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In silico Studies of Biologically Active Molecules

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Research in Computer Science in the Bulgarian Academy of Sciences

Part of the book series: Studies in Computational Intelligence ((SCI,volume 934))

Abstract

Contemporary in silico (computer-aided) approaches to rational drug design and human health and environmental chemical risk assessment combine various ligand- and structure-based methods, including classical and three-dimensional (3D) quantitative structure–activity relationship (QSAR) models, pharmacophore and homology modelling, docking and virtual screening. These approaches are highly interdisciplinary and integrate knowledge from various disciplines in natural sciences. Their ultimate purpose is to quantitatively characterise the relationship between the compounds’ chemical structures and their effects, expressed by theoretical models, while the effect can be different—therapeutic, toxic, etc. In silico approaches effectively help in understanding and elucidation of the mechanisms by which chemical compounds interact with target biomacromolecules, thereby explaining fundamental processes in the living organisms. The chapter describes main methods in the computer-aided design and computational toxicology. The methods are classified according to the information available for modelling. Several case studies are described to illustrate the application of various in silico methods alone or in a combination. The case studies summarize the most recent results of the authors related to development of in silico models, algorithms and software applications to important biologically active molecules, both small drugs and drug-like compounds, and biomacromolecules, including nuclear receptors.

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Notes

  1. 1.

    The term “in silico” has been introduced relatively recently as a synonym for “computer-aided”, the latter dates from 1980s with the massive introduction of personal computers in the research practice.

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Acknowledgements

The authors acknowledge the financial support of the National Scientific Fund of Bulgaria, grant DN 17/6 “A New Approach, Based on an Intercriteria Data Analysis, to Support Decision Making in in silico Studies of Complex Biomolecular Systems” and the Bulgarian Ministry of Education and Science under the National Research Programme “Healthy Foods for a Strong Bio-Economy and Quality of Life” approved by DCM # 577/17.08.2018.

The authors would like to acknowledge also the contributions to the above described achievements of the colleagues from a number of European research institutions (Faculty of Pharmacy, University Paris Descartes (France); Institute of Pharmacy, University of Bonn (Germany); Institute for Health and Consumer Protection, Joint Research Center of the European Commission Ispra (Italy), John Moores University, Liverpool (United Kingdom); Italian Institute of Technology, Rome (Italy); Institute of Microbiology, Czech Academy of Sciences, Prague (Czech Republic)) with whom the QSAR and Molecular Modelling Department is intensively collaborating in the recent years.

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Authors and Affiliations

  1. Department of QSAR and Molecular Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Bl. 105, 1113, Sofia, Bulgaria

    Ilza Pajeva, Ivanka Tsakovska, Tania Pencheva, Petko Alov, Merilin Al Sharif, Iglika Lessigiarska, Dessislava Jereva & Antonia Diukendjieva

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  1. Ilza Pajeva
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  2. Ivanka Tsakovska
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  3. Tania Pencheva
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  4. Petko Alov
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  5. Merilin Al Sharif
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  6. Iglika Lessigiarska
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  7. Dessislava Jereva
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  8. Antonia Diukendjieva
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Correspondence to Ilza Pajeva .

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Editors and Affiliations

  1. Department of Bioinformatics and Mathematical Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Krassimir T. Atanassov

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Pajeva, I. et al. (2021). In silico Studies of Biologically Active Molecules. In: Atanassov, K.T. (eds) Research in Computer Science in the Bulgarian Academy of Sciences. Studies in Computational Intelligence, vol 934. Springer, Cham. https://doi.org/10.1007/978-3-030-72284-5_19

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