Electrostatic properties of promoter recognized by E. coli RNA polymerase Esigma70

A comparative analysis of electrostatic patterns for 359 sigma70-specific promoters and 359 nonpromoter regions on electrostatic map of Escherichia coli genome was carried out. It was found that DNA is not a uniformly charged molecule. There are some local inhomogeneities in its electrostatic profile which correlate with promoter sequences. Electrostatic patterns of promoter DNAs can be specified due to the presence of some distinctive motifs which differ for different promoter groups and may be involved as signal elements in differential recognition of various promoters by the enzyme. Some specific electrostatic elements which are responsible for modulating promoter activities due to ADP-ribosylation of RNA polymerase alpha-subunit were found in far upstream regions of T4 phage early promoters and E. coli ribosomal promoters.     

Electrostatic potentials of DNA. Comparative analysis of promoter and nonpromoter nucleotide sequences.

Distribution of electrostatic potential of DNA fragments was evaluated. A method for calculation of electrostatic potential distribution based on Coulomb's law is proposed for long DNA fragments (approximately 1000 nucleotide pairs). For short DNA sequences, this technique provides a good correlation with the results obtained using Poisson-Boltzmann equation thus justifying its application in comparative studies for long DNA fragments. Calculation was performed for several DNA fragments from E. coli and bacteriophage T7 genomes containing promoter and nonpromoter regions. The results obtained indicate that coding regions are characterized by more homogeneous distribution of electrostatic potential whereas local inhomogeneity of DNA electrostatic profile is typical for promoter regions. The possible role of electrostatic interactions in RNA polymerase-promoter recognition is discussed.     

Electrostatic analysis of bacterial expansins

Expansins are a family of proteins with plant cell wall remodeling‐activity, which bind cell wall components through hydrophobic and electrostatic interactions. A shallow area on the surface of the protein serves as the polysaccharide binding site (PBS) and it is composed of conserved residues. However, electric charge differences on the opposite face of the PBS produce basic, neutral, or acidic proteins. An analysis of forty‐four bacterial expansins, homologues of BsEXLX1, revealed two main groups defined by: (a) the presence or absence of disulfide bonds; and (b) by the proteins isoelectric point (pI). We determined the location of the residues responsible for the pI on the structure of representative expansins. Our results suggest that the electric charge at the opposite site of the PBS may help in substrate differentiation among expansins from different species; in addition, electrostatic polarization between the front and the back of the molecule could affect expansin activity on cellulose. Proteins 2015; 83:215–223. © 2014 Wiley Periodicals, Inc.     

Fold predictions for bacterial genomes

Fold assignments for newly sequenced genomes belong to the most important and interesting applications of the booming field of protein structure prediction. We present a brief survey and a discussion of such assignments completed to date, using as an example several fold assignment projects for proteins from the Escherichia coli genome. This review focuses on steps that are necessary to go beyond the simple assignment projects and into the development of tools extending our understanding of functions of proteins in newly sequenced genomes. This paper also discusses several problems seldom addressed in the literature, such as the problem of domain prediction and complementary predictions (e.g., transmembrane regions and flexible regions) and cross-correlation of predictions from different servers. The influence of sequence and structure database growth on prediction success is also addressed. Finally, we discuss the perspectives of the field in the context of massive sequence and structure determination projects, as well as the development of novel prediction methods.     

Electrostatic properties of cryoimmunoglobulins

Inhibition of the cryoprecipitation of cryoimmunoglobulins by neutral salts suggests that intermolecular electrostatic (charge-charge) interactions are responsible for their abnormal solution properties. To test this hypothesis, H+ titration curves and isoelectric points were measured for two monoclonal IgG cryoglobulins (Ger and Muk) and compared with four normal (cold soluble) monoclonal IgG. The cryoglobulin Ger manifested values outside the range encountered for the other proteins. The partitioning of the IgG proteins was also examined in aqueous polyethylene glycol-dextran two-phase systems in the presence of both positive and negative salt-induced electrostatic potentials across the phase interface. Both cryoglobulins were found to behave as if they were more negatively charged than the noncryoglobulins. The experiments support the hypothesis that the differences in solubility behavior of monoclonal cryoglobulin and noncryoglobulin proteins are caused by differences in the electrostatic properties of the proteins.     

