Dissecting the structural and functional features of the Luteinizing hormone receptor using receptor specific single chain fragment variables.

The Luteinizing hormone receptor (LHR) has a large extracellular domain (amino acid residues, a.a.1-355) and a transmembrane domain (TMD; a.a. 356-699), essential for hormone binding and signaling, respectively. The LHR hinge region (a.a. 256-355) connects the two domains and acts as an activating switch for the receptor by an unknown mechanism. LHR hinge-specific Single chain fragment variables (ScFv) stimulated cAMP production by the stable and transiently transfected cell lines expressing LHR in a hormone-independent manner and the C-terminal region of LHR hinge (a.a. 313-349) was identified as the probable epitope for one agonistic ScFv. This epitope attained a helical conformation upon agonistic ScFv binding and the activity of the ScFv was dependent on Y331 sulfation. ScFv was also able to activate TMD mutants, D578Y and A593P, reemphasizing the role of TM helix VI in LHR activation.

Recognizing drug targets using evolutionary information: implications for repurposing FDA-approved drugs against Mycobacterium tuberculosis H37Rv.

Drug repurposing to explore target space has been gaining pace over the past decade with the upsurge in the use of systematic approaches for computational drug discovery. Such a cost and time-saving approach gains immense importance for pathogens of special interest, such as Mycobacterium tuberculosis H37Rv. We report a comprehensive approach to repurpose drugs, based on the exploration of evolutionary relationships inferred from the comparative sequence and structural analyses between targets of FDA-approved drugs and the proteins of M. tuberculosis. This approach has facilitated the identification of several polypharmacological drugs that could potentially target unexploited M. tuberculosis proteins. A total of 130 FDA-approved drugs, originally intended against other diseases, could be repurposed against 78 potential targets in M. tuberculosis. Additionally, we have also made an attempt to augment the chemical space by recognizing compounds structurally similar to FDA-approved drugs. For three of the attractive cases we have investigated the probable binding modes of the drugs in their corresponding M. tuberculosis targets by means of structural modelling. Such prospective targets and small molecules could be prioritized for experimental endeavours, and could significantly influence drug-discovery and drug-development programmes for tuberculosis.

SInCRe-structural interactome computational resource for Mycobacterium tuberculosis.

We have developed an integrated database for Mycobacterium tuberculosis H37Rv (Mtb) that collates information on protein sequences, domain assignments, functional annotation and 3D structural information along with protein-protein and protein-small molecule interactions. SInCRe (Structural Interactome Computational Resource) is developed out of CamBan (Cambridge and Bangalore) collaboration. The motivation for development of this database is to provide an integrated platform to allow easily access and interpretation of data and results obtained by all the groups in CamBan in the field of Mtb informatics. In-house algorithms and databases developed independently by various academic groups in CamBan are used to generate Mtb-specific datasets and are integrated in this database to provide a structural dimension to studies on tuberculosis. The SInCRe database readily provides information on identification of functional domains, genome-scale modelling of structures of Mtb proteins and characterization of the small-molecule binding sites within Mtb. The resource also provides structure-based function annotation, information on small-molecule binders including FDA (Food and Drug Administration)-approved drugs, protein-protein interactions (PPIs) and natural compounds that bind to pathogen proteins potentially and result in weakening or elimination of host-pathogen protein-protein interactions. Together they provide prerequisites for identification of off-target binding.

NrichD database: sequence databases enriched with computationally designed protein-like sequences aid in remote homology detection.

