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      Evolution of Minimal Specificity and Promiscuity in Steroid Hormone Receptors

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          Abstract

          Most proteins are regulated by physical interactions with other molecules; some are highly specific, but others interact with many partners. Despite much speculation, we know little about how and why specificity/promiscuity evolves in natural proteins. It is widely assumed that specific proteins evolved from more promiscuous ancient forms and that most proteins' specificity has been tuned to an optimal state by selection. Here we use ancestral protein reconstruction to trace the evolutionary history of ligand recognition in the steroid hormone receptors (SRs), a family of hormone-regulated animal transcription factors. We resurrected the deepest ancestral proteins in the SR family and characterized the structure-activity relationships by which they distinguished among ligands. We found that that the most ancient split in SR evolution involved a discrete switch from an ancient receptor for aromatized estrogens—including xenobiotics—to a derived receptor that recognized non-aromatized progestagens and corticosteroids. The family's history, viewed in relation to the evolution of their ligands, suggests that SRs evolved according to a principle of minimal specificity: at each point in time, receptors evolved ligand recognition criteria that were just specific enough to parse the set of endogenous substances to which they were exposed. By studying the atomic structures of resurrected SR proteins, we found that their promiscuity evolved because the ancestral binding cavity was larger than the primary ligand and contained excess hydrogen bonding capacity, allowing adventitious recognition of larger molecules with additional functional groups. Our findings provide an historical explanation for the sensitivity of modern SRs to natural and synthetic ligands—including endocrine-disrupting drugs and pollutants—and show that knowledge of history can contribute to ligand prediction. They suggest that SR promiscuity may reflect the limited power of selection within real biological systems to discriminate between perfect and “good enough.”

          Author Summary

          The functions of most proteins are defined by their interactions with other biological substances, such as DNA, nutrients, hormones, or other proteins. Some proteins are highly specific, but others are more promiscuous and can interact with a variety of natural substances, as well as drugs and pollutants. Understanding molecular interactions is a key goal in pharmacology and toxicology, but there are few general principles to help explain or predict protein specificity. Because every biological entity is the result of evolution, understanding a protein's history might help explain why it interacts with the substances to which it is sensitive. In this paper, we used ancestral protein reconstruction to experimentally trace how specificity evolved in an ancient group of proteins, the steroid hormone receptors (SRs), a family of proteins that regulate reproduction and other biological processes in animals. We show that SRs evolved according to a principle of minimal specificity: at each point in time, these proteins evolved to be specific enough to distinguish among the substances to which they were naturally exposed, but not more so. Our findings provide an historical explanation for modern SRs' diverse sensitivities to natural and man-made substances; they show that knowledge of history can contribute to predicting the ligands to which a modern protein will respond and indicate that promiscuity reflects the limited power of natural selection to discriminate between perfect and “good enough.”

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          Most cited references31

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          Structure validation by Calpha geometry: phi,psi and Cbeta deviation.

          Geometrical validation around the Calpha is described, with a new Cbeta measure and updated Ramachandran plot. Deviation of the observed Cbeta atom from ideal position provides a single measure encapsulating the major structure-validation information contained in bond angle distortions. Cbeta deviation is sensitive to incompatibilities between sidechain and backbone caused by misfit conformations or inappropriate refinement restraints. A new phi,psi plot using density-dependent smoothing for 81,234 non-Gly, non-Pro, and non-prePro residues with B < 30 from 500 high-resolution proteins shows sharp boundaries at critical edges and clear delineation between large empty areas and regions that are allowed but disfavored. One such region is the gamma-turn conformation near +75 degrees,-60 degrees, counted as forbidden by common structure-validation programs; however, it occurs in well-ordered parts of good structures, it is overrepresented near functional sites, and strain is partly compensated by the gamma-turn H-bond. Favored and allowed phi,psi regions are also defined for Pro, pre-Pro, and Gly (important because Gly phi,psi angles are more permissive but less accurately determined). Details of these accurate empirical distributions are poorly predicted by previous theoretical calculations, including a region left of alpha-helix, which rates as favorable in energy yet rarely occurs. A proposed factor explaining this discrepancy is that crowding of the two-peptide NHs permits donating only a single H-bond. New calculations by Hu et al. [Proteins 2002 (this issue)] for Ala and Gly dipeptides, using mixed quantum mechanics and molecular mechanics, fit our nonrepetitive data in excellent detail. To run our geometrical evaluations on a user-uploaded file, see MOLPROBITY (http://kinemage.biochem.duke.edu) or RAMPAGE (http://www-cryst.bioc.cam.ac.uk/rampage). Copyright 2003 Wiley-Liss, Inc.
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            Origins of specificity in protein-DNA recognition.

