In silico identification and characterization of stress and virulence associated repeats in Salmonella.

So much genomic similarities yet causing different diseases, is like a paradox in Salmonella biology. Repeat is one of the probes that can explain such differences. Here, a comparative genomics approach is followed to identify and characterize repeats that might play role in adaptation and pathogenesis. Repeats are non-randomly distributed in the genomes except few typhoid causing strains. Perfect long repeats are rare compare to polymorphic ones and both are statistically consistent. Significant differences in repeat densities in stress related genes manifest its probable participation in survival and virulence. 573 and 1053 repeat loci have been identified which are exclusively associated with stress and virulent genes respectively. In Salmonella Typhi, an octameric VNTR locus is found in between acrD and yffB genes having more than 25 perfect copies across Salmonella Typhi but possesses only single copy in other serovars. This repeat can be used as a diagnostic probe for typhoid.

ProLego: tool for extracting and visualizing topological modules in protein structures.

BACKGROUND: In protein design, correct use of topology is among the initial and most critical feature. Meticulous selection of backbone topology aids in drastically reducing the structure search space. With ProLego, we present a server application to explore the component aspect of protein structures and provide an intuitive and efficient way to scan the protein topology space. RESULT: We have implemented in-house developed "topological representation" in an automated-pipeline to extract protein topology from given protein structure. Using the topology string, ProLego, compares topology against a non-redundant extensive topology database (ProLegoDB) as well as extracts constituent topological modules. The platform offers interactive topology visualization graphs. CONCLUSION: ProLego, provides an alternative but comprehensive way to scan and visualize protein topology along with an extensive database of protein topology. ProLego can be found at http://www.proteinlego.com.

Semantics based approach for analyzing disease-target associations.

BACKGROUND: A complex disease is caused by heterogeneous biological interactions between genes and their products along with the influence of environmental factors. There have been many attempts for understanding the cause of these diseases using experimental, statistical and computational methods. In the present work the objective is to address the challenge of representation and integration of information from heterogeneous biomedical aspects of a complex disease using semantics based approach. METHODS: Semantic web technology is used to design Disease Association Ontology (DAO-db) for representation and integration of disease associated information with diabetes as the case study. The functional associations of disease genes are integrated using RDF graphs of DAO-db. Three semantic web based scoring algorithms (PageRank, HITS (Hyperlink Induced Topic Search) and HITS with semantic weights) are used to score the gene nodes on the basis of their functional interactions in the graph. RESULTS: Disease Association Ontology for Diabetes (DAO-db) provides a standard ontology-driven platform for describing genes, proteins, pathways involved in diabetes and for integrating functional associations from various interaction levels (gene-disease, gene-pathway, gene-function, gene-cellular component and protein-protein interactions). An automatic instance loader module is also developed in present work that helps in adding instances to DAO-db on a large scale. CONCLUSIONS: Our ontology provides a framework for querying and analyzing the disease associated information in the form of RDF graphs. The above developed methodology is used to predict novel potential targets involved in diabetes disease from the long list of loose (statistically associated) gene-disease associations.

Functional relevance of dynamic properties of Dimeric NADP-dependent Isocitrate Dehydrogenases.

BACKGROUND: Isocitrate Dehydrogenases (IDHs) are important enzymes present in all living cells. Three subfamilies of functionally dimeric IDHs (subfamilies I, II, III) are known. Subfamily I are well-studied bacterial IDHs, like that of Escherischia coli. Subfamily II has predominantly eukaryotic members, but it also has several bacterial members, many being pathogens or endosymbionts. subfamily III IDHs are NAD-dependent. The eukaryotic-like subfamily II IDH from pathogenic bacteria such as Mycobacterium tuberculosis IDH1 are expected to have regulation similar to that of bacteria which use the glyoxylate bypass to survive starvation. Yet they are structurally different from IDHs of subfamily I, such as the E. coli IDH. RESULTS: We have used phylogeny, structural comparisons and molecular dynamics simulations to highlight the similarity and differences between NADP-dependent dimeric IDHs with an emphasis on regulation. Our phylogenetic study indicates that an additional subfamily (IV) may also be present. Variation in sequence and structure in an aligned region may indicate functional importance concerning regulation in bacterial subfamily I IDHs. Correlation in movement of prominent loops seen from molecular dynamics may explain the adaptability and diversity of the predominantly eukaryotic subfamily II IDHs. CONCLUSION: This study discusses possible regulatory mechanisms operating in various IDHs and implications for regulation of eukaryotic-like bacterial IDHs such as that of M. tuberculosis, which may provide avenues for intervention in disease.

