A homology/<i>ab initio</i> hybrid algorithm for sampling near‐native protein conformations

Dhingra, Priyanka; Jayaram, B.

doi:10.1002/jcc.23339

Cited by 15 publications

(7 citation statements)

References 107 publications

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“…7A to C). The simulations were carried out with a tertiary structure for VP4 predicted by Bhageerath-H (22)(23)(24)(25)(26). Of the five predicted possible structures, the lowest-energy structure, comprised of a helix-turn-helix conformation, was selected as the Liposomes mimicking late endosomal vesicles were tested at two pH conditions, 7.0 and 5.5.…”

Section: Resultsmentioning

confidence: 99%

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The VP4 Peptide of Hepatitis A Virus Ruptures Membranes through Formation of Discrete Pores

Shukla

Padhi

Gomes

et al. 2014

J Virol

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Membrane-active peptides, components of capsid structural proteins, assist viruses in overcoming the host membrane barrier in the initial stages of infection. Several such peptides have been identified, and their roles in membrane fusion or disruption have been characterized through biophysical studies. In several members of the Picornaviridae family, the role of the VP4 structural peptide in cellular-membrane penetration is well established. However, there is not much information on the membrane-penetrating capsid components of hepatitis A virus (HAV), an unusual member of this family. The VP4 peptide of HAV differs from its analogues in other picornaviruses in being significantly shorter in length and in lacking a signal for myristoylation, thought to be a critical requisite for VP4-mediated membrane penetration. Here we report, for the first time, that the atypical VP4 in HAV contains significant membrane-penetrating activity. Using a combination of biophysical assays and molecular dynamics simulation studies, we show that VP4 integrates into membrane vesicles through its N-terminal region to finally form discrete pores of 5-to 9-nm diameter, which induces leakage in the vesicles without altering their overall size or shape. We further demonstrate that the membrane activity of VP4 is specific toward vesicles mimicking the lipid content of late endosomes at acidic pH. Taken together, our data indicate that VP4 might be essential for the penetration of host endosomal membranes and release of the viral genome during HAV entry. IMPORTANCEHepatitis A virus causes acute hepatitis in humans through the fecal-oral route and is particularly prevalent in underdeveloped regions with poor hygienic conditions. Although a vaccine for HAV exists, its high cost makes it unsuitable for universal application in developing countries. Studies on host-virus interaction for HAV have been hampered due to a lack of starting material, since the virus is extremely slow growing in culture. Among the unknown aspects of the HAV life cycle is its manner of host membrane penetration, which is one of the most important initial steps in viral infection. Here, we present data to suggest that a small peptide, VP4, a component of the HAV structural polyprotein, might be essential in helping the viral genome cross cell membranes during entry. It is hoped that this work might help in elucidating the manner of initial host cell interaction by HAV.

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Section: Resultsmentioning

confidence: 99%

“…The three-dimensional structure of HAV VP4 ( 1 MNMSRQGIFQT-VGSGLDHILSLA 23 ) was predicted using Bhageerath-H (a homology ab initio hybrid web server for protein tertiary structure prediction) (22)(23)(24)(25)(26). Of the five candidate predicted structures (see Fig.…”

Section: Molecular Dynamics Simulation (I) Structure Prediction Of Hmentioning

confidence: 99%

The VP4 Peptide of Hepatitis A Virus Ruptures Membranes through Formation of Discrete Pores

Shukla

Padhi

Gomes

et al. 2014

J Virol

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“…The first step in the pipeline involves generation of a large pool of full length decoys. In the proposed protein structure prediction pipeline, Bhageerath -H Strgen algorithm for protein conformational sampling [ 63 ] is the first module. The module takes as input protein amino acid sequence and provides as output a large pool of decoys.…”

Section: Methodsmentioning

confidence: 99%

“…This article describes Bhageerath -H, a homology/ ab initio hybrid software for predicting tertiary structure of monomeric proteins. Bhageerath -H makes use of Bhageerath -H Strgen algorithm [ 63 ] for extensive sampling of the protein fold space and generates a large basket of decoys containing near-native protein conformations, which are further supplemented by a chemical logic based alignment scheme and then clustered to eliminate non-unique redundant structures. These are then screened by a physico-chemical scoring metric (pcSM) and assessed for their quality.…”

Section: Introductionmentioning

confidence: 99%

Bhageerath-H: A homology/ab initio hybrid server for predicting tertiary structures of monomeric soluble proteins

et al. 2014

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BackgroundThe advent of human genome sequencing project has led to a spurt in the number of protein sequences in the databanks. Success of structure based drug discovery severely hinges on the availability of structures. Despite significant progresses in the area of experimental protein structure determination, the sequence-structure gap is continually widening. Data driven homology based computational methods have proved successful in predicting tertiary structures for sequences sharing medium to high sequence similarities. With dwindling similarities of query sequences, advanced homology/ ab initio hybrid approaches are being explored to solve structure prediction problem. Here we describe Bhageerath-H, a homology/ ab initio hybrid software/server for predicting protein tertiary structures with advancing drug design attempts as one of the goals.ResultsBhageerath-H web-server was validated on 75 CASP10 targets which showed TM-scores ≥0.5 in 91% of the cases and Cα RMSDs ≤5Å from the native in 58% of the targets, which is well above the CASP10 water mark. Comparison with some leading servers demonstrated the uniqueness of the hybrid methodology in effectively sampling conformational space, scoring best decoys and refining low resolution models to high and medium resolution.ConclusionBhageerath-H methodology is web enabled for the scientific community as a freely accessible web server. The methodology is fielded in the on-going CASP11 experiment.

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“…30 Protein structure prediction algorithms are algorithms that attempt to predict the tertiary structure of proteins. 26 These prediction algorithms have been refined over a number of years [31][32][33][34] , but will still deviate when compared to samples of actual, experimentally determined structures. One way of measuring such deviations is through the root-mean-square-deviation.…”

Section: Data Setsmentioning

confidence: 99%

benefits of segmentation: Evidence from a South African bank and other studies

Breed¹,

Verster²

2017

S. Afr. J. Sci.

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We applied different modelling techniques to six data sets from different disciplines in the industry, on which predictive models can be developed, to demonstrate the benefit of segmentation in linear predictive modelling. We compared the model performance achieved on the data sets to the performance of popular non-linear modelling techniques, by first segmenting the data (using unsupervised, semi-supervised, as well as supervised methods) and then fitting a linear modelling technique. A total of eight modelling techniques was compared. We show that there is no one single modelling technique that always outperforms on the data sets. Specifically considering the direct marketing data set from a local South African bank, it is observed that gradient boosting performed the best. Depending on the characteristics of the data set, one technique may outperform another. We also show that segmenting the data benefits the performance of the linear modelling technique in the predictive modelling context on all data sets considered. Specifically, of the three segmentation methods considered, the semi-supervised segmentation appears the most promising.

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A homology/ab initio hybrid algorithm for sampling near‐native protein conformations

Cited by 15 publications

References 107 publications

The VP4 Peptide of Hepatitis A Virus Ruptures Membranes through Formation of Discrete Pores

The VP4 Peptide of Hepatitis A Virus Ruptures Membranes through Formation of Discrete Pores

Bhageerath-H: A homology/ab initio hybrid server for predicting tertiary structures of monomeric soluble proteins

benefits of segmentation: Evidence from a South African bank and other studies

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