Publications by authors named "Rebecca Wade"

164 Publications

G Protein-Coupled Receptor-Ligand Dissociation Rates and Mechanisms from τRAMD Simulations.

J Chem Theory Comput 2021 Sep 8. Epub 2021 Sep 8.

Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies, Schloss-Wolfsbrunnenweg 35, 69118 Heidelberg, Germany.

There is a growing appreciation of the importance of drug-target binding kinetics for lead optimization. For G protein-coupled receptors (GPCRs), which mediate signaling over a wide range of time scales, the drug dissociation rate is often a better predictor of efficacy than binding affinity, although it is more challenging to compute. Here, we assess the ability of the τ-Random Acceleration Molecular Dynamics (τRAMD) approach to reproduce relative residence times and reveal dissociation mechanisms and the effects of allosteric modulation for two important membrane-embedded drug targets: the β2-adrenergic receptor and the muscarinic acetylcholine receptor M2. The dissociation mechanisms observed in the relatively short RAMD simulations (in which molecular dynamics (MD) simulations are performed using an additional force with an adaptively assigned random orientation applied to the ligand) are in general agreement with much more computationally intensive conventional MD and metadynamics simulations. Remarkably, although decreasing the magnitude of the random force generally reduces the number of egress routes observed, the ranking of ligands by dissociation rate is hardly affected and agrees well with experiment. The simulations also reproduce changes in residence time due to allosteric modulation and reveal associated changes in ligand dissociation pathways.
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http://dx.doi.org/10.1021/acs.jctc.1c00641DOI Listing
September 2021

Contact Map Fingerprints of Protein-Ligand Unbinding Trajectories Reveal Mechanisms Determining Residence Times Computed from Scaled Molecular Dynamics.

J Chem Theory Comput 2021 Sep 8. Epub 2021 Sep 8.

Data and Data Science, Sanofi R&D, 91 385 Chilly-Mazarin, France.

The binding kinetic properties of potential drugs may significantly influence their subsequent clinical efficacy. Predictions of these properties based on computer simulations provide a useful alternative to their expensive and time-consuming experimental counterparts, even at an early drug discovery stage. Herein, we perform scaled molecular dynamics (ScaledMD) simulations on a set of 27 ligands of HSP90 belonging to more than seven chemical series to estimate their relative residence times. We introduce two new techniques for the analysis and the classification of the simulated unbinding trajectories. The first technique, which helps in estimating the limits of the free energy well around the bound state, and the second one, based on a new contact map fingerprint, allow the description and the comparison of the paths that lead to unbinding. Using these analyses, we find that ScaledMD's relative residence time generally enables the identification of the slowest unbinders. We propose an explanation for the underestimation of the residence times of a subset of compounds, and we investigate how the biasing in ScaledMD can affect the mechanistic insights that can be gained from the simulations.
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http://dx.doi.org/10.1021/acs.jctc.1c00453DOI Listing
September 2021

Cholenic acid derivative UniPR1331 impairs tumor angiogenesis via blockade of VEGF/VEGFR2 in addition to Eph/ephrin.

Cancer Gene Ther 2021 Aug 23. Epub 2021 Aug 23.

Experimental Oncology and Immunology, Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy.

Angiogenesis, the formation of new blood vessels from preexisting ones, is crucial for tumor growth and metastatization, and is considered a promising therapeutic target. Unfortunately, drugs directed against a specific proangiogenic growth factor or receptor turned out to be of limited benefit for oncology patients, likely due to the high biochemical redundancy of the neovascularization process. In this scenario, multitarget compounds that are able to simultaneously tackle different proangiogenic pathways are eagerly awaited. UniPR1331 is a 3β-hydroxy-Δ-cholenic acid derivative, which is already known to inhibit Eph-ephrin interaction. Here, we employed an analysis pipeline consisting of molecular modeling and simulation, surface plasmon resonance spectrometry, biochemical assays, and endothelial cell models to demonstrate that UniPR1331 directly interacts with the vascular endothelial growth factor receptor 2 (VEGFR2) too. The binding of UniPR1331 to VEGFR2 prevents its interaction with the natural ligand vascular endothelial growth factor and subsequent autophosphorylation, signal transduction, and in vitro proangiogenic activation of endothelial cells. In vivo, UniPR1331 inhibits tumor cell-driven angiogenesis in zebrafish. Taken together, these data shed light on the pleiotropic pharmacological effect of UniPR1331, and point to Δ-cholenic acid as a promising molecular scaffold for the development of multitarget antiangiogenic compounds.
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http://dx.doi.org/10.1038/s41417-021-00379-5DOI Listing
August 2021

DNA sequence-dependent positioning of the linker histone in a nucleosome: A single-pair FRET study.

Biophys J 2021 Sep 20;120(17):3747-3763. Epub 2021 Jul 20.

