Assessing RNA atomistic force fields via energy landscape explorations in implicit solvent.

Predicting the structure and dynamics of RNA molecules still proves challenging because of the relative scarcity of experimental RNA structures on which to train models and the very sensitive nature of RNA towards its environment. In the last decade, several atomistic force fields specifically designed for RNA have been proposed and are commonly used for simulations. However, it is not necessarily clear which force field is the most suitable for a given RNA molecule. In this contribution, we propose the use of the computational energy landscape framework to explore the energy landscape of RNA systems as it can bring complementary information to the more standard approaches of enhanced sampling simulations based on molecular dynamics. We apply the EL framework to the study of a small RNA pseudoknot, the Aquifex aeolicus tmRNA pseudoknot PK1, and we compare the results of five different RNA force fields currently available in the AMBER simulation software, in implicit solvent. With this computational approach, we can not only compare the predicted 'native' states for the different force fields, but the method enables us to study metastable states as well. As a result, our comparison not only looks at structural features of low energy folded structures, but provides insight into folding pathways and higher energy excited states, opening to the possibility of assessing the validity of force fields also based on kinetics and experiments providing information on metastable and unfolded states. Supplementary Information: The online version contains supplementary material available at 10.1007/s12551-024-01202-9.

Energy Landscapes and Structural Ensembles of Glucagon-like Peptide-1 Monomers.

While GLP-1 and its analogues are important pharmaceutical agents in the treatment of type 2 diabetes and obesity, their susceptibility to aggregate into amyloid fibrils poses a significant safety issue. Many factors may contribute to the aggregation propensity, including pH. While it is known that the monomeric structure of GLP-1 has a strong impact on primary nucleation, probing its diverse structural ensemble is challenging. Here, we investigated the monomer structural ensembles at pH 3, 4, and 7.5 using state-of-the-art computational methods in combination with experimental data. We found significant stabilization of ß-strand structures and destabilization of helical structures at lower pH, correlating with observed aggregation lag times, which are lower under these conditions. We further identified helical defects at pH 4, which led to the fastest observed aggregation, in agreement with our far-UV circular dichroism data. The detailed atomistic structures that result from the computational studies help to rationalize the experimental results on the aggregation propensity of GLP-1. This work provides a new insight into the pH-dependence of monomeric structural ensembles of GLP-1 and connects them to experimental observations.

The Effect of Pulling and Twisting Forces on Chameleon Sequence Peptides.

Chameleon sequences are amino acid sequences found in several distinct configurations in experiment. They challenge our understanding of the link between sequence and structure, and provide insight into structural competition in proteins. Here, we study the energy landscapes for three such sequences, and interrogate how pulling and twisting forces impact the available structural ensembles. Chameleon sequences do not necessarily exhibit multiple structural ensembles on a multifunnel energy landscape when we consider them in isolation. The application of even small forces leads to drastic changes in the energy landscapes. For pulling forces, we observe transitions from helical to extended structures in a very small span of forces. For twisting forces, the picture is much more complex, and highly dependent on the magnitude and handedness of the applied force as well as the reference angle for the twist. Depending on these parameters, more complex and more simplistic energy landscapes are observed alongside more and less diverse structural ensembles. The impact of even small forces is significant, confirming their likely role in folding events. In addition, small forces exerted by the remaining scaffold of a protein may be sufficient to lead to the adoption of a specific structural ensemble by a chameleon sequence.

Triplet-Encoded Prebiotic RNA Aminoacylation.

The encoding step of translation involves attachment of amino acids to cognate tRNAs by aminoacyl-tRNA synthetases, themselves the product of coded peptide synthesis. So, the question arises─before these enzymes evolved, how were primordial tRNAs selectively aminoacylated? Here, we demonstrate enzyme-free, sequence-dependent, chemoselective aminoacylation of RNA. We investigated two potentially prebiotic routes to aminoacyl-tRNA acceptor stem-overhang mimics and analyzed those oligonucleotides undergoing the most efficient aminoacylation. Overhang sequences do not significantly influence the chemoselectivity of aminoacylation by either route. For aminoacyl-transfer from a mixed anhydride donor strand, the chemoselectivity and stereoselectivity of aminoacylation depend on the terminal three base pairs of the stem. The results support early suggestions of a second genetic code in the acceptor stem.

Chemical bonds in collagen rupture selectively under tensile stress.

