Quantitative model for genome-wide cyclic AMP receptor protein binding site identification and characteristic analysis.
Brief Bioinform
; 24(3)2023 05 19.
Article
em En
| MEDLINE
| ID: mdl-37114659
ABSTRACT
Cyclic AMP receptor proteins (CRPs) are important transcription regulators in many species. The prediction of CRP-binding sites was mainly based on position-weighted matrixes (PWMs). Traditional prediction methods only considered known binding motifs, and their ability to discover inflexible binding patterns was limited. Thus, a novel CRP-binding site prediction model called CRPBSFinder was developed in this research, which combined the hidden Markov model, knowledge-based PWMs and structure-based binding affinity matrixes. We trained this model using validated CRP-binding data from Escherichia coli and evaluated it with computational and experimental methods. The result shows that the model not only can provide higher prediction performance than a classic method but also quantitatively indicates the binding affinity of transcription factor binding sites by prediction scores. The prediction result included not only the most knowns regulated genes but also 1089 novel CRP-regulated genes. The major regulatory roles of CRPs were divided into four classes carbohydrate metabolism, organic acid metabolism, nitrogen compound metabolism and cellular transport. Several novel functions were also discovered, including heterocycle metabolic and response to stimulus. Based on the functional similarity of homologous CRPs, we applied the model to 35 other species. The prediction tool and the prediction results are online and are available at https//awi.cuhk.edu.cn/â¼CRPBSFinder.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Contexto em Saúde:
3_ND
Base de dados:
MEDLINE
Assunto principal:
Proteína Receptora de AMP Cíclico
/
Proteínas de Escherichia coli
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Idioma:
En
Revista:
Brief Bioinform
Ano de publicação:
2023
Tipo de documento:
Article