Prioritizing drug targets in Clostridium botulinum with a computational systems biology approach.
A computational and in silico system level framework was developed to identify and prioritize the antibacterial drug targets in Clostridium botulinum (Clb), the causative agent of flaccid paralysis in humans that can be fatal in 5 to 10% of cases. This disease is difficult to control due to the emergence of drug-resistant pathogenic strains and the only available treatment antitoxin which can target the neurotoxin at the extracellular level and cannot reverse the paralysis. This study framework is based on comprehensive systems-scale analysis of genomic sequence homology and phylogenetic relationships among Clostridium, other infectious bacteria, host and human gut flora. First, the entire 2628-annotated genes of this bacterial genome were categorized into essential, non-essential and virulence genes. The results obtained showed that 39% of essential proteins that functionally interact with virulence proteins were identified, which could be a key to new interventions that may kill the bacteria and minimize the host damage caused by the virulence factors. Second, a comprehensive comparative COGs and blast sequence analysis of these proteins and host proteins to minimize the risks of side effects was carried out. This revealed that 47% of a set of C. botulinum proteins were evolutionary related with Homo sapiens proteins to sort out the non-human homologs. Third, orthology analysis with other infectious bacteria to assess broad-spectrum effects was executed and COGs were mostly found in Clostridia, Bacilli (Firmicutes), and in alpha and beta Proteobacteria. Fourth, a comparative phylogenetic analysis was performed with human microbiota to filter out drug targets that may also affect human gut flora. This reduced the list of candidate proteins down to 131. Finally, the role of these putative drug targets in clostridial biological pathways was studied while subcellular localization of these candidate proteins in bacterial cellular system exhibited that 68% of the proteins were located in the cytoplasm, out of which 6% was virulent. Finally, this framework may serve as a general computational strategy for future drug target identification in infectious diseases.
Department of Microbiology, Quaid-I-Azam University Islamabad, Pakistan; Indiana Center for Systems Biology and Personalized Medicine, Indiana University-Purdue University, Indianapolis, IN, USA. Electronic address: aunmuhammad78@yahoo.com.
Syed Aun
SA
Muhammad
Department of Microbiology, Quaid-I-Azam University Islamabad, Pakistan. Electronic address: safiamrl@yahoo.com.
Safia
S
Ahmed
Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, Pakistan. Electronic address: amjad_uni@yahoo.com.
Amjad
A
Ali
Indiana Center for Systems Biology and Personalized Medicine, Indiana University-Purdue University, Indianapolis, IN, USA. Electronic address: h.huang@medeolinx.com.
Hui
H
Huang
Indiana Center for Systems Biology and Personalized Medicine, Indiana University-Purdue University, Indianapolis, IN, USA. Electronic address: wu33@iupui.edu.
Xiaogang
X
Wu
Department of Microbiology and Immunology, Indiana University School of Medicine, Indianapolis, IN, USA. Electronic address: xfyang@iupui.edu.
X Frank
XF
Yang
Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, Pakistan. Electronic address: anam.naz88@live.com.
Anam
A
Naz
Indiana Center for Systems Biology and Personalized Medicine, Indiana University-Purdue University, Indianapolis, IN, USA; School of Informatics, Indiana University, Indianapolis, IN, USA; Department of Computer & Information Science, School of Science, Purdue University, Indianapolis, IN, USA. Electronic address: jakechen@iupui.edu.
Jake
J
Chen
D018528:ATP-Binding Cassette Transporters / Q000235:genetics / Q000378:metabolism; D000900:Anti-Bacterial Agents / Q000494:pharmacology*; D001426:Bacterial Proteins / Q000235:genetics / Q000378:metabolism; D003014:Clostridium botulinum / Q000187:drug effects / Q000235:genetics* / Q000472:pathogenicity; D019295:Computational Biology; D017124:Conserved Sequence; D005798:Genes, Bacterial; D020043:Genes, Essential; D015894:Genome, Human; D006801:Humans; D055442:Metabolome; D064307:Microbiota / Q000187:drug effects / Q000235:genetics; D010802:Phylogeny; D011485:Protein Binding; D020543:Proteome / Q000187:drug effects / Q000235:genetics* / Q000378:metabolism; D014774:Virulence / Q000235:genetics; D037521:Virulence Factors / Q000235:genetics / Q000378:metabolism
D018528:ATP-Binding Cassette Transporters; D000900:Anti-Bacterial Agents; D001426:Bacterial Proteins; D020543:Proteome; D037521:Virulence Factors
Clostridium botulinum; Drug targets prioritization; In silico analysis; Interactome