A review on biotechnologically derived techniques to combat COVID-19 situation

Jain, Akanksha; Bajaj, Sonia; Jain, Parag; Majumdar, Ashish; Singh, Ayushi; Soni, Pranay

doi:10.1016/j.hsr.2023.100112

Health Sciences Review

2023

DOI: 10.1016/j.hsr.2023.100112

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A review on biotechnologically derived techniques to combat COVID-19 situation

Akanksha Jain,

Sonia Bajaj,

Parag Jain

et al.

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2024

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Cited by 2 publications

References 161 publications

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Lernen aus Protein‐Engineering durch Dekonvolution von Multi‐Mutationalen Enzymvarianten**

Hollmann,

Sanchis,

Reetz

2024

Angewandte Chemie

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This review analyzes a development in biochemistry, enzymology and biotechnology that originally came as a surprise. As part of directed evolution of stereoselective enzymes in organic chemistry, the concept of partial or complete deconvolution of selective multi‐mutational variants was established and refined during the past 15 years. Early deconvolution experiments of stereoselective variants led to the finding that mutations can interact cooperatively or antagonistically with one another, not just additively. Later, this phenomenon was shown to be general. Molecular dynamics (MD) and quantum mechanics/molecular mechanics (QM/MM) computations were performed in order to shed light on the origin of non‐additivity at all stages of an evolutionary upward climb. Data of complete deconvolution can be used to construct unique multi‐dimensional rugged fitness pathway landscapes, which provide more mechanistic insight than traditional fitness landscapes. Along a related line, biochemists have long tested the result of introducing two point mutations in an enzyme for mechanistic reasons, followed by a comparison of the respective double mutant in so‐called double mutant cycles, which originally showed only additive effects, but more recently also uncovered cooperative and antagonistic non‐additive effects.

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Lernen aus Protein‐Engineering durch Dekonvolution von Multi‐Mutationalen Enzymvarianten**

Hollmann,

Sanchis,

Reetz

2024

Angewandte Chemie

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Learning from Protein Engineering by Deconvolution of Multi‐Mutational Variants

Hollmann,

Sanchis,

Reetz

2024

Angew Chem Int Ed

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scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

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A review on biotechnologically derived techniques to combat COVID-19 situation

Cited by 2 publications

References 161 publications

Lernen aus Protein‐Engineering durch Dekonvolution von Multi‐Mutationalen Enzymvarianten**

Lernen aus Protein‐Engineering durch Dekonvolution von Multi‐Mutationalen Enzymvarianten**

Learning from Protein Engineering by Deconvolution of Multi‐Mutational Variants

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