Molecular Characterisation of Soybean Osmotins and Their Involvement in Drought Stress Response.

Osmotins are multifunctional proteins belonging to the thaumatin-like family related to plant stress responses. To better understand the functions of soybean osmotins in drought stress response, the current study presents the characterisation of four previously described proteins and a novel putative soybean osmotin (GmOLPa-like). Gene and protein structure as well as gene expression analyses were conducted on different tissues and developmental stages of two soybean cultivars with varying dehydration sensitivities (BR16 and EMB48 are highly and slightly sensitive, respectively). The analysed osmotin sequences share the conserved amino acid signature and 3D structure of the thaumatin-like family. Some differences were observed in the conserved regions of protein sequences and in the electrostatic surface potential. P21-like present the most similar electrostatic potential to osmotins previously characterised as promoters of drought tolerance in Nicotiana tabacum and Solanum nigrum. Gene expression analysis indicated that soybean osmotins were differentially expressed in different organs (leaves and roots), developmental stages (R1 and V3), and cultivars in response to dehydration. In addition, under dehydration conditions, the highest level of gene expression was detected for GmOLPa-like and P21-like osmotins in the leaves and roots, respectively, of the less drought sensitive cultivar. Altogether, the results suggest an involvement of these genes in drought stress tolerance.

Theoretical characterization of the shikimate 5-dehydrogenase reaction from Mycobacterium tuberculosis by hybrid QC/MM simulations and quantum chemical descriptors.

In this study, we have investigated the enzyme shikimate 5-dehydrogenase from the causative agent of tuberculosis, Mycobacterium tuberculosis. We have employed a mixture of computational techniques, including molecular dynamics, hybrid quantum chemical/molecular mechanical potentials, relaxed surface scans, quantum chemical descriptors and free-energy simulations, to elucidate the enzyme's reaction pathway. Overall, we find a two-step mechanism, with a single transition state, that proceeds by an energetically uphill hydride transfer, followed by an energetically downhill proton transfer. Our mechanism and calculated free energy barrier for the reaction, 64.9 kJ mol- 1, are in good agreement with those predicted from experiment. An analysis of quantum chemical descriptors along the reaction pathway indicated a possibly important, yet currently unreported, role of the active site threonine residue, Thr65.

A selective method for optimizing ensemble docking-based experiments on an InhA Fully-Flexible receptor model.

BACKGROUND: In the rational drug design process, an ensemble of conformations obtained from a molecular dynamics simulation plays a crucial role in docking experiments. Some studies have found that Fully-Flexible Receptor (FFR) models predict realistic binding energy accurately and improve scoring to enhance selectiveness. At the same time, methods have been proposed to reduce the high computational costs involved in considering the explicit flexibility of proteins in receptor-ligand docking. This study introduces a novel method to optimize ensemble docking-based experiments by reducing the size of an InhA FFR model at docking runtime and scaling docking workflow invocations on cloud virtual machines. RESULTS: First, in order to find the most affordable cost-benefit pool of virtual machines, we evaluated the performance of the docking workflow invocations in different configurations of Azure instances. Second, we validated the gains obtained by the proposed method based on the quality of the Reduced Fully-Flexible Receptor (RFFR) models produced using AutoDock4.2. The analyses show that the proposed method reduced the model size by approximately 50% while covering at least 86% of the best docking results from the 74 ligands tested. Third, we tested our novel method using AutoDock Vina, a different docking software, and showed the positive accuracy achieved in the resulting RFFR models. Finally, our results demonstrated that the method proposed optimized ensemble docking experiments and is applicable to different docking software. In addition, it detected new binding modes, which would be unreachable if employing only the rigid structure used to generate the InhA FFR model. CONCLUSIONS: Our results showed that the selective method is a valuable strategy for optimizing ensemble docking-based experiments using different docking software. The RFFR models produced by discarding non-promising snapshots from the original model are accurately shaped for a larger number of ligands, and the elapsed time spent in the ensemble docking experiments are considerably reduced.

Activity of 2-(quinolin-4-yloxy)acetamides in Mycobacterium tuberculosis clinical isolates and identification of their molecular target by whole-genome sequencing.

