Protein Structure and Dynamics

Negative design enables cell-free expression and folding of designed transmembrane β-Barrels

The paper demonstrates that negative design, which locally destabilizes β-strands, improves folding efficiency of synthetic transmembrane β-barrels in a cell-free system.

Atomistic simulations reveal sub-μs contact dynamics in MUT-16 condensates.

The paper uses atomistic simulations to study contact dynamics in MUT-16 condensates, finding short-lived contacts and identifying key interactions and factors influencing condensate behavior.

A composition-matching algorithm, MatchIDR, identifies prion-like domains that localize to stress granules

MatchIDR identifies prion-like domains that localize to stress granules by finding compositional matches in proteomes.

How Well Can AI and Physics-Based Simulations Predict the Probability a Cryptic Pocket Is Open?

This study evaluates AI and physics-based simulations in predicting cryptic pocket opening probabilities in proteins, finding they can predict mutation effects but not absolute probabilities accurately.

Controllable Protein Design by Prefix-Tuning Protein Language Models

PrefixProt uses prefix tuning to design proteins with controllable properties, outperforming other methods in efficiency and multi-objective control.

Systematic Validation of AlphaFold-Predicted Interactomes with LUCIA

The paper validates AlphaFold-predicted protein interactions using LUCIA, identifying 23 novel interactions and establishing an ipTM score threshold for confidence.

Conformational Dynamics of Na+-Pumping NADH-Quinone Oxidoreductase during Na+ Translocation from AlphaFold-Facilitated Markov State Modeling

This study uses AlphaFold and Markov state modeling to analyze the conformational dynamics of Na+-NQR, revealing how redox state and Na+ binding regulate Na+ translocation.

Several multiple sequence alignment perturbation methods enhance AlphaFold3 sampling of alternative protein states

The paper evaluates MSA perturbation methods on AlphaFold3 to improve sampling of alternative protein states, finding significant improvements in TM-scores compared to unperturbed AF3.

Benchmarking Free Energy Calculations: Analysis of Single and Double Mutations Across Two Simulation Software Platforms for Two Protein Systems

This paper benchmarks free energy calculations for protein mutations using two software platforms, showing strong correlations between predicted and experimental free energy changes.

Rectifying AI-generated protein structure ensembles for equilibrium using physics-based computations

The paper describes a method to generate equilibrium protein structure ensembles using physics-based computations to harmonize AI-generated outputs.

Conserved water molecules as structural ligands modulating pathogenic variation in human protein binding sites

The paper shows that conserved water molecules in protein structures are linked to pathogenic SNPs, particularly in ligand-binding regions, and demonstrates their role in disease mechanisms through molecular dynamics simulations.

MDCompress: better, faster compression of molecular dynamics simulation trajectories

MDCompress introduces a new trajectory compression format and software that reduces file size and improves compression/decompression speed for molecular dynamics simulations.

AlphaFold as a Prior: Experimental StructureDetermination Conditioned on a Pretrained Neural Network

ROCKET refines AlphaFold2 predictions against crystallographic, cryo-EM and cryo-ET data by gradient descent on MSA cluster profiles, capturing loop flips and domain shifts without retraining.

Fast prediction of protein flexibility

The paper introduces a fast, lightweight model to predict protein flexibility using atom coordinates, achieving high accuracy without requiring MD simulations.

emb2dis: a novel protein disorder prediction tool based on ResNets, dilated convolutions & protein language models

emb2dis predicts protein disorder using a deep learning model combining ResNets and dilated convolutions, achieving top performance on benchmark datasets.

De novo Folding Mechanisms of Lasso Peptides

This study uses molecular dynamics and deep learning to uncover the folding mechanisms of lasso peptides, revealing key thermodynamic and kinetic principles.

Protein-peptide binding pathways revealed by two-dimensional replica-exchange molecular dynamics

This study uses molecular dynamics to uncover binding pathways of a peptide to a kinase, identifying key intermediate states and guiding interactions.

Mutation-induced reshaping of protein conformational dynamics revealed by a coarse-grained modeling framework

This paper introduces a coarse-grained modeling framework to analyze how mutations affect protein conformational dynamics and identifies mutation-sensitive regions.

HORI-EN: Atomic-level energetic profiling and higher-order network identification in protein structures

HORI-EN identifies cooperative stabilization networks in protein structures by integrating atomic-level energetic scoring with higher-order graph-theoretic analysis, showing improved performance in predicting mutational hotspots.

Residue burial encodes a protein's fold

This study shows that residue burial information can predict protein backbone conformation more efficiently than other representations, suggesting core identity is a better encoding for fold prediction.

IDBSpred: An intrinsically disordered binding site predictor using machine learning and protein language model

IDBSpred predicts IDP-binding sites on structured proteins using ESM-2 embeddings and a multilayer perceptron, achieving an ROC AUC of 0.87.

Decoupling Topology from Geometry: Detecting Large-Scale Conformational Changes via Conformational Scanning

This paper introduces a method to identify proteins with identical topology but different conformations from the PDB, enabling the study of large-scale structural dynamics.

Millisecond Prediction of Protein Contact Maps from Amino Acid Sequences

This paper introduces a fast method to predict protein contact maps from sequences, achieving high accuracy in 110 milliseconds.

Mutational scan of self-cleavage by HIV-1 protease provides new views of a conformationally dynamic mechanism

The paper identifies mutations that affect HIV-1 protease self-cleavage but not viral fitness, and uses simulations to model its dynamic mechanism.

Co-designing sequence and structure of functional de novo enzymes with EnzyGen2

EnzyGen2 co-designs protein sequences and structures with ligand-guided functionality, outperforming existing methods in in silico benchmarks and generating active enzymes with high novelty.

Symmetric Self-play Online Preference Optimization for Protein Inverse Folding

This paper introduces a symmetric self-play framework for protein inverse folding that improves sequence design self-consistency by decoupling structural objectives.

ECOD: Classification of domains in AFDB Swiss-Prot structure predictions

The paper classifies over 542,000 Swiss-Prot protein structure predictions into ECOD domains, expanding domain coverage and revealing novel evolutionary groups.

Topology-aware multiscale modeling of viral genomes reveals stability determinants in circoviruses

This study uses computational models to analyze the topology of PCV2 viral genomes, revealing that different internal arrangements can produce similar external structures but vary in stability and function.

FoldaVirus, a knowledge-based icosahedral capsid builder using AlphaFold

FoldaVirus generates icosahedral virus capsid models using AlphaFold predictions and structural knowledge, validated by energy minimization and distance metrics.

Structure-informed direct coupling analysis improves protein mutational landscape predictions

This paper introduces StructureDCA, a method that improves mutational landscape predictions by integrating structural information into direct coupling analysis.