Binding of small molecule inhibitors to RNA polymerase-Spt5 complex impacts RNA and DNA stability.

Spt5 is an elongation factor that associates with RNA polymerase II (Pol II) during transcription and has important functions in promoter-proximal pausing and elongation processivity. Spt5 was also recognized for its roles in the transcription of expanded-repeat genes that are related to neurodegenerative diseases. Recently, a set of Spt5-Pol II small molecule inhibitors (SPIs) were reported, which selectively inhibit mutant huntingtin gene transcription. Inhibition mechanisms as well as interaction sites of these SPIs with Pol II and Spt5 are not entirely known. In this study, we predicted the binding sites of three selected SPIs at the Pol II-Spt5 interface by docking and molecular dynamics simulations. Two molecules out of three demonstrated strong binding with Spt5 and Pol II, while the other molecule was more loosely bound and sampled multiple binding sites. Strongly bound SPIs indirectly affected RNA and DNA dynamics at the exit site as DNA became more flexible while RNA was stabilized by increased interactions with Spt5. Our results suggest that the transcription inhibition mechanism induced by SPIs can be related to Spt5-nucleic acid interactions, which were altered to some extent with strong binding of SPIs.

Structural basis of transcription: RNA Polymerase II substrate binding and metal coordination at 3.0 Å using a free-electron laser.

Catalysis and translocation of multi-subunit DNA-directed RNA polymerases underlie all cellular mRNA synthesis. RNA polymerase II (Pol II) synthesizes eukaryotic pre-mRNAs from a DNA template strand buried in its active site. Structural details of catalysis at near atomic resolution and precise arrangement of key active site components have been elusive. Here we present the free electron laser (FEL) structure of a matched ATP-bound Pol II, revealing the full active site interaction network at the highest resolution to date, including the trigger loop (TL) in the closed conformation, bonafide occupancy of both site A and B Mg2+, and a putative third (site C) Mg2+ analogous to that described for some DNA polymerases but not observed previously for cellular RNA polymerases. Molecular dynamics (MD) simulations of the structure indicate that the third Mg2+ is coordinated and stabilized at its observed position. TL residues provide half of the substrate binding pocket while multiple TL/bridge helix (BH) interactions induce conformational changes that could propel translocation upon substrate hydrolysis. Consistent with TL/BH communication, a FEL structure and MD simulations of the hyperactive Rpb1 T834P bridge helix mutant reveals rearrangement of some active site interactions supporting potential plasticity in active site function and long-distance effects on both the width of the central channel and TL conformation, likely underlying its increased elongation rate at the expense of fidelity.

Complex Conformational Space of the RNA Polymerase II C-Terminal Domain upon Phosphorylation.

Intrinsically disordered proteins (IDPs) have been closely studied during the past decade due to their importance in many biological processes. The disordered nature of this group of proteins makes it difficult to observe its full span of the conformational space using either experimental or computational studies. In this article, we explored the conformational space of the C-terminal domain (CTD) of RNA polymerase II (Pol II), which is also an intrinsically disordered low complexity domain, using enhanced sampling methods. We provided a detailed conformational analysis of model systems of CTD with different lengths; first with the last 44 residues of the human CTD sequence and finally the CTD model with 2-heptapeptide repeating units. We then investigated the effects of phosphorylation on CTD conformations by performing simulations at different phosphorylated states. We obtained broad conformational spaces in nonphosphorylated CTD models, and phosphorylation has complex effects on the conformations of the CTD. These complex effects depend on the length of the CTD, spacing between the multiple phosphorylation sites, ion coordination, and interactions with the nearby residues.

Characterization of RNA polymerase II trigger loop mutations using molecular dynamics simulations and machine learning.

