Implementation of Girsanov Reweighting in OpenMM and Deeptime.

Classical molecular dynamics (MD) simulations provide invaluable insights into complex molecular systems but face limitations in capturing phenomena occurring on time scales beyond their reach. To bridge this gap, various enhanced sampling techniques have been developed, which are complemented by reweighting techniques to recover the unbiased dynamics. Girsanov reweighting is a reweighting technique that reweights simulation paths, generated by a stochastic MD integrator, without evoking an effective model of the dynamics. Instead, it calculates the relative path probability density at the time resolution of the MD integrator. Efficient implementation of Girsanov reweighting requires that the reweighting factors are calculated on-the-fly during the simulations and thus needs to be implemented within the MD integrator. Here, we present a comprehensive guide for implementing Girsanov reweighting into MD simulations. We demonstrate the implementation in the MD simulation package OpenMM by extending the library openmmtools. Additionally, we implemented a reweighted Markov state model estimator within the time series analysis package Deeptime.

Fluorinated Protein-Ligand Complexes: A Computational Perspective.

Fluorine is an element renowned for its unique properties. Its powerful capability to modulate molecular properties makes it an attractive substituent for protein binding ligands; however, the rational design of fluorination can be challenging with effects on interactions and binding energies being difficult to predict. In this Perspective, we highlight how computational methods help us to understand the role of fluorine in protein-ligand binding with a focus on molecular simulation. We underline the importance of an accurate force field, present fluoride channels as a showcase for biomolecular interactions with fluorine, and discuss fluorine specific interactions like the ability to form hydrogen bonds and interactions with aryl groups. We put special emphasis on the disruption of water networks and entropic effects.

Dynamical Reweighting for Biased Rare Event Simulations.

Dynamical reweighting techniques aim to recover the correct molecular dynamics from a simulation at a modified potential energy surface. They are important for unbiasing enhanced sampling simulations of molecular rare events. Here, we review the theoretical frameworks of dynamical reweighting for modified potentials. Based on an overview of kinetic models with increasing level of detail, we discuss techniques to reweight two-state dynamics, multistate dynamics, and path integrals. We explore the natural link to transition path sampling and how the effect of nonequilibrium forces can be reweighted. We end by providing an outlook on how dynamical reweighting integrates with techniques for optimizing collective variables and with modern potential energy surfaces.

Prebound State Discovered in the Unbinding Pathway of Fluorinated Variants of the Trypsin-BPTI Complex Using Random Acceleration Molecular Dynamics Simulations.

The serine protease trypsin forms a tightly bound inhibitor complex with the bovine pancreatic trypsin inhibitor (BPTI). The complex is stabilized by the P1 residue Lys15, which interacts with negatively charged amino acids at the bottom of the S1 pocket. Truncating the P1 residue of wildtype BPTI to α-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 the 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 prebound state. The prebound state and the fully bound state differ by a substantial shift in the position, a slight shift in the orientation of the BPTI variants, and changes 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 the fully bound state and prebound state and also lowers the energy minimum of the prebound state. While the effect of fluorination is in general difficult to quantify, here, it is in part caused by favorable stabilization of a hydrogen bond between Gln194 and Cys14. The interaction pattern of the prebound state offers insights into the inhibitory mechanism of BPTI and might add valuable information for the design of serine protease inhibitors.

Impact of glycan nature on structure and viscoelastic properties of glycopeptide hydrogels.

Mucus is a complex biological hydrogel that acts as a barrier for almost everything entering or exiting the body. It is therefore of emerging interest for biomedical and pharmaceutical applications. Besides water, the most abundant components are the large and densely glycosylated mucins, glycoproteins of up to 20 MDa and carbohydrate content of up to 80 wt%. Here, we designed and explored a library of glycosylated peptides to deconstruct the complexity of mucus. Using the well-characterized hFF03 coiled-coil system as a hydrogel-forming peptide scaffold, we systematically probed the contribution of single glycans to the secondary structure as well as the formation and viscoelastic properties of the resulting hydrogels. We show that glycan-decoration does not affect α-helix and coiled-coil formation while it alters gel stiffness. By using oscillatory macrorheology, dynamic light scattering microrheology, and fluorescence lifetime-based nanorheology, we characterized the glycopeptide materials over several length scales. Molecular simulations revealed that the glycosylated linker may extend into the solvent, but more frequently interacts with the peptide, thereby likely modifying the stability of the self-assembled fibers. This systematic study highlights the interplay between glycan structure and hydrogel properties and may guide the development of synthetic mucus mimetics.

Accelerated generation of gene-engineered monoclonal CHO cell lines using FluidFM nanoinjection and CRISPR/Cas9.

