AMBER-DYES: Characterization of Charge Fluctuations and Force Field Parameterization of Fluorescent Dyes for Molecular Dynamics Simulations

Sensing the structural and conformational properties of single-stranded nucleic acids using electrometry and molecular simulations

Inferring the 3D structure and conformation of disordered biomolecules, e.g., single stranded nucleic acids (ssNAs), remains challenging due to their conformational heterogeneity in solution. Here, we use escape-time electrometry (ETe) to measure with sub elementary-charge precision the effective electrical charge in solution of short to medium chain length ssNAs in the range of 5-60 bases. We compare measurements of molecular effective charge with theoretically calculated values for simulated molecular conformations obtained from Molecular Dynamics simulations using a variety of forcefield descriptions. We demonstrate that the measured effective charge captures subtle differences in molecular structure in various nucleic acid homopolymers of identical length, and also that the experimental measurements can find agreement with computed values derived from coarse-grained molecular structure descriptions such as oxDNA, as well next generation ssNA force fields. We further show that comparing the measured effective charge with calculations for a rigid, charged rod-the simplest model of a nucleic acid-yields estimates of molecular structural dimensions such as linear charge spacings that capture molecular structural trends observed using high resolution structural analysis methods such as X-ray scattering. By sensitively probing the effective charge of a molecule, electrometry provides a powerful dimension supporting inferences of molecular structural and conformational properties, as well as the validation of biomolecular structural models. The overall approach holds promise for a high throughput, microscopy-based biomolecular analytical approach offering rapid screening and inference of molecular 3D conformation, and operating at the single molecule level in solution.

Molecular Dynamical and Quantum Mechanical Exploration of the Site-Specific Dynamics of Cy3 Dimers Internally Linked to dsDNA

Performing spectroscopic measurements on biomolecules labeled with fluorescent probes is a powerful approach to locating the molecular behavior and dynamics of large systems at specific sites within their local environments. The indocarbocyanine dye Cy3 has emerged as one of the most commonly used chromophores. The incorporation of Cy3 dimers into DNA enhances experimental resolution owing to the spectral characteristics influenced by the geometric orientation of excitonically coupled monomeric units. Various theoretical models and simulations have been utilized to aid in the interpretation of the experimental spectra. In this study, we employ all-atom molecular dynamics simulations to study the structural dynamics of Cy3 dimers internally linked to the dsDNA backbone. We used quantum mechanical calculations to derive insights from both the linear absorption spectra and the circular dichroism data. Furthermore, we explore potential limitations within a commonly used force field for cyanine dyes. The molecular dynamics simulations suggest the presence of four possible Cy3 dimeric populations. The spectral simulations on the four populations show one of them to agree better with the experimental signatures, suggesting it to be the dominant population. The relative orientation of Cy3 in this population compares very well with previous predictions from the Holstein-Frenkel Hamiltonian model.

FRET-guided modeling of nucleic acids

The functional diversity of RNAs is encoded in their innate conformational heterogeneity. The combination of single-molecule spectroscopy and computational modeling offers new attractive opportunities to map structural transitions within nucleic acid ensembles. Here, we describe a framework to harmonize single-molecule Förster resonance energy transfer (FRET) measurements with molecular dynamics simulations and de novo structure prediction. Using either all-atom or implicit fluorophore modeling, we recreate FRET experiments in silico, visualize the underlying structural dynamics and quantify the reaction coordinates. Using multiple accessible-contact volumes as a post hoc scoring method for fragment assembly in Rosetta, we demonstrate that FRET can be used to filter a de novo RNA structure prediction ensemble by refuting models that are not compatible with in vitro FRET measurement. We benchmark our FRET-assisted modeling approach on double-labeled DNA strands and validate it against an intrinsically dynamic manganese(II)-binding riboswitch. We show that a FRET coordinate describing the assembly of a four-way junction allows our pipeline to recapitulate the global fold of the riboswitch displayed by the crystal structure. We conclude that computational fluorescence spectroscopy facilitates the interpretability of dynamic structural ensembles and improves the mechanistic understanding of nucleic acid interactions.

