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      Comparative insights using the molecular homology model of BDNF (Brain derived neurotrophic factor) of Varanus komodoensis and the known NGF (Nerve growth factor) structure of Naja atra

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          Abstract

          BDNF (Brain derived neurotrophic factor) is a secretion protein and a member of the neurotrophin family of growth factors. Structural and functional characterization of BDNF Varanus komodoensis is of interest while its structure remains unknown. Thus, a homology molecular model of BDNF was constructed for gleaning possible structural insights. The model was compared with the structure of the homologous NGF (Nerve growth factor, another member of neuro-trophin family) from Naja atra. Comparative structural analysis of the models showed structural similarities with their predicted cavities for the interpretation of potential functional analogy.

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          Structure validation by Calpha geometry: phi,psi and Cbeta deviation.

          Simon C. Lovell, Ian W. Davis, W Bryan Arendall … (2003)
          Geometrical validation around the Calpha is described, with a new Cbeta measure and updated Ramachandran plot. Deviation of the observed Cbeta atom from ideal position provides a single measure encapsulating the major structure-validation information contained in bond angle distortions. Cbeta deviation is sensitive to incompatibilities between sidechain and backbone caused by misfit conformations or inappropriate refinement restraints. A new phi,psi plot using density-dependent smoothing for 81,234 non-Gly, non-Pro, and non-prePro residues with B < 30 from 500 high-resolution proteins shows sharp boundaries at critical edges and clear delineation between large empty areas and regions that are allowed but disfavored. One such region is the gamma-turn conformation near +75 degrees,-60 degrees, counted as forbidden by common structure-validation programs; however, it occurs in well-ordered parts of good structures, it is overrepresented near functional sites, and strain is partly compensated by the gamma-turn H-bond. Favored and allowed phi,psi regions are also defined for Pro, pre-Pro, and Gly (important because Gly phi,psi angles are more permissive but less accurately determined). Details of these accurate empirical distributions are poorly predicted by previous theoretical calculations, including a region left of alpha-helix, which rates as favorable in energy yet rarely occurs. A proposed factor explaining this discrepancy is that crowding of the two-peptide NHs permits donating only a single H-bond. New calculations by Hu et al. [Proteins 2002 (this issue)] for Ala and Gly dipeptides, using mixed quantum mechanics and molecular mechanics, fit our nonrepetitive data in excellent detail. To run our geometrical evaluations on a user-uploaded file, see MOLPROBITY (http://kinemage.biochem.duke.edu) or RAMPAGE (http://www-cryst.bioc.cam.ac.uk/rampage). Copyright 2003 Wiley-Liss, Inc.
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            Brain-derived neurotrophic factor regulates glucose metabolism by modulating energy balance in diabetic mice.

            M. Ono, C Nakayama, Tristan Nakagawa … (2000)
            We previously reported that brain-derived neurotrophic factor (BDNF) regulates both food intake and blood glucose metabolism in rodent obese diabetic models such as C57BL/KsJ-lepr(db)/lepr(db) (db/db) mice. To elucidate the effect of BDNF on glucose metabolism, we designed a novel pellet pair-feeding apparatus to eliminate the effect of appetite alteration on glucose metabolism. The apparatus was used to synchronize food intake precisely between BDNF-treated and vehicle-treated db/db mice. It was shown using this pellet pair-feeding apparatus that BDNF administered daily (20 mg x kg(-1) x day(-1)) to db/db mice significantly lowered blood glucose compared with pellet pair-fed db/db mice. To evaluate the effect of BDNF on insulin action, we used streptozotocin-induced type 1 diabetic mice. In this case, BDNF did not lower blood glucose concentration but rather enhanced the hypoglycemic action of insulin. In hyperglycemic db/db mice, pancreatic insulin content was reduced and glucagon content was increased compared with normoglycemic db/m mice. BDNF administered to db/db mice significantly restored both pancreatic insulin and glucagon content. Histological observations of aldehyde-fuchsin staining and immunostaining with anti-insulin indicated that insulin-positive pancreatic beta-cells were extensively regranulated by BDNF administration. We also studied the effect of BDNF on KK mice, normoglycemic animals with impaired glucose tolerance. In these mice, BDNF administration improved insulin resistance in the oral glucose tolerance test. To elucidate how blood glucose was metabolized in BDNF-treated animals, we investigated the effect of BDNF on the energy metabolism of db/db mice. Body temperature and oxygen consumption of the pellet pair-fed vehicle-treated mice were remarkably lower than the ad libitum-fed vehicle-treated mice. Daily BDNF administration for 3 weeks completely ameliorated both of the reductions. Finally, to clarify its action mechanism, the effect of intracerebroventricular administration of BDNF on db/db mice was examined. Here, a small dose of BDNF was found to be effective in lowering blood glucose concentration. This indicates that BDNF regulates glucose metabolism by acting directly on the brain.
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              Shape variation in protein binding pockets and their ligands.

              J Thornton, Abdullah Kahraman, A.-B. Morris … (2007)
              A common assumption about the shape of protein binding pockets is that they are related to the shape of the small ligand molecules that can bind there. But to what extent is that assumption true? Here we use a recently developed shape matching method to compare the shapes of protein binding pockets to the shapes of their ligands. We find that pockets binding the same ligand show greater variation in their shapes than can be accounted for by the conformational variability of the ligand. This suggests that geometrical complementarity in general is not sufficient to drive molecular recognition. Nevertheless, we show when considering only shape and size that a significant proportion of the recognition power of a binding pocket for its ligand resides in its shape. Additionally, we observe a "buffer zone" or a region of free space between the ligand and protein, which results in binding pockets being on average three times larger than the ligand that they bind.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Bioinformation
                Journal ID (iso-abbrev): Bioinformation
                Journal ID (publisher-id): Bioinformation
                Title: Bioinformation
                Publisher: Biomedical Informatics
                ISSN (Print): 0973-8894
                ISSN (Electronic): 0973-2063
                Publication date Collection: 2013
                Publication date (Electronic): 28 August 2013
                Volume: 9
                Issue: 15
                Pages: 755-758
                Affiliations
                Bioinformatics Infrastructure Facility, Gauhati University, Guwahati - 781014, Assam, India
                Author notes
                [* ]Dhirendra Kumar Sharma: dksgu@ 123456yahoo.co.uk
                Article
                Publisher ID: 97320630009755
                DOI: 10.6026/97320630009755
                PMC ID: 3766306
                PubMed ID: 24023416
                SO-VID: f1c65ab7-ae31-4a8c-b1a2-385043ee0da0
                Copyright © © 2013 Biomedical Informatics
                License:

                This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited.

                History
                Date received : 07 August 2013
                Date accepted : 08 August 2013
                Categories
                Subject: Hypothesis

                ScienceOpen disciplines: Bioinformatics & Computational biology
                Data availability:
                ScienceOpen disciplines: Bioinformatics & Computational biology

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