High accuracy of major biological processes relies on the ability of the participating enzymatic molecules to preferentially select the correct substrate from a pool of chemically similar substrates by activating the so-called proofreading mechanisms. While the importance of such mechanisms is widely accepted, it is still unclear how evolution has optimized the biological systems with respect to certain characteristic properties. Here, using a discrete-state stochastic framework with a first-passage analysis, we theoretically investigate trade-offs between four characteristic properties of enzymatic systems, namely, error, speed, noise, and energy dissipation. Specifically, two fundamental biological processes are examined, i.e., DNA replication in the T7 bacteriophage and tRNA selection during protein translation in Escherichia coli. Notably, all of the characteristic properties cannot be completely optimized at the same time due to trade-offs between them. To understand the relative importance of the computed quantities to the enzymatic functionality, we introduce a new quantitative metric to rank the properties. The results demonstrate that the reaction speed is the principal characteristic property that evolution optimizes in both enzymatic systems and that the energy dissipation comes in second. In addition, the error and the noise are always ranked third and fourth, respectively, regardless of the system considered. Physicochemical arguments to explain these observations are presented.
We employ the diffusion Monte Carlo (DMC) method in conjunction with the recently developed, ab initio-based MB-pol potential energy surface to characterize the ground states of small (H2O)2−6 clusters and their deuterated isotopomers. Observables, other than the ground state energies, are computed using the descendant weighting approach. Among those are various spatial correlation functions and relative isomer fractions. Interestingly, the ground states of all clusters considered in this study, except for the dimer, are delocalized over at least two conformations that differ by the orientation of one or more water monomers with the relative isomer populations being sensitive to the isotope substitution. Most remarkably, the ground state of the (H2O)6 hexamer is represented by four distinct cage structures, while that of (D2O)6 is dominated by the prism, i.e., the global minimum geometry, with a very small contribution from a prism-book geometry. In addition, for (H2O)6 and (D2O)6, we performed DMC calculations to compute the ground states constrained to the cage and prism geometries. These calculations compared results for three different potentials, MB-pol, TTM3/F, and q-TIP4P/F.
In this article, we present the first comprehensive study of metallophilic (aurophilic) interactions using dispersion-corrected density-functional theory. Dispersion interactions (an essential component of metallophilicity) are treated using the exchange-hole dipole moment (XDM) model. By comparing against coupled-cluster benchmark calculations on simple dimers, we show that LC-ωPBE-XDM is a viable functional to study interactions between closed-shell transition metals and that it performs uniformly better than second-order Møller-Plesset theory, the basic computational technique used in previous works. We apply LC-ωPBE-XDM to address several open questions regarding metallophilicity, such as the interplay between dispersion and relativistic effects, the interaction strength along group 11, the additivity of homo- and hetero-metallophilic effects, the stability of [E(AuPH3)4]+ cations (E = N, P, As, Sb), and the role of metallophilic effects in crystal packing. We find that relativistic effects explain the prevalence of aurophilicity not by stabilizing metal-metal contacts, but by preventing gold from forming ionic structures involving bridge anions (which are otherwise common for Ag and Cu) as a result of the increased electron affinity of the metal. Dispersion effects are less important than previously assumed and their stabilization contribution is relatively independent of the metal.
Living systems maintain a high fidelity in information processing through kinetic proofreading, a mechanism to preferentially remove incorrect substrates at the cost of energy dissipation and slower speed. Proofreading mechanisms must balance their demand for higher speed, fewer errors, and lower dissipation, but it is unclear how rates of individual reaction steps are evolutionary tuned to balance these needs, especially when multiple proofreading mechanisms are present. Here, using a discrete-state stochastic model, we analyze the optimization strategies in Escherichia coli isoleucyl-tRNA synthetase. Surprisingly, this enzyme adopts an economic proofreading strategy and improves speed and dissipation as long as the error is tolerable. Through global parameter sampling, we reveal a fundamental dissipation-error relation that bounds the enzyme's optimal performance and explains the importance of the post-transfer editing mechanism. The proximity of native system parameters to this bound demonstrates the importance of energy dissipation as an evolutionary force affecting fitness. Graphical TOC EntryM a x i m a l A c c u r a c y M a x i m a l S p e e d Min imal Diss ipati on tRNA Ile synthetase 2 . CC-BY-NC-ND 4.
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