Accounting for fast vs slow exchange in single molecule FRET experiments reveals hidden conformational states

Proteins are dynamic systems whose structural preferences determine their function. Unfortunately, building atomically detailed models of protein structural ensembles remains challenging, limiting our understanding of the relationships between sequence, structure, and function. Combining single molecule Förster resonance energy transfer (smFRET) experiments with molecular dynamics simulations could provide experimentally grounded, all-atom models of a protein's structural ensemble. However, agreement between the two techniques is often insufficient to achieve this goal. Here, we explore whether accounting for important experimental details like averaging across structures sampled during a given smFRET measurement is responsible for this apparent discrepancy. We present an approach to account for this time-averaging by leveraging the kinetic information available from Markov state models of a protein's dynamics. This allows us to accurately assess which timescales are averaged during an experiment. We find this approach significantly improves agreement between simulations and experiments in proteins with varying degrees of dynamics, including the well-ordered protein T4 lysozyme, the partially disordered protein apolipoprotein E (ApoE), and a disordered amyloid protein (Aβ40). We find evidence for hidden states that are not apparent in smFRET experiments because of time averaging with other structures, akin to states in fast exchange in NMR, and evaluate different force fields. Finally, we show how remaining discrepancies between computations and experiments can be used to guide additional simulations and build structural models for states that were previously unaccounted for. We expect our approach will enable combining simulations and experiments to understand the link between sequence, structure, and function in many settings.

FRETpredict: a Python package for FRET efficiency predictions using rotamer libraries

Förster resonance energy transfer (FRET) is a widely-used and versatile technique for the structural characterization of biomolecules. Here, we introduce FRETpredict, an easy-to-use Python software to predict FRET efficiencies from ensembles of protein conformations. FRETpredict uses a rotamer library approach to describe the FRET probes covalently bound to the protein. The software efficiently and flexibly operates on large conformational ensembles such as those generated by molecular dynamics simulations to facilitate the validation or refinement of molecular models and the interpretation of experimental data. We provide access to rotamer libraries for many commonly used dyes and linkers and describe a general methodology to generate new rotamer libraries for FRET probes. We demonstrate the performance and accuracy of the software for different types of systems: a rigid peptide (polyproline 11), an intrinsically disordered protein (ACTR), and three folded proteins (HiSiaP, SBD2, and MalE). FRETpredict is open source (GPLv3) and is available at github.com/KULL-Centre/FRETpredict and as a Python PyPI package at pypi.org/project/FRETpredict .

AMBERff at Scale: Multimillion-Atom Simulations with AMBER Force Fields in NAMD

All-atom molecular dynamics (MD) simulations are an essential structural biology technique with increasing application to multimillion-atom systems, including viruses and cellular machinery. Classical MD simulations rely on parameter sets, such as the AMBER family of force fields (AMBERff), to accurately describe molecular motion. Here, we present an implementation of AMBERff for use in NAMD that overcomes previous limitations to enable high-performance, massively parallel simulations encompassing up to two billion atoms. Single-point potential energy comparisons and case studies on model systems demonstrate that the implementation produces results that are as accurate as running AMBERff in its native engine.

A new twist on PIFE: photoisomerisation-related fluorescence enhancement

PIFE was first used as an acronym for protein-induced fluorescence enhancement, which refers to the increase in fluorescence observed upon the interaction of a fluorophore, such as a cyanine, with a protein. This fluorescence enhancement is due to changes in the rate ofcis/transphotoisomerisation. It is clear now that this mechanism is generally applicable to interactions with any biomolecule. In this review, we propose that PIFE is thereby renamed according to its fundamental working principle as photoisomerisation-related fluorescence enhancement, keeping the PIFE acronym intact. We discuss the photochemistry of cyanine fluorophores, the mechanism of PIFE, its advantages and limitations, and recent approaches to turning PIFE into a quantitative assay. We provide an overview of its current applications to different biomolecules and discuss potential future uses, including the study of protein-protein interactions, protein-ligand interactions and conformational changes in biomolecules.

Molecular Dynamic Studies of Dye-Dye and Dye-DNA Interactions Governing Excitonic Coupling in Squaraine Aggregates Templated by DNA Holliday Junctions

Dye molecules, arranged in an aggregate, can display excitonic delocalization. The use of DNA scaffolding to control aggregate configurations and delocalization is of research interest. Here, we applied Molecular Dynamics (MD) to gain an insight on how dye-DNA interactions affect excitonic coupling between two squaraine (SQ) dyes covalently attached to a DNA Holliday junction (HJ). We studied two types of dimer configurations, i.e., adjacent and transverse, which differed in points of dye covalent attachments to DNA. Three structurally different SQ dyes with similar hydrophobicity were chosen to investigate the sensitivity of excitonic coupling to dye placement. Each dimer configuration was initialized in parallel and antiparallel arrangements in the DNA HJ. The MD results, validated by experimental measurements, suggested that the adjacent dimer promotes stronger excitonic coupling and less dye-DNA interaction than the transverse dimer. Additionally, we found that SQ dyes with specific functional groups (i.e., substituents) facilitate a closer degree of aggregate packing via hydrophobic effects, leading to a stronger excitonic coupling. This work advances a fundamental understanding of the impacts of dye-DNA interactions on aggregate orientation and excitonic coupling.