Chinese hamster ovary (CHO) cells are the commonly used mammalian host system to manufacture recombinant proteins including monoclonal antibodies. However unfavorable non-human glycoprofile displayed on CHO-produced monoclonal antibodies have negative impacts on product quality, pharmacokinetics, and therapeutic efficiency. Glycoengineering such as genetic elimination of genes involved in glycosylation pathway in CHO cells is a viable solution but constrained due to longer timeline and laborious workflow. Here, in this proof-of-concept (PoC) study, we present a novel approach coined CellEDIT to engineer CHO cells by intranuclear delivery of the CRISPR components to single cells using the FluidFM technology. Co-injection of CRISPR system targeting BAX, DHFR, and FUT8 directly into the nucleus of single cells, enabled us to generate triple knockout CHO-K1 cell lines within a short time frame. The proposed technique assures the origin of monoclonality without the requirement of limiting dilution, cell sorting or positive selection. Furthermore, the approach is compatible to develop both single and multiple knockout clones (FUT8, BAX, and DHFR) in CHO cells. Further analyses on single and multiple knockout clones confirmed the targeted genetic disruption and altered protein expression. The knockout CHO-K1 clones showed the persistence of gene editing during the subsequent passages, compatible with serum free chemically defined media and showed equivalent transgene expression like parental clone.

Transposition of HOPPLA in siRNA-deficient plants suggests a limited effect of the environment on retrotransposon mobility in Brachypodium distachyon.

Long terminal repeat retrotransposons (LTR-RTs) are powerful mutagens regarded as a major source of genetic novelty and important drivers of evolution. Yet, the uncontrolled and potentially selfish proliferation of LTR-RTs can lead to deleterious mutations and genome instability, with large fitness costs for their host. While population genomics data suggest that an ongoing LTR-RT mobility is common in many species, the understanding of their dual role in evolution is limited. Here, we harness the genetic diversity of 320 sequenced natural accessions of the Mediterranean grass Brachypodium distachyon to characterize how genetic and environmental factors influence plant LTR-RT dynamics in the wild. When combining a coverage-based approach to estimate global LTR-RT copy number variations with mobilome-sequencing of nine accessions exposed to eight different stresses, we find little evidence for a major role of environmental factors in LTR-RT accumulations in B. distachyon natural accessions. Instead, we show that loss of RNA polymerase IV (Pol IV), which mediates RNA-directed DNA methylation in plants, results in high transcriptional and transpositional activities of RLC_BdisC024 (HOPPLA) LTR-RT family elements, and that these effects are not stress-specific. This work supports findings indicating an ongoing mobility in B. distachyon and reveals that host RNA-directed DNA methylation rather than environmental factors controls their mobility in this wild grass model.

Thermal isomerization rates in retinal analogues using Ab-Initio molecular dynamics.

For a detailed understanding of chemical processes in nature and industry, we need accurate models of chemical reactions in complex environments. While Eyring transition state theory is commonly used for modeling chemical reactions, it is most accurate for small molecules in the gas phase. A wide range of alternative rate theories exist that can better capture reactions involving complex molecules and environmental effects. However, they require that the chemical reaction is sampled by molecular dynamics simulations. This is a formidable challenge since the accessible simulation timescales are many orders of magnitude smaller than typical timescales of chemical reactions. To overcome these limitations, rare event methods involving enhanced molecular dynamics sampling are employed. In this work, thermal isomerization of retinal is studied using tight-binding density functional theory. Results from transition state theory are compared to those obtained from enhanced sampling. Rates obtained from dynamical reweighting using infrequent metadynamics simulations were in close agreement with those from transition state theory. Meanwhile, rates obtained from application of Kramers' rate equation to a sampled free energy profile along a torsional dihedral reaction coordinate were found to be up to three orders of magnitude higher. This discrepancy raises concerns about applying rate methods to one-dimensional reaction coordinates in chemical reactions.

How Chromophore Labels Shape the Structure and Dynamics of a Peptide Hydrogel.

Biocompatible and functionalizable hydrogels have a wide range of (potential) medicinal applications. The hydrogelation process, particularly for systems with very low polymer weight percentages (<1 wt %), remains poorly understood, making it challenging to predict the self-assembly of a given molecular building block into a hydrogel. This severely hinders the rational design of self-assembled hydrogels. In this study, we demonstrate the impact of an N-terminal group on the self-assembly and rheology of the peptide hydrogel hFF03 (hydrogelating, fibril forming peptide 03) using molecular dynamics simulations, oscillatory shear rheology, and circular dichroism spectroscopy. We find that the chromophore and even its specific regioisomers have a significant influence on the microscopic structure and dynamics of the self-assembled fibril, and on the macroscopic mechanical properties. This is because the chromophore influences the possible salt bridges, which form and stabilize the fibril formation. Furthermore, we find that the solvation shell fibrils by itself cannot explain the viscoelasticity of hFF03 hydrogels. Our atomistic model of the hFF03 fibril formation enables a more rational design of these hydrogels. In particular, altering the N-terminal chromophore emerges as a design strategy to tune the mechanic properties of these self-assembled peptide hydrogels.

