Coevolution-based inference of amino acid interactions underlying protein function

Salinas, Víctor; Ranganathan, Rama

doi:10.7554/elife.34300

Cited by 124 publications

(120 citation statements)

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“…The effect of substitutions on binding is substitutions may have little or no effect, while a few may abolish binding entirely 48 . When 439 comprehensive data are available, detailed statistical models can offer reasonable predictions of 440 the effect of specific amino-acid substitutions [49][50][51] . However, this type of data does not yet exist 441 across entire antibody and TCR repertoires, and so simpler models are required.…”

Section: Similarity Measures a Functional Measure Of Similarity Betwmentioning

confidence: 99%

Immunological Diversity with Similarity

Arora

Burke

Arnaout

2018

Preprint

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A diverse immune repertoire is considered a hallmark of good health, but measuring diversity requires a framework that incorporates not only sequences’ relative frequencies but also their functional similarity to each other. Using experimentally measured dissociation constants from over 1,300 antibody-antigen and T-cell receptor (TCR)-peptide pairs, we developed a framework for functional immunological diversity based on binding and applied it to nearly 400 high-throughput antibody and TCR repertoires to reveal patterns in immunological memory, infection, vaccination, and aging. We show that functional diversity adds information that is not captured by raw diversity, revealing signatures of e.g. clonal selection, and that unlike raw diversity, functional diversity is a robust measure that does not require correction for sampling error. Finally, we show that according to functional diversity, unlike raw diversity, individuals’ repertoires overlap substantially, indicating a definable ceiling for the functional diversity of human adaptive immunity. Similarity redefines diversity in complex systems.

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Section: Similarity Measures a Functional Measure Of Similarity Betwmentioning

confidence: 99%

Immunological Diversity with Similarity

Arora

Burke

Arnaout

2018

Preprint

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“…However, contact terms in !# alone do not suffice to reproduce either the alignment statistics in the AroQ family (Fig. S7) or the functional effects of mutations (17). Instead function in proteins seems to depend also on many weaker, non-contacting terms in !# that currently have no simple physical interpretation.…”

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confidence: 97%

Evolution-based design of chorismate mutase enzymes

Russ

Figliuzzi

Stöcker

et al. 2020

Preprint

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The rational design of enzymes is an important goal for both fundamental and practical reasons. 15 Here, we describe a design process in which we learn the constraints for specifying proteins purely from evolutionary sequence data, build libraries of synthetic genes, and test them for activity in vivo using a quantitative complementation assay. For chorismate mutase, a key enzyme in the biosynthesis of aromatic amino acids, we demonstrate the design of natural-like catalytic function with substantial sequence diversity. Further optimization focuses the generative model towards function in a specific 20 genomic context. The data show that sequence-based statistical models suffice to specify proteins and provide access to an enormous space of synthetic functional sequences. This result provides a foundation for a general process for evolution-based design of artificial proteins.One-sentence summary: An evolution-based, data-driven engineering process can build synthetic 25 functional enzymes.Approaches for protein design typically begin with atomic structures and physical models for forces between atoms, but the dramatic expansion of protein sequence databases and the growth of new 30 computational methods (1-4) opens new strategies to this problem. Statistical analyses of homologs comprising a protein family have recently enabled successful prediction of protein structure (5-8), proteinprotein interactions (9-13), mutational effects (14-18), and for a family of small protein interaction modules, have led to the successful design of artificial amino acid sequences that fold and function in a manner 25 8, (2019). 3. D. Repecka et al., Expanding functional protein sequence space using generative adversarial networks.

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“…This can give a hint that pairwise mutant might create higher activity than single mutant; therefore, we will continue to screen double mutants in the future work according to the specific pairwise correlation information. 54…”

Section: Scasim As a Tool For Protein Engineeringmentioning

confidence: 99%

“…Ranganathan using SCA successfully capture the energetic couplings that contribute to protein function which proves the reliability of this method. 9 Covariant residues are distributed around protein active sites but can connect to distant functional surface sites through pathways of residue interactions throughout the protein. 10,11 The combination between amino acid and codon information is used to improve the contact prediction.…”

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confidence: 99%

Algorithm‐based coevolution network identification reveals key functional residues of the α/β hydrolase subfamilies

Líu

et al. 2019

FASEB j.

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Covariant residues identified by computational algorithms have provided new insights into enzyme evolutionary routes. However, the reliability and accuracy of routine statistical coupling analysis (SCA) are unable to satisfy the needs of protein engineering because SCA depends only on sequence information. Here, we set up a new SCA algorithm, SCA.SIM, by integrating structure information and MD simulation data. The more reliable covariant residues with high‐quality scores are obtained from sequence alignment weighted by residual movement for eight related subfamilies, belonging to α/β hydrolase family, with Candida antarctica lipase B (CALB). The 38 predicted covariant residues are tested for function by high‐throughput quantitative evaluation in combination with activity and thermostability assays of a mutant library and deep sequencing. Based on the landscapes of both activity and thermostability, most mutants play key roles in catalysis, and some mutants gain 2.4‐ to 6‐fold increase in half‐life at 50°C and 9‐ to 12‐fold improvement in catalytic efficiency. The activity of double mutants for A225F/T103A is higher than those of A225F and T103A which means that SCA.SIM method might be useful for identifying the allosteric coupling. The SCA.SIM algorithm can be used for protein coevolution and enzyme engineering research.

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Coevolution-based inference of amino acid interactions underlying protein function

Cited by 124 publications

References 50 publications

Immunological Diversity with Similarity

Immunological Diversity with Similarity

Evolution-based design of chorismate mutase enzymes

Algorithm‐based coevolution network identification reveals key functional residues of the α/β hydrolase subfamilies

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