HotPoint A web server for prediction of hot spots in protein interfaces

Date

2010-04-22

Author

Tunçbağ, Nurcan
Gürsoy, Attila

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https://hdl.handle.net/11511/76102

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HotPoint: hot spot prediction server for protein interfaces Tunçbağ, Nurcan; GÜRSOY, Attila (2010-07-01) The energy distribution along the protein-protein interface is not homogenous; certain residues contribute more to the binding free energy, called 'hot spots'. Here, we present a web server, HotPoint, which predicts hot spots in protein interfaces using an empirical model. The empirical model incorporates a few simple rules consisting of occlusion from solvent and total knowledge-based pair potentials of residues. The prediction model is computationally efficient and achieves high accuracy of 70%. The input...
HotSprint: database of computational hot spots in protein interfaces Guney, Emre; Tunçbağ, Nurcan; Keskin, Ozlem; Gursoy, Attila (2008-01-01) We present a new database of computational hot spots in protein interfaces: HotSprint. Hot spots are residues comprising only a small fraction of interfaces yet accounting for the majority of the binding energy. HotSprint contains data for 35 776 protein interfaces among 49 512 protein interfaces extracted from the multi-chain structures in Protein Data Bank (PDB) as of February 2006. The conserved residues in interfaces with certain buried accessible solvent area (ASA) and complex ASA thresholds are flagge...
HotPOINT Hot Spot Prediction Server for Protein Interfaces Tunçbağ, Nurcan; Gürsoy, Attila (null; 2010-08-15)
HotSprint Database of Computational Hot Spots at Protein Interfaces Güney, Emre; Tunçbağ, Nurcan; Keskin Özkaya, Zehra Özlem; Gürsoy, Attila (2007-07-25)
DEEPScreen: high performance drug-target interaction prediction with convolutional neural networks using 2-D structural compound representations Rifaioğlu, Ahmet Süreyya; Nalbat, Esra; Atalay, Mehmet Volkan (2020-03-07) The identification of physical interactions between drug candidate compounds and target biomolecules is an important process in drug discovery. Since conventional screening procedures are expensive and time consuming, computational approaches are employed to provide aid by automatically predicting novel drug-target interactions (DTIs). In this study, we propose a large-scale DTI prediction system, DEEPScreen, for early stage drug discovery, using deep convolutional neural networks. One of the main advantage...

Citation Formats

N. Tunçbağ and A. Gürsoy, “HotPoint A web server for prediction of hot spots in protein interfaces,” 2010, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/76102.