Advances in QSAR Modeling

1. Front Matter

   Pages i-x

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2. Theory

   1. Front Matter

      Pages 1-1

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   2. Towards the Revival of Interpretable QSAR Models

      • Watshara Shoombuatong, Philip Prathipati, Wiwat Owasirikul, Apilak Worachartcheewan, Saw Simeon, Nuttapat Anuwongcharoen et al.

      Pages 3-55

   3. The Use of Topological Indices in QSAR and QSPR Modeling

      • John C. Dearden

      Pages 57-88

   4. Which Performance Parameters Are Best Suited to Assess the Predictive Ability of Models?

      • Károly Héberger, Anita Rácz, Dávid Bajusz

      Pages 89-104

3. Methods

   1. Front Matter

      Pages 105-105

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   2. Structural, Physicochemical and Stereochemical Interpretation of QSAR Models Based on Simplex Representation of Molecular Structure

      • P. Polishchuk, E. Mokshyna, A. Kosinskaya, A. Muats, M. Kulinsky, O. Tinkov et al.

      Pages 107-147

   3. The Maximum Common Substructure (MCS) Search as a New Tool for SAR and QSAR

      • Azadi Golbamaki, Alessio Mauro Franchi, Giuseppina Gini

      Pages 149-165

   4. Generative Topographic Mapping Approach to Chemical Space Analysis

      • Dragos Horvath, Gilles Marcou, Alexandre Varnek

      Pages 167-199

4. Applications

   1. Front Matter

      Pages 201-201

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   2. On Applications of QSARs in Food and Agricultural Sciences: History and Critical Review of Recent Developments

      • Supratik Kar, Kunal Roy, Jerzy Leszczynski

      Pages 203-302

   3. Quantitative Structure-Epigenetic Activity Relationships

      • Mario Omar García-Sánchez, Maykel Cruz-Monteagudo, José L. Medina-Franco

      Pages 303-338

   4. QSAR/QSPR Modeling in the Design of Drug Candidates with Balanced Pharmacodynamic and Pharmacokinetic Properties

      • George Lambrinidis, Fotios Tsopelas, Costas Giaginis, Anna Tsantili-Kakoulidou

      Pages 339-384

   5. Strategy for Identification of Nanomaterials’ Critical Properties Linked to Biological Impacts: Interlinking of Experimental and Computational Approaches

      • Iseult Lynch, Antreas Afantitis, Georgios Leonis, Georgia Melagraki, Eugenia Valsami-Jones

      Pages 385-424

   6. In Silico Approaches for the Prediction of In Vivo Biotransformation Rates

      • Ester Papa, Jon A. Arnot, Alessandro Sangion, Paola Gramatica

      Pages 425-451

   7. Development of Monte Carlo Approaches in Support of Environmental Research

      • Alla P. Toropova, Andrey A. Toropov, Emilio Benfenati, Robert Rallo, Danuta Leszczynska, Jerzy Leszczynski

      Pages 453-469

   8. Environmental Toxicity of Pesticides, and Its Modeling by QSAR Approaches

      • Mabrouk Hamadache, Abdeltif Amrane, Othmane Benkortbi, Salah Hanini, Latifa Khaouane, Cherif Si Moussa

      Pages 471-501

   9. Counter-Propagation Artificial Neural Network Models for Prediction of Carcinogenicity of Non-congeneric Chemicals for Regulatory Uses

      • N. Fjodorova, M. Novic, S. Zuperl, K. Venko

      Pages 503-527

   10. Big Data in Structure-Property Studies—From Definitions to Models

       • Jaroslaw Polanski

       Pages 529-552

5. Back Matter

   Pages 553-555

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The book covers theoretical background and methodology as well as all current applications of Quantitative Structure-Activity Relationships (QSAR). Written by an international group of recognized researchers, this edited volume discusses applications of QSAR in multiple disciplines such as chemistry, pharmacy, environmental and agricultural sciences addressing data gaps and modern regulatory requirements. Additionally, the applications of QSAR in food science and nanoscience have been included – two areas which have only recently been able to exploit this versatile tool.
 
This timely addition to the series is aimed at graduate students, academics and industrial scientists interested in the latest advances and applications of QSAR.

• Quantitative Structure-Activity Relationships
• QSAR Modeling
• QSPR Modeling
• QSAR Drug Discovery
• QSAR Drug Design
• QSAR Environmental Research
• QSAR Food Research
• QSAR Agrochemistry
• QSAR Environmental Toxicology
• QSAR Carcinogenicity
• QSAR Modeling of Nanomaterials
• QSAR Food Chemistry
• QSAR Pharmaceuticals
• QSAR Nanomaterials
• QSAR Pharmacy
• QSAR Hybrid Models

• Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India

  Kunal Roy

Prof. Dr. Kunal Roy is a Professor of the Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology Jadavpur University, Kolkata India. He was previously a Marie Curie International Incoming Fellow and Commonwealth Academic Staff Fellow at the University of Manchester, UK. Prof. Roy has published over 240 articles in peer reviewed journals, two books, one edited book as well as ten book chapters.

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