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


Special Issue On: Interpretable QSAR/QSPR models

Submission Due Date
8/1/2018

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: Applications of in silico Molecular Modeling Tools in the Field of Drug Discovery

Submission Due Date
9/1/2018

Guest Editors
Prof. Swastika Ganguly
Department of Pharmaceutical Sciences & Technology, Birla Institute of Technology, Mesra-835215. India.
E.mail: swastikaganguly@bitmesra.ac.in
Dr. S. Murugesan
Department of Pharmacy, Birla Institute of Technology and Science, Pilani-333031. Rajasthan. India
E.mail: murugesan@pilani.bits-pilani.ac.in

Introduction
The term ‘in silico / computational’ is usually used to mean experimentation performed by computer and is considered as complement to in vivo and in vitro experimentation work. It is a cost effective, rapidly growing area that covers the development of techniques for using software to capture, analyze and integrate biological and medical data from many diverse sources. More specifically, it defines the use of this information in the creation of computational models or simulations that can be used to make predictions, suggest hypotheses, and ultimately provide discoveries or advances in medicine and therapeutics. Thisn i silico methods are helping us to make decisions and simulate virtually every facet of drug discovery and development, moving the pharmaceutical industry closer to engineering-based disciplines. These in silico tools help us in the progress by increasingly demonstrating their ability to deliver enrichment in identifying active molecules for the target of interest when compared with random selection or other traditional methods. In-silico drug design skills are used in nanotechnology, molecular biology, biochemistry etc. It can take part considerably in all stages of drug development from the preclinical discovery stage to late stage clinical development. In silico tools play an important role in target identification, design innovative proteins or novel drugs, in biotechnology or the pharmaceutical field.
Drug discovery is a hugely complex information handling, time consuming and inter-disciplinary interpretation exercise and there are many factors responsible for the failure of different drugs such as lack of effectiveness, side effects, poor pharmacokinetics and marketable reasons. It helps in finding the shortcuts or the rules that will point us as quickly as possible to the targets and molecules that are likely to proceed to the clinic then onto the market. This discovery results in better medicines that are iterative improvements on current medications and are valuable as they may offer benefits over existing medications in terms of potency, safety, tolerability, or convenience, but they usually do not involve the manipulation of biological targets different from those directly affected by existing medications. The drug development process is set up, particularly at the stage of clinical development, to “fail fast, fail early” in a strategy to eliminate key risks before making a expensive late-stage investment.

Objective
This special issue of International Journal of Quantitative Structure-Property Relationships (IJQSPR) focuses on “Applications of in silico molecular modeling tools in the field of Drug Discovery.” This will focus on both the development of novel approaches / methods or application of techniques, such as in silico, in-vitro, in-vivo, ex vivo screening, assay development, safety evaluation, virtual screening, lead identification, optimization and visualization methods that have a potential in aiding early phases of drug discovery, as well as therapeutics development using structure / ligand, de-novo, QSAR, HQSAR, QSPR, Homology modeling, Protein folding-based drug designing processes. We also encourage submissions that involve design, development of in silico tools, online servers for evaluation and prediction of any NME's for it's drug potential.

Recommended Topics
Topics to be discussed in this special issue include (but are not limited to) the following:
• Biological and Chemical applications
• Chemometric modeling
• Development of new descriptors and/or validation metrics
• Drug design applications
• Molecular Modeling including HTS, Homology modeling, Virtual screening and affinity profiling, Docking, pharmacophore modeling, de-novo design, ab-initio method, QSAR (2D, 3D), QSPR, Ligand based approaches, Similarity search, Combinatorial library design, Cheminformatics, Bioinformatics
• New software / program development of QSAR / QSPR, HQSAR, CoMFA, CoMSIA applications • Physicochemical properties prediction including Ro5, Ro3
• Predictive ADME and toxicology, PBPK/PD modeling
• Molecular Mechanics, Quantum Mechanics and Molecular Dynamics
• Drug Repurposing using in silico tools
• Machine learning, data mining, network analysis tools and data analysis tools

Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on "Applications of in silico molecular modeling tools in the field of Drug Discovery" on or before September 01, 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:
Prof. Swastika Ganguly
Department of Pharmaceutical Sciences & Technology, Birla Institute of Technology, Mesra-835215. India.
E.mail: swastikaganguly@bitmesra.ac.in
Dr. S. Murugesan
Department of Pharmacy, Birla Institute of Technology and Science, Pilani-333031. Rajasthan. India.
E.mail:murugesan@pilani.bits-pilani.ac.inn International Journal of Quantitative Structure-Property Relationships (IJQSPR)

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

Submission Due Date
10/30/2018

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 October 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