Evolutionary clues to eukaryotic DNA clamp-loading mechanisms: analysis of the functional constraints imposed on replication factor C AAA+ ATPases

Ring-shaped sliding clamps encircle DNA and bind to DNA polymerase, thereby preventing it from falling off during DNA replication. In eukaryotes, sliding clamps are loaded onto DNA by the replication factor C (RFC) complex, which consists of five distinct subunits (A–E), each of which contains an AAA+ module composed of a RecA-like α/β ATPase domain followed by a helical domain. AAA+ ATPases mediate chaperone-like protein remodeling. Despite remarkable progress in our understanding of clamp loaders, it is still unclear how recognition of primed DNA by RFC triggers ATP hydrolysis and how hydrolysis leads to conformational changes that can load the clamp onto DNA. While these questions can, of course, only be resolved experimentally, the design of such experiments is itself non-trivial and requires that one first formulate the right hypotheses based on preliminary observations. The functional constraints imposed on protein sequences during evolution are potential sources of information in this regard, inasmuch as these presumably are due to and thus reflect underlying mechanisms. Here, rigorous statistical procedures are used to measure and compare the constraints imposed on various RFC clamp-loader subunits, each of which performs a related but somewhat different, specialized function. Visualization of these constraints, within the context of the RFC structure, provides clues regarding clamp-loader mechanisms—suggesting, for example, that RFC-A possesses a triggering component for DNA-dependent ATP hydrolysis. It also suggests that, starting with RFC-A, four RFC subunits (A–D) are sequentially activated through a propagated switching mechanism in which a conserved arginine swings away from a position that disrupts the catalytic Walker B region and into contact with DNA thread through the center of the RFC/clamp complex. Strong constraints near regions of interaction between subunits and with the clamp likewise provide clues regarding possible coupling of hydrolysis-driven conformational changes to the clamp's release and loading onto DNA

The glycine brace: a component of Rab, Rho, and Ran GTPases associated with hinge regions of guanine- and phosphate-binding loops

<p>Abstract</p> <p>Background</p> <p>Ras-like GTPases function as on-off switches in intracellular signalling pathways and include the Rab, Rho/Rac, Ran, Ras, Arf, Sar and Gα families. How these families have evolutionarily diverged from each other at the sequence level provides clues to underlying mechanisms associated with their functional specialization.</p> <p>Results</p> <p>Bayesian analysis of divergent patterns within a multiple alignment of Ras-like GTPase sequences identifies a structural component, termed here the glycine brace, as the feature that most distinguishes Rab, Rho/Rac, Ran and (to some degree) Ras family GTPases from other Ras-like GTPases. The glycine brace consists of four residues: An aromatic residue that forms a stabilizing CH-π interaction with a conserved glycine at the start of the guanine-binding loop; a second aromatic residue, which is nearly always a tryptophan, that likewise forms stabilizing CH-π and NH-π interactions with a glycine at the start of the phosphate-binding P-loop; and two other residues (typically an aspartate and a serine or threonine) that, together with a conserved buried water molecule, form a network of interactions connecting the two aromatic residues.</p> <p>Conclusion</p> <p>It is proposed that the two glycine residues function as hinges and that the glycine brace influences guanine nucleotide binding and release by interacting with these hinges.</p

Bayesian classification of residues associated with protein functional divergence: Arf and Arf-like GTPases

<p>Abstract</p> <p>Background</p> <p>Certain residues within proteins are highly conserved across very distantly related organisms, yet their (presumably critical) structural or mechanistic roles are completely unknown. To obtain clues regarding such residues within Arf and Arf-like (Arf/Arl) GTPases--which function as on/off switches regulating vesicle trafficking, phospholipid metabolism and cytoskeletal remodeling--I apply a new sampling procedure for comparative sequence analysis, termed multiple category Bayesian Partitioning with Pattern Selection (mcBPPS).</p> <p>Results</p> <p>The mcBPPS sampler classified sequences within the entire P-loop GTPase class into multiple categories by identifying those evolutionarily-divergent residues most likely to be responsible for functional specialization. Here I focus on categories of residues that most distinguish various Arf/Arl GTPases from other GTPases. This identified residues whose specific roles have been previously proposed (and in some cases corroborated experimentally and that thus serve as positive controls), as well as several categories of co-conserved residues whose possible roles are first hinted at here. For example, Arf/Arl/Sar GTPases are most distinguished from other GTPases by a conserved aspartate residue within the phosphate binding loop (P-loop) and by co-conserved residues nearby that, together, can form a network of salt-bridge and hydrogen bond interactions centered on the GTPase active site. Residues corresponding to an N-[VI] motif that is conserved within Arf/Arl GTPases may play a role in the interswitch toggle characteristic of the Arf family, whereas other, co-conserved residues may modulate the flexibility of the guanine binding loop. Arl8 GTPases conserve residues that strikingly diverge from those typically found in other Arf/Arl GTPases and that form structural interactions suggestive of a novel interswitch toggle mechanism.</p> <p>Conclusions</p> <p>This analysis suggests specific mutagenesis experiments to explore mechanisms underlying GTP hydrolysis, nucleotide exchange and interswitch toggling within Arf/Arl GTPases. More generally, it illustrates how the mcBPPS sampler can complement traditional evolutionary analyses by providing an objective, quantitative and statistically rigorous way to explore protein functional-divergence in molecular detail. Because the sampler classifies the input sequences at the same time, it can be used to generate subgroup profiles, in which functionally-divergent categories of residues are annotated automatically.</p> <p>Reviewers</p> <p>This article was reviewed by Frank Eisenhaber, L Aravind and Daniel Gaston (nominated by Eric Bapteste). For the full reviews, go to the Reviewers' comments section.</p

