QSAR of Antioxidants

Oncology ◽  
2017 ◽  
pp. 408-433
Author(s):  
Omar Deeb ◽  
Mohammad Goodarzi
Keyword(s):  
Oxidative Stress ◽  
Oxygen Radicals ◽  
Quantitative Structure Activity Relationship ◽  
New Drugs ◽  
Antioxidant Compounds ◽  
Quantitative Structure ◽  
Qsar Modeling ◽  
Structural Requirements ◽  
Qsar Studies ◽  
Structure Activity

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.

QSAR of Antioxidants

2015 ◽  
pp. 212-237
Author(s):  
Omar Deeb ◽  
Mohammad Goodarzi
Keyword(s):  
Oxidative Stress ◽  
Oxygen Radicals ◽  
Quantitative Structure Activity Relationship ◽  
New Drugs ◽  
Antioxidant Compounds ◽  
Quantitative Structure ◽  
Qsar Modeling ◽  
Structural Requirements ◽  
Qsar Studies ◽  
Structure Activity

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.

scholarly journals Quantitative Structure-Activity Relationship (QSAR) Studies on the Toxic Effects of Nitroaromatic Compounds (NACs): A Systematic Review

2021 ◽  
Vol 22 (16) ◽  
pp. 8557
Author(s):  
Tao Huang ◽  
Guohui Sun ◽  
Lijiao Zhao ◽  
Na Zhang ◽  
Rugang Zhong ◽  
...  
Keyword(s):  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Nitroaromatic Compounds ◽  
Toxic Effects ◽  
Activity Relationship ◽  
Quantitative Structure ◽  
Qsar Modeling ◽  
Toxic Response ◽  
Qsar Studies ◽  
Structure Activity

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.

scholarly journals Learnings from quantitative structure–activity relationship (QSAR) studies with respect to food protein-derived bioactive peptides: a review

RSC Advances ◽  
2016 ◽  
Vol 6 (79) ◽  
pp. 75400-75413 ◽  
Author(s):  
Alice B. Nongonierma ◽  
Richard J. FitzGerald
Keyword(s):  
Bioactive Peptides ◽  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Food Protein ◽  
Quantitative Structure ◽  
Structural Requirements ◽  
Qsar Studies ◽  
Structure Activity

QSAR studies may help to better understand structural requirements for peptide bioactivity and therefore to develop potent BAPs.

Computational Approaches for the Design of Mosquito Repellent Chemicals

2020 ◽  
Vol 27 (1) ◽  
pp. 32-41 ◽  
Author(s):  
Subhash C. Basak ◽  
Apurba K. Bhattacharjee
Keyword(s):  
Computational Design ◽  
Quantitative Structure Activity Relationship ◽  
Computer Assisted ◽  
Quantitative Structure ◽  
Mosquito Repellent ◽  
Computational Approaches ◽  
Qsar Studies ◽  
Computer Assisted Design ◽  
Structure Activity ◽  
Mosquito Repellents

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.

An Introduction to the Basic Concepts in QSAR-Aided Drug Design

2015 ◽  
pp. 1-47 ◽  
Author(s):  
Maryam Hamzeh-Mivehroud ◽  
Babak Sokouti ◽  
Siavoush Dastmalchi
Keyword(s):  
Drug Design ◽  
Drug Development ◽  
Biological Activities ◽  
Model Development ◽  
Quantitative Structure Activity Relationship ◽  
Molecular Structures ◽  
New Drugs ◽  
Qsar Modeling ◽  
Qsar Studies ◽  
Modern Drug

The need for the development of new drugs to combat existing and newly identified conditions is unavoidable. One of the important tools used in the advanced drug development pipeline is computer-aided drug design. Traditionally, to find a drug many ligands were synthesized and evaluated for their effectiveness using suitable bioassays and if all other drug-likeness features were met, the candidate(s) would possibly reach the market. Although this approach is still in use in advanced format, computational methods are an indispensable component of modern drug development projects. One of the methods used from very early days of rationalizing the drug design approaches is Quantitative Structure-Activity Relationship (QSAR). This chapter overviews QSAR modeling steps by introducing molecular descriptors, mathematical model development for relating biological activities to molecular structures, and model validation. At the end, several successful cases where QSAR studies were used extensively are presented.

An Introduction to the Basic Concepts in QSAR-Aided Drug Design

Oncology ◽  
2017 ◽  
pp. 20-66
Author(s):  
Maryam Hamzeh-Mivehroud ◽  
Babak Sokouti ◽  
Siavoush Dastmalchi
Keyword(s):  
Drug Design ◽  
Drug Development ◽  
Biological Activities ◽  
Model Development ◽  
Quantitative Structure Activity Relationship ◽  
Molecular Structures ◽  
New Drugs ◽  
Qsar Modeling ◽  
Qsar Studies ◽  
Modern Drug

The need for the development of new drugs to combat existing and newly identified conditions is unavoidable. One of the important tools used in the advanced drug development pipeline is computer-aided drug design. Traditionally, to find a drug many ligands were synthesized and evaluated for their effectiveness using suitable bioassays and if all other drug-likeness features were met, the candidate(s) would possibly reach the market. Although this approach is still in use in advanced format, computational methods are an indispensable component of modern drug development projects. One of the methods used from very early days of rationalizing the drug design approaches is Quantitative Structure-Activity Relationship (QSAR). This chapter overviews QSAR modeling steps by introducing molecular descriptors, mathematical model development for relating biological activities to molecular structures, and model validation. At the end, several successful cases where QSAR studies were used extensively are presented.

QSAR modeling for reaction rate constants of eaq− with diverse organic compounds in water

2020 ◽  
Vol 6 (7) ◽  
pp. 1931-1938
Author(s):  
Shanshan Zheng ◽  
Chao Li ◽  
Gaoliang Wei
Keyword(s):  
Organic Compounds ◽  
Reaction Rate ◽  
Quantitative Structure Activity Relationship ◽  
Structural Features ◽  
Quantitative Structure ◽  
Qsar Modeling ◽  
Reaction Rate Constants ◽  
Structure Activity ◽  
Qsar Models ◽  
The Impact

Two quantitative structure–activity relationship (QSAR) models to predict keaq− of diverse organic compounds were developed and the impact of molecular structural features on eaq− reactivity was investigated.

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