Computational Approaches for the Design of Mosquito Repellent Chemicals

2020 ◽  
Vol 27 (1) ◽  
pp. 32-41 ◽  
Author(s):  
Subhash C. Basak ◽  
Apurba K. Bhattacharjee

Background: In view of many current mosquito-borne diseases there is a need for the design of novel repellents. Objective: The objective of this article is to review the results of the researches carried out by the authors in the computer-assisted design of novel mosquito repellents. Methods: Two methods in the computational design of repellents have been discussed: a) Quantitative Structure Activity Relationship (QSAR) studies from a set of repellents structurally related to DEET using computed mathematical descriptors, and b) Pharmacophore based modeling for design and discovery of novel repellent compounds including virtual screening of compound databases and synthesis of novel analogues. Results: Effective QSARs could be developed using mathematical structural descriptors. The pharmacophore based method is an effective tool for the discovery of new repellent molecules. Conclusion: Results reviewed in this article show that both QSAR and pharmacophore based methods can be used to design novel repellent molecules.

2021 ◽  
Vol 22 (16) ◽  
pp. 8557
Author(s):  
Tao Huang ◽  
Guohui Sun ◽  
Lijiao Zhao ◽  
Na Zhang ◽  
Rugang Zhong ◽  
...  

Nitroaromatic compounds (NACs) are ubiquitous in the environment due to their extensive industrial applications. The recalcitrance of NACs causes their arduous degradation, subsequently bringing about potential threats to human health and environmental safety. The problem of how to effectively predict the toxicity of NACs has drawn public concern over time. Quantitative structure–activity relationship (QSAR) is introduced as a cost-effective tool to quantitatively predict the toxicity of toxicants. Both OECD (Organization for Economic Co-operation and Development) and REACH (Registration, Evaluation and Authorization of Chemicals) legislation have promoted the use of QSAR as it can significantly reduce living animal testing. Although numerous QSAR studies have been conducted to evaluate the toxicity of NACs, systematic reviews related to the QSAR modeling of NACs toxicity are less reported. The purpose of this review is to provide a thorough summary of recent QSAR studies on the toxic effects of NACs according to the corresponding classes of toxic response endpoints.


Oncology ◽  
2017 ◽  
pp. 408-433
Author(s):  
Omar Deeb ◽  
Mohammad Goodarzi

Antioxidants are substances that protect cells from the damaging effects of oxygen radicals, which are chemicals that play a part in some diseases such as cancer and others. Antioxidants are expected to be promising drugs in the management of these diseases by removing oxidative stress. Most of the modeling approaches involved in designing new antioxidants is based on Quantitative Structure-Activity Relationship (QSAR). A number of QSAR studies have been conducted to elucidate the structural requirements of antioxidants for their activities in order to predict the potency of these compounds with regard to the targeted activity and to direct the synthesis of more potent analogues. The main focus of this chapter is on the QSAR modeling of antioxidant compounds. The authors provide different QSAR studies of antioxidant compounds and try to compare between them in terms of the best models obtained and their use in designing potential new drugs.


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