Allostery in tRNA Synthetases Elucidated from MD Simulations and Protein Structure Networks

tRNA synthetases (aaRS) are enzymes crucial in the translation of genetic code. The enzyme accylates the acceptor stem of tRNA by the congnate amino acid bound at the active site, when the anti-codon is recognized by the anti-codon site of aaRS. In a typical aaRS, the distance between the anti-codon region and the amino accylation site is approximately 70 Å. We have investigated this allosteric phenomenon at molecular level by MD simulations followed by the analysis of protein structure networks (PSN) of non-covalent interactions. Specifically, we have generated conformational ensembles by performing MD simulations on different liganded states of methionyl tRNA synthetase (MetRS) from Escherichia coli and tryptophenyl tRNA synthetase (TrpRS) from Human. The correlated residues during the MD simulations are identified by cross correlation maps. We have identified the amino acids connecting the correlated residues by the shortest path between the two selected members of the PSN. The frequencies of paths have been evaluated from the MD snapshots[1]. The conformational populations in different liganded states of the protein have been beautifully captured in terms of network parameters such as hubs, cliques and communities[2]. These parameters have been associated with the rigidity and plasticity of the protein conformations and can be associated with free energy landscape. A comparison of allosteric communication in MetRS and TrpRS [3] elucidated in this study highlights diverse means adopted by different enzymes to perform a similar function. The computational method described for these two enzymes can be applied to the investigation of allostery in other systems.

Specificity in proteinânucleic acid interaction: Solubility study on amino acidânucleoside interaction

The chemical basis of the specificity of proteinnucleic acid interaction, as seen in many biochemical phenomena such as the organization of nucleoprotein complexes (~hro~atin. ribosomes) and gene expression and its regulation, IS not yet understood.A knowledge of such specific interactions is also essential for tracing the chemical evolution of life based an the coupling between protein and nucleic acid and the origin of genetic code [I ,I?].

A novel approach to design of cis-acting DNA structural element for regulation of gene expression in vivo

Taking advantage of the degeneracy of the genetic code we have developed a novel approach to introduce, within a gene, DNA sequences capable of adopting unusual structures and to investigate the role of such sequences in regulation of gene expression in vivo. We used a computer program that generates alternative codon sequences for the same amino-acid sequence to convert a stretch of nucleotides into an inverted-repeat sequence with the potential to adopt cruciform structure. This approach was used to replace a 51-base-pair EcoRI-HindIII segment in the N-terminal region of the beta-galactosidase gene in plasmid pUC19 with a 51-bp synthetic oligonucleotide sequence with the potential to adopt a cruciform structure with 18 bp in the stem region. In selecting the 51-bp sequence, care was taken to include those codons that are preferred in E. coli. E. coli DH5-alpha cells harbouring the plasmid containing the redesigned sequence showed drastic reduction in expression of the beta-galactosidase gene compared to cells harbouring the plasmid with the native sequence. This approach demonstrates the possibility of introducing DNA secondary-structure elements to alter regulation of gene expression in vivo.

Kinetic proofreading at single molecular level: aminoacylation of tRNA(Ile) and the role of water as an editor

Proofreading/editing in protein synthesis is essential for accurate translation of information from the genetic code. In this article we present a theoretical investigation of efficiency of a kinetic proofreading mechanism that employs hydrolysis of the wrong substrate as the discriminatory step in enzyme catalytic reactions. We consider aminoacylation of tRNA(Ile) which is a crucial step in protein synthesis and for which experimental results are now available. We present an augmented kinetic scheme and then employ methods of stochastic simulation algorithm to obtain time dependent concentrations of different substances involved in the reaction and their rates of formation. We obtain the rates of product formation and ATP hydrolysis for both correct and wrong substrates (isoleucine and valine in our case, respectively), in single molecular enzyme as well as ensemble enzyme kinetics. The present theoretical scheme correctly reproduces (i) the amplitude of the discrimination factor in the overall rates between isoleucine and valine which is obtained as (1.8x10(2)).(4.33x10(2)) = 7.8x10(4), (ii) the rates of ATP hydrolysis for both Ile and Val at different substrate concentrations in the aminoacylation of tRNA(Ile). The present study shows a non-michaelis type dependence of rate of reaction on tRNA(Ile) concentration in case of valine. The overall editing in steady state is found to be independent of amino acid concentration. Interestingly, the computed ATP hydrolysis rate for valine at high substrate concentration is same as the rate of formation of Ile-tRNA(Ile) whereas at intermediate substrate concentration the ATP hydrolysis rate is relatively low. We find that the presence of additional editing domain in class I editing enzyme makes the kinetic proofreading more efficient through enhanced hydrolysis of wrong product at the editing CP1 domain.

