Molecular dynamic simulations of protein/RNA complexes: CRISPR/Csy4 endoribonuclease

RNA-protein complexes and force field polarizability

Molecular dynamic (MD) simulations offer a way to study biomolecular interactions and their dynamics at the atomistic level. There are only a few studies of RNA-protein complexes in MD simulations, and here we wanted to study how force fields differ when simulating RNA-protein complexes: 1) argonaute 2 with bound guide RNA and a target RNA, 2) CasPhi-2 bound to CRISPR RNA and 3) Retinoic acid-inducible gene I C268F variant in complex with double-stranded RNA. We tested three non-polarizable force fields: Amber protein force fields ff14SB and ff19SB with RNA force field OL3, and the all-atom OPLS4 force field. Due to the highly charged and polar nature of RNA, we also tested the polarizable AMOEBA force field and the ff19SB and OL3 force fields with a polarizable water model O3P. Our results show that the non-polarizable force fields lead to compact and stable complexes. The polarizability in the force field or in the water model allows significantly more movement from the complex, but in some cases, this results in the disintegration of the complex structure, especially if the protein contains longer loop regions. Thus, one should be cautious when running long-scale simulations with polarizability. As a conclusion, all the tested force fields can be used to simulate RNA-protein complexes and the choice of the optimal force field depends on the studied system and research question.

Insights into the Mechanism of CRISPR/Cas9-Based Genome Editing from Molecular Dynamics Simulations

The CRISPR/Cas9 system is a popular genome-editing tool with immense therapeutic potential. It is a simple two-component system (Cas9 protein and RNA) that recognizes the DNA sequence on the basis of RNA:DNA complementarity, and the Cas9 protein catalyzes the double-stranded break in the DNA. In the past decade, near-atomic resolution structures at various stages of the CRISPR/Cas9 DNA editing pathway have been reported along with numerous experimental and computational studies. Such studies have boosted knowledge of the genome-editing mechanism. Despite such advancements, the application of CRISPR/Cas9 in therapeutics is still limited, primarily due to off-target effects. Several studies aim at engineering high-fidelity Cas9 to minimize the off-target effects. Molecular Dynamics (MD) simulations have been an excellent complement to the experimental studies for investigating the mechanism of CRISPR/Cas9 editing in terms of structure, thermodynamics, and kinetics. MD-based studies have uncovered several important molecular aspects of Cas9, such as nucleotide binding, catalytic mechanism, and off-target effects. In this Review, the contribution of MD simulation to understand the CRISPR/Cas9 mechanism has been discussed, preceded by an overview of the history, mechanism, and structural aspects of the CRISPR/Cas9 system. These studies are important for the rational design of highly specific Cas9 and will also be extremely promising for achieving more accurate genome editing in the future.

Decrypting the mechanistic basis of CRISPR/Cas9 protein

CRISPR/Cas system, a newly but extensively investigated genome-editing method, harbors practical solutions for various genetic problems. It relies on short guide RNAs (gRNAs) to recruit the Cas9 protein, a DNA cleaving enzyme, to its genomic target DNAs. The Cas9 enzyme exhibits some unique properties, like the ability to differentiate self vs. non-self - DNA strands using the base-pairing potential of crRNA, i.e., only CRISPR DNA is entirely complementary to the CRISPR repeat sequences at the crRNA whereas the presence of mismatches in the upstream region of the spacer permit CRISPR interference which is inhibited in case of CRISPR-DNA, allosteric regulation in its domains, and domain reorientation on sgRNA binding. Several groups have contributed their efforts in understanding the functioning of the CRISPR/Cas system, but even then, there is a lot more to explore in this area. The structural and sequence-based understanding of the whole CRISPR-associated bacterial ortholog family landscape is still ambiguous. A better understanding of the underlying energetics of the CRISPR/Cas9 system should reveal critical parameters to design better CRISPR/Cas9s.

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.