A Model for Detecting Motifs in Biological Sequences

A method for detecting patterns in biological sequences is described that incorporates rigorous statistics for determining significances, and an algebraic system that, in combination with a depth first search procedure, can be used to efficiently search for all patterns up to a specified length. This method includes a context free command language grammar and is formulated using a mathematical model amendable to additions enhancements, The method was implemented and verified by detection of various types of patterns in protein sequences

Gapped alignment of protein sequence motifs through Monte Carlo optimization of a hidden Markov model

BACKGROUND: Certain protein families are highly conserved across distantly related organisms and belong to large and functionally diverse superfamilies. The patterns of conservation present in these protein sequences presumably are due to selective constraints maintaining important but unknown structural mechanisms with some constraints specific to each family and others shared by a larger subset or by the entire superfamily. To exploit these patterns as a source of functional information, we recently devised a statistically based approach called contrast hierarchical alignment and interaction network (CHAIN) analysis, which infers the strengths of various categories of selective constraints from co-conserved patterns in a multiple alignment. The power of this approach strongly depends on the quality of the multiple alignments, which thus motivated development of theoretical concepts and strategies to improve alignment of conserved motifs within large sets of distantly related sequences. RESULTS: Here we describe a hidden Markov model (HMM), an algebraic system, and Markov chain Monte Carlo (MCMC) sampling strategies for alignment of multiple sequence motifs. The MCMC sampling strategies are useful both for alignment optimization and for adjusting position specific background amino acid frequencies for alignment uncertainties. Associated statistical formulations provide an objective measure of alignment quality as well as automatic gap penalty optimization. Improved alignments obtained in this way are compared with PSI-BLAST based alignments within the context of CHAIN analysis of three protein families: G(iα )subunits, prolyl oligopeptidases, and transitional endoplasmic reticulum (p97) AAA+ ATPases. CONCLUSION: While not entirely replacing PSI-BLAST based alignments, which likewise may be optimized for CHAIN analysis using this approach, these motif-based methods often more accurately align very distantly related sequences and thus can provide a better measure of selective constraints. In some instances, these new approaches also provide a better understanding of family-specific constraints, as we illustrate for p97 ATPases. Programs implementing these procedures and supplementary information are available from the authors

Hypothesis: bacterial clamp loader ATPase activation through DNA-dependent repositioning of the catalytic base and of a trans-acting catalytic threonine

The prokaryotic DNA polymerase III clamp loader complex loads the β clamp onto DNA to link the replication complex to DNA during processive synthesis and unloads it again once synthesis is complete. This minimal complex consists of one δ, one δ′ and three γ subunits, all of which possess an AAA+ module—though only the γ subunit exhibits ATPase activity. Here clues to underlying clamp loader mechanisms are obtained through Bayesian inference of various categories of selective constraints imposed on the γ and δ′ subunits. It is proposed that a conserved histidine is ionized via electron transfer involving structurally adjacent residues within the sensor 1 region of γ's AAA+ module. The resultant positive charge on this histidine inhibits ATPase activity by drawing the negatively charged catalytic base away from the active site. It is also proposed that this arrangement is disrupted upon interaction of DNA with basic residues in γ implicated previously in DNA binding, regarding which a lysine that is near the sensor 1 region and that is highly conserved both in bacterial and in eukaryotic clamp loader ATPases appears to play a critical role. γ ATPases also appear to utilize a trans-acting threonine that is donated by helix 6 of an adjacent γ or δ′ subunit and that assists in the activation of a water molecule for nucleophilic attack on the γ phosphorous atom of ATP. As eukaryotic and archaeal clamp loaders lack most of these key residues, it appears that eubacteria utilize a fundamentally different mechanism for clamp loader activation than do these other organisms

Evolution of allostery in the cyclic nucleotide binding module

Analysis of cyclic nucleotide binding (CNB) domains shows that they have evolved to sense a wide variety of second messenger signals; a mechanism for allosteric regulation by CNB domains is proposed

Mechanochemical basis of protein degradation by a double-ring AAA+ machine

Molecular machines containing double or single AAA+ rings power energy-dependent protein degradation and other critical cellular processes, including disaggregation and remodeling of macromolecular complexes. How the mechanical activities of double-ring and single-ring AAA+ enzymes differ is unknown. Using single-molecule optical trapping, we determine how the double-ring ​ClpA enzyme from Escherichia coli, in complex with the ​ClpP peptidase, mechanically degrades proteins. We demonstrate that ​ClpA unfolds some protein substrates substantially faster than does the single-ring ​ClpX enzyme, which also degrades substrates in collaboration with ​ClpP. We find that ​ClpA is a slower polypeptide translocase and that it moves in physical steps that are smaller and more regular than steps taken by ​ClpX. These direct measurements of protein unfolding and translocation define the core mechanochemical behavior of a double-ring AAA+ machine and provide insight into the degradation of proteins that unfold via metastable intermediates.Howard Hughes Medical InstituteNational Institutes of Health (U.S.) (Grant AI-16892

Rapid detection, classification and accurate alignment of up to a million or more related protein sequences

Motivation: The patterns of sequence similarity and divergence present within functionally diverse, evolutionarily related proteins contain implicit information about corresponding biochemical similarities and differences. A first step toward accessing such information is to statistically analyze these patterns, which, in turn, requires that one first identify and accurately align a very large set of protein sequences. Ideally, the set should include many distantly related, functionally divergent subgroups. Because it is extremely difficult, if not impossible for fully automated methods to align such sequences correctly, researchers often resort to manual curation based on detailed structural and biochemical information. However, multiply-aligning vast numbers of sequences in this way is clearly impractical