Diverse Fragment Clustering and Water Exclusion Identify Protein Hot Spots

2011 ◽  
Vol 133 (28) ◽  
pp. 10740-10743 ◽  
Author(s):  
John L. Kulp ◽  
John L. Kulp ◽  
David L. Pompliano ◽  
Frank Guarnieri
Keyword(s):  
Hot Spots ◽  
Protein Hot Spots

scholarly journals Protein hot spots at bio-nano interfaces

2011 ◽  
Vol 14 (7-8) ◽  
pp. 360-365 ◽  
Author(s):  
Gerald F. Audette ◽  
Stephanie Lombardo ◽  
Jonathan Dudzik ◽  
Thomas M. Arruda ◽  
Michal Kolinski ◽  
...  
Keyword(s):  
Hot Spots ◽  
Protein Hot Spots

Protein Hot Spots: The Islands of Stability

2012 ◽  
Vol 415 (2) ◽  
pp. 419-428 ◽  
Author(s):  
Yosef Y. Kuttner ◽  
Stanislav Engel
Keyword(s):  
Hot Spots ◽  
Protein Hot Spots

scholarly journals SPOTONE: Hot Spots on Protein Complexes with Extremely Randomized Trees via Sequence-Only Features

2020 ◽  
Vol 21 (19) ◽  
pp. 7281
Author(s):  
A. J. Preto ◽  
Irina S. Moreira
Keyword(s):  
Protein Interactions ◽  
Hot Spots ◽  
Scientific Community ◽  
Protein Complexes ◽  
Protein Sequences ◽  
Prediction Methods ◽  
Fasta File ◽  
Protein Protein Interactions ◽  
Extremely Randomized Trees ◽  
Protein Hot Spots

Protein Hot-Spots (HS) are experimentally determined amino acids, key to small ligand binding and tend to be structural landmarks on protein–protein interactions. As such, they were extensively approached by structure-based Machine Learning (ML) prediction methods. However, the availability of a much larger array of protein sequences in comparison to determined tree-dimensional structures indicates that a sequence-based HS predictor has the potential to be more useful for the scientific community. Herein, we present SPOTONE, a new ML predictor able to accurately classify protein HS via sequence-only features. This algorithm shows accuracy, AUROC, precision, recall and F1-score of 0.82, 0.83, 0.91, 0.82 and 0.85, respectively, on an independent testing set. The algorithm is deployed within a free-to-use webserver, only requiring the user to submit a FASTA file with one or more protein sequences.

A high-performance oil-free backing pump for electron microscopes

1978 ◽  
Vol 36 (1) ◽  
pp. 110-111
Author(s):  
G.K.W. Balkau ◽  
E. Bez ◽  
J.L. Farrant
Keyword(s):  
Molecular Weight ◽  
Electron Microscope ◽  
Hot Spots ◽  
High Performance ◽  
Carbonaceous Material ◽  
Contamination Rate ◽  
Low Molecular Weight ◽  
Principal Source ◽  
Rotary Pumps ◽  
Electron Microscopes

The earliest account of the contamination of electron microscope specimens by the deposition of carbonaceous material during electron irradiation was published in 1947 by Watson who was then working in Canada. It was soon established that this carbonaceous material is formed from organic vapours, and it is now recognized that the principal source is the oil-sealed rotary pumps which provide the backing vacuum. It has been shown that the organic vapours consist of low molecular weight fragments of oil molecules which have been degraded at hot spots produced by friction between the vanes and the surfaces on which they slide. As satisfactory oil-free pumps are unavailable, it is standard electron microscope practice to reduce the partial pressure of organic vapours in the microscope in the vicinity of the specimen by using liquid-nitrogen cooled anti-contamination devices. Traps of this type are sufficient to reduce the contamination rate to about 0.1 Å per min, which is tolerable for many investigations.

World Bank pinpoints disaster hot spots

Nature ◽  
2005 ◽  
Author(s):  
Deirdre Lockwood
Keyword(s):  
World Bank ◽  
Hot Spots
Sign in / Sign up

Export Citation Format

Share Document