CHARMM-GUI supports the Amber force fields Lee, Jumin; Hitzenberger, Manuel; Rieger, Manuel ...
Journal of chemical physics online/The Journal of chemical physics/Journal of chemical physics,
07/2020, Letnik:
153, Številka:
3
Journal Article
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As part of our ongoing efforts to support diverse force fields and simulation programs in CHARMM-GUI, this work presents the development of FF-Converter to prepare Amber simulation inputs with ...various Amber force fields within the current CHARMM-GUI workflow. The currently supported Amber force fields are ff14SB/ff19SB (protein), Bsc1 (DNA), OL3 (RNA), GLYCAM06 (carbohydrate), Lipid17 (lipid), GAFF/GAFF2 (small molecule), TIP3P/TIP4P-EW/OPC (water), and 12-6-4 ions, and more will be added if necessary. The robustness and usefulness of this new CHARMM-GUI extension are demonstrated by two exemplary systems: a protein/N-glycan/ligand/membrane system and a protein/DNA/RNA system. Currently, CHARMM-GUI supports the Amber force fields only for the Amber program, but we will expand the FF-Converter functionality to support other simulation programs that support the Amber force fields.
Several studies showed that seeding of solutions of monomeric fibril proteins with ex vivo amyloid fibrils accelerated the kinetics of fibril formation in vitro but did not necessarily replicate the ...seed structure. In this research we use cryo-electron microscopy and other methods to analyze the ability of serum amyloid A (SAA)1.1-derived amyloid fibrils, purified from systemic AA amyloidosis tissue, to seed solutions of recombinant SAA1.1 protein. We show that 98% of the seeded fibrils remodel the full fibril structure of the main ex vivo fibril morphology, which we used for seeding, while they are notably different from unseeded in vitro fibrils. The seeded fibrils show a similar proteinase K resistance as ex vivo fibrils and are substantially more stable to proteolytic digestion than unseeded in vitro fibrils. Our data support the view that the fibril morphology contributes to determining proteolytic stability and that pathogenic amyloid fibrils arise from proteolytic selection.
γ-secretase, an intramembrane-cleaving aspartyl protease is involved in the cleavage of a large number of intramembrane proteins. The most prominent substrate is the amyloid precursor protein, whose ...proteolytic processing leads to the production of different amyloid Aβ peptides. These peptides are known to form toxic aggregates and may play a key role in Alzheimer's disease (AD). Recently, the three-dimensional structure of γ-secretase has been determined via Cryo-EM, elucidating the spatial geometry of this enzyme complex in different functional states. We have used molecular dynamics (MD) simulations to study the global dynamics and conformational transitions of γ-secretase, as well as the water and lipid distributions in and around the transmembrane domains in atomic detail. Simulations were performed on the full enzyme complex and on the membrane embedded parts alone. The simulations revealed global motions compatible with the experimental enzyme structures and indicated little dependence of the dynamics of the transmembrane domains on the soluble extracellular subunits. During the simulation on the membrane spanning part a transition between an inactive conformation (with catalytic residues far apart) toward a putatively active form (with catalytic residues in close proximity) has been observed. This conformational change is associated with a distinct rearrangement of transmembrane helices, a global compaction of the catalytically active presenilin subunit a change in the water structure near the active site and a rigidification of the protein fold. The observed conformational rearrangement allows the interpretation of the effect of several mutations on the activity of γ-secretase. A number of long-lived lipid binding sites could be identified on the membrane spanning surface of γ-secretase which may coincide with association regions of hydrophobic membrane helices to form putative substrate binding exosites.
Systemic AA amyloidosis is a debilitating protein misfolding disease in humans and animals. In humans, it occurs in two variants that are called 'vascular' and 'glomerular', depending on the main ...amyloid deposition site in the kidneys. Using cryo electron microscopy, we here show the amyloid fibril structure underlying the vascular disease variant. Fibrils purified from the tissue of such patients are mainly left-hand twisted and contain two non-equal stacks of fibril proteins. They contrast in these properties to the fibrils from the glomerular disease variant which are right-hand twisted and consist of two structurally equal stacks of fibril proteins. Our data demonstrate that the different disease variants in systemic AA amyloidosis are associated with different fibril morphologies.
Erroneous activation of the Hedgehog pathway has been linked to a great amount of cancerous diseases and therefore a large number of studies aiming at its inhibition have been carried out. One ...leverage point for novel therapeutic strategies targeting the proteins involved, is the prevention of complex formation between the extracellular signaling protein Sonic Hedgehog and the transmembrane protein Patched 1. In 2009 robotnikinin, a small molecule capable of binding to and inhibiting the activity of Sonic Hedgehog has been identified, however in the absence of X-ray structures of the Sonic Hedgehog-robotnikinin complex, the binding mode of this inhibitor remains unknown. In order to aid with the identification of novel Sonic Hedgehog inhibitors, the presented investigation elucidates the binding mode of robotnikinin by performing an extensive docking study, including subsequent molecular mechanical as well as quantum mechanical/molecular mechanical molecular dynamics simulations. The attained configurations enabled the identification of a number of key protein-ligand interactions, aiding complex formation and providing stabilizing contributions to the binding of the ligand. The predicted structure of the Sonic Hedgehog-robotnikinin complex is provided via a PDB file as Supplementary Material and can be used for further reference.