Molecular and Cellular Modelling Group, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany; Faculty of Biosciences, Heidelberg University, Heidelberg, Germany; Center for Molecular Biology (ZMBH), DKFZ-ZMBH Alliance, Heidelberg University, Heidelberg, Germany; Interdisciplinary Center for Scientific Computing, Heidelberg, Germany. Electronic address:

Linker histones (LHs) bind to nucleosomes with their globular domain (gH) positioned in either an on- or an off-dyad binding mode. Here, we study the effect of the linker DNA (L-DNA) sequence on the binding of a full-length LH, Xenopus laevis H1.0b, to a Widom 601 nucleosome core particle (NCP) flanked by two 40 bp long L-DNA arms, by single-pair FRET spectroscopy. We varied the sequence of the 11 bp of L-DNA adjoining the NCP on either side, making the sequence either A-tract, purely GC, or mixed with 64% AT. The labeled gH consistently exhibited higher FRET efficiency with the labeled L-DNA containing the A-tract than that with the pure-GC stretch, even when the stretches were swapped. However, it did not exhibit higher FRET efficiency with the L-DNA containing 64% AT-rich mixed DNA when compared to the pure-GC stretch. We explain our observations with a model that shows that the gH binds on dyad and that two arginines mediate recognition of the A-tract via its characteristically narrow minor groove. To investigate whether this on-dyad minor groove-based recognition was distinct from previously identified off-dyad major groove-based recognition, a nucleosome was designed with A-tracts on both the L-DNA arms. One A-tract was complementary to thymine and the other to deoxyuridine. The major groove of the thymine-tract was lined with methyl groups that were absent from the major groove of the deoxyuridine tract. The gH exhibited similar FRET for both these A-tracts, suggesting that it does not interact with the thymine methyl groups exposed on the major groove. Our observations thus complement previous studies that suggest that different LH isoforms may employ different ways of recognizing AT-rich DNA and A-tracts. This adaptability may enable the LH to universally compact scaffold-associated regions and constitutive heterochromatin, which are rich in such sequences.
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http://dx.doi.org/10.1016/j.bpj.2021.07.012DOI Listing
September 2021

Ligand unbinding mechanisms and kinetics for T4 lysozyme mutants from τRAMD simulations.

Curr Res Struct Biol 2021 4;3:106-111. Epub 2021 May 4.

Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies, Schloss-Wolfsbrunnenweg 35, 69118, Heidelberg, Germany.

The protein-ligand residence time, τ, influences molecular function in biological networks and has been recognized as an important determinant of drug efficacy. To predict τ, computational methods must overcome the problem that τ often exceeds the timescales accessible to conventional molecular dynamics (MD) simulation. Here, we apply the τ-Random Acceleration Molecular Dynamics (τRAMD) method to a set of kinetically characterized complexes of T4 lysozyme mutants with small, engineered binding cavities. τRAMD yields relative ligand dissociation rates in good accordance with experiments across this diverse set of complexes that differ with regard to measurement temperature, ligand identity, protein mutation and binding cavity. τRAMD thereby allows a comprehensive characterization of the ligand egress routes and determinants of τ. Although ligand dissociation by multiple egress routes is observed, we find that egress via the predominant route determines the value of τ. We also find that the presence of a greater number of metastable states along egress pathways leads to slower protein-ligand dissociation. These physical insights could be exploited in the rational optimization of the kinetic properties of drug candidates.
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http://dx.doi.org/10.1016/j.crstbi.2021.04.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8244441PMC
May 2021

Prediction of the Drug-Target Binding Kinetics for Flexible Proteins by Comparative Binding Energy Analysis.

J Chem Inf Model 2021 07 1;61(7):3708-3721. Epub 2021 Jul 1.

Heidelberg Institute for Theoretical Studies (HITS), Schloß-Wolfsbrunnenweg 35, 69118 Heidelberg, Germany.

There is growing consensus that the optimization of the kinetic parameters for drug-protein binding leads to improved drug efficacy. Therefore, computational methods have been developed to predict kinetic rates and to derive quantitative structure-kinetic relationships (QSKRs). Many of these methods are based on crystal structures of ligand-protein complexes. However, a drawback is that each ligand-protein complex is usually treated as having a single structure. Here, we present a modification of COMparative BINding Energy (COMBINE) analysis, which uses the structures of ligand-protein complexes to predict binding parameters. We introduce the option of using multiple structures to describe each ligand-protein complex in COMBINE analysis and apply this to study the effects of protein flexibility on the derivation of dissociation rate constants () for inhibitors of p38 mitogen-activated protein (MAP) kinase, which has a flexible binding site. Multiple structures were obtained for each ligand-protein complex by performing docking to an ensemble of protein configurations obtained from molecular dynamics simulations. Coefficients to scale ligand-protein interaction energies determined from energy-minimized structures of ligand-protein complexes were obtained by partial least squares regression, and they allowed for the computation of values. The QSKR model obtained using single, energy-minimized crystal structures for each ligand-protein complex had higher predictive power than the QSKR model obtained with multiple structures from ensemble docking. However, incorporation of ligand-protein flexibility helped to highlight additional ligand-protein interactions that lead to longer residence times, such as interactions with residues Arg67 and Asp168, which are close to the ligand in many crystal structures. These results show that COMBINE analysis is a promising method to guide the design of compounds that bind to flexible proteins with improved binding kinetics.
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http://dx.doi.org/10.1021/acs.jcim.1c00639DOI Listing
July 2021

A Blueprint for High Affinity SARS-CoV-2 Mpro Inhibitors from Activity-Based Compound Library Screening Guided by Analysis of Protein Dynamics.

ACS Pharmacol Transl Sci 2021 Jun 16;4(3):1079-1095. Epub 2021 Mar 16.

Institute for Neuroscience and Medicine (INM-9), Forschungszentrum Jülich, Jülich, 52425, Germany.