NrichD (http://proline.biochem.iisc.ernet.in/NRICHD/) is a database of computationally designed protein-like sequences, augmented into natural sequence databases that can perform hops in protein sequence space to assist in the detection of remote relationships. Establishing protein relationships in the absence of structural evidence or natural 'intermediately related sequences' is a challenging task. Recently, we have demonstrated that the computational design of artificial intermediary sequences/linkers is an effective approach to fill naturally occurring voids in protein sequence space. Through a large-scale assessment we have demonstrated that such sequences can be plugged into commonly employed search databases to improve the performance of routinely used sequence search methods in detecting remote relationships. Since it is anticipated that such data sets will be employed to establish protein relationships, two databases that have already captured these relationships at the structural and functional domain level, namely, the SCOP database and the Pfam database, have been 'enriched' with these artificial intermediary sequences. NrichD database currently contains 3,611,010 artificial sequences that have been generated between 27,882 pairs of families from 374 SCOP folds. The data sets are freely available for download. Additional features include the design of artificial sequences between any two protein families of interest to the user.

Enriching the annotation of Mycobacterium tuberculosis H37Rv proteome using remote homology detection approaches: insights into structure and function.

The availability of the genome sequence of Mycobacterium tuberculosis H37Rv has encouraged determination of large numbers of protein structures and detailed definition of the biological information encoded therein; yet, the functions of many proteins in M. tuberculosis remain unknown. The emergence of multidrug resistant strains makes it a priority to exploit recent advances in homology recognition and structure prediction to re-analyse its gene products. Here we report the structural and functional characterization of gene products encoded in the M. tuberculosis genome, with the help of sensitive profile-based remote homology search and fold recognition algorithms resulting in an enhanced annotation of the proteome where 95% of the M. tuberculosis proteins were identified wholly or partly with information on structure or function. New information includes association of 244 proteins with 205 domain families and a separate set of new association of folds to 64 proteins. Extending structural information across uncharacterized protein families represented in the M. tuberculosis proteome, by determining superfamily relationships between families of known and unknown structures, has contributed to an enhancement in the knowledge of structural content. In retrospect, such superfamily relationships have facilitated recognition of probable structure and/or function for several uncharacterized protein families, eventually aiding recognition of probable functions for homologous proteins corresponding to such families. Gene products unique to mycobacteria for which no functions could be identified are 183. Of these 18 were determined to be M. tuberculosis specific. Such pathogen-specific proteins are speculated to harbour virulence factors required for pathogenesis. A re-annotated proteome of M. tuberculosis, with greater completeness of annotated proteins and domain assigned regions, provides a valuable basis for experimental endeavours designed to obtain a better understanding of pathogenesis and to accelerate the process of drug target discovery.

From workstations to workbenches: Towards predicting physicochemically viable protein-protein interactions across a host and a pathogen.

The understanding of protein-protein interactions is indispensable in comprehending most of the biological processes in a cell. Small-scale experiments as well as large-scale high-throughput techniques over the past few decades have facilitated identification and analysis of protein-protein interactions which form the basis of much of our knowledge on functional and regulatory aspects of proteins. However, such rich catalog of interaction data should be used with caution when establishing protein-protein interactions in silico, as the high-throughput datasets are prone to false positives. Numerous computational means developed to pursue genome-wide studies on protein-protein interactions at times overlook the mechanistic and molecular details, thus questioning the reliability of predicted protein-protein interactions. We review the development, advantages, and shortcomings of varied approaches and demonstrate that by providing a structural viewpoint in terms of shape complementarity and interaction energies at protein-protein interfaces coupled with information on expression and localization of proteins homologous to an interacting pair, it is possible to assess the credibility of predicted interactions in biological context. With a focus on human pathogen Mycobacterium tuberculosis H37Rv, we show that such scrupulous use of details at the molecular level can predict physicochemically viable protein-protein interactions across host and pathogen. Such predicted interactions have the potential to provide molecular basis of probable mechanisms of pathogenesis and hence open up ways to explore their usefulness as targets in the light of drug discovery.

Structural biology of Mycobacterium tuberculosis proteins: the Indian efforts.

