Dataset Information

Computational analysis of protein hotspots.

ABSTRACT: Mapping protein hotspots and analysis of the binding free energy associated with each hotspot can provide critical information for drug design. In the present study, we have performed computational analysis for the two known hotspots in thermolysin. Our data showed that the free energy double-decoupling method can determine the binding free energy of different probe molecules associated with the same hotspot or different hotspots with the same probe molecule. The less expensive cosolvent mapping method can be used to readily identify known protein hotspots without prior knowledge and also provide a good estimate of the binding free energy, as compared to the more expensive free energy double-decoupling method. Hence, the combination of the cosolvent mapping method to identify potential protein hotspots followed by more rigorous calculation of the binding free energy associated with each hotspot using the double-decoupling method can provide very useful information for drug design.

SUBMITTER: Yang CY

PROVIDER: S-EPMC4007901 | biostudies-literature | 2010 Jun

REPOSITORIES: biostudies-literature

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Computational analysis of protein hotspots.

Yang Chao-Yie CY Wang Shaomeng S

ACS medicinal chemistry letters 20100325 3

Mapping protein hotspots and analysis of the binding free energy associated with each hotspot can provide critical information for drug design. In the present study, we have performed computational analysis for the two known hotspots in thermolysin. Our data showed that the free energy double-decoupling method can determine the binding free energy of different probe molecules associated with the same hotspot or different hotspots with the same probe molecule. The less expensive cosolvent mapping ...[more]

PMID: 24900186

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Project description:BACKGROUND:Modeling protein-protein interactions (PPIs) using docking algorithms is useful for understanding biomolecular interactions and mechanisms. Typically, a docking algorithm generates a large number of docking poses, and it is often challenging to select the best native-like pose. A further challenge is to recognize key residues, termed as hotspots, at protein-protein interfaces, which contribute more in stabilizing a protein-protein interface. RESULTS:We had earlier developed a computer algorithm, called PPCheck, which ascribes pseudoenergies to measure the strength of PPIs. Native-like poses could be successfully identified in 27 out of 30 test cases, when applied on a separate set of decoys that were generated using FRODOCK. PPCheck, along with conservation and accessibility scores, was able to differentiate 'native-like and non-native-like poses from 1883 decoys of Critical Assessment of Prediction of Interactions (CAPRI) targets with an accuracy of 60%. PPCheck was trained on a 10-fold mixed dataset and tested on a 10-fold mixed test set for hotspot prediction. We obtain an accuracy of 72%, which is in par with other methods, and a sensitivity of 59%, which is better than most existing methods available for hotspot prediction that uses similar datasets. Other relevant tests suggest that PPCheck can also be reliably used to identify conserved residues in a protein and to perform computational alanine scanning. CONCLUSIONS:PPCheck webserver can be successfully used to differentiate native-like and non-native-like docking poses, as generated by docking algorithms. The webserver can also be a convenient platform for calculating residue conservation, for performing computational alanine scanning, and for predicting protein-protein interface hotspots. While PPCheck can differentiate the generated decoys into native-like and non-native-like decoys with a fairly good accuracy, the results improve dramatically when features like conservation and accessibility are included. The method can be successfully used in ranking/scoring the decoys, as obtained from docking algorithms.

Dataset Information

Computational analysis of protein hotspots.

Publications

Computational analysis of protein hotspots.

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