Unusual domain architecture of aminoacyl tRNA synthetases and their paralogs from Leishmania major.

BACKGROUND: Leishmania major, a protozoan parasite, is the causative agent of cutaneous leishmaniasis. Due to the development of resistance against the currently available anti-leishmanial drugs, there is a growing need for specific inhibitors and novel drug targets. In this regards, aminoacyl tRNA synthetases, the linchpins of protein synthesis, have received recent attention among the kinetoplastid research community. This is the first comprehensive survey of the aminoacyl tRNA synthetases, their paralogs and other associated proteins from L. major. RESULTS: A total of 26 aminoacyl tRNA synthetases were identified using various computational and bioinformatics tools. Phylogenetic analysis and domain architectures of the L. major aminoacyl tRNA synthetases suggest a probable archaeal/eukaryotic origin. Presence of additional domains or N- or C-terminal extensions in 11 aminoacyl tRNA synthetases from L. major suggests possibilities such as additional tRNA binding or oligomerization or editing activity. Five freestanding editing domains were identified in L. major. Domain assignment revealed a novel asparagine tRNA synthetase paralog, asparagine synthetase A which has been so far reported from prokaryotes and archaea. CONCLUSIONS: A comprehensive bioinformatic analysis revealed 26 aminoacyl tRNA synthetases and five freestanding editing domains in L. major. Identification of two EMAP (endothelial monocyte-activating polypeptide) II-like proteins similar to human EMAP II-like proteins suggests their participation in multisynthetase complex formation. While the phylogeny of tRNA synthetases suggests a probable archaeal/eukaryotic origin, phylogeny of asparagine synthetase A strongly suggests a bacterial origin. The unique features identified in this work provide rationale for designing inhibitors against parasite aminoacyl tRNA synthetases and their paralogs.

Fractal symmetry of protein interior: what have we learned?

The application of fractal dimension-based constructs to probe the protein interior dates back to the development of the concept of fractal dimension itself. Numerous approaches have been tried and tested over a course of (almost) 30 years with the aim of elucidating the various facets of symmetry of self-similarity prevalent in the protein interior. In the last 5 years especially, there has been a startling upsurge of research that innovatively stretches the limits of fractal-based studies to present an array of unexpected results on the biophysical properties of protein interior. In this article, we introduce readers to the fundamentals of fractals, reviewing the commonality (and the lack of it) between these approaches before exploring the patterns in the results that they produced. Clustering the approaches in major schools of protein self-similarity studies, we describe the evolution of fractal dimension-based methodologies. The genealogy of approaches (and results) presented here portrays a clear picture of the contemporary state of fractal-based studies in the context of the protein interior. To underline the utility of fractal dimension-based measures further, we have performed a correlation dimension analysis on all of the available non-redundant protein structures, both at the level of an individual protein and at the level of structural domains. In this investigation, we were able to separately quantify the self-similar symmetries in spatial correlation patterns amongst peptide-dipole units, charged amino acids, residues with the π-electron cloud and hydrophobic amino acids. The results revealed that electrostatic environments in the interiors of proteins belonging to 'α/α toroid' (all-α class) and 'PLP-dependent transferase-like' domains (α/ß class) are highly conducive. In contrast, the interiors of 'zinc finger design' ('designed proteins') and 'knottins' ('small proteins') were identified as folds with the least conducive electrostatic environments. The fold 'conotoxins' (peptides) could be unambiguously identified as one type with the least stability. The same analyses revealed that peptide-dipoles in the α/ß class of proteins, in general, are more correlated to each other than are the peptide-dipoles in proteins belonging to the all-α class. Highly favorable electrostatic milieu in the interiors of TIM-barrel, α/ß-hydrolase structures could explain their remarkably conserved (evolutionary) stability from a new light. Finally, we point out certain inherent limitations of fractal constructs before attempting to identify the areas and problems where the implementation of fractal dimension-based constructs can be of paramount help to unearth latent information on protein structural properties.

