Osmar Norberto de Souza

Molecular dynamics simulations of a protein-protein dimer: particle-mesh Ewald electrostatic model yields far superior results to standard cutoff model.

In this article we present two 1000 ps molecular dynamics simulations on the rat micro-glutathione S-transferase dimeric enzyme in complex with the product 1-(S-glutathionyl)-2,4-dinitrobenzene, in a periodic box with explicit solvent molecules, and investigate the effect of long-range electrostatics models on the structure and dynamics of the dimer and its components. One simulation used the standard cutoff method (10A), whilst the other used the particle-mesh Ewald (PME) method. We monitored the root mean-square atomic deviation (RMSD) from the initial crystal structure to examine the convergence of both simulations, as well as several other structural parameters such as the distance between active sites, rigid body rotation between domains in subunits, radius of gyration, B-factors, number of hydrogen bonds and salt bridges and solvent-accessible surface area. For example, with the PME method, the dimer structure remains much closer to the initial crystallographic structure with an average RMSD of 1.3A +/- 0.1A and 1.0A +/- 0.1A for all heavy and backbone atoms, respectively, in the last 200 ps; the respective values for the cutoff simulation are 4.7A +/- 0.3A and 4.2A +/- 0.3A. The large deviations observed in the cutoff simulation severely affected the stability of the enzyme dimer and its complex with the bound product. This finding is contrary to that found in a similar study of the monomeric protein ubiquitin [Fox, T. & Kollman, P. A. Proteins Struct. Func. Genet. 25, 315-334 (1996)]. Unlike the earlier published work, the present study provides evidence that the standard cutoff method is not generally valid for the study of protein complexes, or their subunits.

Inherent DNA Curvature and Flexibility Correlate with TATA Box Functionality

Four 1.5 ns molecular dynamics (MD) simulations were performed on the d(GCTATAAAAGGG).d(CCCTTTTATAGC) double helix dodecamer bearing the Adenovirus major late promoter TATA element and three iso-composition mutants for which physical and biochemical data are available from the same laboratory. Three of these DNA sequences experimentally induce tight binding with the TATA box binding protein (TBP) and induce high transcription rates; the other DNA sequence induces much lower TBP binding and transcription. The x-ray crystal structures have previously shown that the duplex DNA in DNA-TBP complexes are highly bent. We performed and analyzed MD simulations for these four DNAs, whose experimental structures are not available, in order to address the issue of whether inherent DNA structure and flexibility play a role in establishing these observed preferences. A comparison of the experimental and simulated results demonstrated that DNA duplex sequence-dependent curvature and flexibility play a significant role in TBP recognition, binding, and transcriptional activation.

Slow-onset inhibition of 2-trans-enoyl-ACP (CoA) reductase from Mycobacterium tuberculosis by an inorganic complex.

Tuberculosis (TB) remains the leading cause of mortality due to a bacterial pathogen, Mycobacterium tuberculosis. The reemergence of tuberculosis as a potential public health threat, the high susceptibility of human immunodeficiency virus-infected persons to the disease, and the proliferation of multi-drug-resistant strains have created a need for the development of new antimycobacterial agents. Mycolic acids, the hallmark of mycobacteria, are high-molecular-weight alpha-alkyl, beta-hydroxy fatty acids, which appear mostly as bound esters in the mycobacterial cell wall. The product of the M. tuberculosis inhA structural gene (InhA) has been shown to be the primary target for isoniazid (INH), the most prescribed drug for active TB and prophylaxis. InhA was identified as an NADH-dependent enoyl-ACP reductase specific for long-chain enoyl thioesters. InhA is a member of the mycobacterial Type II fatty acid biosynthesis system, which elongates acyl fatty acid precursors of mycolic acids. Although the history of chemotherapeutic agent development demonstrates the remarkably successful tinkering of a few structural scaffolds, it also emphasizes the ongoing, cyclical need for innovation. The main focus of our contribution is on new data describing the rationale for the design of a pentacyano(isoniazid)ferrateII compound that requires no KatG-activation, its chemical characterization, in vitro activity studies against WT and INH-resistant I21V M. tuberculosis enoyl reductases, the slow-onset inhibition mechanism of WT InhA by the inorganic complex, and molecular modeling of its interaction with WT InhA. This inorganic complex represents a new class of lead compounds to the development of anti-tubercular agents aiming at inhibition of a validated target.

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

BackgroundMolecular 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.ResultsWe 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.ConclusionsBy 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.

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

BackgroundIn 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.ResultsWe 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.ConclusionsA 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.

Molecular modeling of pathogenesis-related proteins of family 5

The family of pathogenesis-related (PR) 5 proteins have diverse functions, and some of them are classified as thaumatins, osmotins, and inhibitors of α-amylase or trypsin. Although the specific function of many PR5 in plants is unknown, they are involved in the acquired systemic resistance and response to biotic stress, causing the inhibition of hyphal growth and reduction of spore germination, probably by a membrane permeabilization mechanism or by interaction with pathogen receptors. We have constructed three-dimensional models of four proteins belonging to the Rosaceae and Fagaceae botanical families by using the technique of comparative molecular modelling by homology. There are four main structural differences between all the PR5, corresponding to regions with replacements of amino acids. Folding and the secondary structures are very similar for all of them. However, the isoelectric point and charge distributions differ for earch protein.

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

BackgroundThis 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.ResultsThe 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.ConclusionsWe 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.

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.

A Hybrid Method for the Protein Structure Prediction Problem

This article provides the initial results of our effort to develop a hybrid prediction method, combining the principles of de novoand homology modeling, to help solve the protein three-dimensional (3-D) structure prediction problem. A target protein amino acid sequence is fragmented into many short contiguous fragments. Clustered short templates fragments, obtained from experimental protein structures in the Protein Data Bank (PDB), using the NCBI BLASTp program, were used for building an initial conformation, which was further refined by molecular dynamics simulations. We tested our method with the artificially designed alpha helical hairpin (PDB ID: 1ZDD) starting with its amino acids sequence only. The structure obtained with the proposed method is topologically a helical hairpin, with a C( RMSD of ~ 5.0 A with respect to the experimental PDB structure for all 34 amino acids residues, and only ~ 2.0 A when considering amino acids 1 to 22. We discuss further improvements to the method.

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.