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Keller, B. G.

Publications and source records attributed to Keller, B. G..

8 recordsLinked to original sources

A cryptic pocket allosterically modulates oligosaccharide binding to DC-SIGN

DC-SIGN is a C-type lectin receptor expressed on antigen-presenting cells, crucial for pathogen recognition and immune modulation. Here, we identify and characterize a previously unrecognized cryptic allosteric pocket in DC-SIGN using molecular dynamics simulations, NMR spectroscopy, cryogenic electron microscopy and biochemical assays. Rotation of the gatekeeper residue M270 exposes the pocket whose occupancy modulates glycan binding. Mutations M270F and T314A mimic the occupied and unoccupied states of this pocket, respectively, shifting the conformational equilibrium of -helix 2 and altering oligosaccharide affinity via the extended carbohydrate binding site. While Ca{superscript 2} coordination at the canonical binding site remains unaffected, our data reveal a complex interplay between the Ca{superscript 2} binding sites and the canonical and extended glycan binding surfaces. These findings uncover a hierarchical allosteric mechanism that enables selective tuning of glycan affinity and suggest the cryptic pocket as a novel target for drug discovery in C-type lectins.

biochemistry↗

Clostridioides difficile Toxins Unhinged: Allosterically Switchable Network Orients β-flap

Allosteric proteins exhibit a functional response upon substrate binding far from the active site. Clostridioides difficile toxins use allosteric binding by an endogenous co-factor to orchestrate self-cleavage from within the target cell. This binding event induces a conformational shift, primarily effecting a lever-like "{beta}-flap" region, with two known orientations. We uncovered a mechanism for this allosteric transition using extensive atomistic MD simulations and computational and experimental mutagenesis. The mechanism relies on a switchable interaction network. The most prominent interaction pair is K600-E743, with K600 interactions explaining [~]70 % of the allosteric effect. Rather than gradually morphing between two end states, the interaction network adopts two mutually exclusive configurations in the active and inactive state. Similar switchable networks may explain allostery more broadly. This mechanism in particular could aid in drug development targeting the Clostridioides difficile toxins autoproteolysis.

molecular biology↗

Pre-bound State Discovered in the Unbinding Pathway of Fluorinated Variants of the Trypsin-BPTI Complex Using Random AccelerationMolecular Dynamics Simulations

The serine protease trypsin forms a tightly bound inhibitor complex with Bovine Pancreatic Trypsin Inhibitor (BPTI). The complex is stabilized by the P1 residue Lys15, which interacts with the negatively charged amino acids at the bottom of the S1 pocket. Truncating the P1 residue of wildtype BPTI to -aminobutyric acid (Abu) leaves a complex with moderate inhibitor strength, which is held in place by additional hydrogen bonds at the protein-protein interface. Fluorination of the Abu residue partially restores inhibitor strength. The mechanism with which fluorination can restore the inhibitor strength is unknown and accurate computational investigation requires knowledge of the binding and unbinding pathways. The preferred unbinding pathway is likely to be complex, as encounter states have been described before and unrestrained Umbrella Sampling simulations of these complexes suggest additional energetic minima. Here, we use Random Acceleration Molecular Dynamics to find a new metastable state in the unbinding pathway of Abu-BPTI variants and wildtype BPTI from trypsin, which we call the pre-bound state. The pre-bound state and the fully bound state differ by a substantial shift in the position, a slight shift in the orientation of the the BPTI variants and change in the interaction pattern. Particularly important is the breaking of three hydrogen bonds around Arg17. Fluorination of the P1 residue lowers the energy barrier of the transition between fully bound state and pre-bound state and also lowers the energy minimum of the pre-bound state. While the effect of fluorination is in general difficult to quantify, here it is in part caused by a favorable stabilization of a hydrogen bond between Gln194 and Cys14. The interaction pattern of the pre-bound state offers insight into the inhibitory mechanism of BPTI and might add valuable information for the design serine protease inhibitors.

biophysics↗

The influence of N-methylation on the ansamers of an amatoxin: Gly5Sar-amanullin

Amatoxins are strong inhibitors of RNA polymerase II, and cause cell death. Because of their cytotoxicity they are candidates for anti-cancer drugs, and understanding their structure-activity relationship is crucial. Amatoxins have a rigid bicyclic scaffold which consists of a cyclic octapeptide bridged by cysteine and tryptophan side chain forming a tryptathionine bridge. Here we show the influence of the N-methylation on the amatoxin scaffold by studying Gly5Sar-amanullin with MD simulations and NMR experiments. Since we have shown recently that the amatoxin scaffold allows for two isomeric forms (ansamers), we studied both isomers of Gly5Sar-amanullin. We found that both isomers of Gly5Sar-amanullin form two long-living conformations which is unusual for amatoxins, and that they are differently affected by the N-methylation. The natural Gly5Sar-amanullin forfeits the hydrogen bonds to Gly5 due to the N-methylation, which is expected from existing crystal structures for alpha-amanitin. Our results however indicate that this does not cause more flexibility due to a shift in the hydrogen bond pattern. In the unnatural isomer, we observe an interesting cis-trans-isomerisation of the backbone angles in Trp4 and Gly7, which is enabled by the N-methylation. We expect that our perspective on the effect of N-methylation in amatoxins could be a starting point for further SAR-studies which are urgently needed for the design of better anti-cancer agents.

