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


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

Special Issue On: Interpretable QSAR/QSPR models

Submission Due Date
3/1/2018

Guest Editors
Chanin Nantasenamat, Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Thailand

Introduction
Quantitative structure-activity/property relationship (QSAR/QSPR) is a computational approach that makes it possible to predict the activity/property of interest as a function of molecular and physicochemical descriptors through the use of statistical and/or machine learning methods. Historically, QSAR/QSPR models were built from a relatively small number of descriptor(s) using simple linear regression, which enables straightforward correlation and interpretation on how structure influence activity/property. With the exponential growth of bioactivity and/or physicochemical data comes great challenges in developing robust predictive models that had for the most part relied on black-box machine learning methods such as artificial neural networks, deep learning and support vector machine. Although robust, these models are difficult to interpret and are of limited practical use to the bench medicinal chemists. To be of practical use, it is recommended that QSAR/QSPR models be built by transparent learning methods and make use of interpretable descriptors followed by rationalization on the correlation of the structure-activity/property relationship.

Objective
QSAR/QSPR modeling is not only about developing robust models but to be of practical use for medicinal chemists, these models should be able to help elucidate key insights on the underlying structure-activity/property relationship. It is the intent of this special issue to serve as an important resource on this important area of QSAR modeling that will be instrumental in further guiding the design and development of novel and robust drugs, materials, chemicals, etc.

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

  • Interpretable QSAR/QSPR models
  • Best practices for interpretable QSAR/QSPR models
  • Interpretable molecular descriptors
  • Feature selection for interpretable QSAR/QSPR models
  • Interpretable or “white box” learning algorithms
  • QSAR/QSPR model interpretation for gaining Insights on activity/property
  • Cheminformatic approaches for interpretable QSAR/QSPR models
  • Robust validation of QSAR/QSPR model as to ensure valid model for interpretation
  • Application and utility of interpretable QSAR/QSPR models for guiding experimental testings
  • Approaches for avoiding mis-interpretation of QSAR/QSPR models
  • Software and tools to support the development of interpretable QSAR/QSPR models


Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Interpretable QSAR/QSPR Models on or before March 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 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:
Chanin Nantasenamat
Guest Editor
International Journal of Quantitative Structure-Property Relationships (IJQSPR)
E-mail: chanin.nan@mahidol.edu

Special Issue On: Development and Use of Free Software for Computer-Aided Drug Design

Submission Due Date
4/30/2018

Guest Editors
João Paulo Ataide Martins, Federal University of Minas Gerais, Brazil
Eduardo Borges de Melo, Western Paraná State University, Brazil

Introduction
Nowadays, computer-aided drug design (CADD) consists in a crucial discipline for the discovery and development of new therapeutic agents. Besides, environmental problems, development of new materials, a better comprehension of chemical phenomena among others also make use of the same methodologies applied in CADD. In this context, the use of free programs is of a great importance, since several tools actually in use presents this feature, with emphasis in some research fields (like molecular docking, homology modeling and 2D-QSAR), but still with a little presence in other fields (like virtual screening , 3D-QSAR and 4D-QSAR).

Objective
The aim of this special issue is to present new free tools that could be used by both academia and industry to perform in silico studies aimed at the development of new bioactive compounds, as well as for other problems where they could be applied.

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

  • Free software in electronic structure calculations
  • Free software in molecular visualization
  • Free software in 2D-QSAR descriptors generation
  • Free software in 3D-QSAR descriptors generation
  • Free software in 4D-QSAR descriptors generation
  • Free software in molecular docking
  • Free software in molecular dynamics
  • Free software in homology modeling
  • Free software in virtual screening
  • Free software in chemometrics methods applied to QSPR/QSAR model building and validation


Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Development and use of free software for computer-aided drug design on or before April 30, 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 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:
João Paulo Ataide Martins
Eduardo Borges de Melo
Guest Editors
International Journal of Quantitative Structure-Property Relationships (IJQSPR) E-mail: joaopauloam@ufmg.br; eduardo.b.de.melo@gmail.com