Biosynthetic incorporation of fluorinated amino acids into the nonribosomal peptide gramicidin S.

Fluorine is a key element in medicinal chemistry, as it can significantly enhance the pharmacological properties of drugs. In this study, we aimed to biosynthetically produce fluorinated analogues of the antimicrobial cyclic decapeptide gramicidin S (GS). However, our results show that the A-domain of the NRPS module GrsA rejects 4-fluorinated analogues of its native substrate Phe due to an interrupted T-shaped aromatic interaction in the binding pocket. We demonstrate that GrsA mutant W239S improves the incorporation of 4-fluorinated Phe into GS both in vitro and in vivo. Our findings provide new insights into the behavior of NRPSs towards fluorinated amino acids and strategies for the engineered biosynthesis of fluorinated peptides.

Optimizing molecular potential models by imposing kinetic constraints with path reweighting.

Empirical force fields employed in molecular dynamics simulations of complex systems are often optimized to reproduce experimentally determined structural and thermodynamic properties. In contrast, experimental knowledge about the interconversion rates between metastable states in such systems is hardly ever incorporated in a force field due to a lack of an efficient approach. Here, we introduce such a framework based on the relationship between dynamical observables, such as rate constants, and the underlying molecular model parameters using the statistical mechanics of trajectories. Given a prior ensemble of molecular dynamics trajectories produced with imperfect force field parameters, the approach allows for the optimal adaption of these parameters such that the imposed constraint of equally predicted and experimental rate constant is obeyed. To do so, the method combines the continuum path ensemble maximum caliber approach with path reweighting methods for stochastic dynamics. When multiple solutions are found, the method selects automatically the combination that corresponds to the smallest perturbation of the entire path ensemble, as required by the maximum entropy principle. To show the validity of the approach, we illustrate the method on simple test systems undergoing rare event dynamics. Next to simple 2D potentials, we explore particle models representing molecular isomerization reactions and protein-ligand unbinding. Besides optimal interaction parameters, the methodology gives physical insights into what parts of the model are most sensitive to the kinetics. We discuss the generality and broad implications of the methodology.

[Malnutrition in internal medicine : Screening, assessment and importance]. / Mangelernährung in der Inneren Medizin : Screening, Assessment und Bedeutung.

Disease-related malnutrition has a strong influence on the further course of the disease and mortality, especially in chronically ill patients. In recent years it could be shown in large randomized studies that an individual nutrition therapy could significantly and relevantly improve the clinical outcome of patients in internal medicine with a risk of malnutrition, both in hospital and in aftercare. Therefore, due to the increasing proportion of multimorbid patients the significance of malnutrition and its treatment is becoming increasingly more important in the practice and in research. Nutritional medicine should nowadays be considered as an effective and integral component of a holistic treatment in internal medicine; however, further research is necessary in order to investigate new nutritional biomarkers and for a better integration of an evidence-based personalized nutritional medicine into routine clinical practice.

Inflammation and Nutrition: Friend or Foe?

The importance of the interplay between inflammation and nutrition has generated much interest in recent times. Inflammation has been identified as a key driver for disease-related malnutrition, leading to anorexia, reduced food intake, muscle catabolism, and insulin resistance, which are stimulating a catabolic state. Interesting recent data suggest that inflammation also modulates the response to nutritional treatment. Studies have demonstrated that patients with high inflammation show no response to nutritional interventions, while patients with lower levels of inflammation do. This may explain the contradictory results of nutritional trials to date. Several studies of heterogeneous patient populations, or in the critically ill or advanced cancer patients, have not found significant benefits on clinical outcome. Vice versa, several dietary patterns and nutrients with pro- or anti-inflammatory properties have been identified, demonstrating that nutrition influences inflammation. Within this review, we summarize and discuss recent advances in both the role of inflammation in malnutrition and the effect of nutrition on inflammation.

CommonNNClustering─A Python Package for Generic Common-Nearest-Neighbor 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 (core-set) Markov-state models. Here we present the open-source Python project CommonNNClustering, which provides an easy-to-use and efficient reimplementation of the common-nearest-neighbor (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 customization.

Water Network in the Binding Pocket of Fluorinated BPTI-Trypsin Complexes─Insights from Simulation and Experiment.

Structural waters in the S1 binding pocket of ß-trypsin are critical for the stabilization of the complex of ß-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 α-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 noncovalent interactions with 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-ß-trypsin complex (pdb: 7PH1). Both experimental and computational data show a stepwise 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 regard to energetic properties that could explain the increase in inhibitor strength. The analysis of the energy 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.

