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How structural and physicochemical determinants shape sequence constraints in a functional enzyme.

Abriata LA, Palzkill T, Dal Peraro M - PLoS ONE (2015)

Bottom Line: Amino acid volume and steric hindrance shape constraints on the protein core; hydrophobicity and solubility shape constraints on hydrophobic clusters underneath the surface, and on salt bridges and polar networks at the protein surface together with charge and hydrogen bonding capacity.Amino acid solubility, flexibility and conformational descriptors also provide additional constraints at many locations.These findings provide fundamental insights into the chemistry underlying protein evolution and design, by quantitating links between sequence and different protein traits, illuminating subtle and unexpected sequence-trait relationships and pinpointing what traits are sacrificed upon gain-of-function mutation.

View Article: PubMed Central - PubMed

Affiliation: Laboratory for Biomolecular Modeling, School of Life Sciences, and Swiss Institute of Bioinformatics, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.

ABSTRACT
The need for interfacing structural biology and biophysics to molecular evolution is being increasingly recognized. One part of the big problem is to understand how physics and chemistry shape the sequence space available to functional proteins, while satisfying the needs of biology. Here we present a quantitative, structure-based analysis of a high-resolution map describing the tolerance to all substitutions in all positions of a functional enzyme, namely a TEM lactamase previously studied through deep sequencing of mutants growing in competition experiments with selection against ampicillin. Substitutions are rarely observed within 7 Å of the active site, a stringency that is relaxed slowly and extends up to 15-20 Å, with buried residues being especially sensitive. Substitution patterns in over one third of the residues can be quantitatively modeled by monotonic dependencies on amino acid descriptors and predictions of changes in folding stability. Amino acid volume and steric hindrance shape constraints on the protein core; hydrophobicity and solubility shape constraints on hydrophobic clusters underneath the surface, and on salt bridges and polar networks at the protein surface together with charge and hydrogen bonding capacity. Amino acid solubility, flexibility and conformational descriptors also provide additional constraints at many locations. These findings provide fundamental insights into the chemistry underlying protein evolution and design, by quantitating links between sequence and different protein traits, illuminating subtle and unexpected sequence-trait relationships and pinpointing what traits are sacrificed upon gain-of-function mutation.

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Related in: MedlinePlus

Structure mapping of the residues whose substitution patterns can be explained by the nine most common descriptors.The mapped amino acids are shown as red spheres, and residues Ser70, Lys73 and Glu166 as green spheres. All residue representations lack the main chain nitrogen, carbonyl carbon and oxygen atoms for clarity. The letters on the bottom right of each panel indicate the wild type amino acids most often found at the indicated locations, with the font size being roughly proportional to the relative number of occurrences of the amino acid. The small bar on the bottom right of each panel measures the fractional solvent exposure of the wild type residues to which the descriptor was mapped.
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pone.0118684.g004: Structure mapping of the residues whose substitution patterns can be explained by the nine most common descriptors.The mapped amino acids are shown as red spheres, and residues Ser70, Lys73 and Glu166 as green spheres. All residue representations lack the main chain nitrogen, carbonyl carbon and oxygen atoms for clarity. The letters on the bottom right of each panel indicate the wild type amino acids most often found at the indicated locations, with the font size being roughly proportional to the relative number of occurrences of the amino acid. The small bar on the bottom right of each panel measures the fractional solvent exposure of the wild type residues to which the descriptor was mapped.

Mentions: A more general interpretation of the results follows. For this, the descriptors most often selected are color-coded into the dots in Fig. 1 and mapped on TEM-1’s structure in Fig. 4. Different descriptors explain the ΔΔGstat distributions (or in other words, shape the sequence constraints) at different locations of the protein. Correlations with ΔΔGFoldX reflect the importance of hydrophobic clusters at the core (Fig. 4A and black dots in Fig. 1B) suggesting in turn that FoldX might perform particularly well for predictions of destabilization induced upon mutation deep inside protein cores. On top, correlations with Volume/(P(helix)+P(sheet)), Volume, Steric hindrance and Steric hindrance/P(sheet) mirror the need for small volumes and special residue packing at many locations inside the protein (Fig. 4B, D, E, H and Fig. 1B in cyan, blue, green, dark green, respectively). Finally, correlations against numbers of O or N atoms, number of hydrogen bonds or Isoelectric point map to residues involved in salt bridges and hydrogen bonds on the polar surface, like in the examples presented for Arg222 and Ser98.