Large-scale predictions of gram-negative bacterial protein subcellular locations

Many species of Gram-negative bacteria are pathogenic bacteria that can cause disease in a host organism. This pathogenic capability is usually associated with certain components in Gram-negative cells. Therefore, developing an automated method for fast and reliable prediction of Gram-negative protein subcellular location will allow us to not only timely annotate gene products, but also screen candidates for drug discovery. However, protein subcellular location prediction is a very difficult problem, particularly when more location sites need to be involved and when unknown query proteins do not have significant homology to proteins of known subcellular locations. PSORT-B, a recently updated version of PSORT, widely used for predicting Gram-negative protein subcellular location, only covers five location sites. Also, the data set used to train PSORT-B contains many proteins with high degrees of sequence identity in a same location group and, hence, may bear a strong homology bias. To overcome these problems, a new predictor, called "Gneg-PLoc", is developed. Featured by fusing many basic classifiers each being trained with a stringent data set containing proteins with strictly less than 25% sequence identity to one another in a same location group, the new predictor can cover eight subcellular locations; that is, cytoplasm, extracellular space, fimbrium, flagellum, inner membrane, nucleoid, outer membrane, and periplasm. In comparison with PSORT-B, the new predictor not only covers more subcellular locations, but also yields remarkably higher success rates. Gneg-PLoc is available as a Web server at http://202.120.37.186/bioinf/Gneg. To support the demand of people working in the relevant areas, a downloadable file is provided at the same Web site to list the results identified by Gneg-PLoc for 49 907 Gram-negative protein entries in the Swiss-Prot database that have no subcellular location annotations or are annotated with uncertain terms. The large-scale results will be updated twice a year to cover the new entries of Gram-negative bacterial proteins and reflect the new development of Gneg-PLoc.     

Electrostatic factors in DNA intercalation

The factors that determine the binding of a chromophore between the base pairs in DNA intercalation complexes are dissected. The electrostatic potential in the intercalation plane is calculated using an accurate ab initio based distributed multipole electrostatic model for a range of intercalation sites, involving different sequences of base pairs and relative twist angles. There will be a significant electrostatic contribution to the binding energy for chromophores with a predominantly positive electrostatic potential, but this varies significantly with sequence, and somewhat with twist angle. The usefulness of these potential maps for understanding the binding of intercalators is explored by calculating the electrostatic binding energy for 9-aminoacridine, ethidium, and daunomycin in a variety of model binding sites. The electrostatic forces play a major role in the positioning of an intercalating 9-aminoacridine and a significant stabilizing role in the binding of ethidium in its sterically constrained position, but the intercalation of daunomycin is determined by the side-chain binding. Sequence preferences are likely to be determined by a complex and subtle mixture of effects, with electrostatics being just one component. The electrostatic binding energy is also unlikely to be a major determinant of the twist angle, as its variation with angle is modest for most intercalation sites. Overall, the electrostatic potential maps give guidance on how positively charged chromophores can be chemically adapted by heteroatomic substitution to optimise their binding.     

Electrostatic properties of protein-protein complexes

Statistical electrostatic analysis of 37 protein-protein complexes extracted from the previously developed database of protein complexes (ProtCom, http://www.ces.clemson.edu/compbio/protcom) is presented. It is shown that small interfaces have a higher content of charged and polar groups compared to large interfaces. In a vast majority of the cases the average pKa shifts for acidic residues induced by the complex formation are negative, indicating that complex formation stabilizes their ionizable states, whereas the histidines are predicted to destabilize the complex. The individual pKa shifts show the same tendency since 80% of the interfacial acidic groups were found to lower their pKas, whereas only 25% of histidines raise their pKa upon the complex formation. The interfacial groups have been divided into three sets according to the mechanism of their pKa shift, and statistical analysis of each set was performed. It was shown that the optimum pH values (pH of maximal stability) of the complex tend to be the same as the optimum pH values of the complex components. This finding can be used in the homology-based prediction of the 3D structures of protein complexes, especially when one needs to evaluate and rank putative models. It is more likely for a model to be correct if both components of the model complex and the entire complex have the same or at least similar values of the optimum pH.     

