Making novel proteins from pseudogenes.

MOTIVATION: Recently, we made synthetic proteins from non-coding DNA of Escherichia coli. Encouraged by this, we asked: can we artificially express pseudogenes into novel and functional proteins? What kind of structures would be generated? Would these proteins be stable? How would the organism respond to the artificial reactivation of pseudogenes? RESULTS: To answer these questions, we studied 16 full-length protein equivalents of pseudogenes. The sequence-based predictions indicated interesting molecular and cellular functional roles for pseudogene-derived proteins. Most of the proteins were predicted to be involved in the amino acid biosynthesis, energy metabolism, purines and pyrimidine biosynthesis, central intermediary metabolism, transport and binding. Interestingly, many of the pseudogene-derived proteins were predicted to be enzymes. Furthermore, proteins showed strong evidence of stable tertiary structures. The prediction scores for structure, function and stability were found to be favorable in most of the cases. IMPACT: To our best knowledge, this is the first such report that predicts the possibility of making functional and stable proteins from pseudogenes. In future, it would be interesting to experimentally synthesize and validate these predictions.

Computational Prediction of Potential Vaccine Candidates From tRNA Encoded peptides (tREP) Using a Bioinformatic Workflow and Molecular Dynamics Validations.

Transfer RNAs (tRNA) are non-coding RNAs. Encouraged by biological applications discovered for peptides derived from other non-coding genomic regions, we explore the possibility of deriving epitope-based vaccines from tRNA encoded peptides (tREP) in this study. Epitope-based vaccines have been identified as an effective strategy to mitigate safety and specificity concerns observed in vaccine development. In this study, we explore the potential of tREP as a source for epitope-based vaccines for virus pathogens. We present a computational workflow that uses verified data sources and community-validated predictive tools to produce a ranked list of plausible epitope-based vaccines starting from tRNA sequences. The top epitope, bound to the predicted HLA molecule, for the virus pathogen is computationally validated through 200 ns molecular dynamics (MD) simulations followed by binding free energy calculations. The simulation results indicate that two tRNA encoded epitope-based vaccines, RRHIDIVV and IMVRFSAE for Mamastrovirus 3 and Norovirus GII, respectively, are likely candidates. Peptides originating from tRNAs provide unexplored opportunities for vaccine design. Encouraged by our previous experimental study, which established the inhibitory properties of tREPs against infectious parasites, we have proposed a computationally validated set of peptides derived from tREPs as vaccines for viral pathogens.

Looking for a sequence based allostery definition: a statistical journey at different resolution scales.

The aim of this work was to detect allosteric hotspots signatures characterizing protein regions acting as the 'key drivers' of global allosteric conformational change. We computationally estimated the relative strength of intra-molecular interaction in allosteric proteins between two putative allostery-susceptible sites using a co-evolution model based upon the optimization of the cross-correlation in terms of free-energy-transfer hydrophobicity scale (Tanford scale) distribution along the chain. Cross-Recurrence Quantification Analysis (Cross-RQA) applied on the sequences of allostery susceptible sites showed evidence of strong interaction amongst allosteric susceptible sites. This could be due to transient weak molecular bonds between allostery susceptible patches enabling regions far-apart to come together. Further, using a large protein dataset, by comparing allosteric protein set with a randomly generated sequence population as well as a generic protein set, we reconfirmed our earlier findings that hydrophobicity patterning (as formalized by Recurrence Quantification Analysis (RQA) descriptors) may serve as determinant of allostery and its relevance in the transmission of allosteric conformational change. We applied RQA to free-energy-transfer hydrophobicity-transformed amino acid sequences of the allostery dataset to extract allostery specific global sequence features. These free-energy-transfer hydrophobicity-based RQA markers proved to be representative of allosteric signatures and not related to the differences between randomly generated and real proteins. These free-energy-transfer hydrophobicity-based RQA markers when evaluated by pattern recognition tools could distinguish allosteric proteins with 92% accuracy.

