The interactions and recognition of cyclic peptide mimetics of Tat with HIV-1 TAR RNA: a molecular dynamics simulation study

RNA's Dynamic Conformational Selection and Entropic Allosteric Mechanism in Controlling Cascade Protein Binding Events

In the TAR RNA of immunodeficiency viruses, an allosteric communication exists between a distant loop and a bulge. The bulge interacts with the TAT protein vital for transactivating viral RNA, while the loop interacts with cyclin-T1, contingent on TAT binding. Through extensive atomistic and free energy simulations, we investigate TAR-TAT binding in nonpathogenic bovine immunodeficiency virus (BIV) and pathogenic human immunodeficiency virus (HIV). Thermodynamic analysis reveals enthalpically driven binding in BIV and entropically favored binding in HIV. The broader global basin in HIV is attributed to binding-induced loop fluctuation, corroborated by nuclear magnetic resonance (NMR), indicating classical entropic allostery onset. While this loop fluctuation affects the TAT binding affinity, it generates a binding-competent conformation that aids subsequent effector (cyclin-T1) binding. This study underscores how two structurally similar apo-RNA scaffolds adopt distinct conformational selection mechanisms to drive enthalpic and entropic allostery, influencing protein affinity in the signaling cascade.

Structural and computational studies of HIV-1 RNA

Viruses remain a global threat to animals, plants, and humans. The type 1 human immunodeficiency virus (HIV-1) is a member of the retrovirus family and carries an RNA genome, which is reverse transcribed into viral DNA and further integrated into the host-cell DNA for viral replication and proliferation. The RNA structures from the HIV-1 genome provide valuable insights into the mechanisms underlying the viral replication cycle. Moreover, these structures serve as models for designing novel therapeutic approaches. Here, we review structural data on RNA from the HIV-1 genome as well as computational studies based on these structural data. The review is organized according to the type of structured RNA element which contributes to different steps in the viral replication cycle. This is followed by an overview of the HIV-1 transactivation response element (TAR) RNA as a model system for understanding dynamics and interactions in the viral RNA systems. The review concludes with a description of computational studies, highlighting the impact of biomolecular simulations in elucidating the mechanistic details of various steps in the HIV-1's replication cycle.

Leveraging QM/MM and Molecular Dynamics Simulations to Decipher the Reaction Mechanism of the Cas9 HNH Domain to Investigate Off-Target Effects

The clustered regularly interspaced short palindromic repeats (CRISPR) technology is an RNA-guided targeted genome-editing tool using Cas family proteins. Two magnesium-dependent nuclease domains of the Cas9 enzyme, termed HNH and RuvC, are responsible for cleaving the target DNA (t-DNA) and nontarget DNA strands, respectively. The HNH domain is believed to determine the DNA cleavage activity of both endonuclease domains and is sensitive to complementary RNA-DNA base pairing. However, the underlying molecular mechanisms of CRISPR-Cas9, by which it rebukes or accepts mismatches, are poorly understood. Thus, investigation of the structure and dynamics of the catalytic state of Cas9 with either matched or mismatched t-DNA can provide insights into improving its specificity by reducing off-target cleavages. Here, we focus on a recently discovered catalytic-active form of the Streptococcus pyogenes Cas9 (SpCas9) and employ classical molecular dynamics and coupled quantum mechanics/molecular mechanics simulations to study two possible mechanisms of t-DNA cleavage reaction catalyzed by the HNH domain. Moreover, by designing a mismatched t-DNA structure called MM5 (C to G at the fifth position from the protospacer adjacent motif region), the impact of single-guide RNA (sgRNA) and t-DNA complementarity on the catalysis process was investigated. Based on these simulations, our calculated binding affinities, minimum energy paths, and analysis of catalytically important residues provide atomic-level details of the differences between matched and mismatched cleavage reactions. In addition, several residues exhibit significant differences in their catalytic roles for the two studied systems, including K253, K263, R820, K896, and K913.

