimation of overall rate constant of reaction. The most energetically favorable pathways have been investigated at the M062X/6-31G(d) level of theory taking into account the influence of solvent. | |
Ting Wu, Shenlong Jiang, Pabitra Narayan Samanta, Yangbin Xie, Jipeng Li, Xiaoling Wang, Majumdar Devashis, Xiangwei Gu, Yusong Wang, Wei Huang, Qun Zhang, Jerzy Leszczynski,; Dayu Wu Negative thermal quenching of photoluminescence in a copper–organic framework emitter Journal Article Chem. Commun., 56 (80), pp. 12057-12060, 2020. Abstract | Links | BibTeX | Tags: Copper-organic framework, Delayed fluorescence, Negative thermal quenching (NTQ), SOC-TDDFT @article{Wu2020, title = {Negative thermal quenching of photoluminescence in a copper\textendashorganic framework emitter}, author = {Ting Wu, Shenlong Jiang, Pabitra Narayan Samanta, Yangbin Xie, Jipeng Li, Xiaoling Wang, Majumdar Devashis, Xiangwei Gu, Yusong Wang, Wei Huang, Qun Zhang, Jerzy Leszczynski, and Dayu Wu}, doi = {https://doi.org/10.1039/d0cc04788k}, year = {2020}, date = {2020-10-14}, journal = {Chem. Commun.}, volume = {56}, number = {80}, pages = {12057-12060}, abstract = {Negative thermal quenching (NTQ), an abnormal phenomenon that the intensity of photoluminescence (PL) increases with increasing temperature, has essentially been restricted to either bulk semiconductors or very low temperatures. Here, we report a delayed fluorescence copper-organic framework exhibiting negative thermal quenching (NTQ) of photoluminescence, which is driven by the fluctuation between the localized and delocalized form of its imidazole ligand. The process is completely reversible on cooling/heating cycles. This study opens a new avenue to explore the electronically switchable NTQ effect in coordination networks and further to develop the NTQ-based light-emitting diodes.}, keywords = {Copper-organic framework, Delayed fluorescence, Negative thermal quenching (NTQ), SOC-TDDFT}, pubstate = {published}, tppubtype = {article} } Negative thermal quenching (NTQ), an abnormal phenomenon that the intensity of photoluminescence (PL) increases with increasing temperature, has essentially been restricted to either bulk semiconductors or very low temperatures. Here, we report a delayed fluorescence copper-organic framework exhibiting negative thermal quenching (NTQ) of photoluminescence, which is driven by the fluctuation between the localized and delocalized form of its imidazole ligand. The process is completely reversible on cooling/heating cycles. This study opens a new avenue to explore the electronically switchable NTQ effect in coordination networks and further to develop the NTQ-based light-emitting diodes. | |
Supratik Kar, Jerzy Leszczynski Is intraspecies QSTR model answer to toxicity data gap filling: Ecotoxicity modeling of chemicals to avian species Journal Article Sci. Total Environ., 738 , pp. 139858, 2020. Abstract | Links | BibTeX | Tags: Avian; Ecotoxicity; Intraspecies; QSTR; Regulatory @article{Kar2020b, title = {Is intraspecies QSTR model answer to toxicity data gap filling: Ecotoxicity modeling of chemicals to avian species}, author = {Supratik Kar, Jerzy Leszczynski}, doi = {https://doi.org/10.1016/j.scitotenv.2020.139858}, year = {2020}, date = {2020-10-10}, journal = {Sci. Total Environ.}, volume = {738}, pages = {139858}, abstract = {Interspecies model represents an established approach for the response data gap filling for regulatory agencies and researchers. We propose a novel approach of intraspecies modeling within the animals of the same species, instead of animals from different species. The proposed intraspecies model is capable of more precise extrapolation of data than the interspecies model, as animals under the same species share a similar mechanism of action (MOA) and target sites for the response. Along with the advantage of better prediction over the interspecies model, the intraspecies model has all the significant features like recognition of MOA, species-specific toxicity, reduction of animal experimentation, and money and time. To establish and test the intraspecies modeling approach, we have modeled ecotoxicity of organic chemicals to three avian species: Anas platyrhynchos, Colinus virginianus, and Phasianus colchicus. The intraspecies models offer to identify the mechanistic interpretation of the ecotoxicity of the studied chemicals along with the toxicity data gap filling. The success of the intraspecies modeling relies on connecting the missing dots of toxicity for the regulatory purposes, especially when there is a scarcity of ecotoxicity experimental data and in silico models for avian species.}, keywords = {Avian; Ecotoxicity; Intraspecies; QSTR; Regulatory}, pubstate = {published}, tppubtype = {article} } Interspecies model represents an established approach for the response data gap filling for regulatory agencies and researchers. We propose a novel approach of intraspecies modeling within the animals of the same species, instead of animals from different species. The proposed intraspecies model is capable of more precise extrapolation of data than the interspecies model, as animals under the same species share a similar mechanism of action (MOA) and target sites for the response. Along with the advantage of better prediction over the interspecies model, the intraspecies model has all the significant features like recognition of MOA, species-specific toxicity, reduction of animal experimentation, and money and time. To establish and test the intraspecies modeling approach, we have modeled ecotoxicity of organic chemicals to three avian species: Anas platyrhynchos, Colinus virginianus, and Phasianus colchicus. The intraspecies models offer to identify the mechanistic interpretation of the ecotoxicity of the studied chemicals along with the toxicity data gap filling. The success of the intraspecies modeling relies on connecting the missing dots of toxicity for the regulatory purposes, especially when there is a scarcity of ecotoxicity experimental data and in silico models for avian species. | |
ICN Center
Jackson State University