The SARS-CoV-2 coronavirus outbreak continues to spread at a rapid rate worldwide. The main protease (Mpro) is an attractive target for anti-COVID-19 agents. Unexpected difficulties have been encountered in the design of specific inhibitors. Here, by analyzing an ensemble of ∼30 000 SARS-CoV-2 Mpro conformations from crystallographic studies and molecular simulations, we show that small structural variations in the binding site dramatically impact ligand binding properties. Hence, traditional druggability indices fail to adequately discriminate between highly and poorly druggable conformations of the binding site. By performing ∼200 virtual screenings of compound libraries on selected protein structures, we redefine the protein's druggability as the consensus chemical space arising from the multiple conformations of the binding site formed upon ligand binding. This procedure revealed a unique SARS-CoV-2 Mpro blueprint that led to a definition of a specific structure-based pharmacophore. The latter explains the poor transferability of potent SARS-CoV Mpro inhibitors to SARS-CoV-2 Mpro, despite the identical sequences of the active sites. Importantly, application of the pharmacophore predicted novel high affinity inhibitors of SARS-CoV-2 Mpro, that were validated by assays performed here and by a newly solved X-ray crystal structure. These results provide a strong basis for effective rational drug design campaigns against SARS-CoV-2 Mpro and a new computational approach to screen protein targets with malleable binding sites.
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http://dx.doi.org/10.1021/acsptsci.0c00215DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8009102PMC
June 2021

A Bittersweet Computational Journey among Glycosaminoglycans.

Biomolecules 2021 05 15;11(5). Epub 2021 May 15.

Experimental Oncology and Immunology, Department of Molecular and Translational Medicine, University of Brescia, 25123 Brescia, Italy.

Glycosaminoglycans (GAGs) are linear polysaccharides. In proteoglycans (PGs), they are attached to a core protein. GAGs and PGs can be found as free molecules, associated with the extracellular matrix or expressed on the cell membrane. They play a role in the regulation of a wide array of physiological and pathological processes by binding to different proteins, thus modulating their structure and function, and their concentration and availability in the microenvironment. Unfortunately, the enormous structural diversity of GAGs/PGs has hampered the development of dedicated analytical technologies and experimental models. Similarly, computational approaches (in particular, molecular modeling, docking and dynamics simulations) have not been fully exploited in glycobiology, despite their potential to demystify the complexity of GAGs/PGs at a structural and functional level. Here, we review the state-of-the art of computational approaches to studying GAGs/PGs with the aim of pointing out the "bitter" and "sweet" aspects of this field of research. Furthermore, we attempt to bridge the gap between bioinformatics and glycobiology, which have so far been kept apart by conceptual and technical differences. For this purpose, we provide computational scientists and glycobiologists with the fundamentals of these two fields of research, with the aim of creating opportunities for their combined exploitation, and thereby contributing to a substantial improvement in scientific knowledge.
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http://dx.doi.org/10.3390/biom11050739DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8156566PMC
May 2021

Simulation of the Positive Inotropic Peptide S100A1ct in Aqueous Environment by Gaussian Accelerated Molecular Dynamics.

J Phys Chem B 2021 05 4;125(18):4654-4666. Epub 2021 May 4.

Heidelberg Institute for Theoretical Studies (HITS), Schloss-Wolfsbrunnenweg 35, 69118 Heidelberg, Germany.

The S100A1ct peptide, consisting of the C-terminal 20 residues of the S100A1 protein fused to an N-terminal 6-residue hydrophilic tag, has been found to exert a positive inotropic effect, resulting in improved contractile performance of failing cardiac and skeletal muscle without arrhythmic side-effects. The S100A1ct peptide thus has high potential for the treatment of acute heart failure. As a step toward understanding its molecular mechanism of action, and to provide a basis for peptidomimetic design to optimize its properties, we here describe structure predictions and molecular dynamics simulations to characterize the conformational landscape of S100A1ct in aqueous environment. In S100A1, the C-terminal 20 residues form an α-helix, but peptide structure predictions indicate that other conformations are also possible. Conventional molecular dynamics simulations in implicit and explicit solvent corroborated this finding. To ensure adequate sampling, we performed simulations of a tagged 10-residue segment of S100A1ct, and we carried out Gaussian accelerated molecular dynamics simulations of the peptides. These simulations showed that although the helical conformation of S100A1ct was the most energetically stable, the peptide can adopt a range of kinked conformations, suggesting that its activity may be related to its ability to act as a conformational switch.
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http://dx.doi.org/10.1021/acs.jpcb.1c00902DOI Listing
May 2021

Brownian Dynamics Simulations of Proteins in the Presence of Surfaces: Long-Range Electrostatics and Mean-Field Hydrodynamics.

J Chem Theory Comput 2021 Jun 30;17(6):3510-3524. Epub 2021 Mar 30.

Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies (HITS), Schloß-Wolfsbrunnenweg 35, 69118 Heidelberg, Germany.

Simulations of macromolecular diffusion and adsorption in confined environments can offer valuable mechanistic insights into numerous biophysical processes. In order to model solutes at atomic detail on relevant time scales, Brownian dynamics simulations can be carried out with the approximation of rigid body solutes moving through a continuum solvent. This allows the precomputation of interaction potential grids for the solutes, thereby allowing the computationally efficient calculation of forces. However, hydrodynamic and long-range electrostatic interactions cannot be fully treated with grid-based approaches alone. Here, we develop a treatment of both hydrodynamic and electrostatic interactions to include the presence of surfaces by modeling grid-based and long-range interactions. We describe its application to simulate the self-association and many-molecule adsorption of the well-characterized protein hen egg-white lysozyme to mica-like and silica-like surfaces. We find that the computational model can recover a number of experimental observables of the adsorption process and provide insights into their determinants. The computational model is implemented in the Simulation of Diffusional Association (SDA) software package.
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http://dx.doi.org/10.1021/acs.jctc.0c01312DOI Listing
June 2021

A Protocol to Use Comparative Binding Energy Analysis to Estimate Drug-Target Residence Time.