The 2-(quinolin-4-yloxy)acetamides (QOAs) have been reported to be promising molecules for tuberculosis treatment. Recent studies demonstrated their potent antimycobacterial activity, biological stability and synergism with rifampicin. The identification of the molecular target is an essential step towards the development of a novel drug candidate. Here, we report the target identification of the QOAs. We found that these compounds are active against Mycobacterium tuberculosis clinical isolates resistant to isoniazid, rifampicin, ethambutol, streptomycin and ethionamide. The initial evidence that DNA gyrase might be the target of QOAs, based on high minimum inhibitory concentration (MIC) values against ofloxacin-resistant clinical isolates and structural similarities with fluoroquinolones, was discarded by experiments performed with M. tuberculosis GyrA point mutant, DNA gyrase supercoiling inhibition assay and overexpression of DNA gyrase. We selected spontaneous mutants for our lead compound 21 and observed that these strains were also resistant to all QOA derivatives. The genomes of the spontaneous mutants were sequenced, and the results revealed a single mutation in qcrB gene (T313A), which indicates that the QOAs target the cytochrome bc1 complex. The protein-compound interaction was further investigated by molecular docking. These findings reinforce the relevance of these compounds as promising candidates for the treatment of multidrug-resistant tuberculosis.

Functional, thermodynamics, structural and biological studies of in silico-identified inhibitors of Mycobacterium tuberculosis enoyl-ACP(CoA) reductase enzyme.

Novel chemotherapeutics agents are needed to kill Mycobacterium tuberculosis, the main causative agent of tuberculosis (TB). The M. tuberculosis 2-trans-enoyl-ACP(CoA) reductase enzyme (MtInhA) is the druggable bona fide target of isoniazid. New chemotypes were previously identified by two in silico approaches as potential ligands to MtInhA. The inhibition mode was determined by steady-state kinetics for seven compounds that inhibited MtInhA activity. Dissociation constant values at different temperatures were determined by protein fluorescence spectroscopy. van't Hoff analyses of ligand binding to MtInhA:NADH provided the thermodynamic signatures of non-covalent interactions (ΔH°, ΔS°, ΔG°). Phenotypic screening showed that five compounds inhibited in vitro growth of M. tuberculosis H37Rv strain. Labio_16 and Labio_17 compounds also inhibited the in vitro growth of PE-003 multidrug-resistant strain. Cytotoxic effects on Hacat, Vero and RAW 264.7 cell lines were assessed for the latter two compounds. The Labio_16 was bacteriostatic and Labio_17 bactericidal in an M. tuberculosis-infected macrophage model. In Zebrafish model, Labio_16 showed no cardiotoxicity whereas Labio_17 showed dose-dependent cardiotoxicity. Accordingly, a model was built for the MtInhA:NADH:Labio_16 ternary complex. The results show that the Labio_16 compound is a direct inhibitor of MtInhA, and it may represent a hit for the development of chemotherapeutic agents to treat TB.

Piperazine derivatives: synthesis, inhibition of the Mycobacterium tuberculosis enoyl-acyl carrier protein reductase and SAR studies.

The Mycobacterium tuberculosis NADH-dependent enoyl-acyl carrier protein reductase (MtInhA) catalyzes hydride transfer to long-chain enoyl thioester substrates. MtInhA is a member of the mycobacterial type II dissociated fatty acid biosynthesis system, and is the bona fide target for isoniazid, the most prescribed drug for tuberculosis treatment. Here, a series of piperazine derivatives was synthesized and screened as MtInhA inhibitors, which resulted in the identification of compounds with IC50 values in the submicromolar range. A structure-activity relationship (SAR) evaluation indicated the importance of the chemical environment surrounding the carbonyl group for inhibition. In addition, the structure of one selected compound was supported by crystallographic studies, and experimental geometrical values were compared with semi-empirical quantum chemical calculations. Furthermore, the mode of inhibition and inhibitory dissociation constants were determined for the nine most active compounds. These findings suggest that these 9H-fluoren-9-yl-piperazine-containing compounds interact with MtInhA at the enoyl thioester (2-trans-dodecenoyl-CoA) substrate binding site.

