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Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
被引:0
作者:
Cruz, Hector
[1
,2
]
Llanes, Alejandro
[2
,3
]
Fernandez, Patricia L.
[2
,3
]
机构:
[1] Univ Tecnol Panama UTP, Fac Ciencias & Tecnol, Panama City, Panama
[2] Inst Invest Cient & Serv Alta Tecnol AIP INDICASAT, Ctr Biol Mol & Celular Enfermedades, Panama City, Spain
[3] Sistema Nacl Invest Panama SNI, Panama City, Panama
来源:
JOVE-JOURNAL OF VISUALIZED EXPERIMENTS
|
2024年
/
203期
关键词:
INTERFERON REGULATORY FACTOR-3;
SPECIFICITY;
PHOSPHORYLATION;
ACTIVATION;
INSIGHTS;
D O I:
10.3791/66314
中图分类号:
O [数理科学和化学];
P [天文学、地球科学];
Q [生物科学];
N [自然科学总论];
学科分类号:
07 ;
0710 ;
09 ;
摘要:
Many protein -protein interactions involve the binding of short protein segments to peptide -binding domains. Usually, such interactions require the recognition of linear motifs with variable conservation. The combination of highly conserved and more variable regions in the same ligands often contributes to the multispecificity of binding, a common property of enzymes and cell signaling proteins. Characterization of amino acid preferences of peptide -binding domains is important for the design of mediators of protein -protein interactions (PPIs). Computational methods are an efficient alternative to the often costly and cumbersome experimental techniques, enabling the design of potential mediators that can be later validated in downstream experiments. Here, we described a methodology using the Pepspec application of the Rosetta molecular modeling package to predict the amino acid preferences of peptide -binding domains. This methodology is useful when the structure of the receptor protein and the nature of the peptide ligand are both known or can be inferred. The methodology starts with a well -characterized anchor from the ligand, which is extended by randomly adding amino acid residues. The binding affinity of peptides generated this way is then evaluated by flexible -backbone peptide docking in order to select the peptides with the best predicted binding scores. These peptides are then used to calculate amino acid preferences and to optionally compute a position -weight matrix (PWM) that can be used in further studies. To illustrate the application of this methodology, we used the interaction between subunits of human interferon regulatory factor 5 (IRF5), previously known to be multispecific but globally guided by a short conserved motif called pLxIS. The estimated amino acid preferences were consistent with previous knowledge about the IRF5 binding surface. Positions occupied by phosphorylatable serine residues exhibited a high frequency of aspartate and glutamate, likely because their negatively charged side chains are similar to phosphoserine.
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页数:15
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