scholarly journals Learning the structure–activity relationship (SAR) of the Wittig reaction from genetically-encoded substrates

2021 ◽  
Author(s):  
Kejia Yan ◽  
Vivian Triana ◽  
Sunil Vasu Kalmady ◽  
Kwami Aku-Dominguez ◽  
Sharyar Memon ◽  
...  
Keyword(s):  
Deep Sequencing ◽  
Conversion Rate ◽  
Wittig Reaction ◽  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Structure Activity ◽  
The Relationship

160 000 peptides displayed on phage were subjected to the Wittig reaction with a biotinylated ylide. Deep-sequencing estimated the conversion rate for each sequence and unveiled the relationship between sequences and the rate of the Wittig reaction.

scholarly journals Learning Structure Activity Relationship (SAR) of the Wittig Reaction from Genetically-Encoded Substrates

2021 ◽  
Author(s):  
Kejia Yan ◽  
Vivian Triana ◽  
Sunil Vasu Kalmady ◽  
Kwami Aku-Dominguez ◽  
Sharyar Memon ◽  
...  
Keyword(s):  
Deep Sequencing ◽  
Density Functional ◽  
Wittig Reaction ◽  
Characteristic Curve ◽  
Critical Role ◽  
Reaction Rates ◽  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Sequencing Data ◽  
Structure Activity

The Wittig reaction can be used for late stage functionalization of proteins and peptides to ligate glycans, pharmacophores, and many other functionalities. In this manuscript, we modified 160,000 N-terminal glyoxaldehyde peptides displayed on phage with the Wittig reaction by biotin labeled ylide under conditions that functionalize only 1% of the library population. Deep-sequencing of the biotinylated and input populations estimated the rate of conversion for each sequence. This “deep conversion” (DC) from deep sequencing correlates with rate constants measured by HPLC. Peptide sequences with fast and slow reactivity highlighted a critical role of primary backbone amides (N-H) in accelerating the rate of the aqueous Wittig reaction. Experimental measurement of reaction rates and density functional theory (DFT) computation of the transition state geometries corroborated this relationship. We also collected deep-sequencing data to build structure activity relationship (SAR) models that can predict DC value of the Wittig reaction. By using this data, we trained two classifier models based on Gradient Boosted trees. These classifiers achieved area under the ROC (Receiver Operating Characteristic) Curve (ROC AUC) of 81.2 ± 0.4 and 73.7 ± 0.8 (90–92% accuracy) in determining whether a sequence belonged to the top 5% or the bottom 5% in terms of its reactivity. We have deployed our learned models as a publicly available web app: <a href="http://44.226.164.95/">http://44.226.164.95/</a> We anticipate that phage-displayed peptides and related mRNA or DNA-displayed substrates can be employed in a similar fashion to study the substrate scope and mechanisms of many other chemical reactions.

scholarly journals Learning Structure Activity Relationship (SAR) of the Wittig Reaction from Genetically-Encoded Substrates

2021 ◽  
Author(s):  
Kejia Yan ◽  
Vivian Triana ◽  
Sunil Vasu Kalmady ◽  
Kwami Aku-Dominguez ◽  
Sharyar Memon ◽  
...  
Keyword(s):  
Deep Sequencing ◽  
Density Functional ◽  
Wittig Reaction ◽  
Characteristic Curve ◽  
Critical Role ◽  
Reaction Rates ◽  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Sequencing Data ◽  
Structure Activity

The Wittig reaction can be used for late stage functionalization of proteins and peptides to ligate glycans, pharmacophores, and many other functionalities. In this manuscript, we modified 160,000 N-terminal glyoxaldehyde peptides displayed on phage with the Wittig reaction by biotin labeled ylide under conditions that functionalize only 1% of the library population. Deep-sequencing of the biotinylated and input populations estimated the rate of conversion for each sequence. This “deep conversion” (DC) from deep sequencing correlates with rate constants measured by HPLC. Peptide sequences with fast and slow reactivity highlighted a critical role of primary backbone amides (N-H) in accelerating the rate of the aqueous Wittig reaction. Experimental measurement of reaction rates and density functional theory (DFT) computation of the transition state geometries corroborated this relationship. We also collected deep-sequencing data to build structure activity relationship (SAR) models that can predict DC value of the Wittig reaction. By using this data, we trained two classifier models based on Gradient Boosted trees. These classifiers achieved area under the ROC (Receiver Operating Characteristic) Curve (ROC AUC) of 81.2 ± 0.4 and 73.7 ± 0.8 (90–92% accuracy) in determining whether a sequence belonged to the top 5% or the bottom 5% in terms of its reactivity. We have deployed our learned models as a publicly available web app: <a href="http://44.226.164.95/">http://44.226.164.95/</a> We anticipate that phage-displayed peptides and related mRNA or DNA-displayed substrates can be employed in a similar fashion to study the substrate scope and mechanisms of many other chemical reactions.

scholarly journals Theoretical evaluation of the structure–activity relationship in graphene-based electrocatalysts for hydrogen evolution reactions

RSC Advances ◽  
2017 ◽  
Vol 7 (43) ◽  
pp. 27033-27039 ◽  
Author(s):  
Chi Ho Lee ◽  
Byeongsun Jun ◽  
Sang Uck Lee
Keyword(s):  
Hydrogen Evolution ◽  
Hydrogen Evolution Reaction ◽  
Electrocatalytic Activity ◽  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Theoretical Evaluation ◽  
Structure Activity ◽  
Hydrogen Evolution Reactions ◽  
The Relationship

We systematically analyzed the relationship between structure and electrocatalytic activity of heteroatom-doped graphenes (GXs, where G and X represent graphene and the heteroatom dopant) for the hydrogen evolution reaction (HER).

Structure-activity relationship of (-) mammea A/BB derivatives against Leishmania amazonensis

Planta Medica ◽  
2008 ◽  
Vol 74 (09) ◽  
Author(s):  
MA Brenzan ◽  
CV Nakamura ◽  
BPD Filho ◽  
T Ueda-Nakamura ◽  
MCM Young ◽  
...  
Keyword(s):  
Structure Activity Relationship ◽  
Leishmania Amazonensis ◽  
Activity Relationship ◽  
Structure Activity ◽  
Relationship Of
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