Among the many different objectives of large scale structural genomics projects are expanding the protein fold space, enhancing understanding of a model or disease-related organism, and providing foundations for structure-based drug discovery. Systematic analysis of protein structures of Mycobacterium tuberculosis has been ongoing towards meeting some of these objectives. Indian participation in these efforts has been enthusiastic and substantial. The proteins of M. tuberculosis chosen for structural analysis by the Indian groups span almost all the functional categories. The structures determined by the Indian groups have led to significant improvement in the biochemical knowledge on these proteins and consequently have started providing useful insights into the biology of M. tuberculosis. Moreover, these structures form starting points for inhibitor design studies, early results of which are encouraging. The progress made by Indian structural biologists in determining structures of M. tuberculosis proteins is highlighted in this review.

Crystallographic and modelling studies on Mycobacterium tuberculosis RuvA Additional role of RuvB-binding domain and inter species variability.

RuvA, along with RuvB, is involved in branch migration of heteroduplex DNA in homologous recombination. The structures of three new crystal forms of RuvA from Mycobacterium tuberculosis (MtRuvA) have been determined. The RuvB-binding domain is cleaved off in one of them. Detailed models of the complexes of octameric RuvA from different species with the Holliday junction have also been constructed. A thorough examination of the structures presented here and those reported earlier brings to light the hitherto unappreciated role of the RuvB-binding domain in determining inter-domain orientation and oligomerization. These structures also permit an exploration of the interspecies variability of structural features such as oligomerization and the conformation of the loop that carries the acidic pin, in terms of amino acid substitutions. These models emphasize the additional role of the RuvB-binding domain in Holliday junction binding. This role along with its role in oligomerization could have important biological implications.

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.

Structural basis for the function of anti-idiotypic antibody in immune memory.

We had earlier proposed a hypothesis to explain the mechanism of perpetuation of immunological memory based on the operation of idiotypic network in the complete absence of antigen. Experimental evidences were provided for memory maintenance through anti-idiotypic antibody (Ab(2)) carrying the internal image of the antigen. In the present work, we describe a structural basis for such memory perpetuation by molecular modeling and structural analysis studies. A three-dimensional model of Ab(2) was generated and the structure of the antigenic site on the hemagglutinin protein H of Rinderpest virus was modeled using the structural template of hemagglutinin protein of Measles virus. Our results show that a large portion of heavy chain containing the CDR regions of Ab(2) resembles the domain of the hemagglutinin housing the epitope regions. The similarity demonstrates that an internal image of the H antigen is formed in Ab(2), which provides a structural basis for functional mimicry demonstrated earlier. This work brings out the importance of the structural similarity between a domain of hemagglutinin protein to that of its corresponding Ab(2). It provides evidence that Ab(2) is indeed capable of functioning as surrogate antigen and provides support to earlier proposed relay hypothesis which has provided a mechanism for the maintenance of immunological memory.

Localisation of Plasmodium falciparum uroporphyrinogen III decarboxylase of the heme-biosynthetic pathway in the apicoplast and characterisation of its catalytic properties.

Uroporphyrinogen decarboxylase (UROD) is a key enzyme in the heme-biosynthetic pathway and in Plasmodium falciparum it occupies a strategic position in the proposed hybrid pathway for heme biosynthesis involving shuttling of intermediates between different subcellular compartments in the parasite. In the present study, we demonstrate that an N-terminally truncated recombinant P. falciparum UROD (r(Delta)PfUROD) over-expressed and purified from Escherichia coli cells, as well as the native enzyme from the parasite were catalytically less efficient compared with the host enzyme, although they were similar in other enzyme parameters. Molecular modeling of PfUROD based on the known crystal structure of the human enzyme indicated that the protein manifests a distorted triose phosphate isomerase (TIM) barrel fold which is conserved in all the known structures of UROD. The parasite enzyme shares all the conserved or invariant amino acid residues at the active and substrate binding sites, but is rich in lysine residues compared with the host enzyme. Mutation of specific lysine residues corresponding to residues at the dimer interface in human UROD enhanced the catalytic efficiency of the enzyme and dimer stability indicating that the lysine rich nature and weak dimer interface of the wild-type PfUROD could be responsible for its low catalytic efficiency. PfUROD was localised to the apicoplast, indicating the requirement of additional mechanisms for transport of the product coproporphyrinogen to other subcellular sites for its further conversion and ultimate heme formation.

