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 methods for Markov models Kieninger, Stefanie; Donati, Luca; Keller, Bettina G
Current opinion in structural biology,
April 2020, 2020-Apr, 2020-04-00, 20200401, Letnik:
61
Journal Article
Recenzirano
•Advances, limitations and applications of dynamical reweighting for Molecular Dynamics simulations.•Classification of dynamical reweighting methods.•Enhanced sampling techniques for Markov State ...Models.•Dynamical reweighting to study protein conformational changes and (un)binding processes.
Conformational dynamics is essential to biomolecular processes. Markov State Models (MSMs) are widely used to elucidate dynamic properties of molecular systems from unbiased Molecular Dynamics (MD). However, the implementation of reweighting schemes for MSMs to analyze biased simulations is still at an early stage of development. Several dynamical reweighing approaches have been proposed, which can be classified as approaches based on (i) Kramers rate theory, (ii) rescaling of the probability density flux, (iii) reweighting by formulating a likelihood function, (iv) path reweighting. We present the state-of-the-art and discuss the methodological differences of these methods, their limitations and recent applications.
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.
Accurate models of chemical reactions in complex environments are crucial for understanding natural and industrial processes. While Eyring transition state theory is widely used, it's most accurate for small gas‐phase molecules. Molecular dynamics simulations are an alternative, but rate estimates are very hard to converge and require additional assumptions. For the thermal isomerization rates in retinal analogues, we quantify these assumptions and show that the rate estimate can indeed be converged.
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.
Allostery in C-type lectins Keller, Bettina G; Rademacher, Christoph
Current opinion in structural biology,
06/2020, Letnik:
62
Journal Article
Recenzirano
•CTLD provides a scaffold for a multitude of functionalities.•CLRs show remarkable protein dynamics over various time scales.•Allostery fine-tunes the Ca2+ affinity of Langerin.•Secondary binding ...sites exist for various CLRs.
C-type lectins are the largest and most diverse family of mammalian carbohydrate-binding proteins. They share a common protein fold, which provides the unifying basis for calcium-mediated carbohydrate recognition. Their involvement in a multitude of biological functions is remarkable. Here, we review the variety of tasks these lectins are involved in alongside with the structural demands on the overall protein architecture. Subtle changes of the protein structure are implemented to cope with such diverse functional requirements. The presence of a high level of structural dynamics over a broad palette of time scales is paired with the presence of secondary binding sites and allosteric coordination of remote sites and renders this lectin fold a highly adaptable scaffold.
Molecular dynamics (MD) are extremely complex, yet understanding the slow components of their dynamics is essential to understanding their macroscopic properties. To achieve this, one models the MD ...as a stochastic process and analyses the dominant eigenfunctions of the associated Fokker-Planck operator, or of closely related transfer operators. So far, the calculation of the discretized operators requires extensive MD simulations. The square-root approximation of the Fokker-Planck equation is a method to calculate transition rates as a ratio of the Boltzmann densities of neighboring grid cells times a flux, and can in principle be calculated without a simulation. In a previous work we still used MD simulations to determine the flux. Here, we propose several methods to calculate the exact or approximate flux for various grid types, and thus estimate the rate matrix without a simulation. Using model potentials we test computational efficiency of the methods, and the accuracy with which they reproduce the dominant eigenfunctions and eigenvalues. For these model potentials, rate matrices with up to O(106) states can be obtained within seconds on a single high-performance compute server if regular grids are used.
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.
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.
The membrane permeability of cyclic peptides and peptidomimetics, which are generally larger and more complex than typical drug molecules, is likely strongly influenced by the conformational behavior ...of these compounds in polar and apolar environments. The size and complexity of peptides often limit their bioavailability, but there are known examples of peptide natural products such as cyclosporin A (CsA) that can cross cell membranes by passive diffusion. CsA is an undecapeptide with seven methylated backbone amides. Its crystal structure shows a “closed” twisted β-pleated sheet conformation with four intramolecular hydrogen bonds that is also observed in NMR measurements of CsA in chloroform. When binding to its target cyclophilin, on the other hand, CsA adopts an “open” conformation without intramolecular hydrogen bonds. In this study, we attempted to sample the complete conformational space of CsA in chloroform and in water by molecular dynamics simulations in order to better understand its conformational behavior in these two environments and to rationalize the good membrane permeability of CsA observed experimentally. From 10 μs molecular dynamics simulations in each solvent, Markov state models were constructed to characterize the metastable conformational states. The model in chloroform is compared to nuclear Overhauser effect NMR spectroscopy data reported in this study and taken from the literature. The conformational landscapes in the two solvents show significant overlap but also clearly distinct features.
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