Divalent-Metal-Ion Selectivity of the CRISPR-Cas System-Associated Cas1 Protein: Insights from Classical Molecular Dynamics Simulations and Electronic Structure Calculations

CRISPR-associated protein 1 (Cas1) is a universally conserved essential metalloenzyme of the clustered regularly interspaced short palindromic repeat (CRISPR) immune system of prokaryotes (bacteria, archaea) that can cut and integrate a part of viral DNA to its host genome with the help of other proteins. The integrated DNA acts as a memory of viral infection, which can be transcribed to RNA and stop future infection by recognition (based on the RNA/DNA complementarity principle) followed by protein-mediated degradation of the viral DNA. It has been proposed that the presence of a single manganese (Mn²⁺) ion in a conserved divalent-metal-ion binding pocket (key residues: E190, H254, D265, D268) of Cas1 is crucial for its function. Cas1-mediated DNA degradation was proposed to be hindered by metal substitution, metal chelation, or mutation of the binding pocket residues. Cas1 is active toward dsDNA degradation with both Mn²⁺ and Mg²⁺. X-ray structures of Cas1 revealed an intricate atomic interaction network of the divalent-metal-ion binding pocket and opened up the possibility of modeling related metal ions (viz., Mg²⁺, Ca²⁺) in the binding pocket of wild-type (WT) and mutated Cas1 proteins for computational analysis, which includes (1) quantitative estimation of the energetics of the divalent-metal-ion preference and (2) exploring the structural and dynamical aspects of the protein in response to divalent-metal-ion substitution or amino acid mutation. Using the X-ray structure of the Cas1 protein from Pseudomonas aeruginosa as a template (PDB 3GOD), we performed (∼2.23 μs) classical molecular dynamics (MD) simulations to compare structural and dynamical differences between Mg²⁺- and Ca²⁺-bound binding pockets of wild-type (WT) and mutant (E190A, H254A, D265A, D268A) Cas1. Furthermore, reduced binding pocket models were generated from X-ray and molecular dynamics (MD) trajectories, and the resulting structures were subjected to quantum chemical calculations. Results suggest that Cas1 prefers Mg²⁺ binding relative to Ca²⁺ and the preference is the strongest for WT and the weakest for the D268A mutant. Quantum chemical calculations indicate that Mn²⁺ is the most preferred relative to both Mg²⁺ and Ca²⁺ in the wild-type and mutant Cas1. Substitution of Mg²⁺ by Ca²⁺ does not alter the interaction network between Cas1 and the divalent metal ion but increases the wetness of the binding pocket by introducing a single water molecule in the first coordination shell of the latter. The strength of metal-ion preference (Mg²⁺ versus Ca²⁺) seems to be dependent on the solvent accessibility of the divalent-metal-ion binding pocket, strongest for wild-type Cas1 (in which the metal-ion binding pocket is dry, which includes two water molecules) and the weakest for the D268A mutant (in which the metal-ion binding pocket is wet, which includes four water molecules).

Recent Advances in Machine Learning Based Prediction of RNA-protein Interactions

The interactions between RNAs and proteins play critical roles in many biological processes. Therefore, characterizing these interactions becomes critical for mechanistic, biomedical, and clinical studies. Many experimental methods can be used to determine RNA-protein interactions in multiple aspects. However, due to the facts that RNA-protein interactions are tissuespecific and condition-specific, as well as these interactions are weak and frequently compete with each other, those experimental techniques can not be made full use of to discover the complete spectrum of RNA-protein interactions. To moderate these issues, continuous efforts have been devoted to developing high quality computational techniques to study the interactions between RNAs and proteins. Many important progresses have been achieved with the application of novel techniques and strategies, such as machine learning techniques. Especially, with the development and application of CLIP techniques, more and more experimental data on RNA-protein interaction under specific biological conditions are available. These CLIP data altogether provide a rich source for developing advanced machine learning predictors. In this review, recent progresses on computational predictors for RNA-protein interaction were summarized in the following aspects: dataset, prediction strategies, and input features. Possible future developments were also discussed at the end of the review.

