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Hydrophobicity Revisited: a Molecular Story

preprint
submitted on 07.06.2020 and posted on 08.06.2020 by David Cavanaugh, Krishnan Chittur
In a previous paper we have introduced a new hydrophobicity proclivity scale and justified its superior performance characteristics, particularly in the context of a scale for protein alignments, but also for its strong correlation with many other amino-acid physico-chemical properties. Within that paper, we calculated a corrected free energy of residue burial of each amino-acid in folded proteins from a linear regression of amino-acid free energy of transfer from water to n-Octanol (F&P octanol scale dGow, Y axis) and our Hydrophobicity Proclivity Scale
(HPS, X axis). In this present paper we pursue the latter general findings in more detail by considering the relationship of hydrophobicity and other physico-amino-
acid scales with the molecular geometry of amino-acids and secondary group structure/surface chemistry, with a concommitant discussion of the dimensions/geometry
of the caveties that amino-acids make in water. We identify a series of molecular physico-chemical properties that uniquely define the natural selection and geometry of the 20 natural amino-acids. We use the corrected free energy of amino-acid burials in proteins (Y axis) and a multiple linear regression to identify the AA molecular physico-chemical properties (X1, X2, ...) that explain the energetics of amino-
acid water contacts in an unfolded protein state to that of the folded protein state by modeling these two states as a solvent-solvent transfer, thus, providing a thermodynamical model for the initial stages of protein folding. Between our previous paper and the current paper we can greatly simplify and reduce the very large number of amino-acid scales in the literature to a small number of amino-acid property scales. Finally, we explore the numerical relationship between the structure of the genetic code and molecular physico-chemical properties of AA’s that in turn can be related directly to hydrophobicity. We validate and explain our novel models we describe herein with extensive data from the literature.

History

Email Address of Submitting Author

david.cavanaugh@bench.com

Institution

Benchmark

Country

USA

ORCID For Submitting Author

0000-0002-7709-2287

Declaration of Conflict of Interest

None

Version Notes

Revision 1b

Exports