Ligand Binding Mechanism and Its Relationship with Conformational Changes in Adenine Riboswitch

Multidimensional Applications and Challenges of Riboswitches in Biosensing and Biotherapy

Riboswitches have received significant attention over the last two decades for their multiple functionalities and great potential for applications in various fields. This article highlights and reviews the recent advances in biosensing and biotherapy. These fields involve a wide range of applications, such as food safety detection, environmental monitoring, metabolic engineering, live cell imaging, wearable biosensors, antibacterial drug targets, and gene therapy. The discovery, origin, and optimization of riboswitches are summarized to help readers better understand their multidimensional applications. Finally, this review discusses the multidimensional challenges and development of riboswitches in order to further expand their potential for novel applications.

Dynamical characterization and multiple unbinding paths of two PreQ1 ligands in one pocket

Riboswitches naturally regulate gene expression in bacteria by binding to specific small molecules. Class 1 preQ1 riboswitch aptamer is an important model not only for RNA folding but also as a target for designing small molecule antibiotics due to its well-known minimal aptamer domain. Here, we ran a total of 62.4 μs conventional and enhanced-sampling molecular dynamics (MD) simulations to characterize the determinants underlying the binding of the preQ1-II riboswitch aptamer to two preQ1 ligands in one binding pocket. Decomposition of binding free energy suggested that preQ1 ligands at α and β sites interact with four nucleotides (G5, C17, C18, and A30) and two nucleotides (A12 and C31), respectively. Mg2+ ions play a crucial role in both stabilizing the binding pocket and facilitating ligand binding. The flexible preQ1 ligand at the β site leads to the top of the binding pocket loosening and thus pre-organizes the riboswitch for ligand entry. Enhanced sampling simulations further revealed that the preQ1 ligand at the α site unbinds through two orthogonal pathways, which are dependent on whether or not a β site preQ1 ligand is present. One of the two preQ1 ligands has been identified in the binding pocket, which will aid to identify the second preQ1 Ligand. Our work provides new information for designing robust ligands.

RPflex: A Coarse-Grained Network Model for RNA Pocket Flexibility Study

RNA regulates various biological processes, such as gene regulation, RNA splicing, and intracellular signal transduction. RNA’s conformational dynamics play crucial roles in performing its diverse functions. Thus, it is essential to explore the flexibility characteristics of RNA, especially pocket flexibility. Here, we propose a computational approach, RPflex, to analyze pocket flexibility using the coarse-grained network model. We first clustered 3154 pockets into 297 groups by similarity calculation based on the coarse-grained lattice model. Then, we introduced the flexibility score to quantify the flexibility by global pocket features. The results show strong correlations between the flexibility scores and root-mean-square fluctuation (RMSF) values, with Pearson correlation coefficients of 0.60, 0.76, and 0.53 in Testing Sets I–III. Considering both flexibility score and network calculations, the Pearson correlation coefficient was increased to 0.71 in flexible pockets on Testing Set IV. The network calculations reveal that the long-range interaction changes contributed most to flexibility. In addition, the hydrogen bonds in the base–base interactions greatly stabilize the RNA structure, while backbone interactions determine RNA folding. The computational analysis of pocket flexibility could facilitate RNA engineering for biological or medical applications.

In silico molecular modeling and simulations of black tea theaflavins revealed theaflavin-3'-gallate as putative liver X receptor-beta agonist

The low constitutive activation of Liver X receptor, an endogenous nuclear receptor with two subtypes (α and β), is a condition lying at the crossroad of cancer and cardiovascular disease. Both natural and synthetic Liver X receptor agonists have reportedly shown remarkable antiproliferative and atheroprotective effects but the repeated doses of its synthetic ones are also paradoxically associated with hyperlipidaemic effects and neurotoxicity, though attributed to the alpha subtype. This highlights the need for novel, safe, and potent LXR-beta-selective agonists. Hypocholesterolaemic effects of black theaflavins have been widely reported, but data on the exact theaflavin compound (s) responsible for these effects is currently lacking. Neither is information on the possible modulatory effects of the compound (s) on LXR-beta nor its possible implications in the context of drug development for cardiovascular diseases and cancers is explored. On this account, we investigated the potential interaction of four main theaflavin monomers (TF1, TF2A, TF2B & TF3) with human LXR-beta through robust computational modelling that entails molecular docking, free energy calculations and molecular dynamics simulations. The ligands were further profiled (in silico) for absorption, distribution, metabolism, excretion, and toxicological properties. Our result revealed theaflavin TF2B as a putative LXR-beta agonist, possibly responsible for the widely observed hypocholesterolaemic effect in black tea. This finding, while encouraging, needs to be experimentally verified in wet studies.Communicated by Ramaswamy H. Sarma.