RNA-Binding Macrocyclic Peptides

Being able to effectively target RNA with potent ligands will open up a large number of potential therapeutic options. The knowledge on how to achieve this is ever expanding but an important question that remains open is what chemical matter is suitable to achieve this goal. The high flexibility of an RNA as well as its more limited chemical diversity and featureless binding sites can be difficult to target selectively but can be addressed by well-designed cyclic peptides. In this review we will provide an overview of reported cyclic peptide ligands for therapeutically relevant RNA targets and discuss the methods used to discover them. We will also provide critical insights into the properties required for potent and selective interaction and suggestions on how to assess these parameters. The use of cyclic peptides to target RNA is still in its infancy but the lessons learned from past examples can be adopted for the development of novel potent and selective ligands.

Impact of Remdesivir Incorporation along the Primer Strand on SARS-CoV-2 RNA-Dependent RNA Polymerase

Remdesivir was the first antiviral drug that received emergency use authorization from the United States Food and Drug Administration and is now formally approved to treat COVID-19. Remdesivir is a nucleotide analogue that targets the RNA-dependent RNA polymerase (RdRp) of coronaviruses, including SARS-CoV-2. The solution of multiple RdRp structures has been one of the main axes of research in the race against the SARS-CoV-2 virus. Several hypotheses of the mechanism of inhibition of RdRp by remdesivir have been proposed, although open questions remain. This work uses molecular dynamics simulations to explore the impact of remdesivir and two analogues as incoming nucleotides and of up to four incorporations of remdesivir along the primer strand on RdRp. The simulation results suggest that the overall structure and the dynamical behavior of RdRp are destabilized by remdesivir and the two analogues in the incoming position. The incorporation of remdesivir along the primer strand impacts specific non-bonded interactions between the nascent RNA and the polymerase subunit, as well as the overall dynamical networks on RdRp. The strongest impact on the structure and dynamics are observed after three incorporations, when remdesivir is located at position -A3, in agreement with previously reported experimental and computational results. Our results provide atomic-level details of the role played by remdesivir on the disruption of RNA synthesis by RdRp and the main drivers of these disruptions.

Role of salt-bridging interactions in recognition of viral RNA by arginine-rich peptides

Interactions between RNA molecules and proteins are critical to many cellular processes and are implicated in various diseases. The RNA-peptide complexes are good model systems to probe the recognition mechanism of RNA by proteins. In this work, we report studies on the binding-unbinding process of a helical peptide from a viral RNA element using nonequilibrium molecular dynamics simulations. We explored the existence of various dissociation pathways with distinct free-energy profiles that reveal metastable states and distinct barriers to peptide dissociation. We also report the free-energy differences for each of the four pathways to be 96.47 ± 12.63, 96.1 ± 10.95, 91.83 ± 9.81, and 92 ± 11.32 kcal/mol. Based on the free-energy analysis, we further propose the preferred pathway and the mechanism of peptide dissociation. The preferred pathway is characterized by the formation of sequential hydrogen-bonding and salt-bridging interactions between several key arginine amino acids and the viral RNA nucleotides. Specifically, we identified one arginine amino acid (R8) of the peptide to play a significant role in the recognition mechanism of the peptide by the viral RNA molecule.

Conformational dynamics and energetics of viral RNA recognition by lab-evolved proteins

The conserved and structured elements in viral RNA genomes interact with proteins to regulate various events in the viral life cycle and have become key targets for developing novel therapeutic approaches. We probe physical interactions between lab-evolved proteins and a viral RNA element from the HIV-1 genome. Specifically, we study the role of an arginine-rich loop in recognition of designed proteins by the viral RNA element. We report free energy calculations to quantitatively estimate the protein/RNA binding energetics, focusing on the mutations of arginine residues involved in recognition of the major groove of RNA by proteins.

Equally Weighted Multiscale Elastic Network Model and Its Comparison with Traditional and Parameter-Free Models

Dynamical properties of proteins play an essential role in their function exertion. The elastic network model (ENM) is an effective and efficient tool in characterizing the intrinsic dynamical properties encoded in biomacromolecule structures. The Gaussian network model (GNM) and anisotropic network model (ANM) are the two often-used ENM models. Here, we introduce an equally weighted multiscale ENM (equally weighted mENM) based on the original mENM (denoted as mENM), in which fitting weights of Kirchhoff/Hessian matrixes in mENM are removed since they neglect the details of pairwise interactions. Then, we perform its comparison with the mENM, traditional ENM, and parameter-free ENM (pfENM) in reproducing dynamical properties for the six representative proteins whose molecular dynamics (MD) trajectories are available in http://mmb.pcb.ub.es/MoDEL/. In the results, for B-factor prediction, mENM performs best, while the equally weighted mENM performs also well, better than the traditional ENM and pfENM models. As to the dynamical cross-correlation map calculation, mENM performs worst, while the results produced from the equally weighted mENM and pfENM models are close to those from MD trajectories with the latter a little better than the former. Furthermore, encouragingly, the equally weighted mANM displays the best performance in capturing the functional motional modes, followed by pfANM and traditional ANM models, while the mANM fails in all the cases. This work is helpful for strengthening the understanding of the elastic network model and provides a valuable guide for researchers to utilize the model to explore protein dynamics.