Highly potent anti-malarial activity of benzopyrano(4,3-b)benzopyran derivatives and in silico interaction analysis with putative target Plasmodium falciparum lactate dehydrogenase.

Malaria infection caused by Plasmodium falciparum is majorly responsible for millions of deaths in humans every year. Moreover, a rapid increase in resistance to existing drugs has posed an urgent need for new anti-malarials. Herein, we report the highly potent anti-malarial activity of benzopyrano(4,3-b)benzopyran derivatives, inspired from naturally occurring dependensin against chloroquine (CQ) sensitive and resistant P. falciparum strains. Chemically synthesized, four dependensin analogs 85(A-D) exhibited growth inhibition at nanomolar concentrations ranging from 63.96 to 725.8 nM by blocking the parasite development at the ring and early trophozoite stages. The growth inhibitory activity of dependensin analogs was correlated with their anti-plasmodial lactate dehydrogenase activity by computational analysis. Molecular docking, 50 ns simulation and a 2D-Quantitative Structure-Activity Relationship (2D-QSAR) modelling revealed the interaction with their putative target P. falciparum lactate dehydrogenase (PfLDH). Here, developing the predictive 2D descriptors such as thermodynamic, spatial, electronic, and topological with multiple linear regression analysis (MLRA), the structural requirements for potent and selective PfLDH inhibitory activity has been identified. The strong binding of compound 85D to the catalytic Nicotinamide adenine dinucleotide (NADH) binding pocket of the PfLDH further supported the PfLDH targeting potential of dependensin analogs. Overall, this study revealed a highly potent anti-malarial activity of benzopyrano(4,3-b)benzopyran derivatives with their putative anti-PfLDH activity.Communicated by Ramaswamy H. Sarma.

Building Biofoundry India: challenges and path forward.

Biofoundry is a place where biomanufacturing meets automation. The highly modular structure of a biofoundry helps accelerate the design-build-test-learn workflow to deliver products fast and in a streamlined fashion. In this perspective, we describe our efforts to build Biofoundry India, where we see the facility add a substantial value in supporting research, innovation and entrepreneurship. We describe three key areas of our focus, harnessing the potential of non-expressing parts of the sequenced genomes, using deep learning in pathway reconstruction and synthesising enzymes and metabolites. Toward the end, we describe specific challenges in building such facility in India and the path to mitigate some of those working with the other biofoundries worldwide.

Association of miR-760 with cancer: An overview.

MicroRNAs (miRNAs) are small non-coding RNA molecules of around 22 nucleotides in length. They are crucially involved in the post transcriptional regulation and thus play a significant role in the modulation of different diseases. Several studies have suggested that miRNA expression is dysregulated in various cancers through different mechanisms and the dysregulated miRNA in return affects different cancer hallmarks including cell proliferation, cell death suppression, metastasis and angiogenesis. Compilation of the available miRNA data can be a stimulator for proper understanding of the correlation between the miRNA expression and cancer progression. In this review, we have focussed on the role of miR-760 in the progression of different cancer. MicroRNA-760 (miR-760) has been found to be down regulated in various cancers, thus it can be utilized as a possible prognostic marker for cancer detection. Here, we have tried to fill a gap regarding the role of miR-760 in relation to cervical cancer also. Moreover, unravelling the role of miR-760 in different cancers will enlighten the researchers with proper understanding of biology of miR-760 in regulation of different cancers.

Amino-acid residue association models for large scale protein-protein interaction prediction.

UNLABELLED: The computational prediction of protein-protein interactions (PPI) is an essential complement to direct experimental evidence. Traditional approaches rely on less available or computationally predicted surface properties, show database-specific performances and are computationally expensive for large-scale datasets. Several sensitivity and specificity issues remain. Here, we report a novel method based on 'Amino-acid Residue Associations' (ARA) among interacting proteins which utilizes the accurate and easily available primary sequence. Large scale PPI datasets for six model species (from E. coli to human) were studied. The ARA method shows up to 73%sensitivity and 78% specificity. Furthermore, the method performs remarkably well in terms of stability and generalizability. The performance of ARA method benchmarked against existing prediction techniques shows performance improvement upto 25%. Ability of ARA method to predict PPI across species and across databases is also demonstrated. Overall, the ARA method provides a significant improvement over existing ones in correctly identifying large scale protein-protein interactions,irrespective of the data resource, network size or organism. AVAILABILITY: The MATLAB code for ARA approach will be made available upon request.