Decoding the Identification Mechanism of an SAM-III Riboswitch on Ligands through Multiple Independent Gaussian-Accelerated Molecular Dynamics Simulations

S-Adenosyl-l-methionine (SAM)-responsive riboswitches play a central role in the regulation of bacterial gene expression at the level of transcription attenuation or translation inhibition. In this study, multiple independent Gaussian-accelerated molecular dynamics simulations were performed to decipher the identification mechanisms of SAM-III (S_MK) on ligands SAM, SAH, and EEM. The results reveal that ligand binding highly affects the structural flexibility, internal dynamics, and conformational changes of SAM-III. The dynamic analysis shows that helices P3 and P4 as well as two junctions J23 and J24 of SAM-III are highly susceptible to ligand binding. Analyses of free energy landscapes suggest that ligand binding induces different free energy profiles of SAM-III, which leads to the difference in identification sites of SAM-III on ligands. The information on ligand-nucleotide interactions not only uncovers that the π-π, cation-π, and hydrogen bonding interactions drive identification of SAM-III on the three ligands but also reveals that different electrostatic properties of SAM, SAH, and EEM alter the active sites of SAM-III. Meanwhile, the results also verify that the adenine group of SAM, SAH, and EEM is well recognized by conserved nucleotides G7, A29, U37, A38, and G48. We expect that this study can provide useful information for understanding the applications of SAM-III in chemical, synthetic RNA biology, and biomedical fields.

Deciphering Conformational Changes of the GDP-Bound NRAS Induced by Mutations G13D, Q61R, and C118S through Gaussian Accelerated Molecular Dynamic Simulations

The conformational changes in switch domains significantly affect the activity of NRAS. Gaussian-accelerated molecular dynamics (GaMD) simulations of three separate replicas were performed to decipher the effects of G13D, Q16R, and C118S on the conformational transformation of the GDP-bound NRAS. The analyses of root-mean-square fluctuations and dynamics cross-correlation maps indicated that the structural flexibility and motion modes of the switch domains involved in the binding of NRAS to effectors are highly altered by the G13D, Q61R, and C118Smutations. The free energy landscapes (FELs) suggested that mutations induce more energetic states in NRAS than the GDP-bound WT NRAS and lead to high disorder in the switch domains. The FELs also indicated that the different numbers of sodium ions entering the GDP binding regions compensate for the changes in electrostatic environments caused by mutations, especially for G13D. The GDP–residue interactions revealed that the disorder in the switch domains was attributable to the unstable hydrogen bonds between GDP and two residues, V29 and D30. This work is expected to provide information on the energetic basis and dynamics of conformational changes in switch domains that can aid in deeply understanding the target roles of NRAS in anticancer treatment.

Protein DEK and DTA Aptamers: Insight Into the Interaction Mechanisms and the Computational Aptamer Design

By blocking the DEK protein, DEK-targeted aptamers (DTAs) can reduce the formation of neutrophil extracellular traps (NETs) to reveal a strong anti-inflammatory efficacy in rheumatoid arthritis. However, the poor stability of DTA has greatly limited its clinical application. Thus, in order to design an aptamer with better stability, DTA was modified by methoxy groups (DTA_OMe) and then the exact DEK–DTA interaction mechanisms were explored through theoretical calculations. The corresponding 2′-OCH3-modified nucleotide force field was established and the molecular dynamics (MD) simulations were performed. It was proved that the 2′-OCH3-modification could definitely enhance the stability of DTA on the premise of comparative affinity. Furthermore, the electrostatic interaction contributed the most to the binding of DEK–DTA, which was the primary interaction to maintain stability, in addition to the non-specific interactions between positively-charged residues (e.g., Lys and Arg) of DEK and the negatively-charged phosphate backbone of aptamers. The H-bond network analysis reminded that eight bases could be mutated to probably enhance the affinity of DTA_OMe. Therein, replacing the 29th base from cytosine to thymine of DTA_OMe was theoretically confirmed to be with the best affinity and even better stability. These research studies imply to be a promising new aptamer design strategy for the treatment of inflammatory arthritis.