A positive, growth-based PAM screen identifies noncanonical motifs recognized by the S. pyogenes Cas9

CRISPR technologies have overwhelmingly relied on the Streptococcus pyogenes Cas9 (SpyCas9), with its consensus NGG and less preferred NAG and NGA protospacer-adjacent motifs (PAMs). Here, we report that SpyCas9 also recognizes sequences within an N(A/C/T)GG motif. These sequences were identified on the basis of preferential enrichment in a growth-based screen in Escherichia coli. DNA binding, cleavage, and editing assays in bacteria and human cells validated recognition, with activities paralleling those for NAG(A/C/T) PAMs and dependent on the first two PAM positions. Molecular-dynamics simulations and plasmid-clearance assays with mismatch-intolerant variants supported induced-fit recognition of an extended PAM by SpyCas9 rather than recognition of NGG with a bulged R-loop. Last, the editing location for SpyCas9-derived base editors could be shifted by one nucleotide by selecting between (C/T)GG and adjacent N(C/T)GG PAMs. SpyCas9 and its enhanced variants thus recognize a larger repertoire of PAMs, with implications for precise editing, off-target predictions, and CRISPR-based immunity.

Structural and functional insights into the bona fide catalytic state of Streptococcus pyogenes Cas9 HNH nuclease domain

The CRISPR-associated endonuclease Cas9 from Streptococcus pyogenes (SpyCas9), along with a programmable single-guide RNA (sgRNA), has been exploited as a significant genome-editing tool. Despite the recent advances in determining the SpyCas9 structures and DNA cleavage mechanism, the cleavage-competent conformation of the catalytic HNH nuclease domain of SpyCas9 remains largely elusive and debatable. By integrating computational and experimental approaches, we unveiled and validated the activated Cas9-sgRNA-DNA ternary complex in which the HNH domain is neatly poised for cleaving the target DNA strand. In this catalysis model, the HNH employs the catalytic triad of D839-H840-N863 for cleavage catalysis, rather than previously implicated D839-H840-D861, D837-D839-H840, or D839-H840-D861-N863. Our study contributes critical information to defining the catalytic conformation of the HNH domain and advances the knowledge about the conformational activation underlying Cas9-mediated DNA cleavage.

Assessing the Performance of the Nonbonded Mg2+ Models in a Two-Metal-Dependent Ribonuclease

Magnesium ions (Mg²⁺), abundant in living cells, are essential for biomolecular structure, dynamics, and function. The biological importance of Mg²⁺ has motivated continuous development and improvement of various Mg²⁺ models for molecular dynamics (MD) simulations during the last decades. There are four types of nonbonded Mg²⁺ models: the point charge models based on a 12-6 or 12-6-4 type Lennard-Jones (LJ) potential, and the multisite models based on a 12-6 or 12-6-4 LJ potential. Here, we systematically assessed the performance of these four types of nonbonded Mg²⁺ models (21 models in total) in terms of maintaining a challenging intermediate state configuration captured in the structure of a prototypical two-metal-ion RNase H complex with an RNA/DNA hybrid. Our data demonstrate that the 12-6-4 multisite models, which account for charge-induced dipole interactions, perform the best in reproducing all the unique coordination modes in this intermediate state and maintaining the correct carboxylate denticity. Our benchmark work provides a useful guideline for MD simulations and structural refinement of Mg²⁺-containing biomolecular systems.