Methods Mol Biol 2021 ;2266:171-186

Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany.

Comparative Binding Energy (COMBINE) analysis is an approach for deriving a target-specific scoring function to compute binding free energy, drug-binding kinetics, or a related property by exploiting the information contained in the three-dimensional structures of receptor-ligand complexes. Here, we describe the process of setting up and running COMBINE analysis to derive a Quantitative Structure-Kinetics Relationship (QSKR) for the dissociation rate constants (k) of inhibitors of a drug target. The derived QSKR model can be used to estimate residence times (τ, τ=1/k) for similar inhibitors binding to the same target, and it can also help to identify key receptor-ligand interactions that distinguish inhibitors with short and long residence times. Herein, we demonstrate the protocol for the application of COMBINE analysis on a dataset of 70 inhibitors of heat shock protein 90 (HSP90) belonging to 11 different chemical classes. The procedure is generally applicable to any drug target with known structural information on its complexes with inhibitors.
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http://dx.doi.org/10.1007/978-1-0716-1209-5_10DOI Listing
April 2021

Line-FRAP, A Versatile Method to Measure Diffusion Rates In Vitro and In Vivo.

J Mol Biol 2021 04 27;433(9):166898. Epub 2021 Feb 27.

Department of Biomolecular Sciences, Weizmann Institute of Science, Israel. Electronic address:

The crowded cellular milieu affect molecular diffusion through hard (occluded space) and soft (weak, non-specific) interactions. Multiple methods have been developed to measure diffusion coefficients at physiological protein concentrations within cells, each with its limitations. Here, we show that Line-FRAP, combined with rigours data analysis, is able to determine diffusion coefficients in a variety of environments, from in vitro to in vivo. The use of Line mode greatly improves time resolution of FRAP data acquisition, from 20-100 Hz in the classical mode to 800 Hz in the line mode. This improves data analysis, as intensity and radius of the bleach at the first post-bleach frame is critical. We evaluated the method on different proteins labelled chemically or fused to YFP in a wide range of environments. The diffusion coefficients measured in HeLa and in E. coli were ~2.5-fold and 15-fold slower than in buffer, and were comparable to previously published data. Increasing the osmotic pressure on E. coli further decreases diffusion, to the point at which proteins virtually stop moving. The method presented here, which requires a confocal microscope equipped with dual scanners, can be applied to study a large range of molecules with different sizes, and provides robust results in a wide range of environments and protein concentrations for fast diffusing molecules.
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http://dx.doi.org/10.1016/j.jmb.2021.166898DOI Listing
April 2021

Structure-kinetic relationship reveals the mechanism of selectivity of FAK inhibitors over PYK2.

Cell Chem Biol 2021 05 25;28(5):686-698.e7. Epub 2021 Jan 25.

Structural Genomics Consortium, Goethe University Frankfurt, Buchmann Institute for Molecular Life Sciences, Max-von-Laue-Straße 15, 60438 Frankfurt am Main, Germany; Institute of Pharmaceutical Chemistry, Goethe University Frankfurt, Buchmann Institute for Molecular Life Sciences, Max-von-Laue-Straße 9, 60438 Frankfurt am Main, Germany; German Cancer network DKTK and Frankfurt Cancer Institute (FCI), Goethe University Frankfurt, Frankfurt am Main, Germany. Electronic address:

There is increasing evidence of a significant correlation between prolonged drug-target residence time and increased drug efficacy. Here, we report a structural rationale for kinetic selectivity between two closely related kinases: focal adhesion kinase (FAK) and proline-rich tyrosine kinase 2 (PYK2). We found that slowly dissociating FAK inhibitors induce helical structure at the DFG motif of FAK but not PYK2. Binding kinetic data, high-resolution structures and mutagenesis data support the role of hydrophobic interactions of inhibitors with the DFG-helical region, providing a structural rationale for slow dissociation rates from FAK and kinetic selectivity over PYK2. Our experimental data correlate well with computed relative residence times from molecular simulations, supporting a feasible strategy for rationally optimizing ligand residence times. We suggest that the interplay between the protein structural mobility and ligand-induced effects is a key regulator of the kinetic selectivity of inhibitors of FAK versus PYK2.
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http://dx.doi.org/10.1016/j.chembiol.2021.01.003DOI Listing
May 2021

An electron transfer competent structural ensemble of membrane-bound cytochrome P450 1A1 and cytochrome P450 oxidoreductase.

Commun Biol 2021 01 8;4(1):55. Epub 2021 Jan 8.

Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies (HITS), Schloss-Wolfsbrunnenweg 35, 69118, Heidelberg, Germany.

Cytochrome P450 (CYP) heme monooxygenases require two electrons for their catalytic cycle. For mammalian microsomal CYPs, key enzymes for xenobiotic metabolism and steroidogenesis and important drug targets and biocatalysts, the electrons are transferred by NADPH-cytochrome P450 oxidoreductase (CPR). No structure of a mammalian CYP-CPR complex has been solved experimentally, hindering understanding of the determinants of electron transfer (ET), which is often rate-limiting for CYP reactions. Here, we investigated the interactions between membrane-bound CYP 1A1, an antitumor drug target, and CPR by a multiresolution computational approach. We find that upon binding to CPR, the CYP 1A1 catalytic domain becomes less embedded in the membrane and reorients, indicating that CPR may affect ligand passage to the CYP active site. Despite the constraints imposed by membrane binding, we identify several arrangements of CPR around CYP 1A1 that are compatible with ET. In the complexes, the interactions of the CPR FMN domain with the proximal side of CYP 1A1 are supplemented by more transient interactions of the CPR NADP domain with the distal side of CYP 1A1. Computed ET rates and pathways agree well with available experimental data and suggest why the CYP-CPR ET rates are low compared to those of soluble bacterial CYPs.
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http://dx.doi.org/10.1038/s42003-020-01568-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7794467PMC
January 2021

Putative second hit rare genetic variants in families with seemingly GBA-associated Parkinson's disease.

