Biotechnological
Communication
Biosci. Biotech. Res. Comm. 9(1):
The unmasking of
Priya Pradhan1*, Rahul Shrivastava2 and Iftikhar Aslam Tayubi3
1School of Biotechnology, Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, Madhya Pradesh, India
2Department of Biological Sciences & Engineering, Maulana Azad National Institute of Technology, Bhopal, Madhya Pradesh, India
3Faculty of Computing and Information Technology, King Abdulaziz University, Rabigh, Kingdom of Saudi Arabia
ABSTRACT
Coronaviruses such as
KEY WORDS: DRUGS; IMMUNITY; METABOLIC; SWITCH; VACCINES
INTRODUCTION
Severe acute respiratory
ARTICLE INFORMATION:
*Corresponding Author:
Received 12th Feb, 2016
Accepted after revision 22nd March, 2016 BBRC Print ISSN:
Online ISSN:
Thomson Reuters ISI SCI Indexed Journal NAAS Journal Score : 3.48
©A Society of Science and Nature Publication, 2016. All rights reserved.
Online Contents Available at: http//www.bbrc.in/
a sequence of deadly pneumonia cases emerged in Hong Kong (Drosten et al., 2003, Rota et al., 2003).
55
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alveolar damage (Nicholls et al., 2003,
Another challenge for the inactivated
In mice, the inactive whole virus vaccines without or with combination (alum adjuvant) provided frac- tional protection, but this was accompanying the severe eosinophilic lung pathology (Bolles et al., 2011, Tseng et al., 2012,
As far molecular level is considered, it is a well- known fact thatwidespread study on RNA in contem- porary times has stemmed into discovering a category
of genetic regulatory element which is found in variety of organisms that too undergoing different folding and functional process leading to modification of gene and alteration in its expression, these regulatory elements are termed as riboswitch like elements (RLE) (Pradhan P et al., 2015). These elements are present have been acknowledged in the genomes of plants, archaea and fungi and are highly structured elements positioned in the 5’
This term “riboswitch” was coined by Dr. Ronald Breaker in the year 2002 when he reported that mRNA- encoding enzymes involved in vitamin B1 and B12 biosyn- thesis in E. coli could bind associated metabolites without the helper proteins being involved and they are RNA based components that can integrate ligand binding and gene regulation so as to dynamically respond to the molecular signals within cells (Winkler et al., 2002). These control several metabolic pathways counting the biosynthesis of vitamins and the breakdown of methionine, lysine and purines, comprising transcription cessation i.e. the termi- nation process and initiation of translation (Eddy, 2001).A complex network of diverse inter metabolic pathways allowsthe organisms to consume nutrients from their sur- roundings to adapt to the environmental changes. Most of the
These riboswitches act similar to the “ON” and “OFF” mechanism of a switch, which could regulate the metab- olism of the organism in a desired manner. Riboswitches are structurally divided in two parts:
i)A sensor domain known as an aptamer which directly binds the small molecules and is evolutionary conserved domain in the UTR of an organism.
ii)An expression platform thatgo throughits structural var- iations in response to the alterations sensed in, by the aptamer (Mandal and Breaker, 2004).
Riboswitches have a particulararray of ligand bind- ing and its aptamer act in a way that the production of the metabolite generally proteins, gets terminated by
FIGURE 1: Riboswitches and their sensing capa- bilities (Barrick and Breaker, 2007, Regulski
et al., 2008, Spinelli et al., 2008, Sudarsan et al., 2008, Henkin, 2009, Nechooshtan et al., 2009)
taxonomically and regulatory molecular mechanisms it has triggered a focus that these switches represent the oldest regulatory systems (Blouin et al., 2009) among the organisms shown in figure 1.
Bacterial riboswitches devicevarious biological pro- cesses at numerousgoverning levels, such as transcrip- tion and translation (Waters and Storz, 2009). Collins et al., 2007 in their previous study had discussed that the glmS riboswitch perform its
Thus, the folding of
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of different processes; the most characteristic situation is the standard attenuation mechanism (Vitreschak et al., 2004).
