- 作者: Reema Singh; Akansha Saxena; Harpreet Singh
- 作者服務機構: Biomedical Informatics Center, Indian Council of Medical Research, New Delhi, India.
- 中文摘要: --
- 英文摘要:
Background: Beta-lactamases are one of the most serious threats to public health. In
order to combat this threat we need to study the molecular and functional diversity of
these enzymes and identify signatures specific to these enzymes. These signatures will
enable us to develop inhibitors and diagnostic probes specific to lactamases. The existing
classification of beta-lactamases was developed nearly 30 years ago when few lactamases
were available. DLact database contain more than 2000 beta-lactamase, which can be
used to study the molecular diversity and to identify signatures specific to this family.
Method: A set of 2020 beta-lactamase proteins available in the DLact database
(http://59.160.102.202/DLact) were classified using graph-based clustering of Best Bi-
Directional Hits. Non-redundant (>90 percent identical) protein sequences from each
group were aligned using T-Coffee and annotated using information available in
literature. Motifs specific to each group were predicted using PRATT program.
Result: The graph-based classification of beta-lactamase proteins resulted in the
formation of six groups (Four major groups containing 191, 726, 774 and 73 proteins
while two minor groups containing 50 and 8 proteins). Based on the information
available in literature, we found that each of the four major groups correspond to the four
classes proposed by Ambler. The two minor groups were novel and do not contain
molecular signatures of beta-lactamase proteins reported in literature. The group-specific
motifs showed high sensitivity (>70%) and very high specificity (>90%). The motifs
from three groups (corresponding to class A, C and D) had a high level of conservation at
DNA as well as protein level whereas the motifs from the fourth group (corresponding to
class B) showed conservation at only protein level.
Conclusion: The graph-based classification of beta-lactamase proteins corresponds with
the classification proposed by Ambler, thus there is no need for formulating a new
classification. However, further characterization of two small groups may require
updating the existing classification scheme. Better sensitivity and specificity of groupspecific
motifs identified in this study, as compared to PROSITE motifs, and their
proximity to the active site indicates that these motifs represents group-specific signature
of beta-lactamases and can be further developed into diagnostics and therapeutics. - 中文關鍵字: --
- 英文關鍵字: --