FRETpredict: A Python package for FRET efficiency predictions using rotamer libraries

Here, we introduce FRETpredict, a Python software program to predict FRET efficiencies from ensembles of protein conformations. FRETpredict uses an established Rotamer Library Approach to describe the FRET probes covalently bound to the protein. The software efficiently operates on large conformational ensembles such as those generated by molecular dynamics simulations to facilitate the validation or refinement of molecular models and the interpretation of experimental data. We demonstrate the performance and accuracy of the software for different types of systems: a relatively structured peptide (polyproline 11), an intrinsically disordered protein (ACTR), and three folded proteins (HiSiaP, SBD2, and MalE). We also describe a general approach to generate new rotamer libraries for FRET probes of interest. FRETpredict is open source (GPLv3) and is available at github.com/KULL-Centre/FRETpredict and as a Python PyPI package at pypi.org/project/FRETpredict.

Modeling the Electronic Absorption Spectra of the Indocarbocyanine Cy3

Accurate modeling of optical spectra requires careful treatment of the molecular structures and vibronic, environmental, and thermal contributions. The accuracy of the computational methods used to simulate absorption spectra is limited by their ability to account for all the factors that affect the spectral shapes and energetics. The ensemble-based approaches are widely used to model the absorption spectra of molecules in the condensed-phase, and their performance is system dependent. The Franck-Condon approach is suitable for simulating high resolution spectra of rigid systems, and its accuracy is limited mainly by the harmonic approximation. In this work, the absorption spectrum of the widely used cyanine Cy3 is simulated using the ensemble approach via classical and quantum sampling, as well as, the Franck-Condon approach. The factors limiting the ensemble approaches, including the sampling and force field effects, are tested, while the vertical and adiabatic harmonic approximations of the Franck-Condon approach are also systematically examined. Our results show that all the vertical methods, including the ensemble approach, are not suitable to model the absorption spectrum of Cy3, and recommend the adiabatic methods as suitable approaches for the modeling of spectra with strong vibronic contributions. We find that the thermal effects, the low frequency modes, and the simultaneous vibrational excitations have prominent contributions to the Cy3 spectrum. The inclusion of the solvent stabilizes the energetics significantly, while its negligible effect on the spectral shapes aligns well with the experimental observations.

Unraveling multi-state molecular dynamics in single-molecule FRET experiments. I. Theory of FRET-lines

Conformational dynamics of biomolecules are of fundamental importance for their function. Single-molecule studies of Förster Resonance Energy Transfer (smFRET) between a tethered donor and acceptor dye pair are a powerful tool to investigate the structure and dynamics of labeled molecules. However, capturing and quantifying conformational dynamics in intensity-based smFRET experiments remains challenging when the dynamics occur on the sub-millisecond timescale. The method of multiparameter fluorescence detection addresses this challenge by simultaneously registering fluorescence intensities and lifetimes of the donor and acceptor. Together, two FRET observables, the donor fluorescence lifetime τD and the intensity-based FRET efficiency E, inform on the width of the FRET efficiency distribution as a characteristic fingerprint for conformational dynamics. We present a general framework for analyzing dynamics that relates average fluorescence lifetimes and intensities in two-dimensional burst frequency histograms. We present parametric relations of these observables for interpreting the location of FRET populations in E-τD diagrams, called FRET-lines. To facilitate the analysis of complex exchange equilibria, FRET-lines serve as reference curves for a graphical interpretation of experimental data to (i) identify conformational states, (ii) resolve their dynamic connectivity, (iii) compare different kinetic models, and (iv) infer polymer properties of unfolded or intrinsically disordered proteins. For a simplified graphical analysis of complex kinetic networks, we derive a moment-based representation of the experimental data that decouples the motion of the fluorescence labels from the conformational dynamics of the biomolecule. Importantly, FRET-lines facilitate exploring complex dynamic models via easily computed experimental observables. We provide extensive computational tools to facilitate applying FRET-lines.