NPJ Genom Med 2021 Jan 5;6(1). Epub 2021 Jan 5.

Institute of Pathophysiology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.

Rare variants in the beta-glucocerebrosidase gene (GBA1) are common genetic risk factors for alpha synucleinopathy, which often manifests clinically as GBA-associated Parkinson's disease (GBA-PD). Clinically, GBA-PD closely mimics idiopathic PD, but it may present at a younger age and often aggregates in families. Most carriers of GBA variants are, however, asymptomatic. Moreover, symptomatic PD patients without GBA variant have been reported in families with seemingly GBA-PD. These observations obscure the link between GBA variants and PD pathogenesis and point towards a role for unidentified additional genetic and/or environmental risk factors or second hits in GBA-PD. In this study, we explored whether rare genetic variants may be additional risk factors for PD in two families segregating the PD-associated GBA1 variants c.115+1G>A (ClinVar ID: 93445) and p.L444P (ClinVar ID: 4288). Our analysis identified rare genetic variants of the HSP70 co-chaperone DnaJ homolog subfamily B member 6 (DNAJB6) and lysosomal protein prosaposin (PSAP) as additional factors possibly influencing PD risk in the two families. In comparison to the wild-type proteins, variant DNAJB6 and PSAP proteins show altered functions in the context of cellular alpha-synuclein homeostasis when expressed in reporter cells. Furthermore, the segregation pattern of the rare variants in the genes encoding DNAJB6 and PSAP indicated a possible association with PD in the respective families. The occurrence of second hits or additional PD cosegregating rare variants has important implications for genetic counseling in PD families with GBA1 variant carriers and for the selection of PD patients for GBA targeted treatments.
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http://dx.doi.org/10.1038/s41525-020-00163-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785741PMC
January 2021

RASPD+: Fast Protein-Ligand Binding Free Energy Prediction Using Simplified Physicochemical Features.

Front Mol Biosci 2020 17;7:601065. Epub 2020 Dec 17.

Molecular and Cellular Modelling Group, Heidelberg Institute of Theoretical Studies, Heidelberg, Germany.

The virtual screening of large numbers of compounds against target protein binding sites has become an integral component of drug discovery workflows. This screening is often done by computationally docking ligands into a protein binding site of interest, but this has the drawback of a large number of poses that must be evaluated to obtain accurate estimates of protein-ligand binding affinity. We here introduce a fast pre-filtering method for ligand prioritization that is based on a set of machine learning models and uses simple pose-invariant physicochemical descriptors of the ligands and the protein binding pocket. Our method, Rapid Screening with Physicochemical Descriptors + machine learning (RASPD+), is trained on PDBbind data and achieves a regression performance that is better than that of the original RASPD method and traditional scoring functions on a range of different test sets without the need for generating ligand poses. Additionally, we use RASPD+ to identify molecular features important for binding affinity and assess the ability of RASPD+ to enrich active molecules from decoys.
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http://dx.doi.org/10.3389/fmolb.2020.601065DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7773945PMC
December 2020

A workflow for exploring ligand dissociation from a macromolecule: Efficient random acceleration molecular dynamics simulation and interaction fingerprint analysis of ligand trajectories.

J Chem Phys 2020 Sep;153(12):125102

Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies, Schloss-Wolfsbrunnenweg 35, 69118 Heidelberg, Germany.

The dissociation of ligands from proteins and other biomacromolecules occurs over a wide range of timescales. For most pharmaceutically relevant inhibitors, these timescales are far beyond those that are accessible by conventional molecular dynamics (MD) simulation. Consequently, to explore ligand egress mechanisms and compute dissociation rates, it is necessary to enhance the sampling of ligand unbinding. Random Acceleration MD (RAMD) is a simple method to enhance ligand egress from a macromolecular binding site, which enables the exploration of ligand egress routes without prior knowledge of the reaction coordinates. Furthermore, the τRAMD procedure can be used to compute the relative residence times of ligands. When combined with a machine-learning analysis of protein-ligand interaction fingerprints (IFPs), molecular features that affect ligand unbinding kinetics can be identified. Here, we describe the implementation of RAMD in GROMACS 2020, which provides significantly improved computational performance, with scaling to large molecular systems. For the automated analysis of RAMD results, we developed MD-IFP, a set of tools for the generation of IFPs along unbinding trajectories and for their use in the exploration of ligand dynamics. We demonstrate that the analysis of ligand dissociation trajectories by mapping them onto the IFP space enables the characterization of ligand dissociation routes and metastable states. The combined implementation of RAMD and MD-IFP provides a computationally efficient and freely available workflow that can be applied to hundreds of compounds in a reasonable computational time and will facilitate the use of τRAMD in drug design.
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http://dx.doi.org/10.1063/5.0019088DOI Listing
September 2020

Impact of no-touch ultraviolet light room disinfection systems on Clostridioides difficile infections.