Biochemical and cellular analysis of human variants of the DYT1 dystonia protein, TorsinA/TOR1A.

Early-onset dystonia is associated with the deletion of one of a pair of glutamic acid residues (c.904_906delGAG/c.907_909delGAG; p.Glu302del/Glu303del; ΔE 302/303) near the carboxyl-terminus of torsinA, a member of the AAA(+) protein family that localizes to the endoplasmic reticulum lumen and nuclear envelope. This deletion commonly underlies early-onset DYT1 dystonia. While the role of the disease-causing mutation, torsinAΔE, has been established through genetic association studies, it is much less clear whether other rare human variants of torsinA are pathogenic. Two missense variations have been described in single patients: R288Q (c.863G>A; p.Arg288Gln; R288Q) identified in a patient with onset of severe generalized dystonia and myoclonus since infancy and F205I (c.613T>A, p.Phe205Ile; F205I) in a psychiatric patient with late-onset focal dystonia. In this study, we have undertaken a series of analyses comparing the biochemical and cellular effects of these rare variants to torsinAΔE and wild-type (wt) torsinA to reveal whether there are common dysfunctional features. The results revealed that the variants, R288Q and F205I, are more similar in their properties to torsinAΔE protein than to torsinAwt. These findings provide functional evidence for the potential pathogenic nature of these rare sequence variants in the TOR1A gene, thus implicating these pathologies in the development of dystonia.

Biochemical characterization of recombinant nucleoside hydrolase from Mycobacterium tuberculosis H37Rv.

Tuberculosis (TB) is a major global health threat. There is a need for the development of more efficient drugs for the sterilization of the disease's causative agent, Mycobacterium tuberculosis (MTB). A more comprehensive understanding of the bacilli's nucleotide metabolic pathways could aid in the development of new anti-mycobacterial drugs. Here we describe expression and purification of recombinant iunH-encoded nucleoside hydrolase from MTB (MtIAGU-NH). Glutaraldehyde cross-linking results indicate that MtIAGU-NH predominates as a monomer, presenting varied oligomeric states depending upon binding of ligands. Steady-state kinetics results show that MtIAGU-NH has broad substrate specificity, accepting inosine, adenosine, guanosine, and uridine as substrates. Inosine and adenosine displayed positive homotropic cooperativity kinetics, whereas guanosine and uridine displayed hyperbolic saturation curves. Measurements of kinetics of ribose binding to MtIAGU-NH by fluorescence spectroscopy suggest two pre-existing forms of enzyme prior to ligand association. The intracellular concentrations of inosine, uridine, hypoxanthine, and uracil were determined and thermodynamic parameters estimated. Thermodynamic activation parameters (Ea, ΔG(#), ΔS(#), ΔH(#)) for MtIAGU-NH-catalyzed chemical reaction are presented. Results from mass spectrometry, isothermal titration calorimetry (ITC), pH-rate profile experiment, multiple sequence alignment, and molecular docking experiments are also presented. These data should contribute to our understanding of the biological role played by MtIAGU-NH.

wFReDoW: a cloud-based web environment to handle molecular docking simulations of a fully flexible receptor model.

Molecular docking simulations of fully flexible protein receptor (FFR) models are coming of age. In our studies, an FFR model is represented by a series of different conformations derived from a molecular dynamic simulation trajectory of the receptor. For each conformation in the FFR model, a docking simulation is executed and analyzed. An important challenge is to perform virtual screening of millions of ligands using an FFR model in a sequential mode since it can become computationally very demanding. In this paper, we propose a cloud-based web environment, called web Flexible Receptor Docking Workflow (wFReDoW), which reduces the CPU time in the molecular docking simulations of FFR models to small molecules. It is based on the new workflow data pattern called self-adaptive multiple instances (P-SaMIs) and on a middleware built on Amazon EC2 instances. P-SaMI reduces the number of molecular docking simulations while the middleware speeds up the docking experiments using a High Performance Computing (HPC) environment on the cloud. The experimental results show a reduction in the total elapsed time of docking experiments and the quality of the new reduced receptor models produced by discarding the nonpromising conformations from an FFR model ruled by the P-SaMI data pattern.