Single-molecule Detection of Ultrafast Biomolecular Dynamics with Nanophotonics

Single-molecule Förster resonance energy transfer (FRET) is a versatile technique for probing the structure and dynamics of biomolecules even in heterogeneous ensembles. However, because of the limited fluorescence brightness per molecule and the relatively long fluorescence lifetimes, probing ultrafast structural dynamics in the nanosecond time scale has thus far been very challenging. Here, we demonstrate that nanophotonic fluorescence enhancement in zero-mode waveguides enables measurements of previously inaccessible low-nanosecond dynamics by dramatically improving time resolution and reduces data acquisition times by more than an order of magnitude. As a prototypical example, we use this approach to probe the dynamics of a short intrinsically disordered peptide that were previously inaccessible with single-molecule FRET measurements. We show that we are now able to detect the low-nanosecond correlations in this peptide, and we obtain a detailed interpretation of the underlying distance distributions and dynamics in conjunction with all-atom molecular dynamics simulations, which agree remarkably well with the experiments. We expect this combined approach to be widely applicable to the investigation of very rapid biomolecular dynamics.

Recent Efforts and Milestones for Simulating Nucleic Acid FRET Experiments through Computational Methods

Computational methods can greatly aid nucleic acid fluorescence experiments by either offering fully detailed atomic insights into the conformations and interactions present in the studied system or by providing accurate simulations of the fundamental parameters. Fluorescence-based optical biosensors show great potential for clinical diagnosis of life-altering diseases with a very high specificity. Many of the designs for such rely on the concept of Förster resonance energy transfer (FRET). Currently, the methods used experimentally make use of theoretical assumptions which fundamentally affect the results. Having a detailed atomistic overview or significant simulated parameters could improve the understanding of the calculations and provide much more accurate outcomes. However, there are many challenges that need to be addressed before standardized computational protocols can be employed. This review is meant to highlight the progress made for computational methods used to simulate FRET experiments for nucleic acid probes. Recent advances have been made in computational tools, such as force field parametrizations and improved protocols. Complementary simulations to experimental data are also comprised in the this review.

Molecular and Spectroscopic Characterization of Green and Red Cyanine Fluorophores from the Alexa Fluor and AF Series*

The use of fluorescence techniques has an enormous impact on various research fields including imaging, biochemical assays, DNA-sequencing and medical technologies. This has been facilitated by the development of numerous commercial dyes with optimized photophysical and chemical properties. Often, however, information about the chemical structures of dyes and the attached linkers used for bioconjugation remain a well-kept secret. This can lead to problems for research applications where knowledge of the dye structure is necessary to predict or understand (unwanted) dye-target interactions, or to establish structural models of the dye-target complex. Using a combination of optical spectroscopy, mass spectrometry, NMR spectroscopy and molecular dynamics simulations, we here investigate the molecular structures and spectroscopic properties of dyes from the Alexa Fluor (Alexa Fluor 555 and 647) and AF series (AF555, AF647, AFD647). Based on available data and published structures of the AF and Cy dyes, we propose a structure for Alexa Fluor 555 and refine that of AF555. We also resolve conflicting reports on the linker composition of Alexa Fluor 647 maleimide. We also conducted a comprehensive comparison between Alexa Fluor and AF dyes by continuous-wave absorption and emission spectroscopy, quantum yield determination, fluorescence lifetime and anisotropy spectroscopy of free and protein-attached dyes. All these data support the idea that Alexa Fluor and AF dyes have a cyanine core and are a derivative of Cy3 and Cy5. In addition, we compared Alexa Fluor 555 and Alexa Fluor 647 to their structural homologs AF555 and AF(D)647 in single-molecule FRET applications. Both pairs showed excellent performance in solution-based smFRET experiments using alternating laser excitation. Minor differences in apparent dye-protein interactions were investigated by molecular dynamics simulations. Our findings clearly demonstrate that the AF-fluorophores are an attractive alternative to Alexa- and Cy-dyes in smFRET studies or other fluorescence applications.