            Specific interactions between proteins and DNA are fundamental to many biological processes. In this review, we provide a revised view of protein-DNA interactions that emphasizes the importance of the three-dimensional structures of both macromolecules. We divide protein-DNA interactions into two categories: those when the protein recognizes the unique chemical signatures of the DNA bases (base readout) and those when the protein recognizes a sequence-dependent DNA shape (shape readout). We further divide base readout into those interactions that occur in the major groove from those that occur in the minor groove. Analogously, the readout of the DNA shape is subdivided into global shape recognition (for example, when the DNA helix exhibits an overall bend) and local shape recognition (for example, when a base pair step is kinked or a region of the minor groove is narrow). Based on the >1500 structures of protein-DNA complexes now available in the Protein Data Bank, we argue that individual DNA-binding proteins combine multiple readout mechanisms to achieve DNA-binding specificity. Specificity that distinguishes between families frequently involves base readout in the major groove, whereas shape readout is often exploited for higher resolution specificity, to distinguish between members within the same DNA-binding protein family.
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              Protein structure modeling with MODELLER.

              Genome sequencing projects have resulted in a rapid increase in the number of known protein sequences. In contrast, only about one-hundredth of these sequences have been characterized using experimental structure determination methods. Computational protein structure modeling techniques have the potential to bridge this sequence-structure gap. This chapter presents an example that illustrates the use of MODELLER to construct a comparative model for a protein with unknown structure. Automation of similar protocols (correction of protcols) has resulted in models of useful accuracy for domains in more than half of all known protein sequences.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Genet
                PLoS Genet
                plos
                plosgen
                PLoS Genetics
                Public Library of Science (San Francisco, USA )
                1553-7390
                1553-7404
                November 2012
                November 2012
                15 November 2012
                : 8
                : 11
                : e1003072
                Affiliations
                [1 ]Institute of Ecology and Evolution, University of Oregon, Eugene, Oregon, United States of America
                [2 ]Howard Hughes Medical Institute, Eugene, Oregon, United States of America
                [3 ]Biochemistry Department, Emory University School of Medicine, Atlanta, Georgia, United States of America
                [4 ]Department of Human Genetics and Department of Ecology and Evolution, University of Chicago, Chicago, Illinois, United States of America
                University of Michigan, United States of America
                Author notes

                The authors have declared that no competing interests exist.

                Conceived and designed the experiments: JWT GNE JKC MJH EAO. Performed the experiments: GNE JKC MJH. Analyzed the data: GNE JKC MJH JWT EAO. Wrote the paper: JWT GNE MJH JKC EAO.

                Article
                PGENETICS-D-12-01895
                10.1371/journal.pgen.1003072
                3499368
                23166518
                09add3d2-4db7-4a33-9a31-a0230d51d051
                Copyright @ 2012

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 23 July 2012
                : 21 September 2012
                Page count
                Pages: 10
                Funding
                This work was supported by NIH R01-GM081592 and F32-GM090650, NSF IOB-0546906 and DEB-0516530, and the Howard Hughes Medical Institute. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Biochemistry
                Evolutionary Biology
                Evolutionary Processes
                Adaptation
                Evolutionary Systematics
                Phylogenetics
                Synthetic Biology
                Toxicology

                Genetics
                Genetics

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