Identification of delamination in composite beams using spectral estimation and a genetic algorithm

An efficient strategy for identification of delamination in composite beams and connected structures is presented. A spectral finite-element model consisting of a damaged spectral element is used for model-based prediction of the damaged structural response in the frequency domain. A genetic algorithm (GA) specially tailored for damage identification is derived and is integrated with finite-element code for automation. For best application of the GA, sensitivities of various objective functions with respect to delamination parameters are studied and important conclusions are presented. Model-based simulations of increasing complexity illustrate some of the attractive features of the strategy in terms of accuracy as well as computational cost. This shows the possibility of using such strategies for the development of smart structural health monitoring softwares and systems.

A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data

Background: A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data. Results: The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In each S. cerevisiae LP-SLGN, the number of nodes with a particular degree follows an approximate power law suggesting that its degree distributions is similar to that observed in real-world networks. Inspection of these LP-SLGNs suggests biological hypotheses amenable to experimental verification. Conclusion: A statistically robust and computationally efficient LP-based method for estimating the topology of a large sparse undirected graph from high-dimensional data yields representations of genetic networks that are biologically plausible and useful abstractions of the structures of real genetic networks. Analysis of the statistical and topological properties of learned LP-SLGNs may have practical value; for example, genes with high random walk betweenness, a measure of the centrality of a node in a graph, are good candidates for intervention studies and hence integrated computational – experimental investigations designed to infer more realistic and sophisticated probabilistic directed graphical model representations of genetic networks. The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data.

Timing the Emergence of Resistance to Anti-HIV Drugs with Large Genetic Barriers

New antiretroviral drugs that offer large genetic barriers to resistance, such as the recently approved inhibitors of HIV-1 protease, tipranavir and darunavir, present promising weapons to avert the failure of current therapies for HIV infection. Optimal treatment strategies with the new drugs, however, are yet to be established. A key limitation is the poor understanding of the process by which HIV surmounts large genetic barriers to resistance. Extant models of HIV dynamics are predicated on the predominance of deterministic forces underlying the emergence of resistant genomes. In contrast, stochastic forces may dominate, especially when the genetic barrier is large, and delay the emergence of resistant genomes. We develop a mathematical model of HIV dynamics under the influence of an antiretroviral drug to predict the waiting time for the emergence of genomes that carry the requisite mutations to overcome the genetic barrier of the drug. We apply our model to describe the development of resistance to tipranavir in in vitro serial passage experiments. Model predictions of the times of emergence of different mutant genomes with increasing resistance to tipranavir are in quantitative agreement with experiments, indicating that our model captures the dynamics of the development of resistance to antiretroviral drugs accurately. Further, model predictions provide insights into the influence of underlying evolutionary processes such as recombination on the development of resistance, and suggest guidelines for drug design: drugs that offer large genetic barriers to resistance with resistance sites tightly localized on the viral genome and exhibiting positive epistatic interactions maximally inhibit the emergence of resistant genomes.

