arXiv subjects

Jesse D Bloom

Publications and source records attributed to Jesse D Bloom.

4 recordsLinked to original sources

arXiv2019

When Two are Better than One: Modeling the Mechanisms of Antibody Mixtures

It is difficult to predict how antibodies will behave when mixed together, even after each has been independently characterized. Here, we present a statistical mechanical model for the activity of antibody mixtures that accounts for whether pairs of antibodies bind to distinct or overlapping epitopes. This model requires measuring $n$ individual antibodies and their $n(n-1)/2$ pairwise interactions to predict the $2^n$ potential combinations. We apply this model to epidermal growth factor receptor (EGFR) antibodies and find that the activity of antibody mixtures can be predicted without positing synergy at the molecular level. In addition, we demonstrate how the model can be used in reverse, where straightforward experiments measuring the activity of antibody mixtures can be used to infer the molecular interactions between antibodies. Lastly, we generalize this model to analyze engineered multidomain antibodies, where components of different antibodies are tethered together to form novel amalgams, and characterize how well it predicts recently designed influenza antibodies.

q-bio.CB↗

arXiv2007

Neutral genetic drift can aid functional protein evolution

BACKGROUND: Many of the mutations accumulated by naturally evolving proteins are neutral in the sense that they do not significantly alter a protein's ability to perform its primary biological function. However, new protein functions evolve when selection begins to favor other, "promiscuous" functions that are incidental to a protein's biological role. If mutations that are neutral with respect to a protein's primary biological function cause substantial changes in promiscuous functions, these mutations could enable future functional evolution. RESULTS: Here we investigate this possibility experimentally by examining how cytochrome P450 enzymes that have evolved neutrally with respect to activity on a single substrate have changed in their abilities to catalyze reactions on five other substrates. We find that the enzymes have sometimes changed as much as four-fold in the promiscuous activities. The changes in promiscuous activities tend to increase with the number of mutations, and can be largely rationalized in terms of the chemical structures of the substrates. The activities on chemically similar substrates tend to change in a coordinated fashion, potentially providing a route for systematically predicting the change in one function based on the measurement of several others. CONCLUSIONS: Our work suggests that initially neutral genetic drift can lead to substantial changes in protein functions that are not currently under selection, in effect poising the proteins to more readily undergo functional evolution should selection "ask new questions" in the future.

q-bio.PE↗

arXiv2007

Thermodynamics of Neutral Protein Evolution

Naturally evolving proteins gradually accumulate mutations while continuing to fold to thermodynamically stable native structures. This process of neutral protein evolution is an important mode of genetic change, and forms the basis for the molecular clock. Here we present a mathematical theory that predicts the number of accumulated mutations, the index of dispersion, and the distribution of stabilities in an evolving protein population from knowledge of the stability effects (ddG values) for single mutations. Our theory quantitatively describes how neutral evolution leads to marginally stable proteins, and provides formulae for calculating how fluctuations in stability cause an overdispersion of the molecular clock. It also shows that the structural influences on the rate of sequence evolution that have been observed in earlier simulations can be calculated using only the single-mutation ddG values. We consider both the case when the product of the population size and mutation rate is small and the case when this product is large, and show that in the latter case proteins evolve excess mutational robustness that is manifested by extra stability and increases the rate of sequence evolution. Our basic method is to treat protein evolution as a Markov process constrained by a minimal requirement for stable folding, enabling an evolutionary description of the proteins solely in terms of the experimentally measureable ddG values. All of our theoretical predictions are confirmed by simulations with model lattice proteins. Our work provides a mathematical foundation for understanding how protein biophysics helps shape the process of evolution.

q-bio.PE↗

arXiv2004

Stability and the Evolvability of Function in a Model Protein

Functional proteins must fold with some minimal stability to a structure that can perform a biochemical task. Here we use a simple model to investigate the relationship between the stability requirement and the capacity of a protein to evolve the function of binding to a ligand. Although our model contains no built-in tradeoff between stability and function, proteins evolved function more efficiently when the stability requirement was relaxed. Proteins with both high stability and high function evolved more efficiently when the stability requirement was gradually increased than when there was constant selection for high stability. These results show that in our model, the evolution of function is enhanced by allowing proteins to explore sequences corresponding to marginally stable structures, and that it is easier to improve stability while maintaining high function than to improve function while maintaining high stability. Our model also demonstrates that even in the absence of a fundamental biophysical tradeoff between stability and function, the speed with which function can evolve is limited by the stability requirement imposed on the protein.

q-bio.BM↗