Collagen fibres are the main constituent of the extracellular matrix, and fulfil an important role in the structural stability of living multicellular organisms. An open question is how collagen absorbs pulling forces, and if the applied forces are strong enough to break bonds, what mechanisms underlie this process. As experimental studies on this topic are challenging, simulations are an important tool to further our understanding of these mechanisms. Here, we present pulling simulations of collagen triple helices, revealing the molecular mechanisms induced by tensile stress. At lower forces, pulling alters the configuration of proline residues leading to an effective absorption of applied stress. When forces are strong enough to introduce bond ruptures, these are located preferentially in X-position residues. Reduced backbone flexibility, for example through mutations or cross linking, weakens tensile resistance, leading to localised ruptures around these perturbations. In fibre-like segments, a significant overrepresentation of ruptures in proline residues compared to amino acid contents is observed. This study confirms the important role of proline in the structural stability of collagen, and adds detailed insight into the molecular mechanisms underlying this observation.

Investigating the structural changes due to adenosine methylation of the Kaposi's sarcoma-associated herpes virus ORF50 transcript.

Kaposi's sarcoma-associated herpes virus (KSHV) is a human oncovirus. KSHV relies on manipulating the host cell N6-methyl adenosine (m6A) RNA modification pathway to enhance virus replication. Methylation within a RNA stem loop of the open reading frame 50 (ORF50) increases transcript stability via the recruitment of the m6A reader, SND1. In this contribution we explore the energy landscapes of the unmethylated and methylated RNA stem loops of ORF50 to investigate the effect of methylation on the structure of the stem loop. We observe a significant shift upon methylation between an open and closed configuration of the top of the stem loop. In the unmethylated stem loop the closed configuration is much lower in energy, and, as a result, exhibits higher occupancy.

The Energy Landscape Perspective: Encoding Structure and Function for Biomolecules.

The energy landscape perspective is outlined with particular reference to biomolecules that perform multiple functions. We associate these multifunctional molecules with multifunnel energy landscapes, illustrated by some selected examples, where understanding the organisation of the landscape has provided new insight into function. Conformational selection and induced fit may provide alternative routes to realisation of multifunctionality, exploiting the possibility of environmental control and distinct binding modes.

Computer-aided comprehensive explorations of RNA structural polymorphism through complementary simulation methods.

While RNA folding was originally seen as a simple problem to solve, it has been shown that the promiscuous interactions of the nucleobases result in structural polymorphism, with several competing structures generally observed for non-coding RNA. This inherent complexity limits our understanding of these molecules from experiments alone, and computational methods are commonly used to study RNA. Here, we discuss three advanced sampling schemes, namely Hamiltonian-replica exchange molecular dynamics (MD), ratchet-and-pawl MD and discrete path sampling, as well as the HiRE-RNA coarse-graining scheme, and highlight how these approaches are complementary with reference to recent case studies. While all computational methods have their shortcomings, the plurality of simulation methods leads to a better understanding of experimental findings and can inform and guide experimental work on RNA polymorphism.

The effects of glycine to alanine mutations on the structure of GPO collagen model peptides.

Collagen proteins are the main constituents of the extracellular matrix (ECM), and fulfil a number of wide-ranging functions, including contributions to the mechanical and biological behaviour of the ECM. Due to the heterogeneous nature of collagen in tissue samples it is difficult to fully explain the experimental observation, and hence the study of shorter model peptides is common place. Here, the computational energy landscape framework is employed to study Gly to Ala mutations in a GPO model peptide. The results show good agreement with the experimental observations for the GPO reference and a triply mutated peptide, demonstrating the validity of the approach. The modelling predicts that changes in structure are moderate and localised, with an increased dynamic in the backbone and alterations to the hydrogen bonding pattern. Two mechanisms for adjusting to the mutations are observed, with potential consequences regarding protein binding. Finally, in line with a hypothesis that proline puckering allows controlled flexibility (Chow et al., Sci. Rep., 2018, 8, 13809), alterations in the puckering preferences are observed in the strained residues surrounding the mutational sites.

RNA Modeling with the Computational Energy Landscape Framework.

The recent advances in computational abilities, such as the enormous speed-ups provided by GPU computing, allow for large scale computational studies of RNA molecules at an atomic level of detail. As RNA molecules are known to adopt multiple conformations with comparable energies, but different two-dimensional structures, all-atom models are necessary to better describe the structural ensembles for RNA molecules. This point is important because different conformations can exhibit different functions, and their regulation or mis-regulation is linked to a number of diseases. Problematically, the energy barriers between different conformational ensembles are high, resulting in long time scales for interensemble transitions. The computational potential energy landscape framework was designed to overcome this problem of broken ergodicity by use of geometry optimization. Here, we describe the algorithms used in the energy landscape explorations with the OPTIM and PATHSAMPLE programs, and how they are used in biomolecular simulations. We present a recent case study of the 5'-hairpin of RNA 7SK to illustrate how the method can be applied to interpret experimental results, and to obtain a detailed description of molecular properties.

