ReviewThe protein journal2019
Why Proteins are Big: Length Scale Effects on Equilibria and Kinetics.
Review in The protein journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 10 citations in OpenAlex.
- The Effect of Electron Spin-Dependent Polarizability on Protein Activity.Biomolecules · 2025Review
- The solution supramolecular structure of α2 → 8 polysialic acid suggests a structural cause for its low immunogenicity.FEBS letters · 2025Article
- Developing Enzyme Immobilization with Fibrous Membranes: Longevity and Characterization Considerations.Membranes · 2023Review
- QM/MM study of N501 involved intermolecular interaction between SARS-CoV-2 receptor binding domain and antibody of human origin.Computational biology and chemistry · 2023Article
- Mapping the Morphological Landscape of Oligomeric Di-block Peptide-Polymer Amphiphiles.Angewandte Chemie (International ed. in English) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Proteins are polymers, and yet the language used in describing their thermodynamics and kinetics is most often that of small molecules. Using the terminology and mathematical descriptions of small molecules impedes understanding why proteins have evolved to be big in comparison. Many properties of the proteins should be interpreted as polymer behavior, and these arise because of the longer length scale of polymer dimensions. For example, entropic rubber elasticity arises only because of polymer properties, and understanding the separation of entropic and enthalpic contributions shows that the entropic contributions mostly reside within the polymer and enthalpy originates mostly at the site of small-molecule binding. Recognizing the physical chemistry of polymers in descriptions of proteins' structure and function can add clarity to what might otherwise appear to be confusing or even paradoxical behavior. Two of these paradoxes include, first, highly selective binding that is, nevertheless, weak, and, second, small perturbations of an enzyme that cause large changes in reaction rates. Further, for larger structures such as proteins every thermodynamic measurement depends on the length scale of the structure. One reason is that the larger molecule can control up to thousands of waters resulting in collective movements with kcal sums of single-calorie-per-molecule solvent energy changes. In addition, the nature of covalent polypeptides commonly leads to multiple binding-i.e., multivalency-and the benefits of multivalent binding can be assessed semiquantitatively drawing from understanding the chelate effect in coordination chemistry. Such approaches clarify the origins, inter alia, of many low energies of protein denaturation, which lie in the range of only a few kcal mol
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.