ArticleThe Journal of chemical physics2025
Systematic analysis of biomolecular conformational ensembles with PENSA.
Article in The Journal of chemical physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Mechanism of RACK1-dependent ZAKα activation at stalled and collided ribosomes.Molecular cell · 2026Article
- A model for drug transport across two membranes of Gram-negative bacteria by an MFS tripartite assembly.Nature communications · 2026Article
- Mapping Allosteric Communication in the Nucleosome with Conditional Activity.Journal of chemical information and modeling · 2026Article
- Residues of the ribose binding site are required for human ribokinase activity.Journal of structural biology: X · 2025Article
- Dynamic Coupling between Tom22 Motions and Tom40 Pore Dynamics Modulates Ion Transport in the Mitochondrial TOM Complex.Journal of chemical information and modeling · 2025Article
- Conformational plasticity of disordered regions enables sequence-diverse DNA recognition by transcription factor AflR.Nature communications · 2025Article
- Mapping Allosteric Communication in the Nucleosome with Conditional Activity.bioRxiv : the preprint server for biology · 2025Article
- Machine Learning of Molecular Dynamics Simulations Provides Insights into the Modulation of Viral Capsid Assembly.Journal of chemical information and modeling · 2025Article
- In silico characterization of the gating and selectivity mechanism of the human TPC2 cation channel.The Journal of general physiology · 2025Article
- Can Deep Learning Blind Docking Methods be Used to Predict Allosteric Compounds?Journal of chemical information and modeling · 2025Article
- PEG-mCherry interactions beyond classical macromolecular crowding.Protein science : a publication of the Protein Society · 2025Article
- An atomic look at the interface of GHSR and its partners.Computational and structural biotechnology journal · 2024Article
- A hydrophobic funnel governs monovalent cation selectivity in the ion channel TRPM5.Biophysical journal · 2024Article
- High-fidelity, hyper-accurate, and evolved mutants rewire atomic-level communication in CRISPR-Cas9.Science advances · 2024Article
- Protein ensemble modeling and analysis with MMMx.Protein science : a publication of the Protein Society · 2024Article
- Unveiling the RNA-mediated allosteric activation discloses functional hotspots in CRISPR-Cas13a.Nucleic acids research · 2024Article
- EnGens: a computational framework for generation and analysis of representative protein conformational ensembles.Briefings in bioinformatics · 2023Article
- A cooperative knock-on mechanism underpins Ca2+-selective cation permeation in TRPV channels.The Journal of general physiology · 2023Article
- EnGens: a computational framework for generation and analysis of representative protein conformational ensembles.bioRxiv : the preprint server for biology · 2023Article
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6 authors.
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Abstract
Atomic-level simulations are widely used to study biomolecules and their dynamics. A common goal in such studies is to compare simulations of a molecular system under several conditions-for example, with various mutations or bound ligands-in order to identify differences between the molecular conformations adopted under these conditions. However, the large amount of data produced by simulations of ever larger and more complex systems often renders it difficult to identify the structural features that are relevant to a particular biochemical phenomenon. We present a flexible software package named Python ENSemble Analysis (PENSA) that enables a comprehensive and thorough investigation into biomolecular conformational ensembles. It provides featurization and feature transformations that allow for a complete representation of biomolecules such as proteins and nucleic acids, including water and ion binding sites, thus avoiding the bias that would come with manual feature selection. PENSA implements methods to systematically compare the distributions of molecular features across ensembles to find the significant differences between them and identify regions of interest. It also includes a novel approach to quantify the state-specific information between two regions of a biomolecule, which allows, for example, tracing information flow to identify allosteric pathways. PENSA also comes with convenient tools for loading data and visualizing results, making them quick to process and easy to interpret. PENSA is an open-source Python library maintained at https://github.com/drorlab/pensa along with an example workflow and a tutorial. We demonstrate its usefulness in real-world examples by showing how it helps us determine molecular mechanisms efficiently.
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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.