How structural and physicochemical determinants shape sequence constraints in a functional enzyme.

Abriata LA, Palzkill T, Dal Peraro M - PLoS ONE (2015)

Structure mapping of the residues whose substitution patterns can be explained by the nine most common descriptors.The mapped amino acids are shown as red spheres, and residues Ser70, Lys73 and Glu166 as green spheres. All residue representations lack the main chain nitrogen, carbonyl carbon and oxygen atoms for clarity. The letters on the bottom right of each panel indicate the wild type amino acids most often found at the indicated locations, with the font size being roughly proportional to the relative number of occurrences of the amino acid. The small bar on the bottom right of each panel measures the fractional solvent exposure of the wild type residues to which the descriptor was mapped.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4338278&req=5

pone.0118684.g004: Structure mapping of the residues whose substitution patterns can be explained by the nine most common descriptors.The mapped amino acids are shown as red spheres, and residues Ser70, Lys73 and Glu166 as green spheres. All residue representations lack the main chain nitrogen, carbonyl carbon and oxygen atoms for clarity. The letters on the bottom right of each panel indicate the wild type amino acids most often found at the indicated locations, with the font size being roughly proportional to the relative number of occurrences of the amino acid. The small bar on the bottom right of each panel measures the fractional solvent exposure of the wild type residues to which the descriptor was mapped.
Mentions: A more general interpretation of the results follows. For this, the descriptors most often selected are color-coded into the dots in Fig. 1 and mapped on TEM-1’s structure in Fig. 4. Different descriptors explain the ΔΔGstat distributions (or in other words, shape the sequence constraints) at different locations of the protein. Correlations with ΔΔGFoldX reflect the importance of hydrophobic clusters at the core (Fig. 4A and black dots in Fig. 1B) suggesting in turn that FoldX might perform particularly well for predictions of destabilization induced upon mutation deep inside protein cores. On top, correlations with Volume/(P(helix)+P(sheet)), Volume, Steric hindrance and Steric hindrance/P(sheet) mirror the need for small volumes and special residue packing at many locations inside the protein (Fig. 4B, D, E, H and Fig. 1B in cyan, blue, green, dark green, respectively). Finally, correlations against numbers of O or N atoms, number of hydrogen bonds or Isoelectric point map to residues involved in salt bridges and hydrogen bonds on the polar surface, like in the examples presented for Arg222 and Ser98.

Bottom Line: Amino acid volume and steric hindrance shape constraints on the protein core; hydrophobicity and solubility shape constraints on hydrophobic clusters underneath the surface, and on salt bridges and polar networks at the protein surface together with charge and hydrogen bonding capacity.Amino acid solubility, flexibility and conformational descriptors also provide additional constraints at many locations.These findings provide fundamental insights into the chemistry underlying protein evolution and design, by quantitating links between sequence and different protein traits, illuminating subtle and unexpected sequence-trait relationships and pinpointing what traits are sacrificed upon gain-of-function mutation.

View Article: PubMed Central - PubMed

Affiliation: Laboratory for Biomolecular Modeling, School of Life Sciences, and Swiss Institute of Bioinformatics, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.

ABSTRACT
The need for interfacing structural biology and biophysics to molecular evolution is being increasingly recognized. One part of the big problem is to understand how physics and chemistry shape the sequence space available to functional proteins, while satisfying the needs of biology. Here we present a quantitative, structure-based analysis of a high-resolution map describing the tolerance to all substitutions in all positions of a functional enzyme, namely a TEM lactamase previously studied through deep sequencing of mutants growing in competition experiments with selection against ampicillin. Substitutions are rarely observed within 7 Å of the active site, a stringency that is relaxed slowly and extends up to 15-20 Å, with buried residues being especially sensitive. Substitution patterns in over one third of the residues can be quantitatively modeled by monotonic dependencies on amino acid descriptors and predictions of changes in folding stability. Amino acid volume and steric hindrance shape constraints on the protein core; hydrophobicity and solubility shape constraints on hydrophobic clusters underneath the surface, and on salt bridges and polar networks at the protein surface together with charge and hydrogen bonding capacity. Amino acid solubility, flexibility and conformational descriptors also provide additional constraints at many locations. These findings provide fundamental insights into the chemistry underlying protein evolution and design, by quantitating links between sequence and different protein traits, illuminating subtle and unexpected sequence-trait relationships and pinpointing what traits are sacrificed upon gain-of-function mutation.

Show MeSH
Related in: MedlinePlus