Functionally important movements in RecA molecules and filaments: studies involving mutation and environmental changes.

The crystal structures of mutants of Mycobacterium smegmatis RecA (MsRecA) involving changes of Gln196 from glutamine to alanine, asparagine and glutamic acid, wild-type MsRecA and several of their nucleotide complexes have been determined using mostly low-temperature and partly room-temperature X-ray data. At both temperatures, nucleotide binding results in a movement of Gln196 towards the bound nucleotide in the wild-type protein. This movement is abolished in the mutants, thus establishing the structural basis for the triggering action of the residue in terms of the size, shape and the chemical nature of the side chain. The 19 crystal structures reported here, together with 11 previously reported MsRecA structures, provide further elaboration of the relation between the pitch of the ;inactive' RecA filament, the orientation of the C-terminal domain with respect to the main domain and the location of the switch residue. The low-temperature structures define one extreme of the range of positions the C-terminal domain can occupy. The movement of the C-terminal domain is correlated with those of the LexA-binding loop and the loop that connects the main and the N-terminal domains. These elements of molecular plasticity are made use of in the transition to the ;active' filament, as evidenced by the recently reported structures of RecA-DNA complexes. The available structures of RecA resulting from X-ray and electron-microscopic studies appear to represent different stages in the trajectory of the allosteric transformations of the RecA filament. The work reported here contributes to the description of the early stages of this trajectory and provides insight into structures relevant to the later stages.

CancerLectinDB: a database of lectins relevant to cancer.

The role of lectins in mediating cancer metastasis, apoptosis as well as various other signaling events has been well established in the past few years. Data on various aspects of the role of lectins in cancer is being accumulated at a rapid pace. The data on lectins available in the literature is so diverse, that it becomes difficult and time-consuming, if not impossible to comprehend the advances in various areas and obtain the maximum benefit. Not only do the lectins vary significantly in their individual functional roles, but they are also diverse in their sequences, structures, binding site architectures, quaternary structures, carbohydrate affinities and specificities as well as their potential applications. An organization of these seemingly independent data into a common framework is essential in order to achieve effective use of all the data towards understanding the roles of different lectins in different aspects of cancer and any resulting applications. An integrated knowledge base (CancerLectinDB) together with appropriate analytical tools has therefore been developed for lectins relevant for any aspect of cancer, by collating and integrating diverse data. This database is unique in terms of providing sequence, structural, and functional annotations for lectins from all known sources in cancer and is expected to be a useful addition to the number of glycan related resources now available to the community. The database has been implemented using MySQL on a Linux platform and web-enabled using Perl-CGI and Java tools. Data for individual lectins pertain to taxonomic, biochemical, domain architecture, molecular sequence and structural details as well as carbohydrate specificities. Extensive links have also been provided for relevant bioinformatics resources and analytical tools. Availability of diverse data integrated into a common framework is expected to be of high value for various studies on lectin cancer biology. CancerLectinDB can be accessed through http://proline.physics.iisc.ernet.in/cancerdb .

Metabolome based reaction graphs of M. tuberculosis and M. leprae: a comparative network analysis.

