ReviewCurrent opinion in structural biology2026
From static structures to dynamic energy landscapes: the latest revolution in molecular biology.
Review in Current opinion in structural biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Over a decade ago, in an Editorial, we proposed that beyond the foundational discovery of the DNA double helix, modern molecular biology has undergone a second revolution: a shift from static, single-structure models to dynamic, ensemble-based energy landscapes that define biomolecular function. Recently, Quarterly Reviews of Biophysics revisited this question, arguing that this shift is not merely conceptual but represents a revolution that explains functional regulation and enables the design of next-generation allosteric therapies. These ideas-driven by physics and chemistry-have transformed the landscape concept from a theoretical framework into the standard paradigm for biological mechanisms. Here, focusing on proteins, we discuss how the dynamic ensemble vision is reimagining molecular biology, using examples such as allosteric shifts in kinases and the discovery of cryptic pockets for drug design.
Identifiers
What OpenQuestion holds
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.