In Silico Characterization of Fatty Acid Synthase of Mycobacterium tuberculosis H37Rv
C Kumar, C Anuradha, K Rao, K Venkateswara Swamy
Keywords
blast, drug design, fatty acid synthase, mycobacterium tuberculosis, tuberculosis
Citation
C Kumar, C Anuradha, K Rao, K Venkateswara Swamy. In Silico Characterization of Fatty Acid Synthase of Mycobacterium tuberculosis H37Rv. The Internet Journal of Genomics and Proteomics. 2005 Volume 2 Number 1.
Abstract
A study was carried out to characterize fatty acid synthase (FAS) protein of
Introduction
It is well known fact that Tuberculosis (TB) is a leading infectious disease responsible for death and represents more than a quarter of the world's preventable deaths (Cole
From these studies it has been inferred that there is not much information available on characterization of FAS protein sequence of
Methodology
Sequence analysis of FAS
Functional Characterization of FAS
Functional characterization of FAS protein sequence was done by submitting the amino acid sequence of FAS protein to Prosite (http://au.expasy.org/prosite/) and InterProscan (http://www.ebi.ac.uk/InterProScan/). InterProscan is a searchable database providing information on sequence function as well as annotation and further, these sequences are grouped based on protein signatures (Apweiler,
Secondary and 3D structure of FAS complex
The secondary structure of FAS protein was obtained from Jpred (http://www.compbio.dundee.ac.uk/~www-jpred/) by submitting the sequence which predicts secondary structure using a neural network called Jnet (Cuff and Barton, 2000). The secondary structure prediction is the definition of each residue into either alpha helix, beta sheet or random coil secondary structures. Analysis of IinterProscan results suggest that FAS protein as comprising of 3 different subunits such as B_ketoacyl synthase, Acyl transferase, MaoC-like dehydratase. Hence to generate 3D structures of functional domains of FAS protein, the amino acid sequence of each subunit of FAS protein (as suggested by InterProscan results) was submitted to 3DPSSM server (http://www.sbg.bio.ic.ac.uk/~3dpssm/), which is a automatic fold recognition server for predicting the 3D structure (Lawrence Kelley,
Results
The amino acid sequence of FAS protein was retrieved from NCBI and blast-P program was used to find out the sequences that shared structure and sequence similarity against PDB database (Table 1). The result suggest that protein sequence with PDB ID of IJ3N A, which belongs to 3-Oxoacyl- (Acyl-Carrier Protein) Synthase II of
Further, FAS protein was subjected to ClustalW for multiple sequence alignment and phylogram analysis. The result suggests that FAS protein of
The function of FAS protein of
(i)
(ii)
There are numerous ATP- or GTP-binding proteins in which the P-loop is found. We list below a number of protein families for which the relevance of the presence of such motif has been noted:
- ATP synthase alpha and beta subunits, Myosin heavy chains, Kinesis heavy chains and kinesin-like proteins, Dynamins and dynamic-like protein, Guanylate kinase, Thymidine kinase, Thymidylate kinase, Shikimate kinase, Nitrogenase iron protein family, ATP-binding proteins involved in 'active transport' (ABC transporters), DNA and RNA helicases, GTP-binding elongation factors (EF-Tu, EF-1alpha, EF-G, EF- 2, etc.), Ras family of GTP-binding proteins (Ras, Rho, Rab, Rally, Ypt1, SEC4, etc.), Nuclear protein ran, ADP-ribosylation factors family, Bacterial dnaA protein, Bacterial recA protein, Bacterial recF protein, Guanine nucleotide-binding proteins alpha subunits (Gi, Gs, Gt, G0, etc.), DNA mismatch repair proteins mutS family, Bacterial type II secretion system protein E.
(iii)
CCATT-box and enhancer binding protein (C/EBP), cAMP response element (CRE) binding proteins (CREB, CRE-BP1, ATFs), Jun/AP1 family of transcription factors, yeast general control protein GCN4, fos oncogene, and the fos-related proteins fra-1 and fos B, C-myc, L-myc and N-myc oncogenes, octamer-binding transcription factor 2 (Oct-2/OTF-2).
(iv)
Beta-ketoacyl-ACP synthase (KAS) is the enzyme that catalyzes the condensation of malonyl-ACP with the growing fatty acid chain.
It is found as a component of the following enzymatic systems:
Fatty acid synthetase (FAS), The multifunctional 6-methysalicylic acid synthase (MSAS) from Penicillium patulum, Polyketide antibiotic synthase enzyme systems,
(v)
Jpred program that was used to predict secondary structures in
Based on the presence of domains in FAS protein of
Figure 5
In case of beta keto acyl synthase, 3D PSSM was able to predict that these proteins belonged to alpha and beta class of proteins, (Figure 3 B) fold, family and superfamily were related to thiolase like, thiolase related and thiolase like respectively and the protein name was assigned as beta-keto-acyl ACP synthase II (No. of helices-8; No. of strands-4; No. of turns-12).
Figure 6
The structure of MaoC dehydratase (Figure 3 C) that was predicted by 3DPSSM server was able to assign lyase fold followed by assigning enoyl-coA hydratase superfamily and hydratase protein to MaoC dehydratase sequence (No. of helices-4; No. of strands-9; No. of turns-10).
Figure 7
Discussion
TB, which is killing more people than any other infectious disease, was declared as global emergency by the World Health Organization (Kremer and Besra, 2002). About 32 % or 1.86 billion of the world populations are infected with TB. Every year approximately 8 million people develop active TB and almost 2 million of these people die from this disease (Dye
Combining sequence information with 3D structure gives invaluable insights for the development of effective rational strategies for experiments such as site directed mutagenesis, studies of disease related mutations, or the structure based design of specific inhibitors. Techniques for experimental structure solution have made great progress in recent years. However, experimental structure determination is still a time-consuming process without guaranteed success. No experimental structural information is available for the vast majority of protein sequences hence theoretical methods for proteins structure prediction aiming to bridge this structure knowledge gap have gained much interest in recent years. Knowledge based approaches, combined with the current explosion in sequence and structure data, may move us to a new prospective paradigm in which it may be possible to discover a suitable drug against a given target long before any application is known. Combined with advances in single-nucleotide polymorphism detection, this may take possible individualized medicines in which each patient gets a drug designed against his or her particular form of the target (Pfost, 2000). As we move toward a situation where drug discovery projects are bathed in structural and sequence information, it is the role of the structural bioinformatician to integrate this wealth of data accelerating drug discovery. New drugs are urgently needed to reduce the potential impact of the emergence of multidrug-resistant strains of the causative agent
Correspondence to
Chitta Suresh Kumar, Ph.D
Associate Professor
Center for Bioinformatics
Department of Biochemistry
Sri Krishnadevaraya University
ANANTAPUR-515 003, A.P.
India.