HYPO: A Database of Human Hypothetical Proteins.

BACKGROUND: There are genes whose function remains obscure as they may not have similarities to known regions in the genome. Such known 'unknown' genes constituting the Open Reading Frames (ORF) that remain in the epigenome are termed as orphan genes and the proteins encoded by them but having no experimental evidence of translation are termed as 'Hypothetical Proteins' (HPs). OBJECTIVES: We have enhanced our former database of Hypothetical Proteins (HP) in human (HypoDB) with added annotation, application programming interfaces and descriptive features. The database hosts 1000+ manually curated records of the known 'unknown' regions in the human genome. The new updated version of HypoDB with functionalities (Blast, Match) is freely accessible at http://www.bioclues.org/hypo2. METHODS: The total collection of HPs were checked using experimentally validated sets (from Swiss-Prot) or non-experimentally validated set (TrEMBL) or the complete set (UniProtKB). The database was designed with java at the core backend, integrated with databases, viz. EMBL, PIR, HPRD and those including descriptors for structural databases, interaction and association databases. RESULTS: The HypoDB constituted Application Programming Interfaces (API) for implicitly searching resources linking them to other databases like NCBI Link-out in addition to multiple search capabilities along with advanced searches using integrated bio-tools, viz. Match and BLAST were incorporated. CONCLUSION: The HypoDB is perhaps the only open-source HP database with a range of tools for common bioinformatics retrievals and serves as a standby reference to researchers who are interested in finding candidate sequences for their potential experimental work.

The next step in biology: a periodic table?

Systems biology is an approach to explain the behaviour of a system in relation to its individual components. Synthetic biology uses key hierarchical and modular concepts of systems biology to engineer novel biological systems. In my opinion the next step in biology is to use molecule-to-phenotype data using these approaches and integrate them in the form a periodic table. A periodic table in biology would provide chassis to classify, systematize and compare diversity of component properties vis-a-vis system behaviour. Using periodic table it could be possible to compute higher- level interactions from component properties. This paper examines the concept of building a bio-periodic table using protein fold as the fundamental unit.

Computational study of 'HUB' microRNA in human cardiac diseases.

MicroRNAs (miRNAs) are small non-coding RNAs ~22 nucleotides long that do not encode for proteins but have been reported to influence gene expression in normal and abnormal health conditions. Though a large body of scientific literature on miRNAs exists, their network level profile linking molecules with their corresponding phenotypes, is less explored. Here, we studied a network of 191 human miRNAs reported to play a role in 30 human cardiac diseases. Our aim was to study miRNA network properties like hubness and preferred associations, using data mining, network graph theory and statistical analysis. A total of 16 miRNAs were found to have a disease node connectivity of >5 edges (i.e., they were linked to more than 5 diseases) and were considered hubs in the miRNAcardiac disease network. Alternatively, when diseases were considered as hubs, >10 of miRNAs showed up on each 'disease hub node'. Of all the miRNAs associated with diseases, 19 miRNAs (19/24= 79.1% of upregulated events) were found to be upregulated in atherosclerosis. The data suggest micro RNAs as early stage biological markers in cardiac conditions with potential towards microRNA based therapeutics.

Deciphering the role of microRNA - A step by step guide.