Bacterial 2'-Deoxyguanosine Riboswitch Classes as Potential Targets for Antibiotics: A Structure and Dynamics Study

The spread of antibiotic-resistant bacteria represents a substantial health threat. Current antibiotics act on a few metabolic pathways, facilitating resistance. Consequently, novel regulatory inhibition mechanisms are necessary. Riboswitches represent promising targets for antibacterial drugs. Purine riboswitches are interesting, since they play essential roles in the genetic regulation of bacterial metabolism. Among these, class I (2′-dG-I) and class II (2′-dG-II) are two different 2′-deoxyguanosine (2′-dG) riboswitches involved in the control of deoxyguanosine metabolism. However, high affinity for nucleosides involves local or distal modifications around the ligand-binding pocket, depending on the class. Therefore, it is crucial to understand these riboswitches’ recognition mechanisms as antibiotic targets. In this work, we used a combination of computational biophysics approaches to investigate the structure, dynamics, and energy landscape of both 2′-dG classes bound to the nucleoside ligands, 2′-deoxyguanosine, and riboguanosine. Our results suggest that the stability and increased interactions in the three-way junction of 2′-dG riboswitches were associated with a higher nucleoside ligand affinity. Also, structural changes in the 2′-dG-II aptamers enable enhanced intramolecular communication. Overall, the 2′-dG-II riboswitch might be a promising drug design target due to its ability to recognize both cognate and noncognate ligands.

Theoretical exploration of the binding selectivity of inhibitors to BRD7 and BRD9 with multiple short molecular dynamics simulations

Bromodomain-containing proteins 7 and 9 (BRD7 and BRD9) have been considered as potential targets of clinical drug design toward treatment of human cancers and other diseases. Multiple short molecular dynamics simulations and binding free energy predictions were carried out to decipher the binding selectivity of three inhibitors 4L2, 5U6, and 6KT toward BRD7 and BRD9. The results show that 4L2 has more favorable binding ability to BRD7 over BRD9 compared to 5U6 and 6KT, while 5U6 and 6KT possess more favorable associations with BRD9 than BRD7. Furthermore, estimations of residue-based free energy decompositions further identify that four common residue pairs, including (F155, F44), (V160, V49), (Y168, Y57) and (Y217, Y106) in (BRD7, BRD9) generate obvious binding differences with 4L2, 5U6, and 6KT, which mostly drives the binding selectivity of 4L2, 5U6, and 6KT to BRD7 and BRD9. Dynamic information arising from trajectory analysis also suggests that inhibitor bindings affect structural flexibility and motion modes, which is responsible for the partial selectivity of 4L2, 5U6, and 6KT toward BRD7 and BRD9. As per our expectation, this study theoretically provides useful hints for design of dual inhibitors with high selectivity on BRD7 and BRD9.

Bromodomains (BRDs) are structurally conserved epigenetic reader modules observed in numerous chromatin- and transcription-associated proteins that have a capability to identify acetylated lysine residues.

Deciphering binding mechanism of inhibitors to SARS-COV-2 main protease through multiple replica accelerated molecular dynamics simulations and free energy landscapes

The pneumonia outbreak caused by the SARS-CoV-2 virus poses a serious threat to human health and the world economy. Development of safe and highly effective antiviral drugs is of great...

Comparative molecular dynamics simulation analysis of G20 and C92 mutations in c-di-GMP I riboswitch and the wild type with docked c-di-GMP ligand

Riboswitch, a bacterial regulatory RNA consists of an aptamer (specific ligand binding unit) and an expression platform (gene expression modulation unit), which act as a potential drug target as it regulates critical genes. Therefore, it is of interest to glean information on the binding of c-di-GMP ligand to mutated conserved G20 and C92 residues of cyclic diguanosine monophosphate I (c-di-GMP I) riboswitch using molecular dynamics simulation. The result shows that the binding energy of wild/native type riboswitch-ligand complex (3IRW) is lower than the mutant complexes suggesting that the binding affinity for c-di-GMP ligand decreases in case of mutant riboswitches. The hydrogen bonding interactions analysis also showed a high number of hydrogen bonds formation in the wild type riboswitch-ligand complex as compared to the mutant complexes illustrating stronger interaction of ligand to wild type riboswitch than the mutants. The simulation result shows that the mutations affected riboswitch-ligand interactions. The residues G14, G21, C46, A47, and U92 were identified as the key residues which contributed effectively to the binding of c-di-GMP I riboswitch with the natural ligand.