EXPERIMENTAL ANALYSIS
For the first time,riboswitch mechanism was decisive- lyverified in a natural metabolic system in the year 2002 (Breaker, 2012). Ellington and Szostak stated an in vitro protocol that was dealing with the isolation of RNA aptamers which could bind to specific dyes, in 1990. The remarkable aspect about these studies is the creation of an RNA aptamer that did not necessitate a
KINETIC CONTROL OF RIBOSWITCHES
Riboswitches can reversibly switch back and forth between an ‘ON’ and ‘OFF’ state, depending upon the concentration of the ligand that triggered the active site. When the aptitude to repress or activate the gene expression is dictated by its characteristic affinity for the ligand, a riboswitch like element is said to be ther- modynamically regulated. In contrast, functional studies of a riboswitches have exposed that they entail a much higher ligand concentration to be activated, and in turn altering the level of gene expression of the organism. Evidently because riboswitches do not reach equilib- rium with the ligand, the analogy is more like that of a fuse than a switch termed as “ribofuse” (Mehta and Balaji, 2010).In an in vitro study it has been discussed that riboswitch includes mRNA transcripts that can sense the concentration of metabolites over binding the target compound and then regulating the expression of the genes related with the metabolites responding to the concentration of metabolite [42]. Even though ample of riboswitch associated study has captivated on the significant capacity of various aptamer domains so as to adopt the complex structures of biological metabo- lites that are essential to bind with high affinity and specificity(Wickiser, 2009).
MATERIAL AND METHODS
The proposed framework for in silico prediction and identification of riboswitches, their ligands and its
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inhibitors are given below and also have been shown in figure 2.
1.Identification of riboswitch like gene sequence
2.Riboswitch like gene sequence similarity search- between the desired organism’s nucleotide se- quence and human nucleotide sequence (BLAST)
3.Transcription (online) to corresponding Ribo- switch like Element (RLE)
4.3D and 2D Prediction of RLE structure
5.Molecular Docking- Blind Docking (BD)
6.Molecular Docking- Focused Docking (FD) for the identification of ligand binding sites
7.Enhancement of docking results
8.Virtual screening using NCI diversity set by Rac-
9.Assessment of
10.Prediction of ADME, toxicity and hydrophobicity of lead compounds
METHODOLOGY
1. Identification of riboswitch like gene sequence
The whole genome of Human coronavirus OC43 was acquired from the National Center for Biotechnology Information (NCBI) Gene Bank in FASTA format(Vijgen et al., 2005, Vijgen et al., 2015). The viral genome was searched for desired sequences present in its UTR by an online tool Riboswitch Explorer (RibEx) to iden- tify the desired sequence termed as Riboswitch like
2.Riboswitch like gene sequence similarity search between the desired organism’s nucleotide sequence and human nucleotide sequence (BLAST)
BLAST utilized for the sequence similarity search. This tool let the user to know about the percentage of simi- larity between sequences. Sequences having more than
3.Transcription (online) to corresponding Riboswitch Like Element (RLE)
Gene sequencesacknowledged by tool RibEx are tran- scripted to its parallel riboswitch by using the online “Transcription and Translation Tool” (Transcription and Translation Tool, 2015).
4. 3D and 2D Prediction of RLE structure
Three dimensional(3D) structure of the RLE was antic- ipated by using an online program RNA fold (2D) (Vienna, 2015)and RNA Composer (2D to 3D)(Popenda et al., 2012). RNA Composer system offered a new user- friendly approach to fully automated prediction RNA 3D structures. This method was based on the machine translation principle and operated on the RNA FRABASE database acting as the dictionary, relating the RNA secondary structure and tertiary structure elements of riboswitch present in the complete genome of H. coro- navirus OC43.
5. Molecular Docking- Blind Docking (BD)
In the present study, AutoDock based BDwasconducted to explorean apt binding site present in the predicted
FIGURE 2: Flow chart of framework
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Table 1: The coordinates of grid box for the Blind Docking (BD)
riboswitch like element of Human coronavirus OC43. In modus operandi of blind docking(VLifeMDS, 2011) whole structure of riboswitch is roofedunderneaththe virtual three dimensional grid box for the processing of docking. Coordinates of the grid box has been shown in Table 1. Altogetherthe computational studies were con- ceded out by means of AutoDock version 4.2 installed on a single machine whose configurationis 2.80 GHz Intel core2 duo processor using 3 GB Random Access Memory (RAM) and 320 GB hard disk alongwith Win- dows XP as an operating system.Docking software’s like “AutoDock”, “Autogrid” and “AutoDock version 4.2” were downloaded from the Scripps gateway. AutoDock software explored the entire surface of the 3D structure of riboswitch for binding of ligand in the cavities i.e. binding sites(Goodsell et al., 1996).
