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Jerzy Leszczynski   Professor  Senior Scientist or Principal Investigator 
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Jerzy Leszczynski published an article in July 2018.
Top co-authors See all
Jing Wang

1419 shared publications

Rodney J. Bartlett

630 shared publications

Janusz Lipkowski

341 shared publications

Modesto Orozco

256 shared publications

D. Majumdar

218 shared publications

824
Publications
44
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3
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4949
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Publication Record
Distribution of Articles published per year 
(1970 - 2018)
Total number of journals
published in
 
155
 
Publications See all
Article 0 Reads 0 Citations Wartości w teorii prawa Jerzego Wróblewskiego Jerzy Leszczynski Published: 14 July 2018
Filozofia Publiczna i Edukacja Demokratyczna, doi: 10.14746/fped.2013.2.2.27
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The article presents the role of values and evaluation practices in Jerzy Wróblewski`s legal theory. An overview of the theory includes here the interpretation and the application of the law, in both of which Wróblewski shows the axiological choices made by a lawyer. These choices are only partly limited by the interpretative directives, those generally accepted in a legal culture. The author of the article describes the two ideologies (normative theories), distinguished by Wroblewski, of the legal interpretation (and of the application of the law), which are contradictory to each other as they refer to opposing values: legal certainty and flexibility of law. A third type of ideology, identified by Wróblewski refers to the value of rationality and tries to mitigate the contradictions of the previous two. Some similarities between Wróblewski`s legal theory and the theory of H.L.A.Hart may allow to treat him as the co-founder of a sophisticated version of legal positivism.
Article 0 Reads 0 Citations Single or mixture halogenated chemicals? Risk assessment and developmental toxicity prediction on zebrafish embryos base... Supratik Kar, Shinjita Ghosh, Jerzy Leszczynski Published: 01 July 2018
Chemosphere, doi: 10.1016/j.chemosphere.2018.07.051
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Halogenated chemicals including perfluoroalkyl substances (PFASs) represent an emerging class of endocrine-disrupting pollutants for human populations across the globe. Distress related to their environmental fate and toxicity has initiated several research projects, but the amount of experimental data available for these pollutants is limited. The objective of this study is to assess the toxicity of potentially “safer” alternatives, in relation to their existing counterparts. Developmental toxicity data on zebrafish (Danio rerio) embryos of single and tertiary halogenated mixtures were modeled employing quantitative structure-toxicity relationship (QSTR) tool. The computed models are then employed for toxicity prediction of theoretically generated binary and tertiary mixtures (which have no experimental data) to check their possible threshold and mode of toxicity for future risk assessment. Further, for toxicity screening, we have prepared a huge external dataset consists of single (24), binary (276) and tertiary (2024) mixtures of PFASs. It was accomplished by combination method and predicted through developed models for interpretation of toxicity threats for individuals and mixtures along with identification of diverse range and combination of toxicity thresholds. We found that chemicals in mixtures displayed concentration addition of individual chemical suggesting a similar mode of toxic action and non-interaction of chemicals. Not only that, mixtures of halogenated compounds including PFASs showed less toxicity than their single counterparts and the obtained toxicity trend is: Single chemical > Binary mixture > Tertiary mixture.
Article 2 Reads 0 Citations Fullerene quinazolinone conjugates targeting Mycobacterium tuberculosis: a combined molecular docking, QSAR, and ONIOM a... Ali Mirchi, Natalia Sizochenko, Jerzy Leszczynski Published: 10 March 2018
Structural Chemistry, doi: 10.1007/s11224-018-1100-x
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Fullerene and its derivatives may bind to biological molecules, causing inhibitory effects. In this context, investigations of interactions of fullerene-based conjugates with proteins are of general interest. Particularly, fullerene and its derivatives demonstrate antibacterial properties; and one of the potential targets for drug design and health therapy is the inhibition of 6-oxopurine phosphoribosyltransferase in Mycobacterium tuberculosis (PDB code: 4RHY). In this article, the binding interactions between a series of quinazoline-4(3H)-ones and their fullerene derivatives with the target transferase were computationally investigated. Initially, we developed predictive quantitative structure-activity relationships (QSAR) models. Next, we introduced a simplified calculation schema that allows to evaluate relative binding affinities and to reveal specific mechanisms of action. For this purpose, the molecular docking approach was utilized to identify the native poses of the 18 transferase inhibitors. The binding pocket of the target protein was isolated and semi-empirical, and hybrid ONIOM scoring functions at different levels of theory were used to treat the ligands and the isolated binding pocket. The agreement within the calculated binding-free energies trends, as well as the agreement with the experimental data, suggests that the developed calculation schema can be used to estimate relative binding affinities towards 4RH. The combination of quantum-chemical models and QSAR models could be applied for future design of new selective inhibitors.