Structural Basis of Drug Resistance by Genetic Variants of HIV Type 1 Clade C Protease from India

Using computer modeling of three-dimensional structures and structural information available on the crystal structures of HIV-1 protease, we investigated the structural effects of mutations, in treatment-naive and treatment-exposed individuals from India and postulated mechanisms of resistance in clade C variants. A large number of models (14) have been generated by computational mutation of the available crystal structures of drug bound proteases. Localized energy minimization was carried out in and around the sites of mutation in order to optimize the geometry of interactions present. Most of the mutations result in structural differences at the flap that favors the semiopen state of the enzyme. Some of the mutations were also found to confer resistance by affecting the geometry of the active site. The E35D mutation affects the flap structure in clade B strains and E35N and E35K mutation, seen in our modeled strains, have a more profound effect. Common polymorphisms at positions 36 and 63 in clade C also affected flap structure. Apart from a few other residues Gln-58, Asn-83, Asn-88, and Gln-92 and their interactions are important for the transition from the closed to the open state. Development of protease inhibitors by structure-based design requires investigation of mechanisms operative for clade C to improve the efficacy of therapy.

Genetic analysis of foot-and-mouth disease virus serotype A of Indian origin and detection of positive selection and recombination in leader protease- and capsid-coding regions

The leader protease (L-pro) and capsid-coding sequences (P1) constitute approximately 3 kb of the foot-and-mouth disease virus (FMDV). We studied the phylogenetic relationship of 46 FMDV serotype A isolates of Indian origin collected during the period 1968-2005 and also eight vaccine strains using the neighbour-joining tree and Bayesian tree methods. The viruses were categorized under three major groups - Asian, Euro-South American and European. The Indian isolates formed a distinct genetic group among the Asian isolates. The Indian isolates were further classified into different genetic subgroups (<5% divergence). Post-1995 isolates were divided into two subgroups while a few isolates which originated in the year 2005 from Andhra Pradesh formed a separate group. These isolates were closely related to the isolates of the 1970s. The FMDV isolates seem to undergo reverse mutation or onvergent evolution wherein sequences identical to the ancestors are present in the isolates in circulation. The eight vaccine strains included in the study were not related to each other and belonged to different genetic groups. Recombination was detected in the L-pro region in one isolate (A IND 20/82) and in the VP1 coding 1D region in another isolate (A RAJ 21/96). Positive selection was identified at aa positions 23 in the L-pro (P<0.05; 0.046*) and at aa 171 in the capsid protein VP1 (P<0.01; 0.003**).

Inbreeding and the incidence of childhood genetic disorders in Karnataka, South India

Consanguineous marriages are strongly favoured among the populations of South India. In a study conducted on 407 infants and children, a total of 35 genetic diseases was diagnosed in 63 persons: 44 with single gene defects, 12 with polygenic disorders, and seven with Down's syndrome. The coefficient of inbreeding of the total study group, F = 0.0414, was significantly higher than that previously calculated for the general population, F = 0.0271, and autosomal recessive disorders formed the largest single disease category diagnosed. The results suggest that long term inbreeding may not have resulted in appreciable elimination of recessive lethals and sub-lethals from the gene pool.

Development of a computer code to predict cooling of die and billet in forging

A hot billet in contact with relatively cold dies undergoes rapid cooling in the forging operation. This may give rise to unfilled cavities, poor surface finish and stalling of the press. A knowledge of billet-die temperatures as a function of time is therefore essential for process design. A computer code using finite difference method is written to estimate such temperature histories and validated by comparing the predicted cooling of an integral die-billet configuration with that obtained experimentally.

A model for mammalian male determination based on a passive Y chromosome

A model is suggested for mammalian male determination based on interactions postulated to occur among an autosomal repressor gene, an X-linked male-determining gene termed Tdx, and multiple copies of certain DNA sequences on the Y chromosome that do not code for any protein. The repressor, synthesised in limited amounts, has higher affinity for the Y-linked sequences than for Tdx and its affinity for Tdx is greater than that of RNA polymerase. In XY cells the Y effectively binds all available repressor, permitting transcription of Tdx to occur. In XX cells, since competition from the Y-linked high-affinity sequences is absent, the repressor binds to Tdx and prevents transcription. As a result of this competition between Tdx and the Y-linked high-affinity sites for limiting concentrations of the autosomal repressor, the product of the Tdx gene (TDX) is synthesized in the male but not in the female. It is suggested that in determination of the male sex, the role of the Y chromosome is to serve as a sink for the Tdx repressor. The proposed interactions provide a plausible explanation for the genetic properties of several anomalies of sexual development in mouse, man, and other mammals. The model suggests that the postulated multiple, highaffinity sequences on the Y chromosome of the mouse are included among the DNA sequences referred to as the Sxr-Bkm sequences.