Choice of fluorophore affects dynamic DNA nanostructures

The ability to dynamically remodel DNA origami structures or functional nanodevices is highly desired in the field of DNA nanotechnology. Concomitantly, the use of fluorophores to track and validate the dynamics of such DNA-based architectures is commonplace and often unavoidable. It is therefore crucial to be aware of the side effects of popular fluorophores, which are often exchanged without considering the potential impact on the system. Here, we show that the choice of fluorophore can strongly affect the reconfiguration of DNA nanostructures. To this end, we encapsulate a triple-stranded DNA (tsDNA) into water-in-oil compartments and functionalize their periphery with a single-stranded DNA handle (ssDNA). Thus, the tsDNA can bind and unbind from the periphery by reversible opening of the triplex and subsequent strand displacement. Using a combination of experiments, molecular dynamics (MD) simulations, and reaction-diffusion modelling, we demonstrate for 12 different fluorophore combinations that it is possible to alter or even inhibit the DNA nanostructure formation-without changing the DNA sequence. Besides its immediate importance for the design of pH-responsive switches and fluorophore labelling, our work presents a strategy to precisely tune the energy landscape of dynamic DNA nanodevices.

FRET-based dynamic structural biology: Challenges, perspectives and an appeal for open-science practices

Single-molecule FRET (smFRET) has become a mainstream technique for studying biomolecular structural dynamics. The rapid and wide adoption of smFRET experiments by an ever-increasing number of groups has generated significant progress in sample preparation, measurement procedures, data analysis, algorithms and documentation. Several labs that employ smFRET approaches have joined forces to inform the smFRET community about streamlining how to perform experiments and analyze results for obtaining quantitative information on biomolecular structure and dynamics. The recent efforts include blind tests to assess the accuracy and the precision of smFRET experiments among different labs using various procedures. These multi-lab studies have led to the development of smFRET procedures and documentation, which are important when submitting entries into the archiving system for integrative structure models, PDB-Dev. This position paper describes the current 'state of the art' from different perspectives, points to unresolved methodological issues for quantitative structural studies, provides a set of 'soft recommendations' about which an emerging consensus exists, and lists openly available resources for newcomers and seasoned practitioners. To make further progress, we strongly encourage 'open science' practices.

Modeling solvation effects on absorption and fluorescence spectra of indole in aqueous solution

Modeling the optical spectra of molecules in solution presents a challenge, so it is important to understand which of the solvation effects (i.e., electrostatics, mutual polarization, and hydrogen bonding interactions between solute and solvent molecules) are crucial in reproducing the various features of the absorption and fluorescence spectra and to identify a sufficient theoretical model that accurately captures these effects with minimal computational cost. In this study, we use various implicit and explicit solvation models, such as molecular dynamics coupled with non-polarizable and polarizable force fields, as well as Car-Parrinello molecular dynamics, to model the absorption and fluorescence spectra of indole in aqueous solution. The excited states are computed using the equation of motion coupled cluster with single and double excitations combined with the effective fragment potential to represent water molecules, which we found to be a computationally efficient approach for modeling large solute-solvent clusters at a high level of quantum theory. We find that modeling mutual polarization, compared to other solvation effects, is a dominating factor for accurately reproducing the position of the peaks and spectral line shape of the absorption spectrum of indole in solution. We present an in-depth analysis of the influence that different solvation models have on the electronic excited states responsible for the features of the absorption spectra. Modeling fluorescence is more challenging since it is hard to reproduce even the correct emitting state, and force field parameters need to be re-evaluated.

AMBER-DYES in AMBER: Implementation of fluorophore and linker parameters into AmberTools

Molecular dynamics (MD) simulations of explicit representations of fluorescent dyes attached via a linker to a protein allow, e.g., probing commonly used approximations for dye localization and/or orientation or modeling Förster resonance energy transfer. However, setting up and performing such MD simulations with the AMBER suite of biomolecular simulation programs has remained challenging due to the unavailability of an easy-to-use set of parameters within AMBER. Here, we adapted the AMBER-DYES parameter set derived by Graen et al. [J. Chem. Theory Comput. 10, 5505 (2014)] into "AMBER-DYES in AMBER" to generate a force field applicable within AMBER for commonly used fluorescent dyes and linkers attached to a protein. In particular, the computationally efficient graphics processing unit (GPU) implementation of the AMBER MD engine can now be exploited to overcome sampling issues of dye movements. The implementation is compatible with state-of-the-art force fields such as GAFF, GAFF2, ff99SB, ff14SB, lipid17, and GLYCAM_06j, which allows simulating post-translationally modified proteins and/or protein-ligand complexes and/or proteins in membrane environments. It is applicable with frequently used water models such as TIP3P, TIP4P, TIP4P-Ew, and OPC. For ease of use, a LEaP-based workflow was created, which allows attaching (multiple) dye/linker combinations to a protein prior to further system preparation steps. Following the parameter development described by Graen et al. [J. Chem. Theory Comput. 10, 5505 (2014)] and the adaptation steps described here, AMBER-DYES in AMBER can be extended by additional linkers and fluorescent molecules.