Context-based preprocessing of molecular docking data.

BACKGROUND: Data preprocessing is a major step in data mining. In data preprocessing, several known techniques can be applied, or new ones developed, to improve data quality such that the mining results become more accurate and intelligible. Bioinformatics is one area with a high demand for generation of comprehensive models from large datasets. In this article, we propose a context-based data preprocessing approach to mine data from molecular docking simulation results. The test cases used a fully-flexible receptor (FFR) model of Mycobacterium tuberculosis InhA enzyme (FFR_InhA) and four different ligands. RESULTS: We generated an initial set of attributes as well as their respective instances. To improve this initial set, we applied two selection strategies. The first was based on our context-based approach while the second used the CFS (Correlation-based Feature Selection) machine learning algorithm. Additionally, we produced an extra dataset containing features selected by combining our context strategy and the CFS algorithm. To demonstrate the effectiveness of the proposed method, we evaluated its performance based on various predictive (RMSE, MAE, Correlation, and Nodes) and context (Precision, Recall and FScore) measures. CONCLUSIONS: Statistical analysis of the results shows that the proposed context-based data preprocessing approach significantly improves predictive and context measures and outperforms the CFS algorithm. Context-based data preprocessing improves mining results by producing superior interpretable models, which makes it well-suited for practical applications in molecular docking simulations using FFR models.

Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data.

BACKGROUND: This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. RESULTS: The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. CONCLUSIONS: We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor.

Conformational changes in 2-trans-enoyl-ACP (CoA) reductase (InhA) from M. tuberculosis induced by an inorganic complex: a molecular dynamics simulation study.

InhA, the NADH-dependent 2-trans-enoyl-ACP reductase enzyme from Mycobacterium tuberculosis (MTB), is involved in the biosynthesis of mycolic acids, the hallmark of mycobacterial cell wall. InhA has been shown to be the primary target of isoniazid (INH), one of the oldest synthetic antitubercular drugs. INH is a prodrug which is biologically activated by the MTB catalase-peroxidase KatG enzyme. The activation reaction promotes the formation of an isonicotinyl-NAD adduct which inhibits the InhA enzyme, resulting in reduction of mycolic acid biosynthesis. As a result of rational drug design efforts to design alternative drugs capable of inhibiting MTB's InhA, the inorganic complex pentacyano(isoniazid)ferrate(II) (PIF) was developed. PIF inhibited both wild-type and INH-resistant Ile21Val mutants of InhA and this inactivation did not require activation by KatG. Since no three-dimensional structure of the InhA-PIF complex is available to confirm the binding mode and to assess the molecular interactions with the protein active site residues, here we report the results of molecular dynamics simulations of PIF interaction with InhA. We found that PIF strongly interacts with InhA and that these interactions lead to macromolecular instabilities reflected in the long time necessary for simulation convergence. These instabilities were mainly due to perturbation of the substrate binding loop, particularly the partial denaturation of helices α6 and α7. We were also able to correlate the changes in the SASAs of Trp residues with the recent spectrofluorimetric investigation of the InhA-PIF complex and confirm their suggestion that the changes in fluorescence are due to InhA conformational changes upon PIF binding. The InhA-PIF association is very strong in the first 20.0 ns, but becomes very week at the end of the simulation, suggesting that the PIF binding mode we simulated may not reflect that of the actual InhA-PIF complex.

FReDoWS: a method to automate molecular docking simulations with explicit receptor flexibility and snapshots selection.