Is the H4 histone tail intrinsically disordered or intrinsically multifunctional?

The structural versatility of histone tails is one of the key elements in the organisation of chromatin, which allows for the compact storage of genomic information. However, this structural diversity also complicates experimental and computational studies. Here, the potential and free energy landscape for the isolated and bound H4 histone tail are explored. The landscapes exhibit a set of distinct structural ensembles separated by high energy barriers, with little difference between isolated and bound tails. This consistency is a desirable feature that facilitates the formation of transient interactions, which are required for the liquid-like chromatin organisation. The existence of multiple, distinct structures on a multifunnel energy landscape is likely to be associated with multifunctionality, i.e. a set of evolved, distinct functions. Contrasting it with previously reported results for other disordered peptides, this type of landscape may be associated with a conformational selection based binding mechanism. Given the similarity to other systems exhibiting similar multifunnel energy landscapes, the disorder in histone tails might be better described in context of multifunctionality.

Energy Landscapes of Deoxyxylo- and Xylo-Nucleic Acid Octamers.

Artificial analogues of the natural nucleic acids have attracted interest as a diverse class of information storage molecules capable of self-replication. In this study, we use the computational potential energy landscape framework to investigate the structural and dynamical properties of xylo- and deoxyxylo-nucleic acids (XyNA and dXyNA), which are derived from their respective RNA and DNA analogues by inversion of a single chiral center in the sugar moiety of the nucleotides. For an octameric XyNA sequence and the analogue dXyNA, we observe facile conformational transitions between a left-handed helix, which is the free energy global minimum, and a ladder-type structure with approximately zero helicity. The competing ensembles are better separated in the dXyNA, making it a more suitable candidate for a molecular switch, whereas the XyNA exhibits additional flexibility. Both energy landscapes exhibit greater frustration than we observe in RNA or DNA, in agreement with the higher degree of optimization expected from the principle of minimal frustration in evolved biomolecules.

Affinity-Selected Bicyclic Peptide G-Quadruplex Ligands Mimic a Protein-like Binding Mechanism.

The study of G-quadruplexes (G4s) in a cellular context has demonstrated links between these nucleic acid secondary structures, gene expression, and DNA replication. Ligands that bind to the G4 structure therefore present an excellent opportunity for influencing gene expression through the targeting of a nucleic acid structure rather than sequence. Here, we explore cyclic peptides as an alternative class of G4 ligands. Specifically, we describe the development of de novo G4-binding bicyclic peptides selected by phage display. Selected bicyclic peptides display submicromolar affinity to G4 structures and high selectivity over double helix DNA. Molecular simulations of the bicyclic peptide-G4 complexes corroborate the experimental binding strengths and reveal molecular insights into G4 recognition by bicyclic peptides via the precise positioning of amino acid side chains, a binding mechanism reminiscent of endogenous G4-binding proteins. Overall, our results demonstrate that selection of (bi)cyclic peptides unlocks a valuable chemical space for targeting nucleic acid structures.

Structural transitions in the RNA 7SK 5' hairpin and their effect on HEXIM binding.

7SK RNA, as part of the 7SK ribonucleoprotein complex, is crucial to the regulation of transcription by RNA-polymerase II, via its interaction with the positive transcription elongation factor P-TEFb. The interaction is induced by binding of the protein HEXIM to the 5' hairpin (HP1) of 7SK RNA. Four distinct structural models have been obtained experimentally for HP1. Here, we employ computational methods to investigate the relative stability of these structures, transitions between them, and the effects of mutations on the observed structural ensembles. We further analyse the results with respect to mutational binding assays, and hypothesize a mechanism for HEXIM binding. Our results indicate that the dominant structure in the wild type exhibits a triplet involving the unpaired nucleotide U40 and the base pair A43-U66 in the GAUC/GAUC repeat. This conformation leads to an open major groove with enough potential binding sites for peptide recognition. Sequence mutations of the RNA change the relative stability of the different structural ensembles. Binding affinity is consequently lost if these changes alter the dominant structure.

Mutational Basin-Hopping: Combined Structure and Sequence Optimization for Biomolecules.