Alanine(ALA)was utilized as the ligand in blind docking technique so as to identify the binding sites present in the predicted riboswitch, as it is considered as the neutral and simplest ligand out of all the amino acids as a substrate for riboswitch like sequence.Par- ticular binding sites existing in/on the surface of the predicted riboswitch like structurewereacknowledged on the foundation of lowest binding energy
6.Focused Docking (FD) for the identification of ligand binding sites
Focused grid box casing ligand as well as binding resi- dues involved in binding of ligand, wasarranged, pre- cisely targeting specific ligand binding site for the recog- nized riboswitch of Humancoronavirus OC43 (Goodsell et al., 1996, Vijgen et al., 2015).
The X,Y and Z coordinates encompassing the data about the dimensionsof grid box in focused docking of anticipated Human coronavirus OC43 riboswitch has beentabularized in Table 2, these grid dimensions are further exploited for focused docking with different amino acids for the identification of specific receptor/ substrate ligand interaction for the predicted riboswitch.
7. Enhancement of docking results
Subsequently, identifying a suitable ligand for the pre- dicted riboswitch of Human coronavirus OC43 by the molecular modeling technique i.e. focused docking was accomplished. Distinct docking of the identified sub- strate ligand with its corresponding riboswitch,was done for the riboswitch identified in the genome of organism Humancoronavirus OC43 repetitively for a
8.Virtual screening using NCI diversity set by Rac-
The identified binding sites present in predicted struc- ture of novel Human coronavirus OC43 riboswitchis exploited for the virtual screening viaNCI Diversity Set containing diversity of drug molecules (Bikádi et al., 2006). Essential files for the process of virtual screening wereprimed by the online software Raccoon (Forli, 2010).
Raccoon has been used as a graphical user inter- face for AutoDock virtual screening. It can split multi- ple molecule ligand library files, convert them into the AutoDock format (i.e. *.pdbqt), and filter them by using common criteria (e.g., Lipinski’s rule of five, fragment- like “rule of three” and
Molecular docking simulation constructed virtual screening of Human coronavirus OC43 riboswitch was
Table 2: The coordinates of grid box for the Focused Docking (FD)
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Table 3: The coordinates of grid box for the virtual screening
done using similar docking and grid parameters used in focused docking earlier. The coordinates of the grid box used in the virtual screening process of molecular librar- ies downloaded from ZINC database(Irwin and Shoichet, 2005) against the binding site of riboswitch (Human coronavirus OC43, SEQ1) has been tabulated in Table 3.
9.Assessment of
Using zinc database, the best five marked off ligands for the riboswitch identified were evaluated for signifi- cant physicochemical properties such as xlog P,
10.Prediction of ADME, toxicity and hydrophobicity of lead compounds
The top 5 lead molecules for Human coronavirus OC43 riboswitchweregauged using PreADMET online program(Kwang, 2005) for the check of toxicity and ADME properties (Hetényi and van der Spoel, 2002). This program device the presence of major toxicities such as mutagenicity, irritant effect, reproductive effects, etc. in the principle molecules on the basis of functional group present in their chemical conformation. PREADMET also calculates
pute and envisage the hydrophobic/hydrophilic proper- ties between them (Pyrkov et al., 2009).
RESULTS AND DISCUSSION
The stepwise results obtained are summarized and dis- cussed below:
1.Exploration of the genome assembly for identifica- tion of riboswitch like sequence:
The following sequence was identified for transcription into riboswitch like elements present in the viral DNA of Human coronavirus OC43 causing Severe Acute Res- piratory Syndrome.
2.Sequence similarity with human genome: BLAST Score
The identified riboswitch like sequence of H. corona- virus OC43 had shownfollowing results on NCBI data- base search for gene sequence similarity present in the genome of Homo sapiens.
This gene sequence from Human coronavirus OC43 hav- ing the identified riboswitch had shown a BLAST score
77.8with a maximum 100% of gene sequence similar- ity with Bovine coronavirus strain. The BLAST result of human gene sequence similarity to SEQ1 gene sequence is shown in figure 4, depicting no gene sequence simi- larity.
Thus, human genome does not have any similarity with the Human coronavirus OC43 directing towards
3. Transcription of gene sequence to RLE
Sequence after transcription:
FIGURE 3: Riboswitch like sequence
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FIGURE 4: BLAST between Human coronavirus and Homo sapiens
The acknowledged gene sequencewas transcripted to its corresponding riboswitch like elements using “Tran- scription and Translation Tool”. This tool interchanges the thymine (T) with the nucleotide uracil (U) to form its equivalent riboswitch.
