The unprecedented performance of Deepmind's Alphafold2 in predicting protein structure in CASP XIV and the creation of a database of structures for multiple proteomes and protein sequence repositories is reshaping structural biology. However, because this database returns a single structure, it brought into question Alphafold's ability to capture the intrinsic conformational flexibility of proteins. Here we present a general approach to drive Alphafold2 to model alternate protein conformations through simple manipulation of the multiple sequence alignment via in silico mutagenesis. The approach is grounded in the hypothesis that the multiple sequence alignment must also encode for protein structural heterogeneity, thus its rational manipulation will enable Alphafold2 to sample alternate conformations. A systematic modeling pipeline is benchmarked against canonical examples of protein conformational flexibility and applied to interrogate the conformational landscape of membrane proteins. This work broadens the applicability of Alphafold2 by generating multiple protein conformations to be tested biologically, biochemically, biophysically, and for use in structure-based drug design.
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http://dx.doi.org/10.1371/journal.pcbi.1010483 | DOI Listing |
Soft Matter
January 2025
College of Chemistry, Sichuan University, Chengdu 610064, China.
Biomolecules usually adopt ubiquitous circular structures which are important for their functionality. Based on three-dimensional Langevin dynamics simulations, we investigate the conformational change of a polymer confined in a spherical cavity. Both passive and active polymers with either homogeneous or heterogeneous stiffness are analyzed in a comparative manner.
View Article and Find Full Text PDFWe 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.
View Article and Find Full Text PDFUnlabelled: Atomic coordinate models are important in the interpretation of 3D maps produced with cryoEM and sub-tomogram averaging in cryoET, or more generically, 3D electron microscopy (3DEM). In addition to visual inspection of such maps and models, quantitative metrics convey the reliability of the atomic coordinates, in particular how well the model is supported by the experimentally determined 3DEM map. A recently introduced metric, Q-score, was shown to correlate well with the reported resolution of the map for well-fitted models.
View Article and Find Full Text PDFACS Phys Chem Au
January 2025
Department of Chemistry, West Virginia University, Morgantown, West Virginia 26506, United States.
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 ( ) 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.
View Article and Find Full Text PDFHeliyon
January 2025
Department of Bioinformatics, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, India.
The myeloid-specific triggering receptors expressed on myeloid cells 2 (TREM2) is a group of class I receptors expressed in brain microglia plays a decisive role in neurodegenerative diseases such as Alzheimer's disease (AD) and Nasu Hakola disease (NHD). The extracellular domain (ECD) of TREM2 interacts with a wide-range of ligands, yet the molecular mechanism underlying recognition of such ligands to this class I receptor remains underexplored. Herein, we undertook a systematic investigation for exploring the mode of ligand recognition in immunoglobulin-like ectodomain by employing both knowledge-based and machine-learning guided molecular docking approach followed by the state-of-the-art all atoms molecular dynamics (MD) simulations.
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