Solvent Accessible Surface Area-Based Hot-Spot Detection Methods for Protein-Protein and Protein-Nucleic Acid Interfaces

被引：29

作者：

Munteanu, Cristian R. ^{[1
]}

Pimenta, Antonio C. ^{[2
]}

Fernandez-Lozano, Carlos ^{[1
]}

Melo, Andre ^{[2
]}

Cordeiro, Maria N. D. S. ^{[2
]}

Moreira, Irina S. ^{[2
,3
]}

机构：

[1] Univ A Coruna, Fac Comp Sci, Informat & Commun Technol Dept, La Coruna 15071, Spain

[2] Univ Porto, Dept Quim & Bioquim, Fac Ciencias, REQUIMTE, P-4169007 Oporto, Portugal

[3] Univ Coimbra, FMUC, CNC Ctr Neurosci & Cell Biol, P-3004517 Coimbra, Portugal

来源：

JOURNAL OF CHEMICAL INFORMATION AND MODELING | 2015年 / 55卷 / 05期

关键词：

ALANINE SCANNING MUTAGENESIS; O-RING THEORY; THERMODYNAMIC DATABASES; FREE-ENERGIES; BINDING; PREDICTION; COMPLEX; RESIDUES; SEQUENCE; SERVER;

D O I：

10.1021/ci500760m

中图分类号：

R914 [药物化学];

学科分类号：

100701 ;

摘要：

Due to the importance of hot-spots (HS) detection and the efficiency of computational methodologies, several HS detecting approaches have been developed. The current paper presents new models to predict HS for protein-protein and protein-nucleic acid interactions with better statistics compared with the ones currently reported in literature. These models are based on solvent accessible surface area (SASA) and genetic conservation features subjected to simple Bayes networks (protein-protein systems) and a more complex multi-objective genetic algorithm-support vector machine algorithms (protein-nucleic acid systems) The best models for these interactions have been implemented in two free Web tools.

引用

页码：1077 / 1086

页数：10

共 27 条

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Martins, Joao M.
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Pimenta, Antonio C.
Moreira, Irina S.
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Grosdidier, Solene
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EXPERT OPINION ON DRUG DISCOVERY, 2018, 13 (04) : 327 - 338
[4] Prediction of hot spot residues at protein-protein interfaces by combining machine learning and energy-based methods
Lise, Stefano
Archambeau, Cedric
Pontil, Massimiliano
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BMC BIOINFORMATICS, 2009, 10 : 365
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Ozdemir, E. Sila
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BIOINFORMATICS, 2018, 34 (17) : 795 - 801
[6] Densest subgraph-based methods for protein-protein interaction hot spot prediction
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Lee, Jung-Yu
Yang, Jinn-Moon
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BMC BIOINFORMATICS, 2022, 23 (01)
[7] Protein-protein and protein-nucleic acid binding site prediction via interpretable hierarchical geometric deep learning
Zhang, Shizhuo
Han, Jiyun
Liu, Juntao
GIGASCIENCE, 2024, 13
[8] Sequence and structural features of binding site residues in protein-protein complexes: comparison with protein-nucleic acid complexes
Gromiha, M. Michael
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PROTEOME SCIENCE, 2011, 9
[9] Predictions of Hot Spot Residues at Protein-Protein Interfaces Using Support Vector Machines
Lise, Stefano
Buchan, Daniel
Pontil, Massimiliano
Jones, David T.
PLOS ONE, 2011, 6 (02):
[10] Hot-spot analysis to dissect the functional protein-protein interface of a tRNA-modifying enzyme
Jakobi, Stephan
Tran Xuan Phong Nguyen
Debaene, Francois
Metz, Alexander
Sanglier-Cianferani, Sarah
Reuter, Klaus
Klebe, Gerhard
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2014, 82 (10) : 2713 - 2732

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