Application and Comprehensive Analysis of Neighbor Approximated Information Theoretic Configurational Entropy Methods to Protein-Ligand Binding Cases.

The binding entropy is an important thermodynamic quantity which has numerous applications in studies of the biophysical process, and configurational entropy is often one of the major contributors in it. Therefore, its accurate estimation is important, though it is challenging mostly due to sampling limitations, anharmonicity, and multimodality of atomic fluctuations. The present work reports a Neighbor Approximated Maximum Information Spanning Tree (A-MIST) method for conformational entropy and presents its performance and computational advantage over conventional Mutual Information Expansion (MIE) and Maximum Information Spanning Tree (MIST) for two protein-ligand binding cases: indirubin-5-sulfonate to Plasmodium falciparum Protein Kinase 5 (PfPK5) and P. falciparum RON2-peptide to P. falciparum Apical Membrane Antigen 1 (PfAMA1). Important structural regions considering binding configurational entropy are identified, and physical origins for such are discussed. A thorough performance evaluation is done of a set of four entropy estimators (Maximum Likelihood (ML), Miller-Madow (MM), Chao-Shen (CS), and James and Stein shrinkage (JS)) with known varying degrees of sensitivity of the entropy estimate on the extent of sampling, each with two schemes for discretization of fluctuation data of Degrees of Freedom (DFs) to estimate Probability Density Functions (PDFs). Our comprehensive evaluation of influences of variations of parameters shows Neighbor Approximated MIE (A-MIE) outperforms MIE in terms of convergence and computational efficiency. In the case of A-MIE/MIE, results are sensitive to the choice of root atoms, graph search algorithm used for the Bond-Angle-Torsion (BAT) conversion, and entropy estimator, while A-MIST/MIST are not. A-MIST yields binding entropy within 0.5 kcal/mol of MIST with only 20-30% computation. Moreover, all these methods have been implemented in an OpenMP/MPI hybrid parallel C++11 code, and also a python package for data preprocessing and entropy contribution analysis is developed and made available. A comparative analysis of features of current implementation and existing tools is also presented.

A new computational model to study mass inhomogeneity and hydrophobicity inhomogeneity in proteins.

We propose a simple yet reliable computational framework that characterizes the differential mass and hydrophobicity distribution within structural classes of proteins. Radial partitioning of protein interior that could successfully distinguish the mass and hydrophobicity distribution patterns in extremophilic proteins from that in their structurally aligned mesophilic counterparts. Distance-dependent mass and hydrophobicity magnitudes could retrieve vital structural insights; needed to probe the hidden connections between packing, folding and stability within different structural classes of proteins, with causality. New computational markers; one, to represent the total mass content; other, related to hydrophobic centrality of proteins, are proposed as well. Results reveal that mass and hydrophobicity packing within extremophilic proteins is indeed more compact than that in their mesophilic counterparts. Analysis of structural constraints within them vindicate it. Total mass (and hydrophobicity) content is found to be maximum in alpha/beta thermophilic proteins and minimum for the all-alpha mesophilic proteins.

Determination of phosphorylation sites for NADP-specific isocitrate dehydrogenase from mycobacterium tuberculosis.

