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

Jayaram B, Dhingra P, Mishra A, Kaushik R, Mukherjee G, Singh A, Shekhar S - BMC Bioinformatics (2014)

Bottom Line: 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.The methodology is fielded in the on-going CASP11 experiment.

View Article: PubMed Central - HTML - PubMed

ABSTRACT

Background: The 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.

Results: Bhageerath-H web-server was validated on 75 CASP10 targets which showed TM-scores ≥ 0.5 in 91% of the cases and Cα RMSDs ≤ 5 Å 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.

Conclusion: Bhageerath-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.

Show MeSH
Cα RMSD distribution of 75 CASP10 targets.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
getmorefigures.php?uid=PMC4290660&req=5

Figure 4: Cα RMSD distribution of 75 CASP10 targets.

Mentions: Bhageerath-H was validated on 75 CASP10 targets. Cα RMSDs and TM-scores of final five Bhageerath-H predictions from the native were calculated. In 68 out of 75 systems i.e. in 91% of the cases Bhageerath-H predicted model has a TM-score ≥0.5, while in 44 targets i.e. in 59% of the cases Bhageerath-H was able to predict a model in top 5 having a Cα RMSD from the native ≤5.0Å (Additional File 1). Figure 3 shows the TM-score distribution and Figure 4 shows the Cα RMSD distribution of all the75 targets.


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

Jayaram B, Dhingra P, Mishra A, Kaushik R, Mukherjee G, Singh A, Shekhar S - BMC Bioinformatics (2014)

Cα RMSD distribution of 75 CASP10 targets.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4290660&req=5

Figure 4: Cα RMSD distribution of 75 CASP10 targets.
Mentions: Bhageerath-H was validated on 75 CASP10 targets. Cα RMSDs and TM-scores of final five Bhageerath-H predictions from the native were calculated. In 68 out of 75 systems i.e. in 91% of the cases Bhageerath-H predicted model has a TM-score ≥0.5, while in 44 targets i.e. in 59% of the cases Bhageerath-H was able to predict a model in top 5 having a Cα RMSD from the native ≤5.0Å (Additional File 1). Figure 3 shows the TM-score distribution and Figure 4 shows the Cα RMSD distribution of all the75 targets.

Bottom Line: 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.The methodology is fielded in the on-going CASP11 experiment.

View Article: PubMed Central - HTML - PubMed

ABSTRACT

Background: The 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.

Results: Bhageerath-H web-server was validated on 75 CASP10 targets which showed TM-scores ≥ 0.5 in 91% of the cases and Cα RMSDs ≤ 5 Å 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.

Conclusion: Bhageerath-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.

Show MeSH