A Concise Review on the Significance of QSAR in Drug Design
Hiteshi Tandon,
Tanmoy Chakraborty,
Vandana Suhag
Issue:
Volume 4, Issue 4, December 2019
Pages:
45-51
Received:
2 December 2019
Accepted:
16 December 2019
Published:
27 December 2019
Abstract: Drug designing is a crucial step in the exploration of novel drugs which requires potent methodologies. One of such methodologies is Quantitative Structure Activity Relationship (QSAR) which is a widely used statistical tool that correlates the structure of a molecule to a biological activity as a function of molecular descriptors, thereby, playing an essential role in the drug designing. QSAR utilizes Density Functional Theory (DFT) based chemical descriptors for this purpose. The selection of such significant molecular descriptors from various available descriptors is the foremost challenge in a QSAR as structural descriptors are representative of the molecular characteristics accountable for the relevant activity. Recently, new QSAR approaches have been introduced which further enhance the study of the activities. Further, the constructed QSAR models also need to be tested and validated for their efficiency and practical usage. As the QSAR models are structure specific, they may not be universally applicable. However, because of their high precision and efficacy, they have a promising future in the world of drug design. This review briefly summarizes the role of descriptor based QSAR in drug design in conjunction with existing QSAR approaches and also the utility as well as constraints of this approach in drug design.
Abstract: Drug designing is a crucial step in the exploration of novel drugs which requires potent methodologies. One of such methodologies is Quantitative Structure Activity Relationship (QSAR) which is a widely used statistical tool that correlates the structure of a molecule to a biological activity as a function of molecular descriptors, thereby, playing...
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Genetic Variability on Grain Yield and Related Agronomic Traits of Faba Bean (Vicia faba L.) Genotypes Under Soil Acidity Stress in the Central Highlands of Ethiopia
Mesfin Tadele,
Wassu Mohammed,
Mussa Jarso
Issue:
Volume 4, Issue 4, December 2019
Pages:
52-58
Received:
19 July 2019
Accepted:
23 August 2019
Published:
4 January 2020
Abstract: Faba bean is the leading in area coverage and total production of pulses in Ethiopia. However, soil acidity becomes the major production limiting factor of faba bean in the highlands of Ethiopia. Information on genetic variability and heritability of faba bean genotypes on different traits under soil acidity stress is scanty. Thus, this study was conducted to estimate genetic variability of faba bean genotypes on grain yield and related traits at soil of pH 4.66, 4.96 and 4.49 at Holetta, Watebecha Minjaro and Jeldu, respectively, during 2017 main cropping season. The experiment comprised 50 faba bean genotypes arranged in randomized complete block design with three replications. Data were collected on grain yield (g/5plants) and some other agronomic traits: days to 50% flowering, days to 90% maturity, grain filling period, plant height (cm), number of poding nodes/plant, number of pods/ poding node, number of pods/plant, chocolate spot disease (%) and 100-seeds weight (g). Analysis of variance for traits studied showed significant differences among genotypes, locations and their interaction (P ≤ 0.01) for all traits except number of pods/poding node for the interaction. Computed genotypic (GCV) and phenotypic coefficient of variation (PCV) values were ranged from 1.08-23.05 and 1.20-23.26%, respectively, whereas heritability (H2) and genetic advance as percent of the mean (GAM) ranged from 24.63 -98.22% and 2.0 - 47.13%, respectively. The highest values for all components were recorded for 100-seeds weight while lowest values except for H2 computed for days to 90% maturity. The observed PCV and GCV values were high for 100-seed weight and moderate for grain yield, number of poding node/plant and pod/plant. The values of PCV were higher than GCV for all traits. Hence, the high variation between PCV and GCV (6.78) for chocolate spot was due to environmental stress (soil acidity) besides the genetic constitution of tested genotypes. High H2 and GAM were observed for 100-seeds weight, number of pod/plant and poding node/plant. Traits with high H2 indicated that selection based on mean would be successful in improving the traits. Therefore, selection based on phenotypic performance of genotypes would be effective to improve traits that have high GAM coupled with high H2 estimates.
Abstract: Faba bean is the leading in area coverage and total production of pulses in Ethiopia. However, soil acidity becomes the major production limiting factor of faba bean in the highlands of Ethiopia. Information on genetic variability and heritability of faba bean genotypes on different traits under soil acidity stress is scanty. Thus, this study was c...
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