BACKGROUND: Several types of networks, such as transcriptional, metabolic or protein-protein interaction networks of various organisms have been constructed, that have provided a variety of insights into metabolism and regulation. Here, we seek to exploit the reaction-based networks of three organisms for comparative genomics. We use concepts from spectral graph theory to systematically determine how differences in basic metabolism of organisms are reflected at the systems level and in the overall topological structures of their metabolic networks. METHODOLOGY/PRINCIPAL FINDINGS: Metabolome-based reaction networks of Mycobacterium tuberculosis, Mycobacterium leprae and Escherichia coli have been constructed based on the KEGG LIGAND database, followed by graph spectral analysis of the network to identify hubs as well as the sub-clustering of reactions. The shortest and alternate paths in the reaction networks have also been examined. Sub-cluster profiling demonstrates that reactions of the mycolic acid pathway in mycobacteria form a tightly connected sub-cluster. Identification of hubs reveals reactions involving glutamate to be central to mycobacterial metabolism, and pyruvate to be at the centre of the E. coli metabolome. The analysis of shortest paths between reactions has revealed several paths that are shorter than well established pathways. CONCLUSIONS: We conclude that severe downsizing of the leprae genome has not significantly altered the global structure of its reaction network but has reduced the total number of alternate paths between its reactions while keeping the shortest paths between them intact. The hubs in the mycobacterial networks that are absent in the human metabolome can be explored as potential drug targets. This work demonstrates the usefulness of constructing metabolome based networks of organisms and the feasibility of their analyses through graph spectral methods. The insights obtained from such studies provide a broad overview of the similarities and differences between organisms, taking comparative genomics studies to a higher dimension.

Diagnosis and therapy of oral squamous cell carcinoma.

Oral squamous cell carcinoma ranks among the top ten most common cancers worldwide. Despite the success in diagnosis and therapy during the past 30 years, oral squamous cell carcinoma still belongs to the tumor types with a very unfavorable prognosis. In an effort to identify genomic alterations with prognostic relevance, we applied the comparative genomic hybridization technique on oral squamous cell carcinoma. The tumors exhibited from five up to 47 DNA copy number alterations, indicating a considerable degree of genomic imbalance. Out of 35 tumors, 19 showed a gain of chromosome band 7p12. Genomic imbalances were investigated by hierarchical cluster analysis and clustered image mapping to investigate whether genomic profiles correlate with clinical data. Results of the present investigation show that profiling of genomic imbalances in general, and especially of the epidermal growth factor receptor (EGFR) on 7p12, may be suitable as prognostic factors. In order to identify small-molecule inhibitors for EGFR, we established a database of 531 natural compounds derived from medicinal plants used in traditional Chinese medicine. Candidate compounds were identified by correlation analysis using the Kendall tau-test of IC50 values of tumor cell lines and microarray-based EGFR mRNA expression. Further validation was performed by molecular docking studies using the AutoDock program with the crystal structure of EGFR tyrosine kinase domain as docking template. We estimate these results will be a further step toward the ultimate goal of individualized, patient-adapted tumor treatment based on tumor molecular profiling.

Comparison of protein structures by growing neighborhood alignments.

BACKGROUND: Design of protein structure comparison algorithm is an important research issue, having far reaching implications. In this article, we describe a protein structure comparison scheme, which is capable of detecting correct alignments even in difficult cases, e.g. non-topological similarities. The proposed method computes protein structure alignments by comparing, small substructures, called neighborhoods. Two different types of neighborhoods, sequence and structure, are defined, and two algorithms arising out of the scheme are detailed. A new method for computing equivalences having non-topological similarities from pairwise similarity score is described. A novel and fast technique for comparing sequence neighborhoods is also developed. RESULTS: The experimental results show that the current programs show better performance on Fischer and Novotny's benchmark datasets, than state of the art programs, e.g. DALI, CE and SSM. Our programs were also found to calculate correct alignments for proteins with huge amount of indels and internal repeats. Finally, the sequence neighborhood based program was used in extensive fold and non-topological similarity detection experiments. The accuracy of the fold detection experiments with the new measure of similarity was found to be similar or better than that of the standard algorithm CE. CONCLUSION: A new scheme, resulting in two algorithms, have been developed, implemented and tested. The programs developed are accessible at http://mllab.csa.iisc.ernet.in/mp2/runprog.html.

A K52Q substitution in the globular domain of histone H1t modulates its nucleosome binding properties.