BACKGROUND: In silico molecular docking is an essential step in modern drug discovery when driven by a well defined macromolecular target. Hence, the process is called structure-based or rational drug design (RDD). In the docking step of RDD the macromolecule or receptor is usually considered a rigid body. However, we know from biology that macromolecules such as enzymes and membrane receptors are inherently flexible. Accounting for this flexibility in molecular docking experiments is not trivial. One possibility, which we call a fully-flexible receptor model, is to use a molecular dynamics simulation trajectory of the receptor to simulate its explicit flexibility. To benefit from this concept, which has been known since 2000, it is essential to develop and improve new tools that enable molecular docking simulations of fully-flexible receptor models. RESULTS: We have developed a Flexible-Receptor Docking Workflow System (FReDoWS) to automate molecular docking simulations using a fully-flexible receptor model. In addition, it includes a snapshot selection feature to facilitate acceleration the virtual screening of ligands for well defined disease targets. FReDoWS usefulness is demonstrated by investigating the docking of four different ligands to flexible models of Mycobacterium tuberculosis' wild type InhA enzyme and mutants I21V and I16T. We find that all four ligands bind effectively to this receptor as expected from the literature on similar, but wet experiments. CONCLUSIONS: A work that would usually need the manual execution of many computer programs, and the manipulation of thousands of files, was efficiently and automatically performed by FReDoWS. Its friendly interface allows the user to change the docking and execution parameters. Besides, the snapshot selection feature allowed the acceleration of docking simulations. We expect FReDoWS to help us explore more of the role flexibility plays in receptor-ligand interactions. FReDoWS can be made available upon request to the authors.

Effect of the explicit flexibility of the InhA enzyme from Mycobacterium tuberculosis in molecular docking simulations.

BACKGROUND: Protein/receptor explicit flexibility has recently become an important feature of molecular docking simulations. Taking the flexibility into account brings the docking simulation closer to the receptors' real behaviour in its natural environment. Several approaches have been developed to address this problem. Among them, modelling the full flexibility as an ensemble of snapshots derived from a molecular dynamics simulation (MD) of the receptor has proved very promising. Despite its potential, however, only a few studies have employed this method to probe its effect in molecular docking simulations. We hereby use ensembles of snapshots obtained from three different MD simulations of the InhA enzyme from M. tuberculosis (Mtb), the wild-type (InhA_wt), InhA_I16T, and InhA_I21V mutants to model their explicit flexibility, and to systematically explore their effect in docking simulations with three different InhA inhibitors, namely, ethionamide (ETH), triclosan (TCL), and pentacyano(isoniazid)ferrate(II) (PIF). RESULTS: The use of fully-flexible receptor (FFR) models of InhA_wt, InhA_I16T, and InhA_I21V mutants in docking simulation with the inhibitors ETH, TCL, and PIF revealed significant differences in the way they interact as compared to the rigid, InhA crystal structure (PDB ID: 1ENY). In the latter, only up to five receptor residues interact with the three different ligands. Conversely, in the FFR models this number grows up to an astonishing 80 different residues. The comparison between the rigid crystal structure and the FFR models showed that the inclusion of explicit flexibility, despite the limitations of the FFR models employed in this study, accounts in a substantial manner to the induced fit expected when a protein/receptor and ligand approach each other to interact in the most favourable manner. CONCLUSIONS: Protein/receptor explicit flexibility, or FFR models, represented as an ensemble of MD simulation snapshots, can lead to a more realistic representation of the induced fit effect expected in the encounter and proper docking of receptors to ligands. The FFR models of InhA explicitly characterizes the overall movements of the amino acid residues in helices, strands, loops, and turns, allowing the ligand to properly accommodate itself in the receptor's binding site. Utilization of the intrinsic flexibility of Mtb's InhA enzyme and its mutants in virtual screening via molecular docking simulation may provide a novel platform to guide the rational or dynamical-structure-based drug design of novel inhibitors for Mtb's InhA. We have produced a short video sequence of each ligand (ETH, TCL and PIF) docked to the FFR models of InhA_wt. These videos are available at http://www.inf.pucrs.br/~osmarns/LABIO/Videos_Cohen_et_al_19_07_2011.htm.