Electrostatic properties of bovine beta-lactoglobulin

Bovine beta-Lactoglobulin (BLG) has been studied for many decades, but only recently structural data have been obtained, making it possible to simulate its molecular properties. In the present study, electrostatic properties of BLG are investigated theoretically using Poisson-Boltzmann calculations and experimentally following pH titration via NMR. Electrostatic properties are determined for several structural models, including an ensemble of NMR structures obtained at low pH. The changes in electrostatic forces upon changes in ionic strength, solvent dielectric constant, and pH are calculated and compared with experiments. pK(a)s are computed for all titratable sites and compared with NMR titration data. The analysis of theoretical and experimental results suggests that (1) there may be more than one binding sites for negatively charged ligands; (2) at low pH the core of the molecule is more compact than observed in the structures obtained via restrained molecular dynamics from NMR data, but loop and terminal regions must be disordered.     

Electrostatic control of charge separation in bacterial photosynthesis

Electrostatic interaction energies of the electron carriers with their surroundings in a photosynthetic bacterial reaction center are calculated. The calculations are based on the detailed crystal structure of reaction centers from Rhodopseu-domonas viridis, and use an iterative, self-consistent procedure to evaluate the effects of induced dipoles in the protein and the surrounding membrane. To obtain the free energies of radical-pair states, the calculated electrostatic interaction energies are combined with the experimentally measured midpoint redox potentials of the electron carriers and of bacteriochlorophyll (BChl) and bacteriopheophytin (BPh) in vitro. The P+HL- radical-pair, in which an electron has moved from the primary electron donor (P) to a BPh on the 'L' side of the reaction center (HL), is found to lie approx. 2.0 kcal/mol below the lowest excited singlet state (P*), when the radical-pair is formed in the static crystallographic structure. The reorganization energy for the subsequent relaxation of P+HL- is calculated to be 5.0 kcal/mol, so that the relaxed radical-pair lies about 7 kcal/mol below P*. The unrelaxed P+BL- radical-pair, in which the electron acceptor is the accessory BChl located between P and HL, appears to be essentially isoenergetic with P*.P+BM-, in which an electron moves to the BChl on the 'M' side, is calculated to lie about 5.5 kcal/mol above P*. These results have an estimated error range of +/- 2.5 kcal/mol. They are shown to be relatively insensitive to various details of the model, including the charge distribution in P+, the atomic charges used for the amino acid residues, the boundaries of the structural region that is considered microscopically and the treatments of the histidyl ligands of P and of potentially ionizable amino acids. The calculated free energies are consistent with rapid electron transfer from P* to HL by way of BL, and with a much slower electron transfer to the pigments on the M side. Tyrosine M208 appears to play a particularly important role in lowering the energy of P+BL-. Electrostatic interactions with the protein favor localization of the positive charge of P+ on PM, one of the two BChl molecules that make up the electron donor.     

Joint modeling of DNA sequence and physical properties to improve eukaryotic promoter recognition

We present an approach to integrate physical properties of DNA, such as DNA bendability or GC content, into our probabilistic promoter recognition system McPROMOTER. In the new model, a promoter is represented as a sequence of consecutive segments represented by joint likelihoods for DNA sequence and profiles of physical properties. Sequence likelihoods are modeled with interpolated Markov chains, physical properties with Gaussian distributions. The background uses two joint sequence/profile models for coding and non-coding sequences, each consisting of a mixture of a sense and an anti-sense submodel. On a large Drosophila test set, we achieved a reduction of about 30% of false positives when compared with a model solely based on sequence likelihoods.