Isocitrate Dehydrogenase (ICD) catalyzes the oxidative decarboxylation reaction of 2R,3S-isocitrate to yield 2-oxoglutarate in the Tricarboxylic Acid (TCA) cycle. Two isoforms of NADP-specific ICDs with the E.C number 1.1.1.42 have been annotated in the organism Mycobacterium tuberculosis, monomeric ICD2 and dimeric ICD1. BLAST search against the Protein Data Bank (PDB) database shows a marked similarity between dimeric Mycobacterium tuberculosis ICD1 sequence and that of Sus scrofa, a cytosolic eukaryotic ICD (65% identity). Escherischia coli ICD shows less sequence similarity than the eukaryotic structure. A Homology model has thus been built for M. tuberculosis ICD1 using Sus scrofa and human ICD as templates. Inactivation of ICD1 by phosphorylation similar to E. coli ICD is important to open up the shunt pathway in the TCA cycle, which has been indicated in the case of M. tuberculosis. We therefore attempted to identify a number of likely phosphorylation sites in M. tuberculosis using pattern prediction and checked with the homology models for the accessibility of the peptides containing Serine. It was found that the homologous Serine by alignment with E. coli on M. tuberculosis ICD1 is difficult to access by specific kinases. Hence other probable sites of phosphorylation were checked and three highly probable serine-containing peptides were identified. The effect of phosphorylation at each of these sites was determined by checking the degree of conformational changes, the differences caused by the effect of phosphorylation in the active-site and other apparent motion different from that of the control, i.e., unphosphorylated M. tuberculosis ICD1 model, using molecular dynamics simulations.

Coupling Supervised Molecular Dynamics (SuMD) with Entropy Estimations To Shine Light on the Stability of Multiple Binding Sites.

Exploring at the molecular level, all possible ligand-protein approaching pathways and, consequently, identifying the energetically favorable binding sites is considered crucial to depict a clear picture of the whole scenario of ligand-protein binding. In fact, a ligand can recognize a protein in multiple binding sites, adopting multiple conformations in every single binding site and inducing protein modifications upon binding. In the present work, we would like to present how it is possible to couple a supervised molecular dynamics (SuMD) approach to explore, from an unbound state, the most energetically favorable recognition pathways of the ligand to its protein, with an enthalpic and entropic characterization of the most stable ligand-protein bound states, using the protein kinase CK2α as a prototype study. We identified two accessory binding pockets surrounding the ATP-binding site having a strong enthalpic contribution but a different configurational entropy contribution, suggesting that they play a different role.

Simple sequence repeats in different genome sequences of Shigella and comparison with high GC and AT-rich genomes.

Simple sequence repeats (SSRs) are omnipresent in prokaryotes and eukaryotes, and are found anywhere in the genome in both protein encoding and noncoding regions. In present study the whole genome sequences of seven chromosomes (Shigella flexneri 2a str301 and 2457T, Shigella sonnei, Escherichia coli k12, Mycobacterium tuberculosis, Mycobacterium leprae and Staphylococcus saprophyticus) have downloaded from the GenBank database for identifying abundance, distribution and composition of SSRs and also to determine difference between the tandem repeats in real genome and randomness genome (using sequence shuffling tool) of the organisms included in this study. The data obtained in the present study show that: (i) tandem repeats are widely distributed throughout the genomes; (ii) SSRs are differentially distributed among coding and noncoding regions in investigated Shigella genomes; (iii) total frequency of SSRs in noncoding regions are higher than coding regions; (iv) in all investigated chromosomes ratio of Trinucleotide SSRs in real genomes are much higher than randomness genomes and Di nucleotide SSRs are lower; (v) Ratio of total and mononucleotide SSRs in real genome is higher than randomness genomes in E. coli K12, S. flexneri str 301 and S. saprophyticus, while it is lower in S. flexneri str 2457T, S.sonnei and M. tuberculosis and it is approximately same in M. leprae; (vi) frequency of codon repetitions are vary considerably depending on the type of encoded amino acids.

Mapping selectivity and specificity of active site of plasmepsins from Plasmodium falciparum using molecular interaction field approach.

