Yinglong Miao

The paper investigates how specific stalk-derived peptides can reactivate signaling in disease-associated PC1 mutants and uses computational simulations to support these findings.

This paper introduces GaMD-TI, a method combining Gaussian accelerated MD with TI to improve free energy calculations by enhancing conformational sampling in alchemical transformations.

This study benchmarks docking protocols for GPCR allosteric modulators using experimental structures and GaMD simulations, finding that ensemble re-ranking strategies improve early enrichment of known actives.

This paper reports the cryo-EM structure of the M4 mAChR bound to MK-97 and acetylcholine, revealing how MK-97's binding mode improves PAM activity through distributed interactions.

This paper reveals the structural basis of NSD2 degradation via SCF-FBXO22 recruitment, showing how aldehyde-based degraders induce conformational changes for covalent binding and efficient protein degradation.

This study uses Pep-GaMD simulations to reveal how a tethered agonist transitions from a β-strand to a U-shaped helical configuration upon binding to ADGRD1.

This study identifies coumarin derivatives that selectively bind RNA single G bulges, revealing key structural features and using computational and experimental methods to guide rational ligand design.

The paper presents a cryo-EM structure of the M5 mAChR with a novel allosteric binding site identified through mutagenesis, pharmacology, and simulations.

This study uses PPI-GaMD simulations to reveal dynamic mechanisms of peptide agonist dissociation and deactivation in ADGRG1 and ADGRG2.

The paper resolves the structure of an intermediate GPCR-G protein complex and shows it initiates nucleotide exchange without progressing to the fully activated state, providing insights into GPCR signaling complexity.

This study evaluates benzaldehyde derivatives as quorum sensing inhibitors in Pseudomonas aeruginosa, identifying ortho-vanillin as a competitive inhibitor of RhlR.

LiGaMD3 improves prediction of binding thermodynamics and kinetics for small molecules and flexible peptides by enhancing sampling efficiency through triple boosts in energy terms.

This study investigates ligand dissociation from the SARS-CoV-2 spike glycoprotein using simulations, revealing two unbinding pathways and key residues involved in ligand binding and ACE2 interaction.

This study identifies stalk-derived peptides that activate PC1 signaling by binding to specific regions, revealing structural dynamics and potential therapeutic applications for ADPKD.

This study uses deep learning and simulations to reveal dynamic allostery mechanisms in GPCRs, showing modulators restrict conformational space and enhance selectivity.

This study shows that Alzheimer's mutations stabilize harmful enzyme-substrate complexes in gamma-secretase, leading to synaptic loss rather than the released Aβ peptides being the primary cause.

DBMD accelerates molecular simulations by using Bayesian neural networks to generate Gaussian boost potentials, improving sampling efficiency and accuracy in alanine dipeptide, chignolin, and RNA folding simulations.

The paper uses sequence coevolutionary analysis and structural contacts to reveal distinct residue interactions in GPCR classes A and B, providing insights for drug design.

This study uses accelerated molecular simulations to reveal the dynamic mechanism of specific GPCR-G protein coupling, showing that residue interactions at the protein interface determine coupling specificity.