ChemInform Abstract: In silico Mutagenesis and Docking Studies of Pseudomonas aeruginosa PA‐IIL Lectin — Predicting Binding Modes and Energies.

Adam, Jan; Křı́ž, Zdeněk; Prokop, Martin; Wimmerová, Michaela; Koča, Jaroslav

doi:10.1002/chin.200915219

Cited by 3 publications

(6 citation statements)

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“…Current docking programs and empirical scoring functions do not generally provide an accurate description of protein–carbohydrate binding energetics. − Efforts to tackle the problem with end-point free-energy methods such as Molecular Mechanics Poisson–Boltzmann Surface Area (MM-PB/SA), Molecular Mechanics Generalized-Born Surface Area (MM-GB/SA), or Linear Interaction Energy (LIE) have also been reported with mixed success. − Mishra et al have parametrized the LIE approach directly on carbohydrates but found significant overestimations of the calculated binding free energies for low-affinity binders and nonbinders . Topin et al have shown that MM-GB/SA method yields a poor correlation between the predicted and experimentally determined free energies for lectins LecB ( r 2 = 0.22) and BambL ( r 2 = 0.02) .…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Selected Classical Force Fields for Alchemical Binding Free Energy Calculations of Protein-Carbohydrate Complexes

Mishra

Calabró

Loeffler

et al. 2015

J. Chem. Theory Comput.

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Protein-carbohydrate recognition is crucial in many vital biological processes including host-pathogen recognition, cell-signaling, and catalysis. Accordingly, computational prediction of protein-carbohydrate binding free energies is of enormous interest for drug design. However, the accuracy of current force fields (FFs) for predicting binding free energies of protein-carbohydrate complexes is not well understood owing to technical challenges such as the highly polar nature of the complexes, anomerization, and conformational flexibility of carbohydrates. The present study evaluated the performance of alchemical predictions of binding free energies with the GAFF1.7/AM1-BCC and GLYCAM06j force fields for modeling protein-carbohydrate complexes. Mean unsigned errors of 1.1 ± 0.06 (GLYCAM06j) and 2.6 ± 0.08 (GAFF1.7/AM1-BCC) kcal·mol(-1) are achieved for a large data set of monosaccharide ligands for Ralstonia solanacearum lectin (RSL). The level of accuracy provided by GLYCAM06j is sufficient to discriminate potent, moderate, and weak binders, a goal that has been difficult to achieve through other scoring approaches. Accordingly, the protocols presented here could find useful applications in carbohydrate-based drug and vaccine developments.

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Section: Introductionmentioning

confidence: 99%

Evaluation of Selected Classical Force Fields for Alchemical Binding Free Energy Calculations of Protein-Carbohydrate Complexes

Mishra

Calabró

Loeffler

et al. 2015

J. Chem. Theory Comput.

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“…When the protein mutant structure is not available, an in silico mutated structure may be used. 13 The prime focus of the docking software is to determine the geometry of the ligand as accurately as reported in the crystal structure. However, when predicting new binding partners, the quantification of binding affinity by the docking software is also important.…”

Section: ■ Introductionmentioning

confidence: 99%

“…16,17 The performance of selected docking software programs for lectins with ions in the binding site was recently reported. 13 In this study, we applied docking methods to the lectin whose interaction with sugars does not involve any ions and also for saccharides that exhibited low or nonsignificant binding with RSL. 10 In summary, the study was focused on two objectives.…”

Section: ■ Introductionmentioning

confidence: 99%

“…Computational techniques that predict the preferred orientation of a ligand molecule in a protein, when bound to each other, are called docking and are also used to describe when a ligand is bound with a mutated protein. When the protein mutant structure is not available, an in silico mutated structure may be used . The prime focus of the docking software is to determine the geometry of the ligand as accurately as reported in the crystal structure.…”

Section: Introductionmentioning

confidence: 99%

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In Silico Mutagenesis and Docking Study ofRalstonia solanacearumRSL Lectin: Performance of Docking Software To Predict Saccharide Binding