Atomistic Analysis of ToxN and ToxI Complex Unbinding Mechanism

ToxIN is a triangular structure formed by three protein toxins (ToxNs) and three specific noncoding RNA antitoxins (ToxIs). To respond to stimuli, ToxI is preferentially degraded, releasing the ToxN. Thus, the dynamic character is essential in the normal function interactions between ToxN and ToxI. Here, equilibrated molecular dynamics (MD) simulations were performed to study the stability of ToxN and ToxI. The results indicate that ToxI adjusts the conformation of 3' and 5' termini to bind to ToxN. Steered molecular dynamics (SMD) simulations combined with the recently developed thermodynamic integration in 3nD (TI3nD) method were carried out to investigate ToxN unbinding from the ToxIN complex. The potentials of mean force (PMFs) and atomistic pictures suggest the unbinding mechanism as follows: (1) dissociation of the 5' terminus from ToxN, (2) missing the interactions involved in the 3' terminus of ToxI without three nucleotides (G31, A32, and A33), (3) starting to unfold for ToxI, (4) leaving the binding package of ToxN for three nucleotides of ToxI, (5) unfolding of ToxI. This work provides information on the structure-function relationship at the atomistic level, which is helpful for designing new potent antibacterial drugs in the future.

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.

Biomolecular engineering of biocatalysts hydrolyzing neurotoxic organophosphates

Novel methods of molecular modeling help solving urgent problems in drug design, directed evolution of biocatalysts and biosensors, and a lot of other research fields. Implementation of such methods to organophosphorus hydrolase being perfect research object that hydrolyzes dangerous neurotoxic organophosphates could intensify development of antidote and protective preparations to treat poisoning. Structures of enzyme-polyelectrolyte complexes (EPCs) based on hexahistidine-tagged organophosphorus hydrolase (His₆-OPH) with different biopolymers (various modifications of polyglutamic and polyaspartic acid, as well as hydroxyethyl starch and succinylated gelatin) were simulated at different pH using molecular docking. A number of EPCs with expected "positive" effect on maintaining the maximum level of His₆-OPH activity, and some "negative" options were produced, and their catalytic performance was studied. The theoretical results were experimentally confirmed for four of the six "positive" options. EPCs obtained possessed up to 20-40% higher catalytic efficiency in hydrolysis reactions of Paraoxon and Parathion-methyl as compared with that of the native His₆-OPH. The results obtained may be a good proof of concept for implementation of molecular docking to calculate model complexes of proteins with (bio)polymers of 6.4-105.5 kg/mol. Also, the approach used here could be interesting as alternative or addition to the directed modifications of enzymes to alter their catalytic characteristics.

Molecular Dynamics Simulations for Deciphering the Structural Basis of Recognition of Pre-let-7 miRNAs by LIN28

LIN28 protein inhibits biogenesis of miRNAs belonging to the let-7 family by binding to precursor forms of miRNAs. Overexpression of LIN28 and low levels of let-7 miRNAs are associated with several forms of cancer cells. We have performed multiple explicit solvent molecular dynamics simulations ranging from 200 to 500 ns in length on different isoforms of preE-let-7 in complex with LIN28 and also in isolation to identify structural features and key specificity-determining residues (SDRs) that are important for the inhibitory role of LIN28. Our simulations suggest that a conserved structural feature of the loop regions of preE-let-7 miRNAs is more important for LIN28 recognition than sequence conservation among members of the let-7 family or the presence of the GGAG motif in the 3' region. The loop region consisting of a minimum of five nucleotides helps pre-miRNAs to acquire a conformation ideal for binding to LIN28, but pre-let-7c-2 prefers a conformation with a three-nucleotide loop. Thus, our simulations provide a theoretical rationale for the recent experimental observation of the escape of LIN28-mediated repression by pre-let-7c-2. The essential structural and sequence features highlighted in this study might aid in designing synthetic small molecule inhibitors for modulating LIN28-let-7 interaction in malignant cells. We have also identified crucial SDRs of the LIN28-preE-let-7 complex involving 13 residues of LIN28 and 10 residues of the pre-miRNA. On the basis of the conservation profile of these 13 SDRs, we have identified 10 novel proteins that are not annotated as LIN28 like but are similar in sequence, domain, or fold level to LIN28.

