Partial purification and characterization of alkaline proteases from the Black Sea anchovy (Engraulis encrasicholus) digestive tract

Alkaline proteases from the digestive tract of anchovy were partially purified by ammonium sulfate fractionation, dialysis and Sephadex G-75 gel filtration. The purification fold and yield were 6.23 and 4.49%, respectively. The optimum activities of partially purified alkaline proteases were observed at 60°C and at pH 11.0. The alkaline proteases were stable within the temperature range of 40 to 50°C and pH range of 9.0 to 11.0. They were inhibited by the serine-protease inhibitor phenylmethylsulfonyl fluoride (PMSF) and trypsin specific inhibitor benzamidine, but were not inhibited by the β-mercaptoethanol. The enzymes were slightly activated by metal ions such as Na+ and Ba2+ and inhibited by Cu2+, Zn2+, K+ and Mn2+ at different degrees. The molecular weight of the partially purified enzyme was 24 kDa by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE).Key words: Alkaline proteases, Engraulis encrasicholus, purification, characterization, digestive tract

Optimization and evaluation of a coarse-grained model of protein motion using X-ray crystal data

Simple coarse-grained models, such as the Gaussian Network Model, have been shown to capture some of the features of equilibrium protein dynamics. We extend this model by using atomic contacts to define residue interactions and introducing more than one interaction parameter between residues. We use B-factors from 98 ultra-high resolution X-ray crystal structures to optimize the interaction parameters. The average correlation between GNM fluctuation predictions and the B-factors is 0.64 for the data set, consistent with a previous large-scale study. By separating residue interactions into covalent and noncovalent, we achieve an average correlation of 0.74, and addition of ligands and cofactors further improves the correlation to 0.75. However, further separating the noncovalent interactions into nonpolar, polar, and mixed yields no significant improvement. The addition of simple chemical information results in better prediction quality without increasing the size of the coarse-grained model.Comment: 18 pages, 4 figures, 1 supplemental file (cnm_si.tex

Optimization of minimum set of protein–DNA interactions: a quasi exact solution with minimum over-fitting

Motivation: A major limitation in modeling protein interactions is the difficulty of assessing the over-fitting of the training set. Recently, an experimentally based approach that integrates crystallographic information of C2H2 zinc finger–DNA complexes with binding data from 11 mutants, 7 from EGR finger I, was used to define an improved interaction code (no optimization). Here, we present a novel mixed integer programming (MIP)-based method that transforms this type of data into an optimized code, demonstrating both the advantages of the mathematical formulation to minimize over- and under-fitting and the robustness of the underlying physical parameters mapped by the code

Electrostatic hot spot on DNA-binding domains mediates phosphate desolvation and the pre-organization of specificity determinant side chains

A major obstacle towards elucidating the molecular basis of transcriptional regulation is the lack of a detailed understanding of the interplay between non-specific and specific protein–DNA interactions. Based on molecular dynamics simulations of C2H2 zinc fingers (ZFs) and engrailed homeodomain transcription factors (TFs), we show that each of the studied DNA-binding domains has a set of highly constrained side chains in preset configurations ready to form hydrogen bonds with the DNA backbone. Interestingly, those domains that bury their recognition helix into the major groove are found to have an electrostatic hot spot for Cl− ions located on the same binding cavity as the most buried DNA phosphate. The spot is characterized by three protein hydrogen bond donors, often including two basic side chains. If bound, Cl− ions, likely mimicking phosphates, steer side chains that end up forming specific contacts with bases into bound-like conformations. These findings are consistent with a multi-step DNA-binding mechanism in which a pre-organized set of TF side chains assist in the desolvation of phosphates into well defined sites, prompting the re-organization of specificity determining side chains into conformations suitable for the recognition of their cognate sequence

Inactivating KISS1 mutation and hypogonadotropic hypogonadism

Gonadotropin-releasing hormone (GnRH) is the central regulator of gonadotropins, which stimulate gonadal function. Hypothalamic neurons that produce kisspeptin and neurokinin B stimulate GnRH release. Inactivating mutations in the genes encoding the human kisspeptin receptor (KISS1R, formerly called GPR54), neurokinin B (TAC3), and the neurokinin B receptor (TACR3) result in pubertal failure. However, human kisspeptin loss-of-function mutations have not been described, and contradictory findings have been reported in Kiss1-knockout mice. We describe an inactivating mutation in KISS1 in a large consanguineous family that results in failure of pubertal progression, indicating that functional kisspeptin is important for puberty and reproduction in humans. (Funded by the Scientific and Technological Research Council of Turkey [TÜBİTAK] and others.)http://www.nejm.org/nf201

Experimentally based contact energies decode interactions responsible for protein–DNA affinity and the role of molecular waters at the binding interface

A major obstacle towards understanding the molecular basis of transcriptional regulation is the lack of a recognition code for protein–DNA interactions. Using high-quality crystal structures and binding data on the promiscuous family of C2H2 zinc fingers (ZF), we decode 10 fundamental specific interactions responsible for protein–DNA recognition. The interactions include five hydrogen bond types, three atomic desolvation penalties, a favorable non-polar energy, and a novel water accessibility factor. We apply this code to three large datasets containing a total of 89 C2H2 transcription factor (TF) mutants on the three ZFs of EGR. Guided by molecular dynamics simulations of individual ZFs, we map the interactions into homology models that embody all feasible intra- and intermolecular bonds, selecting for each sequence the structure with the lowest free energy. These interactions reproduce the change in affinity of 35 mutants of finger I (R2 = 0.998), 23 mutants of finger II (R2 = 0.96) and 31 finger III human domains (R2 = 0.94). Our findings reveal recognition rules that depend on DNA sequence/structure, molecular water at the interface and induced fit of the C2H2 TFs. Collectively, our method provides the first robust framework to decode the molecular basis of TFs binding to DNA