Knowledge of how transition state inhibitors bind to γ-secretase is of major importance for the design of new Alzheimer’s disease therapies. On the basis of the known structure of γ-secretase in ...complex with a fragment of the amyloid precursor protein, we generated a structural model of γ-secretase in complex with the effective L-685,458 transition state inhibitor. The predicted binding mode is in excellent agreement with experimental data, mimicking all enzyme–substrate interactions at the active site and forming the relevant transition state geometry with the active site aspartate residues. The model also indicates the possible location and nature of the amino acid residues forming the proposed binding pockets S1′, S2′, and S3′ near the active site that are occupied by chemical groups of the inhibitor. In addition, we found that the stability of the complex is very likely sensitive to the pH value. Comparative simulations on the binding of L-685,458 and the epimer L682,679 allowed us to explain the strongly reduced affinity of the epimer for γ-secretase. The structural model could form a valuable basis for the design of new or modified γ-secretase inhibitors.
γ-Secretase is an intramembrane aspartyl-protease catalyzing the final step in the regulated intramembrane proteolysis of a large number of single-span type-1 transmembrane proteins. The most ...extensively studied substrates are the amyloid-β precursor protein (APP) and the NOTCH receptors. An important technique for the characterization of interactions and conformational changes enabling γ-secretase to perform hydrolysis within the confines of the membrane are molecular dynamics simulations on different time and length scales. Here, we review structural and dynamical features of γ−secretase and its substrates including flexibility descriptions from simulations and experiments. We address (1) conformational sampling of apo-enzyme and unbound substrates (exemplified for APP, NOTCH1 and the apparent non-substrate integrin β1), (2) substrate recruitment pathways, (3) conformational changes associated with the formation of the recognition complex, (4) cleavage-site unfolding upon interaction with the enzyme’s active site, (5) substrate processing after endoproteolysis, and (6) inhibition and modulation of γ-secretase. We conclude with still open questions and suggest further investigations in order to advance our understanding on how γ-secretase selects and processes substrates. This knowledge will improve the ability to better target substrates selectively for therapeutic applications.
Cleavage of substrates by γ-secretase is an inherently slow process where substrate–enzyme affinities cannot be broken down into specific sequence requirements in contrast to soluble proteases. ...Nevertheless, despite its apparent sequence tolerance single point mutations in amyloid precursor protein can severely affect cleavage efficiencies and change product line preferences. We have determined by NMR spectroscopy the structures of the transmembrane domain of amyloid precursor protein in TFE/water and compared it to that of four mutants: two FAD mutants, V44M and I45T, and the two diglycine hinge mutants, G38L and G38P. In accordance with previous publications, the transmembrane domain is composed of two helical segments connected by the diglycine hinge. Mutations alter kink angles and structural flexibility. Furthermore, to our surprise, we observe different, but specific mutual orientations of N- and C-terminal helical segments in the four mutants compared to the wildtype. We speculate that the observed orientations for G38L, G38P, V44M, and I45T lead to unfavorable interactions with γ-secretase exosites during substrate movement to the enzymeʼs active site in presenilin and/or for the accommodation into the substrate-binding cavity of presenilin.
Systemic light chain (AL) amyloidosis is a fatal protein misfolding disease in which excessive secretion, misfolding, and subsequent aggregation of free antibody light chains eventually lead to ...deposition of amyloid plaques in various organs. Patient-specific mutations in the antibody VL domain are closely linked to the disease, but the molecular mechanisms by which certain mutations induce misfolding and amyloid aggregation of antibody domains are still poorly understood. Here, we compare a patient VL domain with its nonamyloidogenic germline counterpart and show that, out of the five mutations present, two of them strongly destabilize the protein and induce amyloid fibril formation. Surprisingly, the decisive, disease-causing mutations are located in the highly variable complementarity determining regions (CDRs) but exhibit a strong impact on the dynamics of conserved core regions of the patient VL domain. This effect seems to be based on a deviation from the canonical CDR structures of CDR2 and CDR3 induced by the substitutions. The amyloid-driving mutations are not necessarily involved in propagating fibril formation by providing specific side chain interactions within the fibril structure. Rather, they destabilize the VL domain in a specific way, increasing the dynamics of framework regions, which can then change their conformation to form the fibril core. These findings reveal unexpected influences of CDR-framework interactions on antibody architecture, stability, and amyloid propensity.
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