Mishra

Adam

Wimmerová

et al. 2012

J. Chem. Inf. Model.

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In this study, in silico mutagenesis and docking in Ralstonia solanacearum lectin (RSL) were carried out, and the ability of several docking software programs to calculate binding affinity was evaluated. In silico mutation of six amino acid residues (Agr17, Glu28, Gly39, Ala40, Trp76, and Trp81) was done, and a total of 114 in silico mutants of RSL were docked with Me-α-L-fucoside. Our results show that polar residues Arg17 and Glu28, as well as nonpolar amino acids Trp76 and Trp81, are crucial for binding. Gly39 may also influence ligand binding because any mutations at this position lead to a change in the binding pocket shape. The Ala40 residue was found to be the most interesting residue for mutagenesis and can affect the selectivity and/or affinity. In general, the docking software used performs better for high affinity binders and fails to place the binding affinities in the correct order.

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“…The modeled psychrophilic structure was taken and energy minimization or geometry optimization is carried out by using the hyperchem software to optimize the molecular structure until the gradients of potential energy on atoms become negligible. For carrying out docking studies, only half of the tetrameric molecule (1BHE and 3JUR) was considered so as to skip any detrimental conditions during the substrate binding (Adam et al 2008). …”

Section: Preparation Of Proteinsmentioning

confidence: 99%

Molecular insights into cold active polygalacturonase enzyme for its potential application in food processing

Ramya

Pulicherla

2014

J Food Sci Technol

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Pectin is a complex structural heteropolysaccharide that require numerous pectinolytic enzymes for its complete degradation. Polygalacturonase from mesophilic or thermophilic origin are being widely used in fruit and vegetable processing in the recent decades to degrade pectic substances. Recently cold active pectinases are finding added advantages over meso and thermophilic counterparts, to use in industrial scale particularly in food processing industry. They facilitate in conservation of several properties of foods so that the end product retains its naturality and also generates economic benefits. In the present study, Pseudoalteromonas haloplanktis, a well reported marine psychrophile is taken as a model organism for cold active polygalacturonase and is evaluated in comparision to the routinely used mesophilic and thermophilic enzymes by insicio approach. Polygalacturonase sequences from industrially important microbial sources were subjected to MEME and Pfam wherein motifs and domains involved in the conservation were analyzed. Dendrogram revealed sequence level similarity and motifs showed uniform distribution of conserved regions that are involved in important functions. It was also observed through clustalW analysis that the amount of arginine content of psychrophiles is less when compared with thermophiles. Finally, all the modeled enzyme structures were subjected to docking studies using Autodock 4.2 with the substrate polygalacturonic acid and binding energies were found to be −5.73, −6.22 and −7.27 KCals/mole for meso, thermo and psychrophiles respectively which indicates the efficiency of psychrophilic enzymes when compared with its counterparts giving scope for further experimentation to find their better usage in various food industry applications.

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ChemInform Abstract: In silico Mutagenesis and Docking Studies of Pseudomonas aeruginosa PA‐IIL Lectin — Predicting Binding Modes and Energies.

Abstract: Computers in chemistry V 0380In silico Mutagenesis and Docking Studies of Pseudomonas aeruginosa PA-IIL Lectin -Predicting Binding Modes and Energies. -(ADAM, J.; KRIZ, Z.; PROKOP, M.; WIMMEROVA, M.; KOCA*, J.; J. Chem. Inf. Model. (J. Chem. Inf.

Cited by 3 publications

References 1 publication

Evaluation of Selected Classical Force Fields for Alchemical Binding Free Energy Calculations of Protein-Carbohydrate Complexes

Evaluation of Selected Classical Force Fields for Alchemical Binding Free Energy Calculations of Protein-Carbohydrate Complexes

In Silico Mutagenesis and Docking Study ofRalstonia solanacearumRSL Lectin: Performance of Docking Software To Predict Saccharide Binding

Molecular insights into cold active polygalacturonase enzyme for its potential application in food processing

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