Am J Infect Control 2021 05 26;49(5):646-648. Epub 2020 Aug 26.

Infection Prevention and Hospital Epidemiology, Barnes-Jewish Hospital, St. Louis, MO; Division of Infectious Diseases, Washington University School of Medicine, St. Louis, MO.

Ultraviolet light (UVL) room disinfection has emerged as an adjunct to manual cleaning of patient rooms. Two different no-touch UVL devices were implemented in 3 health system hospitals to reduce Clostridioides difficile infections (CDI). CDI rates at all 3 facilities remained unchanged following implementation of UVL disinfection. Preintervention CDI rates were generally low, and data from one hospital showed high compliance with manual cleaning, which may have limited the impact of UVL disinfection.
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http://dx.doi.org/10.1016/j.ajic.2020.08.030DOI Listing
May 2021

Recent progress in molecular simulation methods for drug binding kinetics.

Curr Opin Struct Biol 2020 10 6;64:126-133. Epub 2020 Aug 6.

Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies, Schloss-Wolfsbrunnenweg 35, 69118 Heidelberg, Germany; Center for Molecular Biology (ZMBH), DKFZ-ZMBH Alliance, Heidelberg University, Im Neuenheimer Feld 282, 69120 Heidelberg, Germany; Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Im Neuenheimer Feld 205, Heidelberg, Germany. Electronic address:

Due to the contribution of drug-target binding kinetics to drug efficacy, there is a high level of interest in developing methods to predict drug-target binding kinetic parameters. During the review period, a wide range of enhanced sampling molecular dynamics simulation-based methods has been developed for computing drug-target binding kinetics and studying binding and unbinding mechanisms. Here, we assess the performance of these methods considering two benchmark systems in detail: mutant T4 lysozyme-ligand complexes and a large set of N-HSP90-inhibitor complexes. The results indicate that some of the simulation methods can already be usefully applied in drug discovery or lead optimization programs but that further studies on more high-quality experimental benchmark datasets are necessary to improve and validate computational methods.
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http://dx.doi.org/10.1016/j.sbi.2020.06.022DOI Listing
October 2020

Myotubularin-related protein 7 activates peroxisome proliferator-activated receptor-gamma.

Oncogenesis 2020 Jun 10;9(6):59. Epub 2020 Jun 10.

Department of Medicine II, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.

Peroxisome proliferator-activated receptor-gamma (PPARγ) is a transcription factor drugable by agonists approved for treatment of type 2 diabetes, but also inhibits carcinogenesis and cell proliferation in vivo. Activating mutations in the Kirsten rat sarcoma viral oncogene homologue (KRAS) gene mitigate these beneficial effects by promoting a negative feedback-loop comprising extracellular signal-regulated kinase 1/2 (ERK1/2) and mitogen-activated kinase kinase 1/2 (MEK1/2)-dependent inactivation of PPARγ. To overcome this inhibitory mechanism, we searched for novel post-translational regulators of PPARγ. Phosphoinositide phosphatase Myotubularin-Related-Protein-7 (MTMR7) was identified as cytosolic interaction partner of PPARγ. Synthetic peptides were designed resembling the regulatory coiled-coil (CC) domain of MTMR7, and their activities studied in human cancer cell lines and C57BL6/J mice. MTMR7 formed a complex with PPARγ and increased its transcriptional activity by inhibiting ERK1/2-dependent phosphorylation of PPARγ. MTMR7-CC peptides mimicked PPARγ-activation in vitro and in vivo due to LXXLL motifs in the CC domain. Molecular dynamics simulations and docking predicted that peptides interact with the steroid receptor coactivator 1 (SRC1)-binding site of PPARγ. Thus, MTMR7 is a positive regulator of PPARγ, and its mimicry by synthetic peptides overcomes inhibitory mechanisms active in cancer cells possibly contributing to the failure of clinical studies targeting PPARγ.
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http://dx.doi.org/10.1038/s41389-020-0238-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7286916PMC
June 2020

Computation of FRAP recovery times for linker histone - chromatin binding on the basis of Brownian dynamics simulations.

Biochim Biophys Acta Gen Subj 2020 10 5;1864(10):129653. Epub 2020 Jun 5.

Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies (HITS), 69118 Heidelberg, Germany; Center for Molecular Biology (ZMBH), DKFZ-ZMBH Alliance, Heidelberg University, 69120 Heidelberg, Germany; Interdisciplinary Center for Scientific Computing (IWR), 69120 Heidelberg, Germany. Electronic address:

Background Fluorescence recovery after photobleaching (FRAP) studies can provide kinetic information about proteins in cells. Single point mutations can significantly affect the binding kinetics of proteins and result in variations in the recovery half time (t) measured in FRAP experiments. FRAP measurements of linker histone (LH) proteins in the cell nucleus have previously been reported by Brown et al. (2006) and Lele et al. (2006). Methods We performed Brownian dynamics (BD) simulations of the diffusional association of the wild-type and 38 single or double point mutants of the globular domain of mouse linker histone H1.0 (gH1.0) to a nucleosome. From these simulations, we calculated the bimolecular association rate constant (k), the Gibbs binding free energy (ΔG) and the dissociation rate constant (k) related to formation of a diffusional encounter complex between the nucleosome and the gH1.0. Results We used these parameters, after application of a correction factor to account for the effects of the crowded environment of the nucleus, to compute FRAP recovery times and curves that are in good agreement with previously published, experimentally measured FRAP recovery time courses. Conclusions Our computational analysis suggests that BD simulations can be used to predict the relative effects of single point mutations on FRAP recovery times related to protein binding. General Significance BD simulations assist in providing a detailed molecular level interpretation of FRAP data.
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http://dx.doi.org/10.1016/j.bbagen.2020.129653DOI Listing
October 2020

Structural characterization of an Arf dimer interface: molecular mechanism of Arf-dependent membrane scission.