Membrane Interactions of Cy3 and Cy5 Fluorophores and Their Effects on Membrane-Protein Dynamics

Organic fluorophores, such as Cy3 and Cy5, have been widely used as chemical labels to probe the structure and dynamics of membrane proteins. Although a number of previous studies have reported on the possibility of some of the water-soluble fluorophores to interact with lipid bilayers, detailed fluorophore-lipid interactions and, more importantly, the potential effect of such interactions on the natural dynamics of the labeled membrane proteins have not been well studied. We have performed a large set of all-atom molecular dynamics simulations employing the highly mobile membrane mimetic model to describe spontaneous partitioning of the fluorophores into lipid bilayers with different lipid compositions. Spontaneous membrane partitioning of Cy3 and Cy5 fluorophores captured in these simulations proceeds in two steps. Electrostatic interaction between the fluorophores and the lipid headgroups facilitates the initial, fast membrane association of the fluorophores, followed by slow insertion of hydrophobic moieties into the lipid bilayer core. After the conversion of the resulting membrane-bound systems to full-membrane representations, biased-exchange umbrella sampling simulations are performed for free energy calculations, revealing a higher energy barrier for partitioning into negatively charged (phosphatidylserine or phosphatidylcholine) membranes than purely zwitterionic (phosphatidylcholine or phosphatidylethanolamine) ones. Furthermore, the potential effect of fluorophore-lipid interactions on membrane proteins has been examined by covalently linking Cy5 to single- and multipass transmembrane helical proteins. Equilibrium simulations show strong position-dependent effects of Cy5-tagging on the structure and natural dynamics of membrane proteins. Interactions between the tagged protein and Cy5 were also observed. Our results suggest that fluorophore-lipid interactions can affect the structure and dynamics of membrane proteins to various extents, especially in systems with higher structural flexibility.

Highly Disordered Amyloid-β Monomer Probed by Single-Molecule FRET and MD Simulation

Monomers of amyloid-β (Aβ) protein are known to be disordered, but there is considerable controversy over the existence of residual or transient conformations that can potentially promote oligomerization and fibril formation. We employed single-molecule Förster resonance energy transfer (FRET) spectroscopy with site-specific dye labeling using an unnatural amino acid and molecular dynamics simulations to investigate conformations and dynamics of Aβ isoforms with 40 (Aβ40) and 42 residues (Aβ42). The FRET efficiency distributions of both proteins measured in phosphate-buffered saline at room temperature show a single peak with very similar FRET efficiencies, indicating there is apparently only one state. 2D FRET efficiency-donor lifetime analysis reveals, however, that there is a broad distribution of rapidly interconverting conformations. Using nanosecond fluorescence correlation spectroscopy, we measured the timescale of the fluctuations between these conformations to be ∼35 ns, similar to that of disordered proteins. These results suggest that both Aβ40 and Aβ42 populate an ensemble of rapidly reconfiguring unfolded states, with no long-lived conformational state distinguishable from that of the disordered ensemble. To gain molecular-level insights into these observations, we performed molecular dynamics simulations with a force field optimized to describe disordered proteins. We find, as in experiments, that both peptides populate configurations consistent with random polymer chains, with the vast majority of conformations lacking significant secondary structure, giving rise to very similar ensemble-averaged FRET efficiencies.

Linking time-series of single-molecule experiments with molecular dynamics simulations by machine learning

Single-molecule experiments and molecular dynamics (MD) simulations are indispensable tools for investigating protein conformational dynamics. The former provide time-series data, such as donor-acceptor distances, whereas the latter give atomistic information, although this information is often biased by model parameters. Here, we devise a machine-learning method to combine the complementary information from the two approaches and construct a consistent model of conformational dynamics. It is applied to the folding dynamics of the formin-binding protein WW domain. MD simulations over 400 μs led to an initial Markov state model (MSM), which was then "refined" using single-molecule Förster resonance energy transfer (FRET) data through hidden Markov modeling. The refined or data-assimilated MSM reproduces the FRET data and features hairpin one in the transition-state ensemble, consistent with mutation experiments. The folding pathway in the data-assimilated MSM suggests interplay between hydrophobic contacts and turn formation. Our method provides a general framework for investigating conformational transitions in other proteins.

