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Summary Phenological response to global climate change can impact ecosystem functions. There are various data sources from which spatiotemporal and taxonomic phenological data may be obtained: mobilized herbaria, community science initiatives, observatory networks, and remote sensing. However, analyses conducted to date have generally relied on single sources of these data. Siloed treatment of data in analyses may be due to the lack of harmonization across different data sources that offer partially nonoverlapping information and are often complementary. Such treatment precludes a deeper understanding of phenological responses at varying macroecological scales. Here, we describe a detailed vision for the harmonization of phenological data, including the direct integration of disparate sources of phenological data using a common schema. Specifically, we highlight existing methods for data harmonization that can be applied to phenological data: data design patterns, metadata standards, and ontologies. We describe how harmonized data from multiple sources can be integrated into analyses using existing methods and discuss the use of automated extraction techniques. Data harmonization is not a new concept in ecology, but the harmonization of phenological data is overdue. We aim to highlight the need for better data harmonization, providing a roadmap for how harmonized phenological data may fill gaps while simultaneously being integrated into analyses. 

Abstract Computationally modeling how mutations affect protein–protein binding not only helps uncover the biophysics of protein interfaces, but also enables the redesign and optimization of protein interactions. Traditional high‐throughput methods for estimating binding free energy changes are currently limited to mutations directly at the interface due to difficulties in accurately modeling how long‐distance mutations propagate their effects through the protein structure. However, the modeling and design of such mutations is of substantial interest as it allows for greater control and flexibility in protein design applications. We have developed a method that combines high‐throughput Rosetta‐based side‐chain optimization with conformational sampling using classical molecular dynamics simulations, finding significant improvements in our ability to accurately predict long‐distance mutational perturbations to protein binding. Our approach uses an analytical framework grounded in alchemical free energy calculations while enabling exploration of a vastly larger sequence space. When comparing to experimental data, we find that our method can predict internal long‐distance mutational perturbations with a level of accuracy similar to that of traditional methods in predicting the effects of mutations at the protein–protein interface. This work represents a new and generalizable approach to optimize protein free energy landscapes for desired biological functions. 

The heterodimerization of wild-type (WT) Cu, Zn superoxide dismutase-1 (SOD1) and mutant SOD1 might be a critical step in the pathogenesis of SOD1-linked amyotrophic lateral sclerosis (ALS). Post-translational modifications that accelerate SOD1 heterodimerization remain unidentified. Here, we used capillary electrophoresis to quantify the effect of cysteine-111 oxidation on the rate and free energy of ALS mutant/WT SOD1 heterodimerization. The oxidation of Cys111-β-SH to sulfinic and sulfonic acid (by hydrogen peroxide) increased rates of heterodimerization (with unoxidized protein) by ∼3-fold. Cysteine oxidation drove the equilibrium free energy of SOD1 heterodimerization by up to ΔΔG = −5.11 ± 0.36 kJ mol–1. Molecular dynamics simulations suggested that this enhanced heterodimerization, between oxidized homodimers and unoxidized homodimers, was promoted by electrostatic repulsion between the two “dueling” Cys111-SO2–/SO3–, which point toward one another in the homodimeric state. Together, these results suggest that oxidation of Cys-111 promotes subunit exchange between oxidized homodimers and unoxidized homodimers, regardless of whether they are mutant or WT dimers.