MicroRNAs (miRNAs), are small non-coding RNAs of approximately 22 nucleotides in length, playing an important role in regulating gene expression post-transcriptionally. Understanding the effect of miRNA regulation in a pathway-specific manner unravels the approaches adopted to apprehend biological mechanisms, the information, which is scanty for researchers, not primed already for miR related research. Here, we describe a quick perspective in 5 steps with probable approaches and assays at every level to unravel the specific role of a microRNA, miR-145a-5p, as an example. This perspective as a guide would help in identifying novel targets for a microRNA, as shown for miR-145a-5p, which down-regulated the mRNA expression of ADD3 and BRCA2, using bioinformatic tools and experimental assays.

Metabolic pathways variability and sequence/networks comparisons.

BACKGROUND: In this work a simple method for the computation of relative similarities between homologous metabolic network modules is presented. The method is similar to classical sequence alignment and allows for the generation of phenotypic trees amenable to be compared with correspondent sequence based trees. The procedure can be applied to both single metabolic modules and whole metabolic network data without the need of any specific assumption. RESULTS: We demonstrate both the ability of the proposed method to build reliable biological classification of a set of microorganisms and the strong correlation between the metabolic network wiring and involved enzymes sequence space. CONCLUSION: The method represents a valuable tool for the investigation of genotype/phenotype correlations allowing for a direct comparison of different species as for their metabolic machinery. In addition the detection of enzymes whose sequence space is maximally correlated with the metabolic network space gives an indication of the most crucial (on an evolutionary viewpoint) steps of the metabolic process.

Transient block of receptor may be a mechanism controlling unidirectional propagation of signaling.

In tissue development, juxtacrine signaling often propagates across cells, carrying and delivering temporal and spatial information for cells to make correct patterning. Observed complex and accurate tissue patterning indicates that signaling propagation via ligand-receptor interactions is precisely controlled. It is important and interesting to reveal the possible control mechanisms. The directionality of signaling in cells, which is a common issue for all intercellular signaling pathways, is a critical aspect. To understand the propagation of Notch signaling in presomitic mesoderm cells in the mouse, a novel method is used to build a multicellular model to simulate Notch signaling. Simulation reveals that the transient block of Notch by Notch induced Lfng and the delayed removal of the block by another Notch induced protein Hes7 may explain the observed unidirectional propagation of Notch signaling in these cells. Both mutation in and overexpression of lfng cause the same signaling profile in the tissue, due to the inappropriate timing of Notch signaling block by Lfng. The reverse Notch/Delta signaling quickly develops into reciprocating signaling among cells, causing irregular expression of cyclic genes. Irregular Notch signaling in cells would change their response to the positional information provided by the Fgf8 gradient, resulting in disordered and irregular somite segmentation. As Notch signaling is highly conserved, we hypothesize that the mechanism of controlling unidirectional propagation of signaling in cells by transient receptor block may exist in other tissues and in other vertebrates. Our simulation results also suggest that segmentation clock and unidirectional propagation may be inherently coupled in Notch signaling.

Bone and the kidney: a systems biology approach to the molecular mechanisms of renal osteodystrophy.

Despite its apparent static condition, the skeleton undergoes a permanent process of remodeling mediated by osteoblasts and osteoclasts. The activity of these cells is regulated by a plethora of factors, ranging from mechanical stress to the effects of hormones to the immune system. One well-studied regulatory system involves the maintenance of calcium homeostasis through a network whose main regulatory components include ionized calcium, phosphate, parathyroid hormone and active vitamin D. This system establishes the link between bone and kidney, as one of the kidney's endocrine functions is the activation of vitamin D, while electrolyte homeostasis is one of its excretory functions. Impaired renal function leads to disturbances in this regulatory system, resulting in the complex syndrome of renal osteodystrophy that affects the majority of patients with chronic renal failure. This review summarizes the current understanding of bone physiology on a molecular level, examines some of the pathological pathways related to renal disease, and concludes with an outlook on how the emerging field of systems biology may contribute to a more dynamic and quantitative understanding of the physiology and pathophysiology of renal bone disease.

Computational identification of novel microRNAs and their targets in the malarial vector, Anopheles stephensi.