An atomistic view on carbocyanine photophysics in the realm of RNA

Carbocyanine dyes have a long-standing tradition in fluorescence imaging and spectroscopy, due to their photostability and large spectral separation between individual dye species. Herein, we explore the versatility of cyanine dyes to probe the dynamics of nucleic acids and we report on the interrelation of fluorophores, RNA, and metal ions, namely K⁺ and Mg²⁺. Photophysical parameters including the fluorescence lifetime, quantum yield and dynamic anisotropy are monitored as a function of the nucleic acid composition, conformation, and metal ion abundance. Occasional excursions to a non-fluorescent cis-state hint at the remarkable sensitivity of carbocyanines to their local environment. Comparison of time-correlated single photon experiments with all-atom molecular dynamics simulations demonstrate that the propensity of photoisomerization is dictated by sterical constraints imposed on the fluorophore. Structural features in the vicinity of the dye play a crucial role in RNA recognition and have far-reaching implications on the mobility of the fluorescent probe. An atomic level description of the mutual interactions will ultimately benefit the quantitative interpretation of single-molecule FRET measurements on large RNA systems.

Molecular Modeling of Multidrug Properties of Resistance Nodulation Division (RND) Transporters

Efflux pumps of the resistance nodulation division (RND) superfamily are among the major contributors to intrinsic and acquired multidrug resistance in Gram-negative bacteria. Structural information on AcrAB-TolC and MexAB-OprM, major efflux pumps of Escherichia coli and Pseudomonas aeruginosa respectively, boosted intensive research aimed at understanding the molecular mechanisms ruling the active extrusion processes. In particular, several studies were devoted to the understanding of the determinants behind the extraordinary broad specificity of the RND transporters AcrB and MexB. In this chapter, we discuss the ever-growing role computational methods have been playing in deciphering key structural and dynamical features of these transporters and of their interaction with substrates and inhibitors. We further discuss and illustrate examples from our lab of how molecular docking, homology modeling, all-atom molecular dynamics simulations and in silico free energy estimations can all together give precious insights into the processes of recognition and extrusion of substrates, as well as on the possible inhibition strategies.

Proximity-Induced H-Aggregation of Cyanine Dyes on DNA-Duplexes

A wide variety of organic dyes form, under certain conditions, clusters know as J- and H-aggregates. Cyanine dyes are such a class of molecules where the spatial proximity of several dyes leads to overlapping electron orbitals and thus to the creation of a new energy landscape compared to that of the individual units. In this work, we create artificial H-aggregates of exactly two Cyanine 3 (Cy3) dyes by covalently linking them to a DNA molecule with controlled subnanometer distances. The absorption spectra of these coupled systems exhibit a blue-shifted peak, whose intensity varies depending on the distance between the dyes and the rigidity of the DNA template. Simulated vibrational resolved spectra, based on molecular orbital theory, excellently reproduce the experimentally observed features. Circular dichroism spectroscopy additionally reveals distinct signals, which indicates a chiral arrangement of the dye molecules. Molecular dynamic simulations of a Cy3-Cy3 construct including a 14-base pair DNA sequence verified chiral stacking of the dye molecules.

Quantitative FRET studies and integrative modeling unravel the structure and dynamics of biomolecular systems

Förster Resonance Energy Transfer (FRET) combined with single-molecule spectroscopy probes macromolecular structure and dynamics and identifies coexisting conformational states. We review recent methodological developments in integrative structural modeling by satisfying spatial restraints on networks of FRET pairs (hybrid-FRET). We discuss procedures to incorporate prior structural knowledge and to obtain optimal distance networks. Finally, a workflow for hybrid-FRET is presented that automates integrative structural modeling and experiment planning to put hybrid-FRET on rails. To test this workflow, we simulate realistic single-molecule experiments and resolve three protein conformers, exchanging at 30μs and 10ms, with accuracies of 1-3Å RMSD versus the target structure. Incorporation of data from other spectroscopies and imaging is also discussed.

