scholarly journals Molecular dynamics simulations of zfP2X4 receptors

2021 ◽  
Author(s):  
kalyan immadisetty ◽  
Peter Kekenes-Huskey
Keyword(s):  
Molecular Dynamics ◽  
Crystal Structures ◽  
Metal Binding ◽  
Binding Sites ◽  
Molecular Mechanisms ◽  
Pain Perception ◽  
Gulf Coast ◽  
Md Simulations ◽  
P2x Receptor ◽  
Metal Binding Sites

The ATP activated P2X4 receptor plays a prominent role in pain perception and modulation and thus may constitute an alternative therapeutic target for controlling pain. Given the biomedical relevance of P2X4 receptors, and poor understanding of molecular mechanisms that describe its gating by ATP, a fundamental understanding of the functional mechanism of these channels is warranted. Through classical all-atom molecular dynamics (MD) simulations we investigated the number of ATP molecules required to open (activate) the receptor for it to conduct ions. Since crystal structures of human P2X4 are not yet available, the crystal structures of highly-homologous zebrafish P2X4 (zfP2X4) structures were utilized for this study. It has been identified that at least two ATP molecules are required to prevent the open state receptor from collapsing back to a closed state. Additionally, we have discovered two metal binding sites, one at the intersection of the three monomers in the ectodomain (MBS1) and the second one near the ATP binding site (MBS2), both of which are occupied by the potassium ions. This observation draws its comparison to the gulf coast P2X receptor that it possesses the same two metal binding sites, however, MBS1 and MBS2 in this receptor are occupied by zinc and magnesium, respectively.

scholarly journals Crystal Structures of Apo and Metal-Bound Forms of the UreE Protein fromHelicobacter pylori: Role of Multiple Metal Binding Sites,

Biochemistry ◽  
2010 ◽  
Vol 49 (33) ◽  
pp. 7080-7088 ◽  
Author(s):  
Rong Shi ◽  
Christine Munger ◽  
Abdalin Asinas ◽  
Stéphane L. Benoit ◽  
Erica Miller ◽  
...  
Keyword(s):  
Crystal Structures ◽  
Metal Binding ◽  
Binding Sites ◽  
Metal Binding Sites

The structure of a deoxygenated 400 kDa haemoglobin reveals ternary- and quaternary-structural changes of giant haemoglobins

2014 ◽  
Vol 70 (7) ◽  
pp. 1823-1831 ◽  
Author(s):  
Nobutaka Numoto ◽  
Taro Nakagawa ◽  
Ryota Ohara ◽  
Tomoyo Hasegawa ◽  
Akiko Kita ◽  
...  
Keyword(s):  
Crystal Structures ◽  
Metal Binding ◽  
Binding Sites ◽  
Structural Changes ◽  
Divalent Cations ◽  
Glycosylation Site ◽  
Metal Binding Sites ◽  
Molecular Masses ◽  
Quaternary Structures ◽  
Intersubunit Interactions

The quaternary structures of invertebrate haemoglobins (Hbs) are quite different from those of vertebrate Hbs. The extracellular giant Hbs of molecular masses of about 400 and 3600 kDa are composed of a dome-shaped dodecameric subassembly which consists of four individual globin subunits. Several crystal structures of 400 kDa Hbs from annelids have been reported, including structures in oxygenated and partially unliganded states, but the structure of the fully deoxygenated state has not been reported. In the present study, crystal structures of V2Hb from the tube wormLamellibrachia satsumahave been determined in both the fully oxygenated and deoxygenated states. A glycosylation site and novel metal-binding sites for divalent cations were clearly observed with no intersubunit interactions in V2Hb. A comparison of the oxygenated and the deoxygenated forms of V2Hb reveals that the ternary- and quaternary-structural changes occur in a manner that maintains the molecularD3symmetry. These structures suggest that the mechanisms of quaternary-structural changes between the oxy and deoxy states for the giant Hbs are identical across species.

scholarly journals Rational design of metal-binding sites in domain-swapped myoglobin dimers

2021 ◽  
Vol 217 ◽  
pp. 111374
Author(s):  
Satoshi Nagao ◽  
Ayaka Idomoto ◽  
Naoki Shibata ◽  
Yoshiki Higuchi ◽  
Shun Hirota
Keyword(s):  
Metal Binding ◽  
Binding Sites ◽  
Rational Design ◽  
Metal Binding Sites

scholarly journals Electron transfer pathways in photoexcited lanthanide(III) complexes of picolinate ligands

2021 ◽  
Author(s):  
Daniel Kovacs ◽  
Daniel Kocsi ◽  
Jordann A. L. Wells ◽  
Salauat R. Kiraev ◽  
Eszter Borbas
Keyword(s):  
Electron Transfer ◽  
Metal Binding ◽  
Binding Sites ◽  
Secondary Amide ◽  
Metal Binding Sites ◽  
Electron Transfer Pathways

A series of luminescent lanthanide(III) complexes consisting of 1,4,7-triazacyclononane frameworks and three secondary amide-linked carbostyril antennae were synthesised. The metal binding sites were augmented with two pyridylcarboxylate donors yielding octadentate...

scholarly journals Machine learning differentiates enzymatic and non-enzymatic metals in proteins

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ryan Feehan ◽  
Meghan W. Franklin ◽  
Joanna S. G. Slusky
Keyword(s):  
Machine Learning ◽  
Metal Binding ◽  
Binding Sites ◽  
Active Sites ◽  
De Novo ◽  
Enzyme Design ◽  
Metal Binding Sites ◽  
Ensemble Machine Learning ◽  
Machine Learning Model ◽  
Physicochemical Features

AbstractMetalloenzymes are 40% of all enzymes and can perform all seven classes of enzyme reactions. Because of the physicochemical similarities between the active sites of metalloenzymes and inactive metal binding sites, it is challenging to differentiate between them. Yet distinguishing these two classes is critical for the identification of both native and designed enzymes. Because of similarities between catalytic and non-catalytic  metal binding sites, finding physicochemical features that distinguish these two types of metal sites can indicate aspects that are critical to enzyme function. In this work, we develop the largest structural dataset of enzymatic and non-enzymatic metalloprotein sites to date. We then use a decision-tree ensemble machine learning model to classify metals bound to proteins as enzymatic or non-enzymatic with 92.2% precision and 90.1% recall. Our model scores electrostatic and pocket lining features as more important than pocket volume, despite the fact that volume is the most quantitatively different feature between enzyme and non-enzymatic sites. Finally, we find our model has overall better performance in a side-to-side comparison against other methods that differentiate enzymatic from non-enzymatic sequences. We anticipate that our model’s ability to correctly identify which metal sites are responsible for enzymatic activity could enable identification of new enzymatic mechanisms and de novo enzyme design.

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