Computational analysis of R and S isoforms of 12-Lipoxygenases: Homology modeling and docking studies

Aparoy, Polamarasetty; Leela, T.; Reddy, Ramalinga; Reddanna, Pallu

doi:10.1016/j.jmgm.2008.11.009

Cited by 13 publications

(6 citation statements)

References 41 publications

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“…Minimization at each stage was performed using 200 steps of steepest descent and 1500 steps of conjugate gradient algorithms. 23 The minimization was mainly to release the bad contact between the antibody and hapten. The antibody−ligand complexes generated were subjected to further analysis.…”

Section: ■ Materials and Methodsmentioning

confidence: 99%

Molecular Characterization of Monoclonal Antibodies against Aflatoxins: A Possible Explanation for the Highest Sensitivity

Zhang

et al. 2012

Anal. Chem.

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We screened and established seven hybridoma cell lines that secrete anti-aflatoxin monoclonal antibodies with different sensitivities. Among these antibodies, 1C11 exhibited the highest sensitivity against all four major kinds of aflatoxins (AFB1, AFB2, AFG1, and AFG2) (IC(50) 0.0012-0.018 ng mL(-1) in the enzyme linked immunosorbent assay (ELISA) system, visual limit of detection of 0.03-0.25 ng mL(-1)). To better understand the interactions between these antibodies and aflatoxins, as well as to guide their potential sensitivity improvement in recombinant antibodies, we used multiple sequence alignment and molecular modeling combined with molecular docking to clarify the molecular mechanism of the highest sensitivity of 1C11 against aflatoxins. Our results show that hydrogen bond and hydrophobic interaction formed by Ser-H49 and Phe-H103 in the antibody with the hapten played the most important roles in determining the binding affinity. Further experiments performed on antibody mutants, designed on the basis of the computational models, supported the prediction of the interaction mode between the antibody and the hapten. Although the factors that influence antibody sensitivity are highly interdependent, our experimental and modeling studies clearly demonstrate how structural differences influence the binding properties of antibodies against the target hapten with different sensitivities.

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Section: ■ Materials and Methodsmentioning

confidence: 99%

Molecular Characterization of Monoclonal Antibodies against Aflatoxins: A Possible Explanation for the Highest Sensitivity

Zhang

et al. 2012

Anal. Chem.

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“…Reddanna et al . [163] generated homology models of human 12R-LOX structure, based upon rabbit reticulocyte 15-Lipoxygenase 1LOX as a template. The 3D model was built using Modeller and BLAST, ClustalW for sequence alignment, AMBER 3.0 for refinement and PROCHECK was used for validation of themodel.…”

Section: Applications Of Homology Modelingmentioning

confidence: 99%

Homology modeling a fast tool for drug discovery: Current perspectives

Vk¹,

Ukawala²,

Ghate³

et al. 2012

Indian J Pharm Sci

219

116

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Major goal of structural biology involve formation of protein-ligand complexes; in which the protein molecules act energetically in the course of binding. Therefore, perceptive of protein-ligand interaction will be very important for structure based drug design. Lack of knowledge of 3D structures has hindered efforts to understand the binding specificities of ligands with protein. With increasing in modeling software and the growing number of known protein structures, homology modeling is rapidly becoming the method of choice for obtaining 3D coordinates of proteins. Homology modeling is a representation of the similarity of environmental residues at topologically corresponding positions in the reference proteins. In the absence of experimental data, model building on the basis of a known 3D structure of a homologous protein is at present the only reliable method to obtain the structural information. Knowledge of the 3D structures of proteins provides invaluable insights into the molecular basis of their functions. The recent advances in homology modeling, particularly in detecting and aligning sequences with template structures, distant homologues, modeling of loops and side chains as well as detecting errors in a model contributed to consistent prediction of protein structure, which was not possible even several years ago. This review focused on the features and a role of homology modeling in predicting protein structure and described current developments in this field with victorious applications at the different stages of the drug design and discovery.

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“…Eicosanoids generated by these LOXs in a tissue specific manner play key role in various diseases. In various LOX isoforms the active sites have modifications to effect specific reactions but the basic enzyme structures are conserved [ 13 - 16 ]. Hence it is very important to identify important conserved/non-conserved amino acids at the active sites of these LOXs.…”

Section: Introductionmentioning

confidence: 99%

Exploration of binding site pattern in arachidonic acid metabolizing enzymes, Cyclooxygenases and Lipoxygenases

et al. 2015

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BackgroundCyclooxygenase (COXs) and Lipoxygenase (LOXs) pathways are the two major enzymatic pathways in arachidonic acid (AA) metabolism. The term eicosanoid is used to describe biologically active lipid mediators including prostaglandins, thromboxanes, leukotrienes and other oxygenated derivatives, which are produced primarily from AA. Eicosanoids generated in a tissue specific manner play a key role in inflammation and cancer. As AA is the substrate common to variety of COXs and LOXs, inhibition of one pathway results in diversion of the substrate to other pathways, which often is responsible for undesirable side effects. Hence there is need for development of not only isozyme specific inhibitors but also dual/multi enzyme inhibitors. Understanding the interactions of AA and characterizing its binding sites in these enzymes therefore is crucial for developing enzyme specific and multi enzyme inhibitors for enhancing therapeutic efficacy and/or overcoming side effects.ResultsAA binding sites in COXs and LOXs are identified and compared by the development of receptor based pharmacophore using MultiBind. Physico chemical properties were compared to understand the details of the binding sites in all the enzymes and to elucidate important amino acids that can be targeted for drug design. The alignment of AA binding sites in the seven enzymes COX-1, COX-2, 5-LOX, 12-LOX, 15-LOX and plant soybean LOX-1 and LOX-3 indicated a common pattern of five common interacting groups. In the same way, comparison of AA binding sites was done pair wise and by multiple alignment in various combinations. It has been identified that aliphatic and aromatic interactions are the most common in all the enzymes. In addition interactions unique to each one of these enzymes were identified.ConclusionThe complete analysis of AA binding sites in the seven enzymes was performed; 120 combinations for the seven enzymes were studied in detail. All the seven enzymes are structurally quite different, yet they share AA as the common binding partner. Comparisons in various combinations showed how they are similar and dissimilar with each other. This information will be helpful in designing specific as well as common inhibitors.Electronic supplementary materialThe online version of this article (doi:10.1186/s13104-015-1101-4) contains supplementary material, which is available to authorized users.

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Computational analysis of R and S isoforms of 12-Lipoxygenases: Homology modeling and docking studies

Cited by 13 publications

References 41 publications

Molecular Characterization of Monoclonal Antibodies against Aflatoxins: A Possible Explanation for the Highest Sensitivity

Molecular Characterization of Monoclonal Antibodies against Aflatoxins: A Possible Explanation for the Highest Sensitivity

Homology modeling a fast tool for drug discovery: Current perspectives

Exploration of binding site pattern in arachidonic acid metabolizing enzymes, Cyclooxygenases and Lipoxygenases

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