The study of energy landscapes has led to a good understanding of how and why proteins and nucleic acids adopt their native structure. Through evolution, sequences have adapted until they exhibit a strongly funneled energy landscape, stabilizing the native fold. Design of artificial biomolecules faces the challenge of creating similar stable, minimally frustrated, and functional sequences. Here we present a biminimization approach, mutational basin-hopping, in which we simultaneously use global optimization to optimize the energy and a target function describing a desired property of the system. This optimization of structure and sequence is a generalized basin-hopping method and produces an efficient design process, which can target properties such as binding affinity or solubility.

Analysis of the Ub to Ub-CR Transition in Ubiquitin.

A new conformation has recently been reported for ubiquitin (Ub). This invisible conformation (Ub-CR), where the C-terminal tail is retracted, has a key functional role in phosphorylation of the Ser65 residue, a trigger for PINK1 and Parkin dependent mitophagy. Here we calculate the transition mechanism and associated rates for the Ub to Ub-CR pathway in the wild-type protein and a selection of mutants. We predict a cooperative one-step process with a transition state that resembles the Ub configuration, characterized by a loss of all interactions of the C-terminal tail with surrounding residues, and an open ubiquitin scaffold. The calculated observables agree well with reported values, and we make a range of predictions to guide future experiments. In particular, the effect of mutations on the pathway and the corresponding structural ensembles should have observable consequences. This feedback between theory and experiment promises new insight into key cellular processes.

Predicting Pathways between Distant Configurations for Biomolecules.

Many of the most interesting rearrangements associated with function and dysfunction of biomolecules involve complex, highly nonlinear pathways. Predicting these convoluted changes in structure is an important research challenge, since knowledge of key intermediate conformations at an atomic level of detail has the potential to inform the design of novel therapeutic strategies with enhanced specificity. The identification of kinetically relevant pathways can be strongly dependent on the construction of a physically relevant initial pathway between specified end points, avoiding artifacts such as chain crossings. In this contribution we describe an enhanced interpolation procedure to characterize initial pathways for complex rearrangements of a histone tail, α-helix to ß-sheet conversion for amyloid-ß17-42, and EGFR kinase activation. Complete connected initial pathways with relatively low overall barriers are obtained in each case using an enhanced quasi-continuous interpolation scheme. This approach will help to extend the complexity and time scales accessible to computer simulation.

Energy Landscapes of Mini-Dumbbell DNA Octanucleotides.

Single-stranded DNA structures play a significant role in biological systems, in particular during replication, translation, and DNA repair. Tracts of simple repetitive DNA are associated with slipped-strand mispairing, which can lead to genetic diseases. Recent NMR studies of TTTA and CCTG repeats have shown that these sequences form mini-dumbbells (MDBs), leading to frameshift mutations. Here we explore the energy landscapes of (CCTG)2 and (TTTA)2, which are currently the smallest known molecules to form MDBs. While (CCTG)2 MDBs are stable, (TTTA)2 exhibits numerous other structures with lower energies. A key factor identified in the stabilization of MDB structures is the bonding strength between residues 1 and 4, and 5 and 8.

Evolved Minimal Frustration in Multifunctional Biomolecules.

Protein folding is often viewed in terms of a funneled potential or free energy landscape. A variety of experiments now indicate the existence of multifunnel landscapes, associated with multifunctional biomolecules. Here, we present evidence that these systems have evolved to exhibit the minimal number of funnels required to fulfill their cellular functions, suggesting an extension to the principle of minimum frustration. We find that minimal disruptive mutations result in additional funnels, and the associated structural ensembles become more diverse. The same trends are observed in an atomic cluster. These observations suggest guidelines for rational design of engineered multifunctional biomolecules.

Energy Landscapes for the Aggregation of Aß17-42.

The aggregation of the Aß peptide (Aß1-42) to form fibrils is a key feature of Alzheimer's disease. The mechanism is thought to be a nucleation stage followed by an elongation process. The elongation stage involves the consecutive addition of monomers to one end of the growing fibril. The aggregation process proceeds in a stop-and-go fashion and may involve off-pathway aggregates, complicating experimental and computational studies. Here we present exploration of a well-defined region in the free and potential energy landscapes for the Aß17-42 pentamer. We find that the ideal aggregation process agrees with the previously reported dock-lock mechanism. We also analyze a large number of additional stable structures located on the multifunnel energy landscape, which constitute kinetic traps. The key contributors to the formation of such traps are misaligned strong interactions, for example the stacking of F19 and F20, as well as entropic contributions. Our results suggest that folding templates for aggregation are a necessity and that aggregation studies could employ such species to obtain a more detailed description of the process.