Mining the protein data bank with CReF to predict approximate 3-D structures of polypeptides.

n this paper we describe CReF, a Central Residue Fragment-based method to predict approximate 3-D structures of polypeptides by mining the Protein Data Bank (PDB). The approximate predicted structures are good enough to be used as starting conformations in refinement procedures employing state-of-the-art molecular mechanics methods such as molecular dynamics simulations. CReF is very fast and we illustrate its efficacy in three case studies of polypeptides whose sizes vary from 34 to 70 amino acids. As indicated by the RMSD values, our initial results show that the predicted structures adopt the expected fold, similar to the experimental ones.

Mining flexible-receptor docking experiments to select promising protein receptor snapshots.

BACKGROUND: Molecular docking simulation is the Rational Drug Design (RDD) step that investigates the affinity between protein receptors and ligands. Typically, molecular docking algorithms consider receptors as rigid bodies. Receptors are, however, intrinsically flexible in the cellular environment. The use of a time series of receptor conformations is an approach to explore its flexibility in molecular docking computer simulations, but it is extensively time-consuming. Hence, selection of the most promising conformations can accelerate docking experiments and, consequently, the RDD efforts. RESULTS: We previously docked four ligands (NADH, TCL, PIF and ETH) to 3,100 conformations of the InhA receptor from M. tuberculosis. Based on the receptor residues-ligand distances we preprocessed all docking results to generate appropriate input to mine data. Data preprocessing was done by calculating the shortest interatomic distances between the ligand and the receptor's residues for each docking result. They were the predictive attributes. The target attribute was the estimated free-energy of binding (FEB) value calculated by the AutodDock3.0.5 software. The mining inputs were submitted to the M5P model tree algorithm. It resulted in short and understandable trees. On the basis of the correlation values, for NADH, TCL and PIF we obtained more than 95% correlation while for ETH, only about 60%. Post processing the generated model trees for each of its linear models (LMs), we calculated the average FEB for their associated instances. From these values we considered a LM as representative if its average FEB was smaller than or equal the average FEB of the test set. The instances in the selected LMs were considered the most promising snapshots. It totalized 1,521, 1,780, 2,085 and 902 snapshots, for NADH, TCL, PIF and ETH respectively. CONCLUSIONS: By post processing the generated model trees we were able to propose a criterion of selection of linear models which, in turn, is capable of selecting a set of promising receptor conformations. As future work we intend to go further and use these results to elaborate a strategy to preprocess the receptors 3-D spatial conformation in order to predict FEB values. Besides, we intend to select other compounds, among the million catalogued, that may be promising as new drug candidates for our particular protein receptor target.

Evaluation of the impact of functional diversification on Poaceae, Brassicaceae, Fabaceae, and Pinaceae alcohol dehydrogenase enzymes.

The plant alcohol dehydrogenases (ADHs) have been intensively studied in the last years in terms of phylogeny and they have been widely used as a molecular marker. However, almost no information about their three-dimensional structure is available. Several studies point to functional diversification of the ADH, with evidence of its importance, in different organisms, in the ethanol, norepinephrine, dopamine, serotonin, and bile acid metabolism. Computational results demonstrated that in plants these enzymes are submitted to a functional diversification process, which is reinforced by experimental studies indicating distinct enzymatic functions as well as recruitment of specific genes in different tissues. The main objective of this article is to establish a correlation between the functional diversification occurring in the plant alcohol dehydrogenase family and the three-dimensional structures predicted for 17 ADH belonging to Poaceae, Brassicaceae, Fabaceae, and Pinaceae botanical families. Volume, molecular weight and surface areas are not markedly different among them. Important electrostatic and pI differences were observed with the residues responsible for some of them identified, corroborating the function diversification hypothesis. These data furnish important background information for future specific structure-function and evolutionary investigations.

Sequence and structural aspects of the functional diversification of plant alcohol dehydrogenases.