Identifying allosteric fluctuation transitions between different protein conformational states as applied to Cyclin Dependent Kinase 2

BACKGROUND: The mechanisms underlying protein function and associated conformational change are dominated by a series of local entropy fluctuations affecting the global structure yet are mediated by only a few key residues. Transitional Dynamic Analysis (TDA) is a new method to detect these changes in local protein flexibility between different conformations arising from, for example, ligand binding. Additionally, Positional Impact Vertex for Entropy Transfer (PIVET) uses TDA to identify important residue contact changes that have a large impact on global fluctuation. We demonstrate the utility of these methods for Cyclin-dependent kinase 2 (CDK2), a system with crystal structures of this protein in multiple functionally relevant conformations and experimental data revealing the importance of local fluctuation changes for protein function. RESULTS: TDA and PIVET successfully identified select residues that are responsible for conformation specific regional fluctuation in the activation cycle of Cyclin Dependent Kinase 2 (CDK2). The detected local changes in protein flexibility have been experimentally confirmed to be essential for the regulation and function of the kinase. The methodologies also highlighted possible errors in previous molecular dynamic simulations that need to be resolved in order to understand this key player in cell cycle regulation. Finally, the use of entropy compensation as a possible allosteric mechanism for protein function is reported for CDK2. CONCLUSION: The methodologies embodied in TDA and PIVET provide a quick approach to identify local fluctuation change important for protein function and residue contacts that contributes to these changes. Further, these approaches can be used to check for possible errors in protein dynamic simulations and have the potential to facilitate a better understanding of the contribution of entropy to protein allostery and function

Guanine Holes Are Prominent Targets for Mutation in Cancer and Inherited Disease

Albino Bacolla, Guliang Wang, Aklank Jain, Karen M. Vasquez, Division of Pharmacology and Toxicology, The University of Texas at Austin, Dell Pediatric Research Institute, Austin, Texas, United States of AmericaAlbino Bacolla, Nuri A. Temiz, Ming Yi, Joseph Ivanic, Regina Z. Cer, Duncan E. Donohue, Uma S. Mudunuri, Natalia Volfovsky, Brian T. Luke, Robert M., Stephens, Jack R. Collins, Advanced Biomedical Computing Center, SAIC-Frederick, Inc., Frederick National Laboratory for Cancer Research, Frederick, Maryland, United States of AmericaEdward V. Ball, David N. Cooper, Institute of Medical Genetics, School of Medicine, Cardiff University, Cardiff, United KingdomSingle base substitutions constitute the most frequent type of human gene mutation and are a leading cause of cancer and inherited disease. These alterations occur non-randomly in DNA, being strongly influenced by the local nucleotide sequence context. However, the molecular mechanisms underlying such sequence context-dependent mutagenesis are not fully understood. Using bioinformatics, computational and molecular modeling analyses, we have determined the frequencies of mutation at G•C bp in the context of all 64 5′-NGNN-3′ motifs that contain the mutation at the second position. Twenty-four datasets were employed, comprising >530,000 somatic single base substitutions from 21 cancer genomes, >77,000 germline single-base substitutions causing or associated with human inherited disease and 16.7 million benign germline single-nucleotide variants. In several cancer types, the number of mutated motifs correlated both with the free energies of base stacking and the energies required for abstracting an electron from the target guanines (ionization potentials). Similar correlations were also evident for the pathological missense and nonsense germline mutations, but only when the target guanines were located on the non-transcribed DNA strand. Likewise, pathogenic splicing mutations predominantly affected positions in which a purine was located on the non-transcribed DNA strand. Novel candidate driver mutations and tissue-specific mutational patterns were also identified in the cancer datasets. We conclude that electron transfer reactions within the DNA molecule contribute to sequence context-dependent mutagenesis, involving both somatic driver and passenger mutations in cancer, as well as germline alterations causing or associated with inherited disease.This work was supported by grants from the NIH (CA097175 and CA093729) to KMV, NCI/NIH contract HHSN261200800001E to AB and the Frederick National Laboratory for Cancer Research, and CBIIT/caBIG ISRCE yellow task #09-260 to the Frederick National Laboratory for Cancer Research. DNC and EVB received financial support from BIOBASE GmbH through a license agreement (for HGMD) with Cardiff University. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.PharmacyEmail: [email protected]

The Polyamine Inhibitor Alpha-Difluoromethylornithine Modulates Hippocampus-Dependent Function after Single and Combined Injuries

Exposure to uncontrolled irradiation in a radiologic terrorism scenario, a natural disaster or a nuclear battlefield, will likely be concomitantly superimposed on other types of injury, such as trauma. In the central nervous system, radiation combined injury (RCI) involving irradiation and traumatic brain injury may have a multifaceted character. This may entail cellular and molecular changes that are associated with cognitive performance, including changes in neurogenesis and the expression of the plasticity-related immediate early gene Arc. Because traumatic stimuli initiate a characteristic early increase in polyamine metabolism, we hypothesized that treatment with the polyamine inhibitor alpha-difluoromethylornithine (DFMO) would reduce the adverse effects of single or combined injury on hippocampus structure and function. Hippocampal dependent cognitive impairments were quantified with the Morris water maze and showed that DFMO effectively reversed cognitive impairments after all injuries, particularly traumatic brain injury. Similar results were seen with respect to the expression of Arc protein, but not neurogenesis. Given that polyamines have been found to modulate inflammatory responses in the brain we also assessed the numbers of total and newly born activated microglia, and found reduced numbers of newly born cells. While the mechanisms responsible for the improvement in cognition after DFMO treatment are not yet clear, the present study provides new and compelling data regarding the potential use of DFMO as a potential countermeasure against the adverse effects of single or combined injury