Kresten Lindorff‐Larsen

This study uses enhanced sampling simulations to explore the conformational space of Gaussia luciferase, revealing structural dynamics and substrate-binding features not captured by existing methods.

The paper improves a coarse-grained model for biomolecular condensates by enhancing dilute-state properties, showing better condensed-phase behavior but not full quantitative accuracy.

The paper develops coarse-grained models for simulating double-stranded RNA and DNA in the CALVADOS framework to study their behavior in protein-nucleic acid condensates.

This study uses NMR to measure nanosecond methyl dynamics in the RNA exosome core, showing that relaxation-violated coherence transfer experiments can quantify side chain order parameters in large protein complexes.

AF-CALVADOS uses AlphaFold to simulate multi-domain proteins at the proteome level, showing good performance across ordered and disordered regions.

This study develops a high-throughput method to quantify interactions driving condensate formation in intrinsically disordered proteins and shows amino acid content primarily determines partitioning behavior.

This study shows multi-component biomolecular condensates suppress amyloid formation by sequestering proteins, limiting their availability for fibril formation.

This paper shows that arginine substitutions, despite similar charge, compact α-synuclein more than lysine, accelerating amyloid formation and reshaping its disordered ensemble.

This paper introduces a Bayesian method to interpret time-resolved experiments using molecular simulations, demonstrating its application to protein unfolding studies.

The paper combines variant effect data from six VAMP-seq experiments to analyze 31,614 substitution effects on protein abundance, finding that structural environment (buried/exposed) predicts abundance with high accuracy.

The paper develops a stickiness scale for disordered proteins based on biophysical experiments and compares it to existing hydropathy scales.

This paper introduces OPES multithermal sampling to efficiently explore rare conformations in intrinsically disordered proteins, revealing transient tertiary structures in ACTR.

The paper identifies and models interactions between transactivation domains and arginine-glycine-rich regions using proteome-scale data and simulations, revealing electrostatic mechanisms driving TF-RBP coupling.

The paper identifies proteins where variant effect predictors disagree, suggesting these are prioritized for experimental validation to improve variant interpretation.

The paper develops a framework to train supervised models on MAVE data by accounting for experimental protocol differences, improving variant effect prediction across datasets.

This paper maps the functional effects of Parkin variants in mitophagy, distinguishing pathogenic from benign variants with high accuracy.

This study uses double mutant cycles to analyze molecular interactions in biomolecular condensates, finding additive and non-additive contributions to phase separation propensity.

The paper identifies BAG6 and RNF126 as key players in PQC degradation of non-native missense protein variants using CRISPR screens and VAMP-seq.

This paper introduces IDPFold2, a framework for predicting conformational ensembles of proteins, including multidomain proteins and complexes, and shows it outperforms existing methods.

The paper characterizes GCK variants' effects on GKRP interaction using deep mutational scanning, identifying variants that specifically perturb interactions and reveal allosteric effects.

The paper uses simulations to study how proteins partition into MED1 and FUS condensates, identifying sequence features that predict partitioning and developing a sequence-based predictor.

This study shows that ubiquitylation of UBQLN2's UBL domain regulates its stability and localization, with implications for proteasomal degradation and ALS.

This paper uses computational methods to study GumK, a glycosyltransferase, revealing its dynamic behavior and substrate specificity mechanisms.

This study examines how protein tags affect condensate formation in different contexts and identifies charge as a key factor influencing condensation behavior.

The paper introduces a benchmark for evaluating protein ensemble generators across ordered and disordered proteins and presents a new model that improves performance on disordered regions.

This paper develops a coarse-grained model for PEG to study crowding effects on disordered proteins, showing how PEG titrations can quantify phase separation propensities.

This study develops a coarse-grained model to simulate phosphorylated disordered proteins, showing that phosphorylation's effect on global dimensions is mainly due to additional charge.

StruCloze reconstructs atomistic structures from coarse-grained models and inpaints missing regions in biomolecules, achieving state-of-the-art accuracy and transferability.

This study maps degrons in human transcription factors, identifies new degrons, and links degron potency to variant effects and transcriptional activation.