Recent Developments in Free Energy Calculations for Drug Discovery

The grand challenge in structure-based drug design is achieving accurate prediction of binding free energies. Molecular dynamics (MD) simulations enable modeling of conformational changes critical to the binding process, leading to calculation of thermodynamic quantities involved in estimation of binding affinities. With recent advancements in computing capability and predictive accuracy, MD based virtual screening has progressed from the domain of theoretical attempts to real application in drug development. Approaches including the Molecular Mechanics Poisson Boltzmann Surface Area (MM-PBSA), Linear Interaction Energy (LIE), and alchemical methods have been broadly applied to model molecular recognition for drug discovery and lead optimization. Here we review the varied methodology of these approaches, developments enhancing simulation efficiency and reliability, remaining challenges hindering predictive performance, and applications to problems in the fields of medicine and biochemistry.

Binding Selectivity of Inhibitors toward Bromodomains BAZ2A and BAZ2B Uncovered by Multiple Short Molecular Dynamics Simulations and MM-GBSA Calculations

Two Bromodomain-Containing proteins BAZ2A and BAZ2B are responsible for remodeling chromatin and regulating noncoding RNAs. As for our current studies, integration of multiple short molecular dynamics simulations (MSMDSs) with molecular mechanics generalized Born surface area (MM-GBSA) method is adopted for insights into binding selectivity of three small molecules D8Q, D9T and UO1 to BAZ2A against BAZ2B. The calculations of MM-GBSA unveil that selectivity of inhibitors toward BAZ2A and BAZ2B highly depends on the enthalpy changes and the details uncover that D8Q has better selectivity toward BAZ2A than BAZ2B, D9T more favorably bind to BAZ2B than BAZ2A, and UO1 does not show obvious selectivity toward these two proteins. The analysis of interaction network between residues and inhibitors indicates that seven residues are mainly responsible for the selectivity of D8Q, six residues for D9T and four residues provide significant contributions to associations of UO1 with two proteins. Moreover the analysis of interaction network not only reveals warm spots of inhibitor bindings to BAZ2A and BAZ2B but also unveils that common residue pairs, including (W1816, W1887), (P1817, P1888), (F1818, F1889), (V1822, V1893), (N1823, N1894),(L1826, L1897), (V1827, V1898), (F1872, F1943), (N1873, N1944) and (V1879, I1950) belonging to (BAZ2A, BAZ2B), induce mainly binding differences of inhibitors to BAZ2A and BAZ2B. Hence, insights from our current studies offer useful dynamics information relating with conformational alterations and structure-affinity relationship at atomistic levels for novel therapeutic strategies toward BAZ2A and BAZ2B.

Unveiling conformational dynamics changes of H-Ras induced by mutations based on accelerated molecular dynamics

Uncovering molecular basis with regard to the conformational change of two switches I and II in the GppNHp (GNP)-bound H-Ras is highly significant for the understanding of Ras signaling. For this purpose, accelerated molecular dynamics (aMD) simulations and principal component (PC) analysis are integrated to probe the effect of mutations G12V, T35S and Q61K on conformational transformation between two switches of the GNP-bound H-Ras. The RMSF and cross-correlation analyses suggest that three mutations exert a vital effect on the flexibility and internal dynamics of two switches in the GNP-bound H-Ras. The results stemming from PC analysis indicate that two switches in the GNP-bound WT H-Ras tend to form a closed state in most conformations, while those in the GNP-bound mutated H-Ras display transformation between different states. This conclusion is further supported by free energy landscapes constructed by using the distances of residues 12 away from 35 and 35 away from 61 as reaction coordinates and different experimental studies. Interaction scanning is performed on aMD trajectories and the information shows that conformational transformations of two switches I and II induced by mutations extremely affect the GNP-residue interactions. Meanwhile, the scanning results also signify that residues G15, A18, F28, K117, A146 and K147 form stable contacts with GNP, while residues D30, E31, Y32, D33, P34 and E62 in two switches I and II produce unstable contacts with GNP. This study not only reveals dynamic behavior changes of two switches in H-Ras induced by mutations, but also unveils general principles and mechanisms with regard to functional conformational changes of H-Ras.