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


Special Issue On: QSPR in Nanotechnology

Submission Due Date
9/15/2017

Guest Editors
Agnieszka Gajewicz and Tomasz Puzyn (Laboratory of Environmental Chemometrics, University of Gdansk, Poland)

Introduction
More than 50 years after the Feynman's “There’s plenty of room at the bottom”, nanotechnology has emerged at the forefront of science and technology developments and nanomaterials have found a wide range of applications in different aspects of human life. However, there is an increasing number of contributions reporting toxicity and/or ecotoxicity of selected nanoparticles and highlighting the potential risk related to the development of nanotechnology.

Quantitative structure-property relationship (QSPR) methods can play an important role in both: designing new products and predicting their risk to human health and the environment. But, regarding the specific properties of nanomaterials and their still unexplored modes of toxic action, this class of compounds seems to be much more problematic for QSPR modelers than the ‘classic’ (relatively small, ‘drug-like’) chemicals.

Objective
This special issue discusses current advances and challenges of QSPR development for nanomaterials including: (1) modeling of scarce and/or inconsistent experimental data available for nanoparticles; (2) development of appropriate descriptors able to express specificity of “nano” structure; (3) validated models to be used for predicting physical-chemical properties and biological activity of nanoparticles.

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

  • Modeling of scarce and/or inconsistent experimental data available for nanoparticles
  • Nanotechnology data curation for modeling
  • Descriptors of nanostructure
  • Models for predicting interactions of nanoparticles with macromolecules
  • (Quantitative) Structure-Property Relationships models for physical-chemical properties of nanoparticles
  • (Quantitative) Structure-Activity Relationships models for nanoparticles
  • Chemoinformatics methods for supporting grouping of nanomaterials
  • Chemoinformatics algorithms of read-across
  • Application of QSPR/QSAR models in developing Adverse Outcome Pathways for nanomaterials
  • Application of QSPR/QSAR models for risk assessment of nanotechnology


Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on QSPR in Nanotechnology on or before September 15th, 2017. 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:
Agnieszka Gajewicz and Tomasz Puzyn
Guest Editors
International Journal of Quantitative Structure-Property Relationships (IJQSPR)
E-mail: a.gajewicz@qsar.eu.org; t.puzyn@qsar.eu.org

Special Issue On: Natural Products in Computer-aided Drug Design Studies

Submission Due Date
1/1/2018

Guest Editors
Luciana Scotti, Federal University of Paraíba, Campus I; 58051-970, João Pessoa, PB, Brazil.
Marcus Tullius Scotti, Federal University of Paraíba, Campus I; 58051-970, João Pessoa, PB, Brazil.

Introduction
Traditionally, plants have been utilized to treat many diseases, whether infections, the various metabolic disorders, such as diabetes, obesity, hypertension, and heart disease, or for other ills plaguing humanity today. The use of natural products-of plant, marine, and microorganism origin-has been the single most successful strategy for discovering new medicines. Many medical breakthroughs are based on natural products. Half of the top 20 best-selling drugs are natural chemical compounds, and their total sales amount to US$ 16 billion yearly. The numbers suggest that natural chemicals may well be pre-optimized for bioactive potential, and therefore possess “drug-like properties”. Theoretical studies using in silico methods have aided in the process of drug discovery. Technological advances in the areas of structural characterization, computational science, and molecular biology have contributed to faster planning of new feasible molecules. In silico methods or CADD (Computer aided drug design studies) are increasingly being used in both industry and in universities. They involve an understanding of the molecular interactions from both qualitative and quantitative points of view. These methods generate and manipulate three-dimensional (3D) molecular structures, calculate descriptors and the dependent molecular properties, model constructions, and employ other tools that encompass computational drug research. Analysis of the molecular structure of a given system allows relevant information to be extracted, and to predict the potential of bioactive compounds.

Objective
The objective for this thematic issue is to report recent studies about different approaches using natural products in CADD (theoretical approaches as structure-based approaches, SAR, QSAR, docking and several cheminformatics methods). These efforts involve several studies to aid the discovery of new legends to treatment or cure of the diseases.

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

  • SAR
  • QSAR
  • QSPR
  • PLS
  • PLS-DA
  • Random Forest
  • Neural Network
  • PCA
  • CPCA
  • CoMFA
  • Any CADD study


Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Natural products in Computer-aided drug design studies on or before January 1st, 2018. 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 athttp://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:
Luciana Scotti
Guest Editor
International Journal of Quantitative Structure-Property Relationships (IJQSPR)
E-mail: Luciana.scotti@gmail.com