Article 1 Read 0 Citations Interactions of Substituted Nitroaromatics with Model Graphene Systems: Applicability of Hammett Substituent Constants T... Mehedi H. Khan, Danuta Leszczynska, D. Majumdar, Szczepan Ro... Published: 08 March 2018
ACS Omega, doi: 10.1021/acsomega.7b01912
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Applicability of Hammett parameters (σm and σp) was tested in extended π-systems in gas phase. Three different model graphene systems, viz. 5,5-graphene (GR), 3-B-5,5-graphene (3BGR), and 3-N-5,5-graphene (3NGR), were designed as extended π-systems, and interactions of various nitrobenzene derivatives (mainly m- and p-substituted together with some multiple substitutions) on such platforms were monitored using density functional theory (M06/cc-pVDZ, M06/cc-pVTZ, M06/sp-aug-cc-pVTZ) and Møller–Plesset second-order perturbation (MP2/cc-pV-DZ) theory. Offset face to face (OSFF) stackings were found to be the favored orientations, and reasonable correlations were found between binding energies (ΔEB) and the ∑|σm| values of the substituted nitrobenzenes. It was proposed previously that |σm| contains information about the substituents’ polarizability and controls electrostatic and dispersion interactions. The combination of ∑|σm| and molar refractivity (as ∑Mr) or change in polarizability (Δα: with respect to benzene) of nitrobenzene derivatives generated statistically significant correlation with respect to ΔEB, thereby supporting the hypothesis related to the validity of |σm| correlations. The |σp| parameters also maintain similar correlations for the various p-substituted nitrobenzene derivatives together with several multiply-substituted nitrobenzene derivatives. The correlation properties in such cases are similar to the |σm| cases, and the energy partition analysis for both the situations reveled importance of electrostatic and dispersion contributions in such interactions. The applicability of Hammett parameters was observed previously on the restricted parallel face to face orientation of benzene···substituted benzene systems, and the present results show that such an idea could be used to predict ΔEB values in OSFF orientations, if the scaffolds are designed in such a way that substituted benzene systems cannot escape their π-clouds.
CONFERENCE-ARTICLE 10 Reads 0 Citations <strong>Ecotoxicological assessment of pharmaceuticals using computational toxicology approaches: QSTR and interspecies ... Kabir Khan, Supratik Kar, Hans Sanderson, Kunal Roy, Jerzy L... Published: 23 February 2018
Proceedings of MOL2NET 2017, International Conference on Multidisciplinary Sciences, 3rd edition, doi: 10.3390/mol2net-03-05129
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Although pharmaceuticals have been released into the environment for decades with seemingly no or very little care, their environmental toxicity has been studied experimentally only to a limited extent until today. There are reports of measurable quantities of drug molecules and other bioactive metabolites in rivers and other surface water bodies (mg/L range), notably in China and India where bulk production occurs. It is virtually impossible to carry out experimental evaluation of the impact of pharmaceuticals on all relevant and exposed organisms – this is also both unethical, costly and slow.  However, computational tools such as Quantitative Structure-Activity Relationship (QSAR) can be used to fill the data gaps where limited number of experimental data is available. In the current study, we have developed Quantitative Structure-Toxicity Relationship (QSTR) models for toxicity of pharmaceuticals on three different organisms namely algae, daphnia and fish. In order to study relationships between structural features and toxicity responses we developed models by partial least squares regression approach using descriptors selected through a genetic algorithm approach. The novel developed models were subsequently extensively validated following OECD guidelines. An additional interspecies quantitative structure-toxicity-toxicity relationship (QSTTR) modelling was performed to check for the interrelationship of various pattern of response as we moved across the hierarchy of genetics in different taxonomical class. Various descriptor calculating software such as PaDEL-Descriptor, DRAGON and SiRMS were used to compute a wide array of 2D descriptors for capturing chemical information required to correlate the biological properties (toxicities) inherited in the chemical structure of the molecules. All the obtained models showed that with an increase in hydrophobic characteristics (in terms of Log P) toxicity also increases linearly while with an increase in hydrogen bond donating groups, toxicity decreases. An applicability domain study was carried out in order to define the scope of developed model and to highlight compounds falling outside the domain of the respective models. The obtained QSTTR models were finally utilized to fill the data gaps of 275 pharmaceuticals, by using as a template to predict toxicity of pharmaceuticals where experimental data were missing for at least one of the endpoints. Finally, the developed QSTR models were used to predict a large dataset of approximately 7000 drug like molecules in order to prioritize the existing drug like substances in accordance to their acute predicted aquatic toxicities.