Identification of a unique Ca2+-binding site in rat acid-sensing ion channel 3

Acid-sensing ion channels (ASICs) evolved to sense changes in extracellular acidity with the divalent cation calcium (Ca²⁺) as an allosteric modulator and channel blocker. The channel-blocking activity is most apparent in ASIC3, as removing Ca²⁺ results in channel opening, with the site's location remaining unresolved. Here we show that a ring of rat ASIC3 (rASIC3) glutamates (Glu435), located above the channel gate, modulates proton sensitivity and contributes to the formation of the elusive Ca²⁺ block site. Mutation of this residue to glycine, the equivalent residue in chicken ASIC1, diminished the rASIC3 Ca²⁺ block effect. Atomistic molecular dynamic simulations corroborate the involvement of this acidic residue in forming a high-affinity Ca²⁺ site atop the channel pore. Furthermore, the reported observations provide clarity for past controversies regarding ASIC channel gating. Our findings enhance understanding of ASIC gating mechanisms and provide structural and energetic insights into this unique calcium-binding site.

RNA Structural Dynamics As Captured by Molecular Simulations: A Comprehensive Overview

With both catalytic and genetic functions, ribonucleic acid (RNA) is perhaps the most pluripotent chemical species in molecular biology, and its functions are intimately linked to its structure and dynamics. Computer simulations, and in particular atomistic molecular dynamics (MD), allow structural dynamics of biomolecular systems to be investigated with unprecedented temporal and spatial resolution. We here provide a comprehensive overview of the fast-developing field of MD simulations of RNA molecules. We begin with an in-depth, evaluatory coverage of the most fundamental methodological challenges that set the basis for the future development of the field, in particular, the current developments and inherent physical limitations of the atomistic force fields and the recent advances in a broad spectrum of enhanced sampling methods. We also survey the closely related field of coarse-grained modeling of RNA systems. After dealing with the methodological aspects, we provide an exhaustive overview of the available RNA simulation literature, ranging from studies of the smallest RNA oligonucleotides to investigations of the entire ribosome. Our review encompasses tetranucleotides, tetraloops, a number of small RNA motifs, A-helix RNA, kissing-loop complexes, the TAR RNA element, the decoding center and other important regions of the ribosome, as well as assorted others systems. Extended sections are devoted to RNA-ion interactions, ribozymes, riboswitches, and protein/RNA complexes. Our overview is written for as broad of an audience as possible, aiming to provide a much-needed interdisciplinary bridge between computation and experiment, together with a perspective on the future of the field.

Molecular dynamics and MM/GBSA-integrated protocol probing the correlation between biological activities and binding free energies of HIV-1 TAR RNA inhibitors

The interaction of HIV-1 transactivator protein Tat with its cognate transactivation response (TAR) RNA has emerged as a promising target for developing antiviral compounds and treating HIV infection, since it is a crucial step for efficient transcription and replication. In the present study, molecular dynamics (MD) simulations and MM/GBSA calculations have been performed on a series of neamine derivatives in order to estimate appropriate MD simulation time for acceptable correlation between ΔG_bind and experimental pIC₅₀ values. Initially, all inhibitors were docked into the active site of HIV-1 TAR RNA. Later to explore various conformations and examine the docking results, MD simulations were carried out. Finally, binding free energies were calculated using MM/GBSA method and were correlated with experimental pIC₅₀ values at different time scales (0-1 to 0-10 ns). From this study, it is clear that in case of neamine derivatives as simulation time increased the correlation between binding free energy and experimental pIC₅₀ values increased correspondingly. Therefore, the binding energies which can be interpreted at longer simulation times can be used to predict the bioactivity of new neamine derivatives. Moreover, in this work, we have identified some plausible critical nucleotide interactions with neamine derivatives that are responsible for potent inhibitory activity. Furthermore, we also provide some insights into a new class of oxadiazole-based back bone cyclic peptides designed by incorporating the structural features of neamine derivatives. On the whole, this approach can provide a valuable guidance for designing new potent inhibitors and modify the existing compounds targeting HIV-1 TAR RNA.