FEBS Lett 2020 07 31;594(14):2240-2253. Epub 2020 May 31.

Heidelberg University Biochemistry Center (BZH), University of Heidelberg, Germany.

Dimerization of the small GTPase Arf is prerequisite for the scission of COPI-coated transport vesicles. Here, we quantify the monomer/dimer equilibrium of Arf within the membrane and show that after membrane scission, Arf dimers are restricted to donor membranes. By hydrogen exchange mass spectrometry, we define the interface of activated dimeric Arf within its switch II region. Single amino acid exchanges in this region reduce the propensity of Arf to dimerize. We suggest a mechanism of membrane scission by which the dimeric form of Arf is segregated to the donor membrane. Our data are consistent with the previously reported absence of dimerized Arf in COPI vesicles and could explain the presence of one single scar-like noncoated region in each COPI vesicle.
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http://dx.doi.org/10.1002/1873-3468.13808DOI Listing
July 2020

The Effect of Force-Field Parameters on Cytochrome P450-Membrane Interactions: Structure and Dynamics.

Sci Rep 2020 04 29;10(1):7284. Epub 2020 Apr 29.

Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies (HITS), Heidelberg, Germany.

The simulation of membrane proteins requires compatible protein and lipid force fields that reproduce the properties of both the protein and the lipid bilayer. Cytochrome P450 enzymes are bitopic membrane proteins with a transmembrane helical anchor and a large cytosolic globular domain that dips into the membrane. As such, they are representative and challenging examples of membrane proteins for simulations, displaying features of both peripheral and integral membrane proteins. We performed molecular dynamics simulations of three cytochrome P450 isoforms (2C9, 2C19 and 1A1) in a 2-oleoyl-1-palmitoyl-sn-glycerol-3-phosphocholine bilayer using two AMBER force field combinations: GAFF-LIPID with ff99SB for the protein, and LIPID14 with ff14SB for the protein. Comparison of the structural and dynamic properties of the proteins, the lipids and the protein-membrane interactions shows differing sensitivity of the cytochrome P450 isoforms to the choice of force field, with generally better agreement with experiment for the LIPID14 + ff14SB combination.
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http://dx.doi.org/10.1038/s41598-020-64129-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7190701PMC
April 2020

Correction to: Long range Debye-Hückel correction for computation of grid-based electrostatic forces between biomacromolecules.

BMC Biophys 2019 11;12. Epub 2020 Feb 11.

1Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies (HITS), Schloß-Wolfsbrunnenweg 35, 69118 Heidelberg, Germany.

[This corrects the article DOI: 10.1186/2046-1682-7-4.].
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http://dx.doi.org/10.1186/s13628-020-0026-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7017603PMC
February 2020

Druggability Assessment in TRAPP Using Machine Learning Approaches.

J Chem Inf Model 2020 03 11;60(3):1685-1699. Epub 2020 Mar 11.

Molecular and Cellular Modeling Group, Heidelberg Institute of Theoretical Studies (HITS), 69118 Heidelberg, Germany.

Accurate protein druggability predictions are important for the selection of drug targets in the early stages of drug discovery. Because of the flexible nature of proteins, the druggability of a binding pocket may vary due to conformational changes. We have therefore developed two statistical models, a logistic regression model (TRAPP-LR) and a convolutional neural network model (TRAPP-CNN), for predicting druggability and how it varies with changes in the spatial and physicochemical properties of a binding pocket. These models are integrated into TRAnsient Pockets in Proteins (TRAPP), a tool for the analysis of binding pocket variations along a protein motion trajectory. The models, which were trained on publicly available and self-augmented datasets, show equivalent or superior performance to existing methods on test sets of protein crystal structures and have sufficient sensitivity to identify potentially druggable protein conformations in trajectories from molecular dynamics simulations. Visualization of the evidence for the decisions of the models in TRAPP facilitates identification of the factors affecting the druggability of protein binding pockets.
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http://dx.doi.org/10.1021/acs.jcim.9b01185DOI Listing
March 2020

A function of profilin in force generation during malaria parasite motility that is independent of actin binding.

J Cell Sci 2020 04 15;134(5). Epub 2020 Apr 15.

Integrative Parasitology, Center for Infectious Diseases, Heidelberg University Medical School, Im Neuenheimer Feld 324, 69120 Heidelberg, Germany

During transmission of malaria-causing parasites from mosquito to mammal, sporozoites migrate at high speed within the skin to access the bloodstream and infect the liver. This unusual gliding motility is based on retrograde flow of membrane proteins and highly dynamic actin filaments that provide short tracks for a myosin motor. Using laser tweezers and parasite mutants, we previously suggested that actin filaments form macromolecular complexes with plasma membrane-spanning adhesins to generate force during migration. Mutations in the actin-binding region of profilin, a near ubiquitous actin-binding protein, revealed that loss of actin binding also correlates with loss of force production and motility. Here, we show that different mutations in profilin, that do not affect actin binding , still generate lower force during sporozoite migration. Lower force generation inversely correlates with increased retrograde flow suggesting that, like in mammalian cells, the slow down of flow to generate force is the key underlying principle governing gliding motility.
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http://dx.doi.org/10.1242/jcs.233775DOI Listing
April 2020

Chromatosome Structure and Dynamics from Molecular Simulations.

