IPFP: An Integrated Software Package for Automated Protein Feature Prediction

Satpathy, Raghunath; Konkimalla, Venkata Sai Badireenath; Ratha, Jagnyeswar

doi:10.5958/0975-8089.2014.00014.1

Cited by 2 publications

(2 citation statements)

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“…Conservation of amino acid residues was computed by Consurf server [ 23 ]. The core amino acids of the fungal and bacterial structural models were computed by IPFP tool [ 24 ] and the conservation pattern of the core and the surface amino acid residues was analysed.…”

Section: Methodsmentioning

confidence: 99%

In Silico Phylogenetic Analysis and Molecular Modelling Study of 2-Haloalkanoic Acid Dehalogenase Enzymes from Bacterial and Fungal Origin

Satpathy

Konkimalla

Ratha

2016

Advances in Bioinformatics

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2-Haloalkanoic acid dehalogenase enzymes have broad range of applications, starting from bioremediation to chemical synthesis of useful compounds that are widely distributed in fungi and bacteria. In the present study, a total of 81 full-length protein sequences of 2-haloalkanoic acid dehalogenase from bacteria and fungi were retrieved from NCBI database. Sequence analysis such as multiple sequence alignment (MSA), conserved motif identification, computation of amino acid composition, and phylogenetic tree construction were performed on these primary sequences. From MSA analysis, it was observed that the sequences share conserved lysine (K) and aspartate (D) residues in them. Also, phylogenetic tree indicated a subcluster comprised of both fungal and bacterial species. Due to nonavailability of experimental 3D structure for fungal 2-haloalkanoic acid dehalogenase in the PDB, molecular modelling study was performed for both fungal and bacterial sources of enzymes present in the subcluster. Further structural analysis revealed a common evolutionary topology shared between both fungal and bacterial enzymes. Studies on the buried amino acids showed highly conserved Leu and Ser in the core, despite variation in their amino acid percentage. Additionally, a surface exposed tryptophan was conserved in all of these selected models.

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Section: Methodsmentioning

confidence: 99%

In Silico Phylogenetic Analysis and Molecular Modelling Study of 2-Haloalkanoic Acid Dehalogenase Enzymes from Bacterial and Fungal Origin

Satpathy

Konkimalla

Ratha

2016

Advances in Bioinformatics

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“…Calculations for core and surface amino acids in a given PDB file were performed using IPFP tool, available on line (Satpathy et al, 2014). This tool first computes the accessible surface area of all the residues by calculating the atomic accessible surface defined by a rolling probe of given size around a van der Waals surface explained by Lee and Richards (Hubbard & Thornton, 1993; Lee & Richards, 1971).…”

Section: Calculation Of Core and Surface Residues And Propensitiesmentioning

confidence: 99%

Propensity based classification: Dehalogenase and non-dehalogenase enzymes

Satpathy

Konkimalla

Ratha

2015

JAIDM

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The present work was designed to classify and differentiate between the dehalogenase enzyme and nondehalogenases (other hydrolases) by taking the amino acid propensity at the core, surface and both the parts. The data sets were made on an individual basis by selecting the 3D structures of protein available in the PDB (Protein Data Bank). The prediction of the core amino acids were predicted by IPFP tool and their structural propensity calculation was performed by an in-house built software, Propensity Calculator which is available online. All datasets were finally grouped into two categories, namely dehalogenase and non-dehalogenase using Naïve Bayes, J-48, Random forest, K-means clustering, and SMO classification algorithm. By making the comparison of various classification methods, the proposed tree method (Random forest) performs well with a classification accuracy of 98.88 % (maximum) for the core propensity data set. Therefore, we proposed that, the core amino acid propensity could be approved as a novel potential descriptor for the classification of enzymes.

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IPFP: An Integrated Software Package for Automated Protein Feature Prediction

Cited by 2 publications

References 0 publications

In Silico Phylogenetic Analysis and Molecular Modelling Study of 2-Haloalkanoic Acid Dehalogenase Enzymes from Bacterial and Fungal Origin

In Silico Phylogenetic Analysis and Molecular Modelling Study of 2-Haloalkanoic Acid Dehalogenase Enzymes from Bacterial and Fungal Origin

Propensity based classification: Dehalogenase and non-dehalogenase enzymes

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