Protein Structure and Dynamics

Modeling Protein Sequence Evolution as an Ornstein-Uhlenbeck Process in a Latent Space

The paper models protein sequence evolution using an Ornstein-Uhlenbeck process in a latent space to improve contact prediction by integrating directed evolution data with natural homologs.

Calibrated structural homology transfer yields putative molecular functions for domains of unknown function in four model proteomes

The paper evaluates functional annotation reliability from remote homology searches using retrospective DUFs and finds Foldseek performs better than MMseq2 but not significantly better than ESM-2 embeddings.

Evaluation of methods for AlphaFold-based integrative modeling

This study evaluates AlphaFold-based integrative modeling methods using chemical crosslinks, finding they often rely more on learned priors than input data.

Molecular rewiring and compensatory mechanisms sustain DNA recognition in mutant ZTA transcription factor: insights from molecular dynamics simulations

This study uses molecular dynamics simulations to analyze how mutations in ZTA transcription factor affect DNA recognition by rewiring interaction networks and compensatory mechanisms.

Ourotide: decoding the hierarchical peptide recognition for generative design

The paper introduces Ourotide, a deep learning framework for peptide recognition that outperforms generalist models by capturing a unique hierarchical binding mode through physics-guided data augmentation.

Martini 3 Coarse-Grained Model of DNA for Heterogeneous Molecular Systems

The paper develops a coarse-grained DNA model compatible with the Martini 3 force field, enabling simulations of DNA in diverse molecular systems.

Mechanistic Dissection of Conformational Transition of Bicyclic Peptide via Molecular Modeling and Deep Learning

This study introduces a deep learning model to analyze conformational transitions in cyclic peptides, revealing key residues and nonlinear torsional motions that govern structural changes.

Ten numbers from the Laplace-Beltrami spectrum facilitate training-free classification of protein structures based on surface shape

The paper proposes using the first 10 Laplace-Beltrami eigenvalues to classify protein structures by surface shape, achieving high accuracy on benchmark datasets.

Predictive all-atom simulations of disordered proteins and biomolecular condensates through osmometry-guided force-field optimization

This paper optimizes force fields for simulating disordered proteins and condensates using osmometry data, improving agreement with experimental measurements.

Conformational Ensembles of the Disordered 4E-BP2:eIF4E Complex Restrained by smFRET Experiments

The paper generates conformational ensembles of the 4E-BP2:eIF4E complex using smFRET and NMR data, revealing dynamic structural changes and new contact regions.

Sampling Protein Language Models for Functional Protein Design

This paper evaluates sampling methods for protein language models, showing that multi-mutant strategies outperform single-mutant approaches in capturing epistatic interactions for functional protein design.

EvoMut: A Computational Framework for Engineering Oxidative Stability in Proteins

EvoMut identifies oxidation-prone protein residues and evaluates their mutation feasibility to design oxidation-resistant proteins.

Substrate binding reorganizes the energetic landscape of Plasmodium falciparum hexose transporter PfHT1

This study shows how glucose binding reorganizes the conformational and energetic landscape of PfHT1, a malaria parasite transporter, using computational methods and experimental validation.

The cytokine structural homologs IL-1β and IL-1Ra have distinct dynamical character that potentially influence their roles in allosteric regulation of the IL-1 receptor.

This study compares the dynamic properties of IL-1β and IL-1Ra using NMR relaxation to show that their distinct functional roles in IL-1R signaling arise from differences in conformational entropy at the receptor interface.

Conformational plasticity and sequence specificity interplay in non-canonical tandem RRM-RNA binding

This study investigates how conformational plasticity and sequence specificity interact in tandem RRM-RNA binding using molecular dynamics simulations of DND1.

Assessing multi-eGO Predictions of PDZ2-Peptide Binding across Mutations

This study evaluates multi-eGO's ability to predict PDZ2-peptide binding changes across mutations, showing good thermodynamic agreement but limited kinetic accuracy.

PANDA: Protein All-atom Nested-tree Denoising Architecture for End-to-End Generation

PANDA generates high-quality all-atom protein structures by denoising atomic occupancy patterns, achieving high self-consistency and scaffolding success on functional design tasks.

Mechanistic Interpretability of Protein Language Models Reveals Encoded Structural and Functional Properties of Intrinsically Disordered Proteins

This study examines how protein language models handle intrinsically disordered proteins, finding they encode structural and functional information despite reduced attention on disordered regions.

Functional alignment of protein language models via reinforcement learning

This paper introduces RLXF, a framework that aligns protein language models with experimental functional goals, improving the generation of high-functioning protein variants.

Evolution promotes transition-state-like conformations with enhanced basicity and electric fields in the substrate complex of a designer enzyme

This study shows directed evolution improves a designed enzyme by enhancing its transition-state-like conformation, reducing reaction barriers through desolvation and electric field organization.

Inverse FoldDir: Structure-conditioned Protein Sequence Design by Dirichlet Flow Matching

Inverse FoldDir designs protein sequences compatible with a given backbone structure, achieving high accuracy and experimental validation in nanobody redesign.

Structural basis of lipid-mediated self-regulation of Tissue Factor.

This paper identifies two lipid-mediated mechanisms of Tissue Factor self-regulation through structural analysis, revealing conformational changes and their impact on FVII binding.

Solvent-Isotope Effects in Biomolecular Phase Separation and Fibrillation of Disordered Proteins and Peptides

This study shows that heavy water (D2O) systematically biases liquid-liquid phase separation and aggregation processes in disordered proteins and peptides, highlighting its role as an active experimental variable.

EnZight: A Structure-Guided Algorithm to Identify and Prioritize Substitution Hotspots for Enzyme Engineering

EnZight identifies and prioritizes substitution hotspots in enzymes using structural alignment, demonstrating effectiveness in improving catalytic activity and thermostability.

De novo design of allosterically controlled enzymes

This study designs allosterically controlled enzymes using denoising diffusion models, showing that activity can be activated or repressed by designed effectors.

A novel SXXLF motif in the FXR N-terminal domain mediates coregulator and interdomain interactions

This study identifies a novel SXXLF motif in the FXR N-terminal domain that mediates interactions with coregulators and the ligand binding domain, modulating transcriptional activity.

Predicting Supramolecular Self-Assembly of Peptide Structures with AlphaFold3

This paper evaluates AlphaFold3's ability to predict supramolecular self-assembly of peptides, finding it captures trends but has limitations in modeling complex assemblies and charge effects.

Interplay of stability and dynamics in the optimization of a highly proficient de novo enzyme

This study identifies features contributing to catalytic efficiency in a de novo enzyme through computational design and directed evolution, showing how stability and dynamics interplay in enzyme optimization.

Integrative Structural Modeling of Intrinsically Disordered Regions in a Human HDAC2 Chromatin Remodeling Complex

The paper uses an integrative approach to model the structure of an IDR-driven HDAC2 complex, revealing interactions not captured by AlphaFold alone.

Sampling in structure-token space enables accurate prediction of multiple protein conformations

The paper introduces MultiStateFold, a framework that improves prediction of multiple protein conformations by integrating Parallel Tempering into a protein language model, achieving better performance than existing methods.