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Zhang Y, Jiang Y, Gao K, Sui D, Yu P, Su M, Wei GW, Hu J. Structural insights into the elevator-type transport mechanism of a bacterial ZIP metal transporter. Nat Commun 2023; 14:385. [PMID: 36693843 PMCID: PMC9873690 DOI: 10.1038/s41467-023-36048-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 01/13/2023] [Indexed: 01/26/2023] Open
Abstract
The Zrt-/Irt-like protein (ZIP) family consists of ubiquitously expressed divalent metal transporters critically involved in maintaining systemic and cellular homeostasis of zinc, iron, and manganese. Here, we present a study on a prokaryotic ZIP from Bordetella bronchiseptica (BbZIP) by combining structural biology, evolutionary covariance, computational modeling, and a variety of biochemical assays to tackle the issue of the transport mechanism which has not been established for the ZIP family. The apo state structure in an inward-facing conformation revealed a disassembled transport site, altered inter-helical interactions, and importantly, a rigid body movement of a 4-transmembrane helix (TM) bundle relative to the other TMs. The computationally generated and biochemically validated outward-facing conformation model revealed a slide of the 4-TM bundle, which carries the transport site(s), by approximately 8 Å toward the extracellular side against the static TMs which mediate dimerization. These findings allow us to conclude that BbZIP is an elevator-type transporter.
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Affiliation(s)
- Yao Zhang
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, USA
| | - Yuhan Jiang
- Department of Chemistry, Michigan State University, East Lansing, MI, USA
| | - Kaifu Gao
- Department of Mathematics, Michigan State University, East Lansing, MI, USA
| | - Dexin Sui
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, USA
| | - Peixuan Yu
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, USA
| | - Min Su
- Life Sciences Institute, University of Michigan, Ann Arbor, MI, USA
| | - Guo-Wei Wei
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, USA
- Department of Mathematics, Michigan State University, East Lansing, MI, USA
| | - Jian Hu
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, USA.
- Department of Chemistry, Michigan State University, East Lansing, MI, USA.
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2
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Neuwald AF, Yang H, Tracy Nixon B. SPARC: Structural properties associated with residue constraints. Comput Struct Biotechnol J 2022; 20:1702-1715. [PMID: 35495120 PMCID: PMC9020082 DOI: 10.1016/j.csbj.2022.04.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 03/22/2022] [Accepted: 04/05/2022] [Indexed: 11/17/2022] Open
Abstract
SPARC facilitates the generation of plausible hypotheses regarding underlying biochemical mechanisms by structurally characterizing protein sequence constraints. Such constraints appear as residues co-conserved in functionally related subgroups, as subtle pairwise correlations (i.e., direct couplings), and as correlations among these sequence features or with structural features. SPARC performs three types of analyses. First, based on pairwise sequence correlations, it estimates the biological relevance of alternative conformations and of homomeric contacts, as illustrated here for death domains. Second, it estimates the statistical significance of the correspondence between directly coupled residue pairs and interactions at heterodimeric interfaces. Third, given molecular dynamics simulated structures, it characterizes interactions among constrained residues or between such residues and ligands that: (a) are stably maintained during the simulation; (b) undergo correlated formation and/or disruption of interactions with other constrained residues; or (c) switch between alternative interactions. We illustrate this for two homohexameric complexes: the bacterial enhancer binding protein (bEBP) NtrC1, which activates transcription by remodeling RNA polymerase (RNAP) containing σ54, and for DnaB helicase, which opens DNA at the bacterial replication fork. Based on the NtrC1 analysis, we hypothesize possible mechanisms for inhibiting ATP hydrolysis until ADP is released from an adjacent subunit and for coupling ATP hydrolysis to restructuring of σ54 binding loops. Based on the DnaB analysis, we hypothesize that DnaB 'grabs' ssDNA by flipping every fourth base and inserting it into cavities between subunits and that flipping of a DnaB-specific glutamine residue triggers ATP hydrolysis.
