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      A hydrophobic ratchet entrenches molecular complexes

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          Abstract

          Most proteins assemble into multisubunit complexes 1 . The persistence of these complexes across evolutionary time is usually explained as the result of natural selection for functional properties that depend upon multimerization, like intersubunit allostery or the capacity to do mechanical work 2 . In many complexes, however, multimerization does not enable any known function 3 . An alternative explanation is that multimers could become entrenched if substitutions accumulate that are neutral in multimers but deleterious in monomers; purifying selection would then prevent reversion to the unassembled form, even if assembly per se does not enhance biological function 37 . Here we show that a hydrophobic mutational ratchet systematically entrenches molecular complexes. By applying ancestral protein reconstruction and biochemical assays to the evolution of steroid hormone receptors (SRs), we show that an ancient hydrophobic interface, conserved for hundreds of millions of years, is entrenched because exposing this interface to solvent reduces protein stability and causes aggregation, despite making no detectable contribution to function. Using structural bioinformatics, we show that a universal mutational propensity drives sites that are buried in multimeric interfaces to accumulate hydrophobic substitutions to levels not tolerated in monomers. In a database of hundreds of families of multimers, the majority show signatures of long-term hydrophobic entrenchment. It is therefore likely that many protein complexes persist because a simple ratchet-like mechanism entrenches them across evolutionary time, even when they are functionally gratuitous.

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          GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers

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              New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0.

              PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasonable starting tree topology. Since the original publication (Guindon S., Gascuel O. 2003. A simple, fast and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52:696-704), PhyML has been widely used (>2500 citations in ISI Web of Science) because of its simplicity and a fair compromise between accuracy and speed. In the meantime, research around PhyML has continued, and this article describes the new algorithms and methods implemented in the program. First, we introduce a new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves. The parsimony criterion is used here to filter out the least promising topology modifications with respect to the likelihood function. The analysis of a large collection of real nucleotide and amino acid data sets of various sizes demonstrates the good performance of this method. Second, we describe a new test to assess the support of the data for internal branches of a phylogeny. This approach extends the recently proposed approximate likelihood-ratio test and relies on a nonparametric, Shimodaira-Hasegawa-like procedure. A detailed analysis of real alignments sheds light on the links between this new approach and the more classical nonparametric bootstrap method. Overall, our tests show that the last version (3.0) of PhyML is fast, accurate, stable, and ready to use. A Web server and binary files are available from http://www.atgc-montpellier.fr/phyml/.
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                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                19 May 2021
                09 December 2020
                December 2020
                09 June 2021
                : 588
                : 7838
                : 503-508
                Affiliations
                [1. ]Department of Ecology and Evolution, University of Chicago, Chicago USA 60637
                [2. ]Department of Chemistry, Texas A&M University, College Station, Texas USA 77843-3255
                [3. ]Department of Chemistry – BMC, Uppsala University, Uppsala, Sweden 75123
                [4. ]Department of Human Genetics, University of Chicago, Chicago USA 60637
                Author notes

                Author contributions. GKAH and JWT conceived the project and oversaw the manuscript writing. GKA performed phylogenetics, ancestral sequence reconstruction, protein purification, cell culture, and biophysical experiments. YL and AL performed and interpreted native MS experiments. EGM performed and analyzed molecular dynamics simulations. GKAH and BPHM designed bioinformatic analyses, which GKAH performed. GKAH and JWT interpreted all data. All authors contributed to manuscript writing.

                [* ]Editorial correspondence: Joseph Thornton, joet1@ 123456uchicago.edu , 1-773-834-3423
                Article
                NIHMS1639716
                10.1038/s41586-020-3021-2
                8168016
                33299178
                af95e736-51d4-4824-9df4-e2d7506aa4b7

                Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

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