Annu Rev Phys Chem 2020 04 4;71:101-119. Epub 2020 Feb 4.

Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies (HITS), 69118 Heidelberg, Germany; email:

Chromatosomes are fundamental units of chromatin structure that are formed when a linker histone protein binds to a nucleosome. The positioning of the linker histone on the nucleosome influences the packing of chromatin. Recent simulations and experiments have shown that chromatosomes adopt an ensemble of structures that differ in the geometry of the linker histone-nucleosome interaction. In this article we review the application of Brownian, Monte Carlo, and molecular dynamics simulations to predict the structure of linker histone-nucleosome complexes, to study the binding mechanisms involved, and to predict how this binding affects chromatin fiber structure. These simulations have revealed the sensitivityof the chromatosome structure to variations in DNA and linker histone sequence, as well as to posttranslational modifications, thereby explaining the structural variability observed in experiments. We propose that a concerted application of experimental and computational approaches will reveal the determinants of chromatosome structural variability and how it impacts chromatin packing.
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http://dx.doi.org/10.1146/annurev-physchem-071119-040043DOI Listing
April 2020

Regulation of adenylyl cyclase 5 in striatal neurons confers the ability to detect coincident neuromodulatory signals.

PLoS Comput Biol 2019 10 30;15(10):e1007382. Epub 2019 Oct 30.

Science for Life Laboratory, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden.

Long-term potentiation and depression of synaptic activity in response to stimuli is a key factor in reinforcement learning. Strengthening of the corticostriatal synapses depends on the second messenger cAMP, whose synthesis is catalysed by the enzyme adenylyl cyclase 5 (AC5), which is itself regulated by the stimulatory Gαolf and inhibitory Gαi proteins. AC isoforms have been suggested to act as coincidence detectors, promoting cellular responses only when convergent regulatory signals occur close in time. However, the mechanism for this is currently unclear, and seems to lie in their diverse regulation patterns. Despite attempts to isolate the ternary complex, it is not known if Gαolf and Gαi can bind to AC5 simultaneously, nor what activity the complex would have. Using protein structure-based molecular dynamics simulations, we show that this complex is stable and inactive. These simulations, along with Brownian dynamics simulations to estimate protein association rates constants, constrain a kinetic model that shows that the presence of this ternary inactive complex is crucial for AC5's ability to detect coincident signals, producing a synergistic increase in cAMP. These results reveal some of the prerequisites for corticostriatal synaptic plasticity, and explain recent experimental data on cAMP concentrations following receptor activation. Moreover, they provide insights into the regulatory mechanisms that control signal processing by different AC isoforms.
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http://dx.doi.org/10.1371/journal.pcbi.1007382DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6821081PMC
October 2019

Differing Membrane Interactions of Two Highly Similar Drug-Metabolizing Cytochrome P450 Isoforms: CYP 2C9 and CYP 2C19.

Int J Mol Sci 2019 Sep 4;20(18). Epub 2019 Sep 4.

Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies (HITS), 69118 Heidelberg, Germany.

The human cytochrome P450 (CYP) 2C9 and 2C19 enzymes are two highly similar isoforms with key roles in drug metabolism. They are anchored to the endoplasmic reticulum membrane by their N-terminal transmembrane helix and interactions of their cytoplasmic globular domain with the membrane. However, their crystal structures were determined after N-terminal truncation and mutating residues in the globular domain that contact the membrane. Therefore, the CYP-membrane interactions are not structurally well-characterized and their dynamics and the influence of membrane interactions on CYP function are not well understood. We describe herein the modeling and simulation of CYP 2C9 and CYP 2C19 in a phospholipid bilayer. The simulations revealed that, despite high sequence conservation, the small sequence and structural differences between the two isoforms altered the interactions and orientations of the CYPs in the membrane bilayer. We identified residues (including K72, P73, and I99 in CYP 2C9 and E72, R73, and H99 in CYP 2C19) at the protein-membrane interface that contribute not only to the differing orientations adopted by the two isoforms in the membrane, but also to their differing substrate specificities by affecting the substrate access tunnels. Our findings provide a mechanistic interpretation of experimentally observed effects of mutagenesis on substrate selectivity.
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http://dx.doi.org/10.3390/ijms20184328DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6770661PMC
September 2019

KBbox: A Toolbox of Computational Methods for Studying the Kinetics of Molecular Binding.

J Chem Inf Model 2019 09 20;59(9):3630-3634. Epub 2019 Aug 20.

Heidelberg Institute for Theoretical Studies , Schloss-Wolfsbrunnenweg 35 , 69118 Heidelberg , Germany.

The past few years have seen increasing recognition of the importance of understanding molecular binding kinetics. This has led to the development of myriad computational methods for studying the kinetics of binding processes and predicting their associated rate constants that show varying ranges of application, degrees of accuracy, and computational requirements. In order to help researchers decide which method might be suitable for their projects, we have developed KBbox, a web server that guides users in choosing the methods they should consider on the basis of the information they wish to obtain, the data they currently have available, and the computational resources to which they have access. KBbox provides information on the toolbox of available methods, their associated software tools, an expanding list of curated examples of published applications, and tutorials explaining how to apply some of the methods. It has been designed to allow the easy addition of new methods, tools, and examples as they are developed and published. KBbox is available at https://kbbox.h-its.org/ .
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http://dx.doi.org/10.1021/acs.jcim.9b00485DOI Listing
September 2019
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