A comparison of the globular domain sequences of the somatic H1d and testis-specific H1t revealed a single substitution of lysine 52 in H1d to glutamine 54 in H1t, which is one of the three crucial residues within the second DNA binding site. The globular domains of both histones were modeled using the crystal structure of chicken GH5 as a template and was also docked onto the nucleosome structure. The glutamine residue in histone H1t forms a hydrogen bond with main chain carbonyl of methionine-52 (in H1t) and is spatially oriented away from the nucleosome dyad axis. A consequence of this change was a lower affinity of recombinant histone H1t towards Four-way junction DNA and reconstituted 5S mononucleosomes. When Gln-54 in Histone H1t was mutated to lysine, its binding affinity towards DNA substrates was comparable to that of histone H1d. The differential binding of histones H1d and H1t towards reconstituted mononucleosomes was also reflected in the chromatosome-stop assay.

Structure of Mycobacterium tuberculosis RuvA, a protein involved in recombination.

The process of recombinational repair is crucial for maintaining genomic integrity and generating biological diversity. In association with RuvB and RuvC, RuvA plays a central role in processing and resolving Holliday junctions, which are a critical intermediate in homologous recombination. Here, the cloning, purification and structure determination of the RuvA protein from Mycobacterium tuberculosis (MtRuvA) are reported. Analysis of the structure and comparison with other known RuvA proteins reveal an octameric state with conserved subunit-subunit interaction surfaces, indicating the requirement of octamer formation for biological activity. A detailed analysis of plasticity in the RuvA molecules has led to insights into the invariant and variable regions, thus providing a framework for understanding regional flexibility in various aspects of RuvA function.

Lectindb: a plant lectin database.

Lectins, a class of carbohydrate-binding proteins, are now widely recognized to play a range of crucial roles in many cell-cell recognition events triggering several important cellular processes. They encompass different members that are diverse in their sequences, structures, binding site architectures, quaternary structures, carbohydrate affinities, and specificities as well as their larger biological roles and potential applications. It is not surprising, therefore, that the vast amount of experimental data on lectins available in the literature is so diverse, that it becomes difficult and time consuming, if not impossible to comprehend the advances in various areas and obtain the maximum benefit. To achieve an effective use of all the data toward understanding the function and their possible applications, an organization of these seemingly independent data into a common framework is essential. An integrated knowledge base ( Lectindb, http://nscdb.bic.physics.iisc.ernet.in ) together with appropriate analytical tools has therefore been developed initially for plant lectins by collating and integrating diverse data. The database has been implemented using MySQL on a Linux platform and web-enabled using PERL-CGI and Java tools. Data for each lectin pertain to taxonomic, biochemical, domain architecture, molecular sequence, and structural details as well as carbohydrate and hence blood group specificities. Extensive links have also been provided for relevant bioinformatics resources and analytical tools. Availability of diverse data integrated into a common framework is expected to be of high value not only for basic studies in lectin biology but also for basic studies in pursuing several applications in biotechnology, immunology, and clinical practice, using these molecules.

Crystallographic identification of an ordered C-terminal domain and a second nucleotide-binding site in RecA: new insights into allostery.

RecA protein is a crucial and central component of the homologous recombination and DNA repair machinery. Despite numerous studies on the protein, several issues concerning its action, including the allosteric regulation mechanism have remained unclear. Here we report, for the first time, a crystal structure of a complex of Mycobacterium smegmatis RecA (MsRecA) with dATP, which exhibits a fully ordered C-terminal domain, with a second dATP molecule bound to it. ATP binding is an essential step for all activities of RecA, since it triggers the formation of active nucleoprotein filaments. In the crystal filament, dATP at the first site communicates with a dATP of the second site of an adjacent subunit, through conserved residues, suggesting a new route for allosteric regulation. In addition, subtle but definite changes observed in the orientation of the nucleotide at the first site and in the positions of the segment preceding loop L2 as well as in the segment 102-105 situated between the 2 nt, all appear to be concerted and suggestive of a biological role for the second bound nucleotide.