In the search for selectivity, the aspartic proteases are known to be a very difficult case because the enzymes of this family are not only sequentially but structurally also very similar. To gain insight into the selectivity and specificity of the aspartic proteases family we characterized the binding sites of four malarial aspartic protease (plasmepsin I, plasmepsin II, plasmepsin IV, P. vivax plasmepsin) and two human aspartic proteases (cathepsin D and pepsin) with the intention of identifying the regions that could be potential sites for obtaining selectivity using molecular interaction field approach.

Kinetic modeling of tricarboxylic acid cycle and glyoxylate bypass in Mycobacterium tuberculosis, and its application to assessment of drug targets.

BACKGROUND: Targeting persistent tubercule bacilli has become an important challenge in the development of anti-tuberculous drugs. As the glyoxylate bypass is essential for persistent bacilli, interference with it holds the potential for designing new antibacterial drugs. We have developed kinetic models of the tricarboxylic acid cycle and glyoxylate bypass in Escherichia coli and Mycobacterium tuberculosis, and studied the effects of inhibition of various enzymes in the M. tuberculosis model. RESULTS: We used E. coli to validate the pathway-modeling protocol and showed that changes in metabolic flux can be estimated from gene expression data. The M. tuberculosis model reproduced the observation that deletion of one of the two isocitrate lyase genes has little effect on bacterial growth in macrophages, but deletion of both genes leads to the elimination of the bacilli from the lungs. It also substantiated the inhibition of isocitrate lyases by 3-nitropropionate. On the basis of our simulation studies, we propose that: (i) fractional inactivation of both isocitrate dehydrogenase 1 and isocitrate dehydrogenase 2 is required for a flux through the glyoxylate bypass in persistent mycobacteria; and (ii) increasing the amount of active isocitrate dehydrogenases can stop the flux through the glyoxylate bypass, so the kinase that inactivates isocitrate dehydrogenase 1 and/or the proposed inactivator of isocitrate dehydrogenase 2 is a potential target for drugs against persistent mycobacteria. In addition, competitive inhibition of isocitrate lyases along with a reduction in the inactivation of isocitrate dehydrogenases appears to be a feasible strategy for targeting persistent mycobacteria. CONCLUSION: We used kinetic modeling of biochemical pathways to assess various potential anti-tuberculous drug targets that interfere with the glyoxylate bypass flux, and indicated the type of inhibition needed to eliminate the pathogen. The advantage of such an approach to the assessment of drug targets is that it facilitates the study of systemic effect(s) of the modulation of the target enzyme(s) in the cellular environment.

Modularity in protein structures: study on all-alpha proteins.

Modularity is known as one of the most important features of protein's robust and efficient design. The architecture and topology of proteins play a vital role by providing necessary robust scaffolds to support organism's growth and survival in constant evolutionary pressure. These complex biomolecules can be represented by several layers of modular architecture, but it is pivotal to understand and explore the smallest biologically relevant structural component. In the present study, we have developed a component-based method, using protein's secondary structures and their arrangements (i.e. patterns) in order to investigate its structural space. Our result on all-alpha protein shows that the known structural space is highly populated with limited set of structural patterns. We have also noticed that these frequently observed structural patterns are present as modules or "building blocks" in large proteins (i.e. higher secondary structure content). From structural descriptor analysis, observed patterns are found to be within similar deviation; however, frequent patterns are found to be distinctly occurring in diverse functions e.g. in enzymatic classes and reactions. In this study, we are introducing a simple approach to explore protein structural space using combinatorial- and graph-based geometry methods, which can be used to describe modularity in protein structures. Moreover, analysis indicates that protein function seems to be the driving force that shapes the known structure space.

An Ab Initio Method for Designing Multi-Target Specific Pharmacophores using Complementary Interaction Field of Aspartic Proteases.