Probing the Action of Chemical Denaturant on an Intrinsically Disordered Protein by Simulation and Experiment

Chemical denaturants are the most commonly used agents for unfolding proteins and are thought to act by better solvating the unfolded state. Improved solvation is expected to lead to an expansion of unfolded chains with increasing denaturant concentration, providing a sensitive probe of the denaturant action. However, experiments have so far yielded qualitatively different results concerning the effects of chemical denaturation. Studies using Förster resonance energy transfer (FRET) and other methods found an increase in radius of gyration with denaturant concentration, but most small-angle X-ray scattering (SAXS) studies found no change. This discrepancy therefore challenges our understanding of denaturation mechanism and more generally the accuracy of these experiments as applied to unfolded or disordered proteins. Here, we use all-atom molecular simulations to investigate the effect of urea and guanidinium chloride on the structure of the intrinsically disordered protein ACTR, which can be studied by experiment over a wide range of denaturant concentration. Using unbiased molecular simulations with a carefully calibrated denaturant model, we find that the protein chain indeed swells with increasing denaturant concentration. This is due to the favorable association of urea or guanidinium chloride with the backbone of all residues and with the side-chains of almost all residues, with denaturant-water transfer free energies inferred from this association in reasonable accord with experimental estimates. Interactions of the denaturants with the backbone are dominated by hydrogen bonding, while interactions with side-chains include other contributions. By computing FRET efficiencies and SAXS intensities at each denaturant concentration, we show that the simulation trajectories are in accord with both experiments on this protein, demonstrating that there is no fundamental inconsistency between the two types of experiment. Agreement with experiment also supports the picture of chemical denaturation described in our simulations, driven by weak association of denaturant with the protein. Our simulations support some assumptions needed for each experiment to accurately reflect changes in protein size, namely, that the commonly used FRET chromophores do not qualitatively alter the results and that possible effects such as preferential solvent partitioning into the interior of the chain do not interfere with the determination of radius of gyration from the SAXS experiments.

Quantitative interpretation of FRET experiments via molecular simulation: force field and validation

Molecular simulation is a valuable and complementary tool that may assist with the interpretation of single-molecule Förster resonance energy transfer (FRET) experiments, if the energy function is of sufficiently high quality. Here we present force-field parameters for one of the most common pairs of chromophores used in experiments, AlexaFluor 488 and 594. From microsecond molecular-dynamics simulations, we are able to recover both experimentally determined equilibrium constants and association/dissociation rates of the chromophores with free tryptophan, as well as the decay of fluorescence anisotropy of a labeled protein. We find that it is particularly important to obtain a correct balance of solute-water interactions in the simulations in order to faithfully capture the experimental anisotropy decays, which provide a sensitive benchmark for fluorophore mobility. Lastly, by a combination of experiment and simulation, we address a potential complication in the interpretation of experiments on polyproline, used as a molecular ruler for FRET experiments, namely the potential association of one of the chromophores with the polyproline helix. Under conditions where simulations accurately capture the fluorescence anisotropy decay, we find at most a modest, transient population of conformations in which the chromophores associate with the polyproline. Explicit calculation of FRET transfer efficiencies for short polyprolines yields results in good agreement with experiment. These results illustrate the potential power of a combination of molecular simulation and experiment in quantifying biomolecular dynamics.

A Database of Force-Field Parameters, Dynamics, and Properties of Antimicrobial Compounds

We present an on-line database of all-atom force-field parameters and molecular properties of compounds with antimicrobial activity (mostly antibiotics and some beta-lactamase inhibitors). For each compound, we provide the General Amber Force Field parameters for the major species at physiological pH, together with an analysis of properties of interest as extracted from µs-long molecular dynamics simulations in explicit water solution. The properties include number and population of structural clusters, molecular flexibility, hydrophobic and hydrophilic molecular surfaces, the statistics of intraand inter-molecular H-bonds, as well as structural and dynamical properties of solvent molecules within first and second solvation shells. In addition, the database contains several key molecular parameters, such as energy of the frontier molecular orbitals, vibrational properties, rotational constants, atomic partial charges and electric dipole moment, computed by Density Functional Theory. The present database (to our knowledge the first extensive one including dynamical properties) is part of a wider project aiming to build-up a database containing structural, physico-chemical and dynamical properties of medicinal compounds using different force-field parameters with increasing level of complexity and reliability. The database is freely accessible at http://www.dsf.unica.it/translocation/db/.