The History and Development of Quantitative Structure-Activity Relationships (QSARs)

Following the publication of the history and development of QSAR, it became apparent that a number of matters had not been covered. This addendum is an attempt to rectify that. A very early approach (ca. 60 B.C.) by Lucretius shows that he understood how molecular size and complexity affect liquid viscosity. Comments by Kant (1724-1804) emphasized the necessity of mathematics in science. A claim that the work of von Bibra and Harless in 1847 pre-dated that of Overton and H.H. Meyer is shown not to be correct. K.H. Meyer and Gottlieb-Billroth published in 1920 what is probably the first QSAR equation. Brown, who with his co-author Fraser is credited with the first definitive recognition in 1868-9 that biological activity is a function of molecular structure, is often cited as Crum Brown; in fact, Crum was his second given name. The QSAR work of the Soviet chemist N.V. Lazarev in the 1940s was far ahead of his time, showing numerous correlations of biological activities and physicochemical properties with molecular descriptors. The subject of inverse QSAR is discussed.

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Studies on the EC50 of Natural Monoterpenes as Fungal Inhibitors with Quantitative Structure-Activity Relationships (QSARs)

The Natural Products Journal ◽

10.2174/2210315509666190117150153 ◽

2020 ◽

Vol 10 (1) ◽

pp. 44-60

Author(s):

Mohamed E.I. Badawy ◽

Entsar I. Rabea ◽

Samir A.M. Abdelgaleil

Keyword(s):

Biological Activity ◽

Plant Pathogens ◽

Molecular Descriptors ◽

Microbial Pathogens ◽

Quantitative Structure ◽

Qsar Study ◽

Qsar Analysis ◽

Pharmacophore Modelling ◽

Structure Activity ◽

Wide Range

Background:Monoterpenes are the main constituents of the essential oils obtained from plants. These natural products offered wide spectra of biological activity and extensively tested against microbial pathogens and other agricultural pests.Methods:Antifungal activity of 10 monoterpenes, including two hydrocarbons (camphene and (S)- limonene) and eight oxygenated hydrocarbons ((R)-camphor, (R)-carvone, (S)-fenchone, geraniol, (R)-linalool, (+)-menthol, menthone, and thymol), was determined against fungi of Alternaria alternata, Botrytis cinerea, Botryodiplodia theobromae, Fusarium graminearum, Phoma exigua, Phytophthora infestans, and Sclerotinia sclerotiorum by the mycelia radial growth technique. Subsequently, Quantitative Structure-Activity Relationship (QSAR) analysis using different molecular descriptors with multiple regression analysis based on systematic search and LOOCV technique was performed. Moreover, pharmacophore modelling was carried out using LigandScout software to evaluate the common features essential for the activity and the hypothetical geometries adopted by these ligands in their most active forms.Results:The results showed that the antifungal activities were high, but depended on the chemical structure and the type of microorganism. Thymol showed the highest effect against all fungi tested with respective EC50 in the range of 10-86 mg/L. The QSAR study proved that the molecular descriptors HBA, MR, Pz, tPSA, and Vp were correlated positively with the biological activity in all of the best models with a correlation coefficient (r) ≥ 0.98 and cross-validated values (Q2) ≥ 0.77.Conclusion:The results of this work offer the opportunity to choose monoterpenes with preferential antimicrobial activity against a wide range of plant pathogens.

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Biological Activity, Physical Properties, and Toxicity

International Journal of Quantitative Structure-Property Relationships ◽

10.4018/ijqspr.2021070102 ◽

2021 ◽

Vol 6 (3) ◽

pp. 25-34

Author(s):

Ranita Pal ◽

Pratim Kumar Chattaraj

Keyword(s):

Molecular Structure ◽

Biological Activity ◽

Molecular Biology ◽

Drug Design ◽

Physical Properties ◽

Quantitative Structure Activity Relationship ◽

Molecular Properties ◽

Quantitative Structure ◽

Qsar Analysis ◽

Structure Activity

In the current pandemic-stricken world, quantitative structure-activity relationship (QSAR) analysis has become a necessity in the domain of molecular biology and drug design, realizing that it helps estimate properties and activities of a compound, without actually having to spend time and resources to synthesize it in the laboratory. Correlating the molecular structure of a compound with its activity depends on the choice of the descriptors, which becomes a difficult and confusing task when we have so many to choose from. In this mini-review, the authors delineate the importance of very simple and easy to compute descriptors in estimating various molecular properties/toxicity.

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