trans gene regulation in adaptive evolution: A genetic algorithm model

This is a continuation of earlier studies on the evolution of infinite populations of haploid genotypes within a genetic algorithm framework. We had previously explored the evolutionary consequences of the existence of indeterminate—“plastic”—loci, where a plastic locus had a finite probability in each generation of functioning (being switched “on”) or not functioning (being switched “off”). The relative probabilities of the two outcomes were assigned on a stochastic basis. The present paper examines what happens when the transition probabilities are biased by the presence of regulatory genes. We find that under certain conditions regulatory genes can improve the adaptation of the population and speed up the rate of evolution (on occasion at the cost of lowering the degree of adaptation). Also, the existence of regulatory loci potentiates selection in favour of plasticity. There is a synergistic effect of regulatory genes on plastic alleles: the frequency of such alleles increases when regulatory loci are present. Thus, phenotypic selection alone can be a potentiating factor in a favour of better adaptation.

Genetic studies of the PRP17 gene of Saccharomyces cerevisiae: a domain essential for function maps to a nonconserved region of the protein

The PRP17 gene product is required for the second step of pre-mRNA splicing reactions. The C-terminal half of this protein bears four repeat units with homology to the beta transducin repeat. Missense mutations in three temperature-sensitive prp17 mutants map to a region in the N-terminal half of the protein. We have generated, in vitro, 11 missense alleles at the beta transducin repeat units and find that only one affects function in vivo. A phenotypically silent missense allele at the fourth repeat unit enhances the slow-growing phenotype conferred by an allele at the third repeat, suggesting an interaction between these domains. Although many missense mutations in highly conserved amino acids lack phenotypic effects, deletion analysis suggests an essential role for these units. Only mutations in the N-terminal nonconserved domain of PRP17 are synthetically lethal in combination with mutations in PRP16 and PRP18, two other gene products required for the second splicing reaction. A mutually allele-specific interaction between Prp17 and snr7, with mutations in U5 snRNA, was observed. We therefore suggest that the functional region of Prp17p that interacts with Prp18p, Prp16p, and U5 snRNA is the N terminal region of the protein.

An extragenic suppressor of prp24-1 defines genetic interaction between PRP24 and PRP21 gene products of Saccharomyces cerevisiae

The temperature-sensitive prp24-1 mutation defines a gene product required for the first step in pre-mRNA splicing. PRP24 is probably a component of the U6 snRNP particle. We have applied genetic reversion analysis to identify proteins that interact with PRP24. Spontaneous revertants of the temperature-sensitive (ts) prp24-1 phenotype were analyzed for those that are due to extragenic suppression. We then extended our analysis to screen for suppressors that confer a distinct conditional phenotype. We have identified a temperature-sensitive extragenic suppressor, which was shown by genetic complementation analysis to be allelic to prp21-1. This suppressor, prp21-2, accumulates pre-mRNA at the non-permissive temperature, a phenotype similar to that of prp21-1. prp21-2 completely suppresses the splicing defect and restores in vivo levels of the U6 snRNA in the prp24-1 strain. Genetic analysis of the suppressor showed that prp21-2 is not a bypass suppressor of prp24-1. The suppression of prp24-1 by prp21-2 is gene specific and also allele specific with respect to both the loci. Genetic interactions with other components of the pre-spliceosome have also been studied. Our results indicate an interaction between PRP21, a component of the U2 snRNP, and PRP24, a component of the U6 snRNP. These results substantiate other data showing U2-U6 snRNA interactions.