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Affiliation(s)
- Andrew F. Neuwald
- Institute for Genome Sciences and Department of Biochemistry & Molecular Biology, University of Maryland School of Medicine, 670 W. Baltimore Steet, Baltimore, MD 21201, USA,Corresponding author.
| | - Hui Yang
- Department of Biology. Penn State University, 304A Frear South Building, University Park, PA 16802
| | - B. Tracy Nixon
- Department of Biochemistry and Molecular Biology, 335 Frear South Building, University Park, PA 16802, USA
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Neuwald AF, Lanczycki CJ, Hodges TK, Marchler-Bauer A. Obtaining extremely large and accurate protein multiple sequence alignments from curated hierarchical alignments. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2021; 2020:5850901. [PMID: 32500917 PMCID: PMC7297217 DOI: 10.1093/database/baaa042] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Revised: 04/01/2020] [Accepted: 05/06/2020] [Indexed: 11/12/2022]
Abstract
For optimal performance, machine learning methods for protein sequence/structural analysis typically require as input a large multiple sequence alignment (MSA), which is often created using query-based iterative programs, such as PSI-BLAST or JackHMMER. However, because these programs align database sequences using a query sequence as a template, they may fail to detect or may tend to misalign sequences distantly related to the query. More generally, automated MSA programs often fail to align sequences correctly due to the unpredictable nature of protein evolution. Addressing this problem typically requires manual curation in the light of structural data. However, curated MSAs tend to contain too few sequences to serve as input for statistically based methods. We address these shortcomings by making publicly available a set of 252 curated hierarchical MSAs (hiMSAs), containing a total of 26 212 066 sequences, along with programs for generating from these extremely large MSAs. Each hiMSA consists of a set of hierarchically arranged MSAs representing individual subgroups within a superfamily along with template MSAs specifying how to align each subgroup MSA against MSAs higher up the hierarchy. Central to this approach is the MAPGAPS search program, which uses a hiMSA as a query to align (potentially vast numbers of) matching database sequences with accuracy comparable to that of the curated hiMSA. We illustrate this process for the exonuclease–endonuclease–phosphatase superfamily and for pleckstrin homology domains. A set of extremely large MSAs generated from the hiMSAs in this way is available as input for deep learning, big data analyses. MAPGAPS, auxiliary programs CDD2MGS, AddPhylum, PurgeMSA and ConvertMSA and links to National Center for Biotechnology Information data files are available at https://www.igs.umaryland.edu/labs/neuwald/software/mapgaps/.
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Affiliation(s)
- Andrew F Neuwald
- Institute for Genome Sciences.,Department of Biochemistry & Molecular Biology, University of Maryland School of Medicine, 670 W. Baltimore Street, Baltimore, MD 21201, USA
| | - Christopher J Lanczycki
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Building 38 A, 8600 Rockville Pike, Bethesda, MD 20894, USA
| | | | - Aron Marchler-Bauer
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Building 38 A, 8600 Rockville Pike, Bethesda, MD 20894, USA
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Neuwald AF, Kolaczkowski BD, Altschul SF. eCOMPASS: evaluative comparison of multiple protein alignments by statistical score. Bioinformatics 2021; 37:3456-3463. [PMID: 33983436 PMCID: PMC8545322 DOI: 10.1093/bioinformatics/btab374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 03/31/2021] [Accepted: 05/12/2021] [Indexed: 11/21/2022] Open
Abstract
Motivation Detecting subtle biologically relevant patterns in protein sequences often requires the construction of a large and accurate multiple sequence alignment (MSA). Methods for constructing MSAs are usually evaluated using benchmark alignments, which, however, typically contain very few sequences and are therefore inappropriate when dealing with large numbers of proteins. Results eCOMPASS addresses this problem using a statistical measure of relative alignment quality based on direct coupling analysis (DCA): to maintain protein structural integrity over evolutionary time, substitutions at one residue position typically result in compensating substitutions at other positions. eCOMPASS computes the statistical significance of the congruence between high scoring directly coupled pairs and 3D contacts in corresponding structures, which depends upon properly aligned homologous residues. We illustrate eCOMPASS using both simulated and real MSAs. Availability and implementation The eCOMPASS executable, C++ open source code and input data sets are available at https://www.igs.umaryland.edu/labs/neuwald/software/compass Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Andrew F Neuwald
- Department of Biochemistry & Molecular Biology, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Bryan D Kolaczkowski
- Department of Microbiology & Cell Science, University of Florida, Gainesville, FL 32611, USA
| | - Stephen F Altschul
- Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA
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Neverov AD, Popova AV, Fedonin GG, Cheremukhin EA, Klink GV, Bazykin GA. Episodic evolution of coadapted sets of amino acid sites in mitochondrial proteins. PLoS Genet 2021; 17:e1008711. [PMID: 33493156 PMCID: PMC7861529 DOI: 10.1371/journal.pgen.1008711] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Revised: 02/04/2021] [Accepted: 12/07/2020] [Indexed: 11/19/2022] Open
