Protein–protein association properties of human <scp>βB2</scp> ‐crystallins is a research paper published in Proteins: Structure, Function, and Bioinformatics (2025). On theSindex it has a DataRank of 0.119. It has been cited 1 time, with 1 citing works in its 1-hop citation network.
Abstract Protein–protein association events are involved in many physiological and pathological processes. Cataract disease is a pathology that manifests protein aggregation of crystallins. β‐Crystallins are present in a high proportion in the eye lens. Therefore, the structural study of the dimerization properties of crystallins can shed light on the first stages of protein aggregation. In the present work, we examine the protein–protein association profiles of the human βB2‐crystallin by employing extensive coarse‐grained molecular dynamics (CG‐MD) and the Markov state analysis. Interestingly, our results clearly show important changes in the protein dimerization kinetics between wt‐HβB2C and the deamidated systems. The two systems show dimeric conformations. However, the association and dissociation rates are very different. Our results show that the deamidated system can associate faster and dissociate slower than the wt‐ HβB2C. The deamidated system is in a slightly opened conformation with the Greek‐key motifs well folded, suggesting that a complete unfolding of the protein is not required for aggregation. Our results describe the first stages of crystallin aggregation due to post‐translational modifications.
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Base Score Contribution
0.104
From this paper's citation signal
Citation Network Contribution
0.0153
From 1 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 87% comes from its base citations and 13% from the citation network (1 citing paper contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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