Simulation study of the ability of a computationally-designed peptide to recognize target tRNALys3 and other decoy tRNAs

In this paper, we investigate the ability of our computationally-designed peptide, Pept10 (PNWNGNRWLNNCLRG), to recognize the anticodon stem and loop (ASL) domain of the hypermodified tRNA^Lys3 (mcm⁵ s² U₃₄ ,ms² t⁶ A₃₇ ), a reverse transcription primer of HIV replication. Five other ASLs, the singly modified ASL^Lys3 (ms² t⁶ A₃₇ ), ASL^Lys3 (s² U₃₄ ), ASL^Lys3 (Ψ₃₉ ), ASL^Lys1,2 (t⁶ A₃₇ ), and ASL^Glu (s² U₃₄ ), were used as decoys. Explicit-solvent atomistic molecular dynamics simulations were performed to examine the process of binding of Pept10 with the target ASL^Lys3 (mcm⁵ s² U₃₄ ,ms² t⁶ A₃₇ ) and the decoy ASLs. Simulation results demonstrated that Pept10 is capable of recognizing the target ASL^Lys3 (mcm⁵ s² U₃₄ ,ms² t⁶ A₃₇ ) as well as one of the decoys, ASL^Lys3 (Ψ₃₉ ), but screens out the other four decoy ASLs. The interchain van der Waals (VDW) and charge-charge (ELE + EGB) energies for the two best complexes were evaluated to shed light on the molecular recognition mechanism between Pept10 and ASLs. The results indicated that Pept10 recognizes and binds to the target ASL^Lys3 (mcm⁵ s² U₃₄ ,ms² t⁶ A₃₇ ) through residues W₃ and R₇ which interact with the nucleotides mcm⁵ s² U₃₄ , U₃₅ , and ms² t⁶ A₃₇ via the interchain VDW energy. Pept10 also recognizes the decoy ASL^Lys3 (Ψ₃₉ ) through residue R₁₄ which contacts the nucleotide U₃₆ via the interchain VDW energy. Regardless of the type of ASL, the positively charged arginines on Pept10 are attracted to the negatively charged phosphate linkages on the ASL via the interchain ELE + EGB energy, thereby enhancing the binding affinity.

Insights into the Inhibitory Mechanism of D13-9001 to the Multidrug Transporter AcrB through Molecular Dynamics Simulations

The resistance-nodulation-cell division transporter AcrB is responsible for energy transduction and substrate recognition in the tripartite AcrAB-TolC efflux system in Escherichia coli. Despite a broad substrate specificity, only a few compounds have been cocrystallized with AcrB inside the distal binding pocket (DBP), including doxorubicin (DOX) and D13-9001. D13-9001 is a promising efflux pump inhibitor that potentiates the efficacy of a wide variety of antibiotics. To understand its inhibition effect under the framework of functional rotating mechanism, we performed targeted and steered molecular dynamics simulations to compare the binding and extrusion processes of this inhibitor and the substrate DOX in AcrB. The results demonstrate that, with respect to DOX, the interaction of D13-9001 with the hydrophobic trap results in delayed disassociation from the DBP. Notably, the detachment of D13-9001 is tightly correlated with the side-chain reorientation of Phe628 and large-scale displacement of Tyr327. Furthermore, the inhibitor induces much more significant conformational changes at the exit gate than DOX does, thereby causing higher energy cost for extrusion and contributing to the inhibitory effect in addition to the tight binding at DBP.

Molecular recognition mechanism of peptide chain bound to the tRNA(Lys3) anticodon loop in silico

The mechanism by which proteins recognize and bind the post-transcriptional modifications of RNAs is unknown, yet these interactions play important functions in biology. Atomistic molecular dynamics simulations were performed to examine the folding of the model peptide chain -RVTHHAFLGAHRTVG- and the complex formed by the folded peptide with the native anticodon stem and loop of the human tRNA(Lys3) (hASL(Lys3)) in order to explore the binding mechanism. By analyzing and comparing two folded conformations of this peptide obtained from the folding simulation, we found that the van der Waals (VDW) energy is necessary for the thermal stability of the peptide, and the charge-charge (ELE + EGB) energy is crucial for determining the three-dimensional folded structure of the peptide backbone. Subsequently, two conformations of the peptide were employed to investigate their binding behaviors to hASL(Lys3). The metastable folded peptide was found to bind to hASL(Lys3) much easier than the stable folded peptide in the binding simulations. An energetic analysis reveals that the VDW energy favors the binding, whereas the ELE + EGB energies disfavor the binding. Arginines on the peptide preferentially attract the phosphate backbone via the inter-chain ELE + EGB interaction, significantly contributing to the binding affinity. The hydrophobic phenylalanine interacts with the anticodon loop of hASL(Lys3) via the inter-chain VDW interaction, significantly contributing to the binding specificity.