MicroRNAs are a ~22 nucleotide small non-coding RNAs found in animals, plants and viruses. They regulate key cellular processes by enhancing, degrading or silencing protein coding targets. Currently most of the data on miRNA is available from Drosophila . Given their important post-transcriptional role in several organisms, there is a need to understand the miRNA mediated processes in normal and abnormal conditions. Here we report four novel microRNAs ast - mir - 2502, ast - mir - 2559, ast - mir - 3868 and ast - mir - 9891 in Anopheles stephensi identified from a set of 3,052 transcriptome sequences, showing average minimum free energy of -31.8 kcal/mol of duplex formation with mRNA indicating their functional relevance. Phylogenetic study shows conservation of sequence signatures within the Class Insecta. Furthermore, 26 potential targets of these four miRNAs have been predicted that play an important role in the mosquito life-cycle. This work leads to novel leads and experimental possibilities for improved understanding of gene regulatory processes in mosquito.

Predicting stable functional peptides from the intergenic space of E. coli.

Expression of synthetic proteins from intergenic regions of E. coli and their functional association was recently demonstrated (Dhar et al. in J Biol Eng 3:2, 2009. doi:10.1186/1754-1611-3-2). This gave birth to the question: if one can make 'user-defined' genes from non-coding genome-how big is the artificially translatable genome? (Dinger et al. in PLoS Comput Biol 4, 2008; Frith et al. in RNA Biol 3(1):40-48, 2006a; Frith et al. in PLoS Genet 2(4):e52, 2006b). To answer this question, we performed a bioinformatics study of all reported E. coli intergenic sequences, in search of novel peptides and proteins, unexpressed by nature. Overall, 2500 E. coli intergenic sequences were computationally translated into 'protein sequence equivalents' and matched against all known proteins. Sequences that did not show any resemblance were used for building a comprehensive profile in terms of their structure, function, localization, interactions, stability so on. A total of 362 protein sequences showed evidence of stable tertiary conformations encoded by the intergenic sequences of E. coli genome. Experimental studies are underway to confirm some of the key predictions. This study points to a vast untapped repository of functional molecules lying undiscovered in the non-expressed genome of various organisms.

In silico study of peptide inhibitors against BACE 1.

Peptides are increasingly used as inhibitors of various disease specific targets. Several naturally occurring and synthetically developed peptides are undergoing clinical trials. Our work explores the possibility of reusing the non-expressing DNA sequences to predict potential drug-target specific peptides. Recently, we experimentally demonstrated the artificial synthesis of novel proteins from non-coding regions of Escherichia coli genome. In this study, a library of synthetic peptides (Synpeps) was constructed from 2500 intergenic E. coli sequences and screened against Beta-secretase 1 protein, a known drug target for Alzheimer's disease (AD). Secondary and tertiary protein structure predictions followed by protein-protein docking studies were performed to identify the most promising enzyme inhibitors. Interacting residues and favorable binding poses of lead peptide inhibitors were studied. Though initial results are encouraging, experimental validation is required in future to develop efficient target specific inhibitors against AD.

Computational approach to systems biology: from fraction to integration and beyond.

Systems biology is an approach to understanding the workings of whole biological systems. The various methods used for systems analyses range from experimental to computational. In this paper, we describe basic concepts of systems biology, modeling challenges that arise from the massively parallel interaction among components in biological systems, and what lies beyond integration of modular knowledge.

Decahydroquinolines from the venom of a formicinae ant, Oecophylla smaragdina.

Ecologically significant species in controlling pests, Oecophylla smaragdina uses its venom to paralyze their prey and to communicate with their colony mates. But no significant analysis of the ant's venom gland secretions has been carried out hitherto. This study describes the identification of venom constituents of Oecophylla smaragdina using coupled gas chromatography and mass spectroscopy (GC-MS) analysis. The results indicate the anticipated presence of a neurotoxin i.e., 2, 5 dipropyl decahydroquinoline and phenol, 2, 4-bis (1, 1 dimethylethyl). This is the first report on presence of decahydroquinolines in the venom of formicinae ant species of genera Oecophylla.