For past few decades, key objectives of rational drug discovery have been the designing of specific and selective ligands for target proteins. Infectious diseases like malaria are continuously becoming resistant to traditional medicines, which inculcates need for new approaches to design inhibitors for antimalarial targets. A novel method for ab initio designing of multi target specific pharmacophores using the interaction field maps of active sites of multiple proteins has been developed to design 'specificity' pharmacophores for aspartic proteases. The molecular interaction field grid maps of active sites of aspartic proteases (plasmepsin II & IV from Plasmodium falciparum, plasmepsin from Plasmodium vivax, pepsin & cathepsin D from human) are calculated and common pharmacophoric features for favourable binding spots in active sites are extracted in the form of cliques of graphs using inductive logic programming (ILP). The two pharmacophore ensembles are constructed from largest common cliques by imposing size of receptor active site (L) and domain-specific receptor-ligand information (S). The overlap of chemical space between two ensembles and the results of virtual screening of inhibitor database with known activities show that this method can design efficient pharmacophores with no prior ligand information.

Biochemical characterization of Plasmodium falciparum hypoxanthine-guanine-xanthine phosphorybosyltransferase: role of histidine residue in substrate selectivity.

The enzyme hypoxanthine-guanine phosphorybosyltransferase (HGPRT) in the malarial parasite Plasmodium falciparum (Pf) is central to the salvage pathway for purine nucleotide biosynthesis and is a potential antimalarial chemotherapeutic target. The pH profile of the enzyme activity using xanthine as a substrate shows the possible involvement of a histidine residue in the activity of the enzyme. Chemical modification studies using diethylpyrocarbonate (DEPC) also corroborate this hypothesis. A comparative sequence alignment of Pf HGPRT with the human, Tricomonus foetus and Toxoplasma gondii HGPRT, coupled with the 3D structural alignment between these enzymes indicated that a histidine residue at position 196 of the Pf HGPRT sequence was located in the close proximity to the active site. Site directed mutagenesis of this histidine residue to lysine (the corresponding residue in the human enzyme) specifically abrogated xanthine and guanine utilization of the enzyme without affecting the conversion of hypoxanthine to its corresponding nucleotide. The mechanism of action for this enzyme was evaluated by steady state kinetics for the substrates xanthine, guanine and PRPP and product inhibition studies. The results indicate the possibility of ping-pong mechanism for the enzyme in contrast to the ternary complex mechanism followed by the human enzyme. These results show that the difference in human and malarial HGPRT can be gainfully exploited to design specific inhibitor for this enzyme.

PfalDB: an integrated drug target and chemical database for Plasmodium falciparum.

Plasmodium falciparum is one of the deadliest protozoan parasite species among those that cause malaria. Uncontrolled use of antimalarial drugs has resulted in evolutionary selection pressure favoring high levels of resistance to antimalarials; currently P.falciparum shows resistance to all classes of antimalarials. Therefore it is essential to identify novel drug targets, and design selective anti-malarials which can overcome resistance. While many drug targets are freely available in various public domain resources, a single comprehensive source of data containing easily searchable and retrievable information is currently lacking. To facilitate the total integration and mining of data emerging from different drug consortia and also to prioritize drug targets for structure-based drug design, an open-access, inclusive comprehensive database for Plasmodium falciparum was established. Meta data of known/modeled structures along with binding site parameters of drug targets have been included in the database. Additionally, chemical compounds showing a positive inhibitory assay against Plasmodium falciparum or known drug targets have also been provided. The database is accessible at http://pfaldb.jnu.ac.in. The database provides diverse information regarding the structure, sequence, stage specific gene expression, pathway, action mechanism, essentiality and druggability for each drug target, and literature to assess the validation status of individual drug targets. It also includes information on individual anti-malarials with their activity and bioassay.

Methylerythritol phosphate pathway to isoprenoids: kinetic modeling and in silico enzyme inhibitions in Plasmodium falciparum.