The glycolytic proteins in plants are coded by small multigene families, which provide an interesting contrast to the high copy number of gene families studied to date. The alcohol dehydrogenase (Adh) genes encode glycolytic enzymes that have been characterized in some plant families. Although the amino acid sequences of zinc-containing long-chain ADHs are highly conserved, the metabolic function of this enzyme is variable. They also have different patterns of expression and are submitted to differences in nonsynonymous substitution rates between gene copies. It is possible that the Adh copies have been retained as a consequence of adaptative amino acid replacements which have conferred subtle changes in function. Phylogenetic analysis indicates that there have been a number of separate duplication events within angiosperms, and that genes labeled Adh1, Adh2 and Adh3 in different groups may not be homologous. Nonsynonymous/synonymous ratios yielded no signs of positive selection. However, the coefficients of functional divergence (theta) estimated between the Adh1 and Adh2 gene groups indicate statistically significant site-specific shift of evolutionary rates between them, as well as between those of different botanical families, suggesting that altered functional constraints may have taken place at some amino acid residues after their diversification. The theoretical three-dimensional structure of the alcohol dehydrogenase from Arabis blepharophylla was constructed and verified to be stereochemically valid.

Molecular dynamics simulation studies of the wild-type, I21V, and I16T mutants of isoniazid-resistant Mycobacterium tuberculosis enoyl reductase (InhA) in complex with NADH: toward the understanding of NADH-InhA different affinities.

The increasing prevalence of tuberculosis in many areas of the world, associated with the rise in drug-resistant Mycobacterium tuberculosis (MTB) strains, presents a major threat to global health. InhA, the enoyl-ACP reductase from MTB, catalyzes the nicotinamide adenine dinucleotide (NADH)-dependent reduction of long-chain trans-2-enoyl-ACP fatty acids, an intermediate in mycolic acid biosynthesis. Mutations in the structural gene for InhA are associated with isoniazid resistance in vivo due to a reduced affinity for NADH, suggesting that the mechanism of drug resistance may be related to specific interactions between enzyme and cofactor within the NADH binding site. To compare the molecular events underlying ligand affinity in the wild-type, I21V, and I16T mutant enzymes and to identify the molecular aspects related to resistance, molecular dynamics simulations of fully solvated NADH-InhA (wild-type and mutants) were performed. Although very flexible, in the wild-type InhA-NADH complex, the NADH molecule keeps its extended conformation firmly bound to the enzyme's binding site. In the mutant complexes, the NADH pyrophosphate moiety undergoes considerable conformational changes, reducing its interactions with its binding site and probably indicating the initial phase of ligand expulsion from the cavity. This study should contribute to our understanding of specific molecular mechanisms of drug resistance, which is central to the design of more potent antimycobacterial agents for controlling tuberculosis.

Plasmodium falciparum histidine-rich protein II binds to actin, phosphatidylinositol 4,5-bisphosphate and erythrocyte ghosts in a pH-dependent manner and undergoes coil-to-helix transitions in anionic micelles.

The recombinant histidine-rich protein II (HRPII) from Plasmodium falciparum was shown to bind actin and phosphatidylinositol 4,5-bisphosphate (PIP(2)) in vitro in a pH-dependent manner, very similar to hisactophilin, an actin-binding protein from ameba. Binding of HRPII to actin and PIP(2) occurred at pH 6.0 and 6.5, but not above pH 7.0. Circular dichroism (CD) spectroscopy confirmed that HRPII interacts with actin at pH below 7.0, as judged by the changes induced in the secondary structure of the HRPII/actin mixture. Further CD analysis demonstrated that HRPII adopts a predominantly alpha-helical conformation with anionic micelles of PIP(2) and SDS, but not with neutral micelles of phosphatidylcholine (PC), a feature that is common to many actin-binding proteins involved in cytoskeleton remodeling. Similarly to hisactophilin, a GFP-HRPII fusion protein shuttled from the cytoplasm to the nucleus of HeLa cells as the cellular pH was lowered from 8.0 to 6.0. HeLa cells transfected with the HRPII gene showed increased levels of histidine-rich proteins (HRPs) in the soluble cell fraction at pH 8.0. At pH 6.0, however, HRPs were detected mainly in the insoluble cell fraction. Interestingly, we found that HRPII binds to human erythrocyte membranes at pH 6.0 and 6.5 but not at pH above 7.0. Our results point to remarkable similarities between HRPII, hisactophilin, and actin-binding proteins. Possible roles of the HRPII during Plasmodium infection are discussed in the light of these findings.