4. Predicted tertiary structures of riboswitch
Tertiary structure of the identified riboswitch in Human coronavirus OC43 were predicted by online program RNAfold(2D)(Vienna, 2015)and RNAcomposer (2Dto 3D) (Popenda et al., 2012), SEQ1 riboswitch consists of a sin- gle chain of 39 nucleotides. The predicted secondary and tertiary structure of SEQ1 riboswitch in H. coronavirus OC43 has been shown belowin Figure 5a (2D) and 5b (3D).
5. Blind and Focused Docking results
Binding site present in H. coronavirus riboswitch SEQ1 identified by FD with LYS suggested that there are some residues ingene sequence that are involved and are capable in ligand binding.Docking results obtained by BD of the riboswitch i.e. SEQ1 has been tabulated in Table 4.The results of FD of SEQ1 using the identified binding residues intricate in the binding of the ligand to the predicted riboswitch advocated that the amino acid lysine (LYS) as its substrate ligand had displayed the
superlative binding amongstthe 20 amino acids with the Binding Energy (BE) value as
Further, to enhance the rate of affinity, the results of individual docking of riboswitch SEQ1 with LYS for a repeated number of timeswas conducted to enhance the affinity of receptor and ligand for which the result has been shown in Table 6.
6. Virtual Screening results
The 5 lead/principle molecules were selected after virtual screening against predicted Human coronavirus OC43 riboswitch of SEQ1. The BE and Ki value of 5 principle molecules for the H. coronavirus OC43 riboswitch has beentabulated in Table 7.
The following five lead molecules were obtained for SEQ1 riboswitch after the virtual screening; these were obtained from ZINC database: ZINC02418906 (A), ZINC02418945 (B), ZINC03838665 (C), ZINC02418909 (D)and ZINC11322328 (E).
7.
The
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FIGURE 5A: 2 dimensional structure
FIGURE 5B: 3 dimensional structure
8. ADME
The results of
9. Hydrophobicity/Hydrophilicity
PLATINUM program was used for the detection of hydrophobicity/hydrophilicity of the ligands. Most of the ligands were found to be hydrophilic in nature. The interactions between the ligands and other molecules are principally electrostatic in nature as these objects
Table 4: Blind docking results
Table 5: Focused docking results for SEQ1
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FIGURE 6: Biinding sites (A29, A30) predicted after focused docking by
PyMol
FIGURE 7:
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Table 6: Enhanced docking results
shows polarity. Hydrophilic interaction is in force not only in solvating ions, but also in stabilizing DNA, pro- teins, etc. As per the tutorial of PLATINUM program, an hydrogen bond has been assigned a value ranging from
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CONCLUSION
We have been able to accomplish in silico prediction and identification of the riboswitch for Human coronavirus OC43 straincausing Severe Acute Respiratory Syndrome (SARS). This approach has given supplementary infor- mation about the peculiar binding sites and ligands for the strain of H. coronavirus OC43. After the comprehen- sive analysis of molecular docking study this prediction approach has drawn our focus that the complete genome of Human coronavirus OC43 is having elements that might act as switches for the “ON” and “OFF” mecha- nisms of metabolic pathway involved in the detrimental viral activities of an organism. The stretch of sequence (RLE) obtained after the analysis has paved the way
for the
Table 11: Hydrophobicity results
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pathway of humans and their metabolic activities, if the organism is targeted inside their body. These inhibitors anticipated are free from the side effects of the antiviral drugs and have distant chances of emerging resistance in humans. Furthermore,targeting nucleocapsid pro- tein has also proven its authenticity after the similarity search via BLAST since the predicted sequence has its root in Bovine coronavirus also, that has been acting as the major causing agent to the members of subfamily Bovinae. This subfamily is having a diversified group of 10 genera that are the victims of this organism and are prone to respiratory and enteric infections.Hence, the study directs towards the prediction of novel drug targets that might aid in the treatment of Severe Acute Respiratory Syndrome and also Bovine Respiratory Dis- ease Complex.
FUTURE PROSPECTS
Further, aptamers and the RNA structures can be gener- ated by in vitro selection to interact with small mol- ecules for the expression and binding of a wide range of ligands (Famulok, 1999, Hermann and Patel, 2000).
Moreover, riboswitches can also be worked on in vivo experiments as an artificial regulatory construct that involves an aptamer structure leading to the addition of the
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