Deep Analysis of Residue Constraints (DARC): identifying determinants of protein functional specificity

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 semicircularly arranged in the order δ-γ 1-γ 2-γ 3-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 transacting 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. An important question in biology is which sequence and structural features enable proteins sharing a common catalytic core to perform entirely different functions. Consider, for example, AAA+ ATPases, which mediate a wide variety of cellular activities, including membrane fusion, DNA replication, microtubule dynamics, intracellular transport, transcriptional activation, protein refolding or degradation, and the disassembly of protein complexes 1,2. These form homomeric or heteromeric complexes consisting of from five to seven AAA+ modules with ATP-binding sites typically interacting with an adjacent module. Each complex channels the energy of ATP hydrolysis into coordinated conformational changes specific to its function. Although we cannot directly observe the biochemical mechanisms mediating these processes, given enough sequence data we can infer mechanistically imposed constraints. The nature of these constraints varies. They may appear as residues conserved in an entire superfamily or in functionally related protein subgroups (i.e., as correlations between sequence patterns and biochemical properties), as subtle pairwise correlations, or as correlations among these sequence features or with structural features. Previously investigated protein constraints include function determining residues (FDRs), "coevolving sectors", directly coupled (DC) residue pairs, and subgroup-specific patterns. FDR methods 3-24 generally focus on predicting specific, well-characterized residue functions, such as in substrate recognition and catalysis, that can be benchmarked experimentally 25. However, due to the incompleteness of experimental annotatio...

Allosteric communication in DNA polymerase clamp loaders relies on a critical hydrogen-bonded junction

“…Gln 118 is conserved in phage and eukaryotic clamp loaders, but there is no corresponding residue in bacterial clamp loaders. A recent analysis of the sequences of bacterial clamp loaders has identified residues that are uniquely present in those clamp loaders ( Tondnevis et al, 2020 ), and it will be interesting to see if that analysis provides clues as to how the bacterial proteins compensate for the absence of the glutamine residue.…”

Extending the application of the SCA/Sectors method for the identification of domain boundaries and subtype specific residues in multi-domain biosynthetic proteins: Application to Polyketide Synthases

“…Since the depth of the sequence alignment was clearly important in the analysis presented in this paper, the incorporation of such techniques into neural networks proposes exciting possibilities for the future. Beyond this other methods for calculating groups of co-evolving residues, not investigated here, already exist [55, 56] and using unsupervised training of deep networks also seems to reveal information about the structure of proteins [57]. However, the aforementioned methods have yet to be tested against experiment in the way that SCA/sectors analysis has.…”

Allosteric communication in DNA polymerase clamp loaders relies on a critical hydrogen-bonded junction

“…Gln 118 is conserved in phage and eukaryotic clamp loaders, but there is no corresponding residue in bacterial clamp loaders. A recent analysis of the sequences of bacterial clamp loaders has identified residues that are uniquely present in those clamp loaders (Tondnevis et al, 2020), . CC-BY-ND 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.…”