Searcharxiv⌕ Search

arXiv · physics/0102044

Optimality of the genetic code with respect to protein stability and amino acid frequencies

Abstract

How robust is the natural genetic code with respect to mistranslation errors? It has long been known that the genetic code is very efficient in limiting the effect of point mutation. A misread codon will commonly code either for the same amino acid or for a similar one in terms of its biochemical properties, so the structure and function of the coded protein remain relatively unaltered. Previous studies have attempted to address this question more quantitatively, namely by statistically estimating the fraction of randomly generated codes that do better than the genetic code regarding its overall robustness. In this paper, we extend these results by investigating the role of amino acid frequencies in the optimality of the genetic code. When measuring the relative fitness of the natural code with respect to a random code, it is indeed natural to assume that a translation error affecting a frequent amino acid is less favorable than that of a rare one, at equal mutation cost. We find that taking the amino acid frequency into account accordingly decreases the fraction of random codes that beat the natural code, making the latter comparatively even more robust. This effect is particularly pronounced when more refined measures of the amino acid substitution cost are used than hydrophobicity. To show this, we devise a new cost function by evaluating with computer experiments the change in folding free energy caused by all possible single-site mutations in a set of known protein structures. With this cost function, we estimate that of the order of one random code out of 100 millions is more fit than the natural code when taking amino acid frequencies into account. The genetic code seems therefore structured so as to minimize the consequences of translation errors on the 3D structure and stability of proteins.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Dimitri Gilis, Serge Massar, Nicolas Cerf, Marianne Rooman. 2001-02-14. Optimality of the genetic code with respect to protein stability and amino acid frequencies. https://arxiv.org/abs/physics/0102044

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Exploring the World of Lipids with Machine-Learned Coarse-Grained Models

Lipid bilayers are central to cellular organization and function, yet their atomistic modelling remains constrained by its high computational cost. While coarse-grained (CG) models can overcome this bottleneck, they are limited in accuracy due to the use of simplified functional forms based on molecular mechanics. Using a hybrid functional form combining physics-based terms with a graph neural network, we present implicit-solvent, machine-learned CG models for POPC. When trained on single-lipid data, the model recovers the atomistic conformational landscape. By adding short atomistic simulations of a small flat bilayer to the training data and combining force matching with a denoising objective, we train a model that accurately reproduces bilayer structure and dynamics, in closer agreement with the atomistic reference than existing models, like Martini3 and DryMartini. Beyond its training data, the model stabilizes curved geometries, including vesicles, and captures complex cooperative phenomena such as bilayer and vesicle self-assembly and pore sealing. While limitations remain, particularly regarding chemical transferability, our results establish machine-learned coarse-grained potentials as a promising path towards robust and accurate CG models of lipids and membranes.

physics.bio-ph↗

Mechanical properties of chiral helical polymers-from single filaments to actin bundles

The mechanical properties of biological polymers are essential to their biological functions. Here, we introduce a highly coarse-grained model of helical filaments that preserves helicity and chirality while enabling mesoscale simulations. This is implemented in Cytosim, a widely-used open-source cytoskeleton simulation platform. We first show that we can predict the shape and mechanical properties of this helical filament, allowing for its fine control. We find the parameters that allow the resulting filament to accurately match the properties of actin filaments found experimentally}. Using this model of actin, we investigated the role of actin chirality in motor-driven dynamics. We first show that in two different experimental configurations, motor movement along a helical filament results in a chiral motion of the filament. In a bundle of helical filaments, dimeric motors exert torques on each filament, inducing collective behaviors in the bundle such as rotation, coiling, and helical buckling, reminiscent of those observed in filopodia. Together, these results demonstrate the central role of helicity and chirality in actin mechanics and motor-driven dynamics, and establish our framework as a powerful tool for mesoscale simulations. This framework can also be used for other helical filaments beyond actin.

physics.bio-ph↗

Finite-size scaling and cutoff functions of critical avalanches under cubic saturation

Power-law avalanche statistics characterize the branching bulk but leave open how finite systems terminate their largest events. Here we determine both the finite-size cutoff and the full crossover function connecting the branching regime to the large-event tail for an exchangeable absorbing event process motivated by Cauchy-stable recurrent dynamics. The Cauchy dynamical mean-field theory yields a linear-cubic low-activity drift, while a repeatable-event lift supplies absorbing branching fluctuations. Their competition at criticality generates a distinct finite-size edge controlled by cubic saturation. For avalanches initiated by a fixed microscopic seed, the rescaled edge measure connects the universal branching power law continuously to an exponential large-area tail. This full crossover admits an analytic spectral representation in terms of the boundary spectrum of a quartic Schrödinger operator on the half-line: high modes reconstruct the branching singularity, while the ground state fixes the far-tail decay. Exact finite-size calculations and Monte Carlo simulations confirm both the predicted cutoff behavior and the full spectral crossover.

physics.bio-ph↗