The occurrence of ansamers in the synthesis of cyclic peptides.

α-Amanitin is a bicyclic octapeptide composed of a macrolactam with a tryptathionine cross-link forming a handle. Previously, the occurrence of isomers of amanitin, termed atropisomers has been postulated. Although the total synthesis of α-amanitin has been accomplished this aspect still remains unsolved. We perform the synthesis of amanitin analogs, accompanied by in-depth spectroscopic, crystallographic and molecular dynamics studies. The data unambiguously confirms the synthesis of two amatoxin-type isomers, for which we propose the term ansamers. The natural structure of the P-ansamer can be ansa-selectively synthesized using an optimized synthetic strategy. We believe that the here described terminology does also have implications for many other peptide structures, e.g. norbornapeptides, lasso peptides, tryptorubins and others, and helps to unambiguously describe conformational isomerism of cyclic peptides.

GROMACS Stochastic Dynamics and BAOAB Are Equivalent Configurational Sampling Algorithms.

Two of the most widely used Langevin integrators for molecular dynamics simulations are the GROMACS Stochastic Dynamics (GSD) integrator and the splitting method BAOAB. In this letter, we show that the GROMACS Stochastic Dynamics integrator is equal to the less frequently used splitting method BAOA. It immediately follows that GSD and BAOAB sample the same configurations and have the same high configurational accuracy. Our numerical results indicate that GSD/BAOA has higher kinetic accuracy than BAOAB.

A Formylglycine-Peptide for the Site-Directed Identification of Phosphotyrosine-Mimetic Fragments.

Discovery of protein-binding fragments for precisely defined binding sites is an unmet challenge to date. Herein, formylglycine is investigated as a molecular probe for the sensitive detection of fragments binding to a spatially defined protein site . Formylglycine peptide 3 was derived from a phosphotyrosine-containing peptide substrate of protein tyrosine phosphatase PTP1B by replacing the phosphorylated amino acid with the reactive electrophile. Fragment ligation with formylglycine occurred in situ in aqueous physiological buffer. Structures and kinetics were validated by NMR spectroscopy. Screening and hit validation revealed fluorinated and non-fluorinated hit fragments being able to replace the native phosphotyrosine residue. The formylglycine probe identified low-affinity fragments with high spatial resolution as substantiated by molecular modelling. The best fragment hit, 4-amino-phenyl-acetic acid, was converted into a cellularly active, nanomolar inhibitor of the protein tyrosine phosphatase SHP2.

Fluorine-induced polarity increases inhibitory activity of BPTI towards chymotrypsin.

Substituting the P1 position in bovine pancreatic trypsin inhibitor (BPTI) is known to heavily influence its inhibitory activity towards serine proteases. Side-chain fluorinated aliphatic amino acids have been shown to alter numerous properties of peptides and proteins and thus are of interest in the context of BPTI. In our study, we systematically investigated the site-specific incorporation of non-canonical amino acids into BPTI by microwave-assisted solid-phase peptide synthesis (SPPS). Inhibitor activity of the variants was tested towards the serine protease α-chymotrypsin. We observed enhanced inhibition of two fluorinated BPTIs compared to wild type and hydrocarbon variants. To further investigate the complexes, we performed X-ray structure analysis. Our findings underline the power fluorine offers as a tool in protein engineering to beneficially alter the effects on phenomena as protein-protein interactions.

Experimentally heat-induced transposition increases drought tolerance in Arabidopsis thaliana.

Eukaryotic genomes contain a vast diversity of transposable elements (TEs). Formerly often described as selfish and parasitic DNA sequences, TEs are now recognised as a source of genetic diversity and powerful drivers of evolution. However, because their mobility is tightly controlled by the host, studies experimentally assessing how fast TEs may mediate the emergence of adaptive traits are scarce. We exposed Arabidopsis thaliana high-copy TE lines (hcLines) with up to c. eight-fold increased copy numbers of the heat-responsive ONSEN TE to drought as a straightforward and ecologically highly relevant selection pressure. We provide evidence for increased drought tolerance in five out of the 23 tested hcLines and further pinpoint one of the causative mutations to an exonic insertion of ONSEN in the ribose-5-phosphate-isomerase 2 gene. The resulting loss-of-function mutation caused a decreased rate of photosynthesis, plant size and water consumption. Overall, we show that the heat-induced transposition of a low-copy TE increases phenotypic diversity and leads to the emergence of drought-tolerant individuals in A. thaliana. This is one of the rare empirical examples substantiating the adaptive potential of mobilised stress-responsive TEs in eukaryotes. Our work demonstrates the potential of TE-mediated loss-of-function mutations in stress adaptation.