Calls for Papers (special): International Journal of Quantitative Structure-Property Relationships (IJQSPR)


Special Issue On: QSPR/QSAR in Materials and Toxicological Sciences

Submission Due Date
6/1/2019

Guest Editors
Supratik Kar
Jerzy Leszczynski
Interdisciplinary Nanotoxicity Center, Department of Chemistry, Physics and Atmospheric Sciences
Jackson State University, Jackson, MS, USA

Introduction
Quantitative structure-property/activity relationship (QSPR/QSAR) modeling is a technique that allows the interdisciplinary exploration of knowledge on chemical compounds covering the aspects of chemistry, physics, biology, and toxicology. It provides a formalism for developing mathematical correlations between the chemical features and the behavioral manifestations of structurally similar compounds. The tool is developed based on a strong mathematical algorithm, and it provides a reasonable basis for establishing a predictive correlation models. Apart from providing a mathematical correlation, QSPR technique also enables the exploration of chemical features encoded within descriptors. The QSPR technique proves to be a valuable alternative method in this perspective and is encouraged for the design and development of biologically active molecules as well as in predictive toxicology analysis. The QSPR formalism is also widely employed to serve different purposes of materials science toward the design and development of purpose-specific novel and/or alternative chemicals. It may be very interesting to note that historically the earliest inception for the ideology of QSPR modeling emerged from the simple concept of a correlation between response and chemical nature of molecules which remains the same even today after various developments and nourishments in the QSAR algorithms.

Objective
Although QSPR/QSAR methods are frequently used in modeling physical and biological properties of materials and ecotoxicity modeling of pharmaceuticals, personal care products, dyes, nanomaterials, etc., there is a lack of clearly assessing their advantages or disadvantages in building QSAR/QSPR. Not only for data gap filling purpose as well as for regulatory decision making, QSAR models have immense role to play in medicinal chemistry and drug design. But, the implicit knowledge, interpretation, and extracting and organizing knowledge from such models are still thought-provoking. This special issue will try to give answer to questions such as:
• How accurate and predictive QSAR/QSPR models can be developed in material science and toxicology science?
• Which kind of chemical and biological knowledge should be required to model advanced materials and toxicity modeling?
• What are the next challenges for QSAR/QSPR methods in material science and toxicity modeling?
• How and why users can employ multiple QSAR tools in materials science and toxicity modeling?

Recommended Topics
Topics to be discussed in this special issue include (but are not limited to) the following:

1. QSPR in material sciences
-Quantitative structure-property relationships as tools in property prediction of advanced materials
-Role of QSPR/machine learning techniques in diverse property prediction of nanomaterials
-Application of QSPR in designing of solar cells
-Predictive QSPR models in ionic liquids research
-In silico approaches to model biocatalytic materials

2. QSAR in drug toxicity to humans
-In silico methods in prediction of drug toxicity to humans
-Database for modeling of drug toxicity
-Expert systems/open source software for the toxicity prediction of drug to human
-Predictive QSAR modeling for Prenatal developmental/reproductive toxicity/Mammalian systemic toxicity/Carcinogenicity/Immunotoxicity/Neurotoxicity/Respiratory toxicity/ Nephrotoxicity/Endocrine disruption/Skin sensitization/Skin irritation and corrosion/Eye irritation and corrosion/Cardiovascular toxicity/Ocular toxicity
- Machine learning models in drug toxicity prediction to human
-Read-across approach to predict drug toxicity to human
-In silico model to encode the complexity of drug mixture toxicity

3. QSAR in environmental toxicity due to Industrial chemicals, Pharmaceuticals, personal care products, dyes, nanomaterials
-Ecotoxicological risk assessment in the context of different EU regulations
-Quantitative structure-activity relationships as tools in predictive ecotoxicology
-Read across for computational ecotoxicology
-Feature selection and modeling algorithms in ecotoxicological QSARs
-Validation tools for ecotoxicological QSARs
-Methods for assessment of applicability domain and reliability of predictions of ecotoxicological QSARs
-Mechanistic interpretation of ecotoxicological QSARs
-Machine learning models in ecotoxicological QSAR modeling
-Big data in computational toxicology
-Ecotoxicological QSAR modeling of REACH chemicals/ pharmaceuticals/personal care products/biocides/agrochemicals/dyes/nanomaterial
-Role of QSAR in Bioaccumulation, bioconcentration and biotransformation
-QSAR in mixture toxicity

Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue onQSPR/QSAR in materials and toxicological sciences on or before June 01, 2019.. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/publish/contributor-resources/before-you-write/. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.

All submissions and inquiries should be directed to the attention of:
Dr. Supratik Kar
Prof. Jerzy Leszczynski
Guest Editors
International Journal of Quantitative Structure-Property Relationships (IJQSPR)
E-mail: supratik.kar@icnanotox.org, jerzy@icnanotox.org