scholarly journals Quantifying structural relationships of metal-binding sites suggests origins of biological electron transfer

2022 ◽  
Vol 8 (2) ◽  
Author(s):  
Yana Bromberg ◽  
Ariel A. Aptekmann ◽  
Yannick Mahlich ◽  
Linda Cook ◽  
Stefan Senn ◽  
...  
Keyword(s):  
Electron Transfer ◽  
Metal Binding ◽  
Binding Sites ◽  
Binding Protein ◽  
Origins Of Life ◽  
Metal Binding Sites ◽  
Structural Relationships ◽  
Computational Exploration ◽  
Metal Binding Protein ◽  
Biological Electron Transfer

Computational exploration of similarities among metal-binding protein structural motifs elucidates the origins of life.

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 Identification of Metal-binding Sites in Rat Brain Calcium-binding Protein

1995 ◽  
Vol 270 (51) ◽  
pp. 30353-30358 ◽  
Author(s):  
Timothy D. Veenstra ◽  
Myron D. Gross ◽  
Willi Hunziker ◽  
Rajiv Kumar
Keyword(s):  
Rat Brain ◽  
Metal Binding ◽  
Binding Sites ◽  
Calcium Binding ◽  
Binding Protein ◽  
Calcium Binding Protein ◽  
Metal Binding Sites

scholarly journals Rational design of a conformation-switchable Ca2+- and Tb3+-binding protein without the use of multiple coupled metal-binding sites

FEBS Journal ◽  
2008 ◽  
Vol 275 (20) ◽  
pp. 5048-5061 ◽  
Author(s):  
Shunyi Li ◽  
Wei Yang ◽  
Anna W. Maniccia ◽  
Doyle Barrow Jr ◽  
Harianto Tjong ◽  
...  
Keyword(s):  
Metal Binding ◽  
Binding Sites ◽  
Rational Design ◽  
Binding Protein ◽  
Metal Binding Sites

scholarly journals Site 2 of the Yersinia pestis substrate-binding protein YfeA is a dynamic surface metal-binding site

2021 ◽  
Vol 77 (9) ◽  
pp. 286-293
Author(s):  
Christopher D. Radka ◽  
Stephen G. Aller
Keyword(s):  
Yersinia Pestis ◽  
Metal Binding ◽  
Binding Sites ◽  
Unique Feature ◽  
Binding Protein ◽  
Substrate Binding ◽  
Dynamic Surface ◽  
Metal Binding Sites ◽  
Surface Metal ◽  
Substrate Binding Protein

The substrate-binding protein YfeA (also known as YPO2439 or y1897) is a polyspecific metal-binding protein that is crucial for nutrient acquisition and virulence in Yersinia pestis, the causative microbe of plague. YfeA folds into a monomeric c-clamp like other substrate-binding proteins and has two metal-binding sites (sites 1 and 2). Site 2 is a bidentate surface site capable of binding Zn and Mn atoms and is a unique feature of YfeA. Occasionally, the site 2 residues of two YfeA molecules will cooperate with the histidine tag of a third YfeA molecule in coordinating the same metal and lead to metal-dependent crystallographic packing. Here, three crystal structures of YfeA are presented at 1.85, 2.05 and 2.25 Å resolution. A comparison of the structures reveals that the metal can be displaced at five different locations ranging from ∼4 to ∼16 Å away from the canonical site 2. These observations reveal different configurations of site 2 that enable cooperative metal binding and demonstrate how site 2 is dynamic and freely available for inter-protein metal coordination.

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 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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