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Synthesis and chemoinformatics analysis of N-aryl-β-alanine derivatives

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Abstract

Carbohydrazides of N-substituted β-amino acids exhibit a variety of different biological activities including antibacterial, antiviral, fungicidal, antihelminthic, anticancer, antiinflammatory, etc. New potentially biologically active N-(4-iodophenyl)-β-alanine derivatives, N-(4-iodophenyl)-N-carboxyethyl-β-alanine derivatives, and their cyclization products were designed and synthesized. To determine the most propitious directions for further investigation of the obtained compounds, we tried to appraise their biological activity in silico using the ChemSpider and chemical structure lookup service (CSLS), chemical similarity assessment (Integrity and SuperPred), and machine learning methods [prediction of activity spectra for substances (PASS)]. No useful hints on potential biological activity of the obtained novel compounds were delivered by ChemSpider, CSLS, Integrity or SuperPred. In contrast, PASS predicted some biological activities that could be verified experimentally. Neither antibacterial nor antifungal activity was predicted for the compounds under study despite these actions being known for compounds from this chemical class. Evaluation of antibacterial (Escherichia coli B-906, Staphylococcus aureus 209-P, and Mycobacterium luteum B-91) and antifungal (Candida tenuis VKM Y-70 and Aspergillus niger F-1119) activities in vitro did not reveal any significant antimicrobial action, which corresponds to the computational prediction. Advantages and shortcomings of chemical similarity and machine learning techniques in computational assessment of biological activities are discussed. Based on the obtained results, we conclude that academic organic chemistry studies could provide a significant impact on drug discovery due to the novelty and diversity of the designed and synthesized compounds; however, practical utilization of this potential is narrowed by the limited facilities for assaying biological activities.

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Acknowledgments

This work was performed with partial financial support of the State Fund for Fundamental Research of Ukraine (agreement F53/97-2013) and the Russian Foundation for Basic Research (projects 13-04-90425, 12-07-00597).

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Authors and Affiliations

  1. Kaunas University of Technology, Radvilėnų Pl. 19, 50254, Kaunas, Lithuania

    Kazimieras Anusevicius & Vytautas Mickevicius

  2. Lviv Polytechnic National University, Bandera Str. 12, 79013, Lviv, Ukraine

    Maryna Stasevych, Victor Zvarych, Olena Komarovska-Porokhnyavets & Volodymyr Novikov

  3. Orekhovich Institute of Biomedical Chemistry, Pogodinskaya Str. 10/8, 119121, Moscow, Russia

    Olga Tarasova, Tatyana Gloriozova & Vladimir Poroikov

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  1. Kazimieras Anusevicius
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  2. Vytautas Mickevicius
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  8. Tatyana Gloriozova
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  9. Vladimir Poroikov
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Correspondence to Maryna Stasevych.

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Anusevicius, K., Mickevicius, V., Stasevych, M. et al. Synthesis and chemoinformatics analysis of N-aryl-β-alanine derivatives. Res Chem Intermed 41, 7517–7540 (2015). https://doi.org/10.1007/s11164-014-1841-0

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