bims-lances 2025-02-02 papers

bioRxiv. 2025 Jan 19. pii: 2025.01.09.632263. [Epub ahead of print]

Dimerization and dynamics of angiotensin-I converting enzyme revealed by cryoEM and MD simulations.

Jordan M Mancl, Xiaoyang Wu, Minglei Zhao, Wei-Jen Tang.

Angiotensin-I converting enzyme (ACE) regulates the levels of disparate bioactive peptides, notably converting angiotensin-I to angiotensin-II and degrading amyloid beta. ACE is a heavily glycosylated dimer, containing 4 analogous catalytic sites, and exists in membrane bound and soluble (sACE) forms. ACE inhibition is a frontline, FDA-approved, therapy for cardiovascular diseases yet is associated with significant side effects, including higher rates of lung cancer. To date, structural studies have been confined to individual domains or partially denatured cryoEM structures. Here we report the cryoEM structure of the full-length, glycosylated, sACE dimer. We resolved four structural states at 2.99 to 3.65 Å resolution which are primarily differentiated by varying degrees of solvent accessibility to the active sites and reveal the full dimerization interface. We also employed all-atom molecular dynamics (MD) simulations and heterogeneity analysis in cryoSPARC, cryoDRGN, and RECOVAR to elucidate the conformational dynamics of sACE and identify key regions mediating conformational change. We identify differences in the mechanisms governing the conformational dynamics of individual domains that have implications for the design of domain-specific sACE modulators.

DOI: https://doi.org/10.1101/2025.01.09.632263

ACS Phys Chem Au. 2025 Jan 22. 5(1): 17-29

Structure Characterization of a Disordered Peptide Using In-Droplet Hydrogen/Deuterium Exchange Mass Spectrometry and Molecular Dynamics.

Mohammad A Rahman, Mst Nigar Sultana, Daud Sharif, Sultan Mahmud, Justin Legleiter, Peng Li, Blake Mertz, Stephen J Valentine.

In-droplet hydrogen/deuterium exchange (HDX)-mass spectrometry (MS) experiments have been conducted for peptides of highly varied conformational type. A new model is presented that combines the use of protection factors (PF) from molecular dynamics (MD) simulations with intrinsic HDX rates (k int) to obtain a structure-to-reactivity calibration curve. Using the model, the relationship of peptide structural flexibility and HDX reactivity for different peptides is elucidated. Additionally, the model is used to describe the degree of conformational flexibility and structural bias for the disease-relevant Nt17 peptide; although highly flexible, intrinsically primed for facile conversion to α-helical conformation upon binding with molecular partners imparts significant in-droplet HDX protection for this peptide. In the future, a scale may be developed whereby HDX reactivity is predictive of the degree of structural flexibility and bias (propensity to form 2° structural elements such as α-helix, β-sheet, and β-turn) for intrinsically disordered regions (IDRs). Such structural resolution may ultimately be used for high-throughput screening of IDR structural transformation(s) upon binding of ligands such as drug candidates.

DOI: https://doi.org/10.1021/acsphyschemau.4c00048

bioRxiv. 2025 Jan 17. pii: 2025.01.13.632795. [Epub ahead of print]

Integrating Hydrogen Exchange with Molecular Dynamics for Improved Ligand Binding Predictions.

Benjamin T Walters, Alexander W Patapoff, James A Kiefer, Ping Wu, Weiru Wang.

We introduce Hydrogen-Exchange Experimental Structure Prediction (HX-ESP), a method that integrates hydrogen exchange (HX) data with molecular dynamics (MD) simulations to accurately predict ligand binding modes, even for targets requiring significant conformational changes. Benchmarking HX-ESP by fitting two ligands to PAK1 and four ligands to MAP4K1 (HPK1), and comparing the results to X-ray crystallography structures, demonstrated that HX-ESP successfully identified binding modes across a range of affinities significantly outperforming flexible docking for ligands necessitating large conformational adjustments. By objectively guiding simulations with experimental HX data, HX-ESP overcomes the long timescales required for binding predictions using traditional MD. This advancement promises to enhance the accuracy of computational modeling in drug discovery, potentially accelerating the development of effective therapeutics.

DOI: https://doi.org/10.1101/2025.01.13.632795