Expanding Chemical and Structural Space in mRNA Display

10.33540/788 ◽  
2021 ◽  
Author(s):  
◽  
MINGLONG LIU
Keyword(s):  
Mrna Display ◽  
Structural Space

TEM visualization of surface replicated acid and base catalyzed sol-gel glasses

1986 ◽  
Vol 44 ◽  
pp. 448-449
Author(s):  
George C. Ruben ◽  
Merrill W. Shafer
Keyword(s):  
Elevated Temperatures ◽  
Sol Gel ◽  
Basic Medium ◽  
Glass Transition Point ◽  
Structural Space ◽  
Acid And Base ◽  
Organometallic Precursors ◽  
New Processing ◽  
Gel Glasses ◽  
Physical Phenomena

Traditionally ceramics have been shaped from powders and densified at temperatures close to their liquid point. New processing methods using various types of sols, gels, and organometallic precursors at low temperature which enable densificatlon at elevated temperatures well below their liquidus, hold the promise of producing ceramics and glasses of controlled and reproducible properties that are highly reliable for electronic, structural, space or medical applications. Ultrastructure processing of silicon alkoxides in acid medium and mixtures of Ludox HS-40 (120Å spheres from DuPont) and Kasil (38% K2O &62% SiO2) in basic medium have been aimed at producing materials with a range of well defined pore sizes (∼20-400Å) to study physical phenomena and materials behavior in well characterized confined geometries. We have studied Pt/C surface replicas of some of these porous sol-gels prepared at temperatures below their glass transition point.

scholarly journals Selection of macrocyclic peptides that bind STING from an mRNA‐display library with split degenerate codons

2021 ◽  
Author(s):  
Chi-Wang Lin ◽  
Mary J. Harner ◽  
Andrew E. Douglas ◽  
Virginie Lafont ◽  
Fei Yu ◽  
...  
Keyword(s):  
Mrna Display ◽  
Macrocyclic Peptides ◽  
Selection Of

scholarly journals Potent Cyclic Peptide Inhibitors of FXIIa Discovered by mRNA Display with Genetic Code Reprogramming

2021 ◽  
Author(s):  
Daniel J. Ford ◽  
Nisharnthi M. Duggan ◽  
Sarah E. Fry ◽  
Jorge Ripoll-Rozada ◽  
Stijn M. Agten ◽  
...  
Keyword(s):  
Genetic Code ◽  
Cyclic Peptide ◽  
Peptide Inhibitors ◽  
Mrna Display

Person-in-Context Synthesis with Compositional Structural Space

2021 ◽  
Author(s):  
Weidong Yin ◽  
Ziwei Liu ◽  
Leonid Sigal
Keyword(s):  
Structural Space

scholarly journals Structural Basis for Inhibition of the MDM2:p53 Interaction by an Optimized MDM2-Binding Peptide Selected with mRNA Display

PLoS ONE ◽  
2014 ◽  
Vol 9 (10) ◽  
pp. e109163 ◽  
Author(s):  
Takashi Nagata ◽  
Kie Shirakawa ◽  
Naohiro Kobayashi ◽  
Hirokazu Shiheido ◽  
Noriko Tabata ◽  
...  
Keyword(s):  
Structural Basis ◽  
Mrna Display ◽  
Binding Peptide

scholarly journals Potential landscape phytocomplexes of Sudety Mountains

2015 ◽  
Vol 48 (1) ◽  
pp. 3-25
Author(s):  
Jan M. Matuszkiewicz
Keyword(s):  
Vegetation Landscape ◽  
Structural Space ◽  
Sudety Mountains ◽  
Potential Landscape

The author presents his own concept of potential landscape phytocomplexes as the structural space units on the level of plant organization higher than an ecosystem (i.e. above biogeocenosis). He also defines the concept of vegetation landscape in a typological sense. Basing on the example of Sudety Mountains and Foreland regions, the author demonstrates a method of distinguishing landscape phytocomplexes and their utilization for regional description of vegetation and geobotanical regionalization.

scholarly journals Self-Supervised Representation Learning of Protein Tertiary Structures (PtsRep): Protein Engineering as A Case Study

2020 ◽  
Author(s):  
Junwen Luo ◽  
Yi Cai ◽  
Jialin Wu ◽  
Hongmin Cai ◽  
Xiaofeng Yang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Protein Engineering ◽  
Structural Information ◽  
Representation Learning ◽  
Sequence Information ◽  
Structural Representation ◽  
Tertiary Structures ◽  
Structural Space ◽  
General Protein ◽  
And Function

AbstractIn recent years, deep learning has been increasingly used to decipher the relationships among protein sequence, structure, and function. Thus far deep learning of proteins has mostly utilized protein primary sequence information, while the vast amount of protein tertiary structural information remains unused. In this study, we devised a self-supervised representation learning framework to extract the fundamental features of unlabeled protein tertiary structures (PtsRep), and the embedded representations were transferred to two commonly recognized protein engineering tasks, protein stability and GFP fluorescence prediction. On both tasks, PtsRep significantly outperformed the two benchmark methods (UniRep and TAPE-BERT), which are based on protein primary sequences. Protein clustering analyses demonstrated that PtsRep can capture the structural signals in proteins. PtsRep reveals an avenue for general protein structural representation learning, and for exploring protein structural space for protein engineering and drug design.

scholarly journals mRNA display: Diversity matters during in vitro selection

2001 ◽  
Vol 98 (9) ◽  
pp. 4825-4826 ◽  
Author(s):  
L. Gold
Keyword(s):  
In Vitro Selection ◽  
Mrna Display
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