Abstract
The rate of evolution differs between protein sites and changes with time. However, the link between these two phenomena remains poorly understood. Here, we design a phylogenetic approach for distinguishing pairs of amino acid sites that evolve concordantly, i.e., such that substitutions at one site trigger subsequent substitutions at the other; and also pairs of sites that evolve discordantly, so that substitutions at one site impede subsequent substitutions at the other. We distinguish groups of amino acid sites that undergo coordinated evolution and evolve discordantly from other such groups. In mitochondrion-encoded proteins of metazoans and fungi, we show that concordantly evolving sites are clustered in protein structures. By analysing the phylogenetic patterns of substitutions at concordantly and discordantly evolving site pairs, we find that concordant evolution has two distinct causes: epistatic interactions between amino acid substitutions and episodes of selection independently affecting substitutions at different sites. The rate of substitutions at concordantly evolving groups of protein sites changes in the course of evolution, indicating episodes of selection limited to some of the lineages. The phylogenetic positions of these changes are consistent between proteins, suggesting common selective forces underlying them. The mode and rate of evolution of a protein site depends on the effect of its mutations on protein fitness. The fitness effect of a mutation itself can change in the course of evolution for at least two reasons. First, it can be modulated by substitutions occurring at other sites, a phenomenon called epistasis. Second, changes in selection can be non-epistatic, affecting sites independently of one another. Here, we analyse substitutions accumulated by the evolving lineages of the five proteins encoded by the mitochondrial genomes of thousands of species of metazoans and fungi. We show that substitutions at different amino acid sites occur in a coordinated fashion, and this coordination is caused both by epistasis and by episodes of selection affecting groups of sites. We partition each protein into several groups of concordantly evolving sites such that evolution of sites from different groups is discordant, and show that the proteins encoded by the mitochondrial genome consist of coevolving structural blocks. Some of these blocks have a clear functional specialization, e.g. are associated with interfaces between proteins composing respiratory complexes. Together, our results reveal a previously unrecognized complexity in the causes of variation in evolutionary rates between protein sites.
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Affiliation(s)
- Alexey D. Neverov
- Department of Molecular Diagnostics, Central Research Institute for Epidemiology, Moscow, Russia
- * E-mail:
| | - Anfisa V. Popova
- Department of Molecular Diagnostics, Central Research Institute for Epidemiology, Moscow, Russia
| | - Gennady G. Fedonin
- Department of Molecular Diagnostics, Central Research Institute for Epidemiology, Moscow, Russia
- Institute for Information Transmission Problems (Kharkevich Institute), Russian Academy of Sciences, Moscow, Russia
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow region, Russia
| | | | - Galya V. Klink
- Institute for Information Transmission Problems (Kharkevich Institute), Russian Academy of Sciences, Moscow, Russia
| | - Georgii A. Bazykin
- Institute for Information Transmission Problems (Kharkevich Institute), Russian Academy of Sciences, Moscow, Russia
- Skolkovo Institute of Science and Technology, Skolkovo, Russia
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Deep Analysis of Residue Constraints (DARC): identifying determinants of protein functional specificity. Sci Rep 2020; 10:1691. [PMID: 32015389 PMCID: PMC6997377 DOI: 10.1038/s41598-019-55118-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2019] [Accepted: 11/23/2019] [Indexed: 01/03/2023] Open
Abstract
Protein functional constraints are manifest as superfamily and functional-subgroup conserved residues, and as pairwise correlations. Deep Analysis of Residue Constraints (DARC) aids the visualization of these constraints, characterizes how they correlate with each other and with structure, and estimates statistical significance. This can identify determinants of protein functional specificity, as we illustrate for bacterial DNA clamp loader ATPases. These load ring-shaped sliding clamps onto DNA to keep polymerase attached during replication and contain one δ, three γ, and one δ’ AAA+ subunits semi-circularly arranged in the order δ-γ1-γ2-γ3-δ’. Only γ is active, though both γ and δ’ functionally influence an adjacent γ subunit. DARC identifies, as functionally-congruent features linking allosterically the ATP, DNA, and clamp binding sites: residues distinctive of γ and of γ/δ’ that mutually interact in trans, centered on the catalytic base; several γ/δ’-residues and six γ/δ’-covariant residue pairs within the DNA binding N-termini of helices α2 and α3; and γ/δ’-residues associated with the α2 C-terminus and the clamp-binding loop. Most notable is a trans-acting γ/δ’ hydroxyl group that 99% of other AAA+ proteins lack. Mutation of this hydroxyl to a methyl group impedes clamp binding and opening, DNA binding, and ATP hydrolysis—implying a remarkably clamp-loader-specific function.
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