Protein-RNA interactions: structural biology and computational modeling techniques

RNA-binding proteins are functionally diverse within cells, being involved in RNA-metabolism, translation, DNA damage repair, and gene regulation at both the transcriptional and post-transcriptional levels. Much has been learnt about their interactions with RNAs through structure determination techniques and computational modeling. This review gives an overview of the structural data currently available for protein-RNA complexes, and discusses the technical issues facing structural biologists working to solve their structures. The review focuses on three techniques used to solve the 3-dimensional structure of protein-RNA complexes at atomic resolution, namely X-ray crystallography, solution nuclear magnetic resonance (NMR) and cryo-electron microscopy (cryo-EM). The review then focuses on the main computational modeling techniques that use these atomic resolution data: discussing the prediction of RNA-binding sites on unbound proteins, docking proteins, and RNAs, and modeling the molecular dynamics of the systems. In conclusion, the review looks at the future directions this field of research might take.

Synergy between NMR measurements and MD simulations of protein/RNA complexes: application to the RRMs, the most common RNA recognition motifs

RNA recognition motif (RRM) proteins represent an abundant class of proteins playing key roles in RNA biology. We present a joint atomistic molecular dynamics (MD) and experimental study of two RRM-containing proteins bound with their single-stranded target RNAs, namely the Fox-1 and SRSF1 complexes. The simulations are used in conjunction with NMR spectroscopy to interpret and expand the available structural data. We accumulate more than 50 μs of simulations and show that the MD method is robust enough to reliably describe the structural dynamics of the RRM-RNA complexes. The simulations predict unanticipated specific participation of Arg142 at the protein-RNA interface of the SRFS1 complex, which is subsequently confirmed by NMR and ITC measurements. Several segments of the protein-RNA interface may involve competition between dynamical local substates rather than firmly formed interactions, which is indirectly consistent with the primary NMR data. We demonstrate that the simulations can be used to interpret the NMR atomistic models and can provide qualified predictions. Finally, we propose a protocol for 'MD-adapted structure ensemble' as a way to integrate the simulation predictions and expand upon the deposited NMR structures. Unbiased μs-scale atomistic MD could become a technique routinely complementing the NMR measurements of protein-RNA complexes.

Molecular modeling of structural and functional variance in the SAGA deubiquitinating module caused by Sgf73 Y57A mutation

Summary of the structural and dynamic impact caused by Sgf73 Y57A mutation.

Modeling of Protein-RNA Complex Structures Using Computational Docking Methods

A significant part of biology involves the formation of RNA-protein complexes. X-ray crystallography has added a few solved RNA-protein complexes to the repertoire; however, it remains challenging to capture these complexes and often only the unbound structures are available. This has inspired a growing interest in finding ways to predict these RNA-protein complexes. In this study, we show ways to approach this problem by computational docking methods, either with a fully automated NPDock server or with a workflow of methods for generation of many alternative structures followed by selection of the most likely solution. We show that by introducing experimental information, the structure of the bound complex is rendered far more likely to be within reach. This study is meant to help the user of docking software understand how to grapple with a typical realistic problem in RNA-protein docking, understand what to expect in the way of difficulties, and recognize the current limitations.

Can We Execute Stable Microsecond-Scale Atomistic Simulations of Protein-RNA Complexes?

We report over 30 μs of unrestrained molecular dynamics simulations of six protein-RNA complexes in explicit solvent. We utilize the AMBER ff99bsc0χ(OL3) RNA force field combined with the ff99SB protein force field and its more recent ff12SB version with reparametrized side-chain dihedrals. The simulations show variable behavior, ranging from systems that are essentially stable to systems with progressive deviations from the experimental structure, which we could not stabilize anywhere close to the starting experimental structure. For some systems, microsecond-scale simulations are necessary to achieve stabilization after initial sizable structural perturbations. The results show that simulations of protein-RNA complexes are challenging and every system should be treated individually. The simulations are affected by numerous factors, including properties of the starting structures (the initially high force field potential energy, resolution limits, conformational averaging, crystal packing, etc.), force field imbalances, and real flexibility of the studied systems. These factors, and thus the simulation behavior, differ from system to system. The structural stability of simulated systems does not correlate with the size of buried interaction surface or experimentally determined binding affinities but reflects the type of protein-RNA recognition. Protein-RNA interfaces involving shape-specific recognition of RNA are more stable than those relying on sequence-specific RNA recognition. The differences between the protein force fields are considerably smaller than the uncertainties caused by sampling and starting structures. The ff12SB improves description of the tyrosine side-chain group, which eliminates some problems associated with tyrosine dynamics.