The methylerythritol phosphate (MEP) pathway of Plasmodium falciparum (P. falciparum) has become an attractive target for anti-malarial drug discovery. This study describes a kinetic model of this pathway, its use in validating 1-deoxy-d-xylulose 5-phosphate reductoisomerase (DXR) as drug target from the systemic perspective, and additional target identification, using metabolic control analysis and in silico inhibition studies. In addition to DXR, 1-deoxy-d-xylulose 5-phosphate synthase (DXS) can be targeted because it is the first enzyme of the pathway and has the highest flux control coefficient followed by that of DXR. In silico inhibition of both enzymes caused large decrement in the pathway flux. An added advantage of targeting DXS is its influence on vitamin B1 and B6 biosynthesis. Two more potential targets, 2-C-methyl-d-erythritol 2,4-cyclodiphosphate synthase and 1-hydroxy-2-methyl-2-(E)-butenyl 4-diphosphate synthase, were also identified. Their inhibition caused large accumulation of their substrates causing instability of the system. This study demonstrates that both types of enzyme targets, one acting via flux reduction and the other by metabolite accumulation, exist in P. falciparum MEP pathway. These groups of targets can be exploited for independent anti-malarial drugs.

A plausible mechanism for the antimalarial activity of artemisinin: A computational approach.

Artemisinin constitutes the frontline treatment to aid rapid clearance of parasitaemia and quick resolution of malarial symptoms. However, the widespread promiscuity about its mechanism of action is baffling. There is no consensus about the biochemical target of artemisinin but recent studies implicate haem and PfATP6 (a calcium pump). We investigated the role of iron and artemisinin on PfATP6, in search of a plausible mechanism of action, via density functional theory calculations, docking and molecular dynamics simulations. Results suggest that artemisinin gets activated by iron which in turn inhibits PfATP6 by closing the phosphorylation, nucleotide binding and actuator domains leading to loss of function of PfATP6 of the parasite and its death. The mechanism elucidated here should help in the design of novel antimalarials.

Different designs of kinase-phosphatase interactions and phosphatase sequestration shapes the robustness and signal flow in the MAPK cascade.

BACKGROUND: The three layer mitogen activated protein kinase (MAPK) signaling cascade exhibits different designs of interactions between its kinases and phosphatases. While the sequential interactions between the three kinases of the cascade are tightly preserved, the phosphatases of the cascade, such as MKP3 and PP2A, exhibit relatively diverse interactions with their substrate kinases. Additionally, the kinases of the MAPK cascade can also sequester their phosphatases. Thus, each topologically distinct interaction design of kinases and phosphatases could exhibit unique signal processing characteristics, and the presence of phosphatase sequestration may lead to further fine tuning of the propagated signal. RESULTS: We have built four architecturally distinct types of models of the MAPK cascade, each model with identical kinase-kinase interactions but unique kinases-phosphatases interactions. Our simulations unravelled that MAPK cascade's robustness to external perturbations is a function of nature of interaction between its kinases and phosphatases. The cascade's output robustness was enhanced when phosphatases were sequestrated by their target kinases. We uncovered a novel implicit/hidden negative feedback loop from the phosphatase MKP3 to its upstream kinase Raf-1, in a cascade resembling the B cell MAPK cascade. Notably, strength of the feedback loop was reciprocal to the strength of phosphatases' sequestration and stronger sequestration abolished the feedback loop completely. An experimental method to verify the presence of the feedback loop is also proposed. We further showed, when the models were activated by transient signal, memory (total time taken by the cascade output to reach its unstimulated level after removal of signal) of a cascade was determined by the specific designs of interaction among its kinases and phosphatases. CONCLUSIONS: Differences in interaction designs among the kinases and phosphatases can differentially shape the robustness and signal response behaviour of the MAPK cascade and phosphatase sequestration dramatically enhances the robustness to perturbations in each of the cascade. An implicit negative feedback loop was uncovered from our analysis and we found that strength of the negative feedback loop is reciprocally related to the strength of phosphatase sequestration. Duration of output phosphorylation in response to a transient signal was also found to be determined by the individual cascade's kinase-phosphatase interaction design.