Literature DB >> 19543755

Docking and 3D QSAR studies of protoporphyrinogen oxidase inhibitor 3H-pyrazolo[3,4-d][1,2,3]triazin-4-one derivatives.

Kunal Roy1, Somnath Paul.   

Abstract

Docking and three dimensional quantitative structure - activity relationship (3D-QSAR) studies have been performed for protoporphyrinogen oxidase (PPO) inhibitor 3H-pyrazolo[3,4-d][1,2,3]triazin-4-one analogues which are potential herbicides to protect agricultural products from unwanted weeds. The 3D-QSAR studies have been carried out using shape, spatial, electronic and molecular field descriptors along with a few structural parameters. The chemometric tools used for the analyses are genetic function approximation (GFA), partial least squares (PLS) and genetic partial least squares (G/PLS). The whole data set (n = 34) was divided into a training set (75% of the data set) and a test set (remaining 25%) on the basis of K-means clustering technique applied on topological, spatial and electronic descriptor matrix. Models developed from the training set were used to predict the activity of the test set compounds. All the models have been validated internally, externally and by Y-randomization technique. Docking studies suggest that the molecules bind with a hydrophobic pocket of the enzyme formed by some nonpolar amino acid (Ile168, Ile311, Ile412, Met365, Phe65 and Val164) residues. The QSAR studies suggest that for better activity the molecules should have symmetrical shape in the 3D space. For better PPO inhibitory activity, there should be a balance between the electrophilic and nucleophilic characters of the inhibitors. The charged surface area descriptors suggest that, the positive charge distributed over a large surface area may enhance the activity. Molecular field probes reflect that increase in steric volume and positively charged surface area may enhance the herbicidal activity.

Entities:  

Mesh:

Substances:

Year:  2009        PMID: 19543755     DOI: 10.1007/s00894-009-0528-8

Source DB:  PubMed          Journal:  J Mol Model        ISSN: 0948-5023            Impact factor:   1.810


  16 in total

Review 1.  Inference from clustering with application to gene-expression microarrays.

Authors:  Edward R Dougherty; Junior Barrera; Marcel Brun; Seungchan Kim; Roberto M Cesar; Yidong Chen; Michael Bittner; Jeffrey M Trent
Journal:  J Comput Biol       Date:  2002       Impact factor: 1.479

2.  Determining the validity of a QSAR model--a classification approach.

Authors:  Rajarshi Guha; Peter C Jurs
Journal:  J Chem Inf Model       Date:  2005 Jan-Feb       Impact factor: 4.956

3.  Development of a general quantum-chemical descriptor for steric effects: density functional theory based QSAR study of herbicidal sulfonylurea analogues.

Authors:  Zhen Xi; Zhihong Yu; Congwei Niu; Shurong Ban; Guangfu Yang
Journal:  J Comput Chem       Date:  2006-10       Impact factor: 3.376

Review 4.  Development of quantitative structure-activity relationships and its application in rational drug design.

Authors:  Guang-Fu Yang; Xiaoqin Huang
Journal:  Curr Pharm Des       Date:  2006       Impact factor: 3.116

5.  Structure-activity relationships for a new family of sulfonylurea herbicides.

Authors:  Jian-Guo Wang; Zheng-Ming Li; Ning Ma; Bao-Lei Wang; Lin Jiang; Siew Siew Pang; Yu-Ting Lee; Luke W Guddat; Ronald G Duggleby
Journal:  J Comput Aided Mol Des       Date:  2005-12-23       Impact factor: 3.686

6.  Molecular docking and three-dimensional quantitative structure-activity relationship studies on the binding modes of herbicidal 1-(substituted phenoxyacetoxy)alkylphosphonates to the E1 component of pyruvate dehydrogenase.

Authors:  Hao Peng; Tao Wang; Peng Xie; Ting Chen; Hong-Wu He; Jian Wan
Journal:  J Agric Food Chem       Date:  2007-02-09       Impact factor: 5.279

7.  Three-dimensional quantitative similarity-activity relationships (3D QSiAR) from SEAL similarity matrices.

Authors:  H Kubinyi; F A Hamprecht; T Mietzner
Journal:  J Med Chem       Date:  1998-07-02       Impact factor: 7.446

8.  Quantitative structure-antitumor activity relationships of camptothecin analogues: cluster analysis and genetic algorithm-based studies.

Authors:  Y Fan; L M Shi; K W Kohn; Y Pommier; J N Weinstein
Journal:  J Med Chem       Date:  2001-09-27       Impact factor: 7.446

9.  A DFT-based QSARs study of protoporphyrinogen oxidase inhibitors: phenyl triazolinones.

Authors:  Li Zhang; Jian Wan; Guangfu Yang
Journal:  Bioorg Med Chem       Date:  2004-12-01       Impact factor: 3.641

10.  Comparative QSAR studies of CYP1A2 inhibitor flavonoids using 2D and 3D descriptors.

Authors:  Kunal Roy; Partha Pratim Roy
Journal:  Chem Biol Drug Des       Date:  2008-11       Impact factor: 2.817

View more
  3 in total

1.  Quantitative Structure Activity Relationship Studies and Molecular Dynamics Simulations of 2-(Aryloxyacetyl)cyclohexane-1,3-Diones Derivatives as 4-Hydroxyphenylpyruvate Dioxygenase Inhibitors.

Authors:  Ying Fu; Yong-Xuan Liu; Ke-Han Yi; Ming-Qiang Li; Jia-Zhong Li; Fei Ye
Journal:  Front Chem       Date:  2019-08-20       Impact factor: 5.221

2.  Synthesis of new pyrazolo[1,2,3]triazines by cyclative cleavage of pyrazolyltriazenes.

Authors:  Nicolai Wippert; Martin Nieger; Claudine Herlan; Nicole Jung; Stefan Bräse
Journal:  Beilstein J Org Chem       Date:  2021-11-22       Impact factor: 2.883

3.  Novel Thiazole Phenoxypyridine Derivatives Protect Maize from Residual Pesticide Injury Caused by PPO-Inhibitor Fomesafen.

Authors:  Li-Xia Zhao; Min-Lei Yin; Qing-Rui Wang; Yue-Li Zou; Tao Ren; Shuang Gao; Ying Fu; Fei Ye
Journal:  Biomolecules       Date:  2019-09-20
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.