Keywords: QSAR, QSTR, QSTTR, Ecotoxicity, Pharmaceuticals

References

  1. Ternes, Thomas A. "Occurrence of drugs in German sewage treatment plants and rivers." Water research32, no. 11 (1998): 3245-3260.
  2. Hirsch, Roman, Thomas Ternes, Klaus Haberer, and Karl-Ludwig Kratz. "Occurrence of antibiotics in the aquatic environment." Science of the Total Environment225, no. 1-2 (1999): 109-118.
  3. Sanderson, Hans, and Marianne Thomsen. "Comparative analysis of pharmaceuticals versus industrial chemicals acute aquatic toxicity classification according to the United Nations classification system for chemicals. Assessment of the (Q) SAR predictability of pharmaceuticals acute aquatic toxicity and their predominant acute toxic mode-of-action." Toxicology Letters187, no. 2 (2009): 84-93.
  4. Kar Supratik, Das Rudra Narayan, Roy Kunal, and Leszcznyski, Jerzy, Can Toxicity for Different Species be Correlated?: The Concept and Emerging Applications of Interspecies Quantitative Structure-Toxicity Relationship (i-QSTR) Modeling. Int J Quant Struct-Prop Relat 1, no. 2 (2016): 23-51, http://dx.doi.org/10.4018/IJQSPR.2016070102
  5. Das, Rudra Narayan, Kunal Roy, and Paul LA Popelier. "Interspecies quantitative structure–toxicity–toxicity (QSTTR) relationship modeling of ionic liquids. Toxicity of ionic liquids to V. fischeri, D. magna and S. vacuolatus." Ecotoxicology and Environmental Safety122 (2015): 497-520.
Article 1 Read 0 Citations QSPR modeling of optical rotation of amino acids using specific quantum chemical descriptors Karina Kapusta, Natalia Sizochenko, Sedat Karabulut, Sergiy ... Published: 17 February 2018
Journal of Molecular Modeling, doi: 10.1007/s00894-018-3593-z
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Many chemical phenomena occur in solution. Different solvents can change the optical activity of chiral molecules. The optical rotation angles of solutes of 75 amino acids in dimethylformamide, water and methanol were analyzed using the quantitative structure–activity relationships approach. For an accurate description of chirality, we used specific quantum chemical descriptors, which reflect the properties of a chiral center, and continuous symmetry measures. The set of specific quantum chemical descriptors for atoms located near the chiral center, such as Mulliken charges, the sum of Mulliken charges on an atom (with the hydrogen charges summed up with the adjacent non-hydrogen atoms), and nuclear magnetic resoncance tensors was applied. To represent solvent effects, we used mixture-like structural simplex descriptors and quantum chemical descriptors obtained for structures optimized for specified solvent using PBE1PBE/6-31G** level of theory with the polarizable continuum model. Multiple linear regression, M5P, and locally weighted learning techniques were used to achieve accurate predictions. The specific quantum chemical descriptors proposed here demonstrated high specificity in the majority of the developed models and established direct quantitative structure–property relationships.