molecular biology↗

CommonNNClustering--A Python package for generic common-nearest-neighbour clustering

Density-based clustering procedures are widely used in a variety of data science applications. Their advantage lies in the capability to find arbitrarily shaped and sized clusters and robustness against outliers. In particular, they proved effective in the analysis of Molecular Dynamics simulations, where they serve to identify relevant, low energetic molecular conformations. As such, they can provide a convenient basis for the construction of kinetic (coreset) Markov-state models. Here we present the opensource Python project CommonNNClustering, which provides an easy-to-use and efficient re-implementation of the commonnearest-neighbour (CommonNN) method. The package provides functionalities for hierarchical clustering and an evaluation of the results. We put our emphasis on a generic API design to keep the implementation flexible and open for customisation.

bioinformatics↗

Water network in the binding pocket of fluorinated BPTI-Trypsin complexes - insights from simulation and experiment

Structural waters in the S1 binding pocket of {beta}-trypsin are critical for the stabilization of the complex of {beta}-trypsin with its inhibitor bovine pancreatic trypsin inhibitor (BPTI). The inhibitor strength of BPTI can be modulated by replacing the critical lysine residue at the P1 position by non-natural amino acids. We study BPTI variants in which the critical Lys15 in BPTI has been replaced by -aminobutyric acid (Abu) and its fluorinated derivatives monofluoroethylglycine (MfeGly), difluoroethylglycine (DfeGly) and trifluoroethylglycine (TfeGly). We investigate the hypothesis that additional water molecules in the binding pocket can form specific non-covalent interactions to the fluorinated side chains and thereby act as an extension of the inhibitors. We report potentials of mean force (PMF) of the unbinding process for all four complexes and enzyme activity inhibition assays. Additionally, we report the protein crystal structure of the Lys15MfeGly-BPTI-{beta}-trypsin complex (pdb: 7PH1). Both, experimental and computational data, show a step-wise increase in inhibitor strength with increasing fluorination of the Abu side chain. The PMF additionally shows a minimum for the encounter complex and an intermediate state just before the bound state. In the bound state, the computational analysis of the structure and dynamics of the water molecules in the S1 pocket shows a highly dynamic network of water molecules that does not indicate a rigidification or stabilizing trend in regards to energetic properties that could explain the increase in inhibitor strength. The analysis of the enthalpy and the entropy of the water molecules in the S1 binding pocket using Grid Inhomogeneous Solvation Theory confirms this result. Overall, fluorination systematically changes the binding affinity but the effect cannot be explained by a persistent water network in the binding pocket. Other effects, such as the hydrophobicity of fluorinated amino acids and the stability of the encounter complex as well as the additional minimum in the potential of mean force in the bound state, likely influence the affinity more directly. TOC GRAPHIC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=124 SRC="FIGDIR/small/496563v3_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@1177443org.highwire.dtl.DTLVardef@d20760org.highwire.dtl.DTLVardef@e252ecorg.highwire.dtl.DTLVardef@b22121_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

Target recognition in tandem WW domains: complex structures for parallel and antiparallel ligand orientation in h-FBP21 tandem WW

Protein-protein interactions often rely on specialized recognition domains, such as WW domains, which bind to specific proline-rich sequences. The specificity of these protein-protein interactions can be increased by tandem repeats, i.e. two WW domains connected by a linker. With a flexible linker, the WW domains can move freely with respect to each other. Additionally, the tandem WW domains can bind in two different orientations to their target sequences. This makes the elucidation of complex structures of tandem WW domains extremely challenging. Here, we identify and characterize two complex structures of the tandem WW domain of human formin-binding protein 21 and a peptide sequence from its natural binding partner, the core-splicing protein SmB/B. The two structures differ in the ligand orientation, and consequently also in the relative orientation of the two WW domains. We analyze and probe the interactions in the complexes by molecular simulations and NMR experiments. The workflow to identify the complex structures uses molecular simulations, density-based clustering and peptide docking. It is designed to systematically generate possible complex structures for repeats of recognition domains. These structures will help us to understand the synergistic and multivalency effects that generate the astonishing versatility and specificity of protein-protein interactions.

molecular biology↗

Molecular Mechanism of the pH-Dependent Calcium Affinity in Langerin

The C-type lectin receptor langerin plays a vital role in the mammalian defense against invading pathogens. Its function hinges on the affinity to its co-factor Ca2+ which in turn is regulated by the pH. We studied the structural consequences of protonating the allosteric pH-sensor histidine H294 by molecular dynamics simulations (total simulation time: about 120 {micro}s) and Markov models. We discovered a mechanism in which the signal that the pH has dropped is transferred to the Ca2+-binding site without transferring the initial proton. Instead, protonation of H294 unlocks a conformation in which a protonated lysine side-chain forms a hydrogen bond with a Ca2+-coordinating aspartic acid. This destabilizes Ca2+ in the binding pocket, which we probed by steered molecular dynamics. After Ca2+-release, the proton is likely transferred to the aspartic acid and stabilized by a dyad with a nearby glutamic acid, triggering a conformational transition and thus preventing Ca2+-rebinding.

molecular biology↗