Catalysis and fidelity of multisubunit RNA polymerases rely on a highly conserved active site domain called the trigger loop (TL), which achieves roles in transcription through conformational changes and interaction with NTP substrates. The mutations of TL residues cause distinct effects on catalysis including hypo- and hyperactivity and altered fidelity. We applied molecular dynamics simulation (MD) and machine learning (ML) techniques to characterize TL mutations in the Saccharomyces cerevisiae RNA Polymerase II (Pol II) system. We did so to determine relationships between individual mutations and phenotypes and to associate phenotypes with MD simulated structural alterations. Using fitness values of mutants under various stress conditions, we modeled phenotypes along a spectrum of continual values. We found that ML could predict the phenotypes with 0.68 R2 correlation from amino acid sequences alone. It was more difficult to incorporate MD data to improve predictions from machine learning, presumably because MD data is too noisy and possibly incomplete to directly infer functional phenotypes. However, a variational auto-encoder model based on the MD data allowed the clustering of mutants with different phenotypes based on structural details. Overall, we found that a subset of loss-of-function (LOF) and lethal mutations tended to increase distances of TL residues to the NTP substrate, while another subset of LOF and lethal substitutions tended to confer an increase in distances between TL and bridge helix (BH). In contrast, some of the gain-of-function (GOF) mutants appear to cause disruption of hydrophobic contacts among TL and nearby helices.

Molecular Dynamics Simulations of Rhodamine B Zwitterion Diffusion in Polyelectrolyte Solutions.

Polyelectrolytes continue to find wide interest and application in science and engineering, including areas such as water purification, drug delivery, and multilayer thin films. We have been interested in the dynamics of small molecules in a variety of polyelectrolyte (PE) environments; in this paper, we report simulations and analysis of the small dye molecule rhodamine B (RB) in several very simple polyelectrolyte solutions. Translational diffusion of the RB zwitterion has been measured in fully atomistic, 2 µs long molecular dynamics simulations in four different polyelectrolyte solutions. Two solutions contain the common polyanion sodium poly(styrene sulfonate) (PSS), one with a 30-mer chain and the other with 10 trimers. The other two solutions contain the common polycation poly(allyldimethylammonium) chloride (PDDA), one with two 15-mers and the other with 10 trimers. RB diffusion was also simulated in several polymer-free solutions to verify its known experimental value for the translational diffusion coefficient, DRB, of 4.7 × 10-6 cm2/s at 300 K. RB diffusion was slowed in all four simulated PE solutions, but to varying degrees. DRB values of 3.07 × 10-6 and 3.22 × 10-6 cm2/s were found in PSS 30-mer and PSS trimer solutions, respectively, whereas PDDA 15-mer and trimer solutions yielded values of 2.19 × 10-6 and 3.34 × 10-6 cm2/s. Significant associations between RB and the PEs were analyzed and interpreted via a two-state diffusion model (bound and free diffusion) that describes the data well. Crowder size effects and anomalous diffusion were also analyzed. Finally, RB translation along the polyelectrolytes during association was characterized.

Protein-Nucleic Acid Interactions for RNA Polymerase II Elongation Factors by Molecular Dynamics Simulations.

RNA polymerase II (Pol II) forms a complex with elongation factors to proceed to the elongation stage of the transcription process. In this work, we studied the elongation factor SPT5 and explored the protein-nucleic acid interactions for the isolated systems of KOW1 and KOW4 domains of SPT5 with DNA and RNA, respectively. We performed molecular dynamics (MD) simulations using three commonly used force fields that are CHARMM c36m, AMBER ff14sb, and ff19sb. Simulations showed strong protein-nucleic acid interactions and low electrostatic binding free energies for all force fields used. RNA was found to be highly dynamic with all force fields, while DNA had relatively more stable conformations with the AMBER force fields compared to that with CHARMM. Furthermore, we performed MD simulations of the complete elongation complex using CHARMM c36m and AMBER ff19sb force fields to compare the dynamics and interactions with the isolated systems. Similarly, strong KOW1 and DNA interactions were observed in the complete elongation complex simulations and DNA was further stabilized by a network of interactions involving SPT5-KOW1, SPT4, and rpb2 of Pol II. Overall, our study showed that the differences between CHARMM and AMBER force fields strongly affect the dynamics of the nucleic acids. CHARMM provides highly flexible DNA, while AMBER largely stabilizes the DNA structure. Although the presence of the entire interaction network stabilized the DNA and decreased the differences in the results from the two force fields, the discrepancies of the force fields for smaller systems may reflect their problems in generating accurate dynamics of nucleic acids.

Charge-driven condensation of RNA and proteins suggests broad role of phase separation in cytoplasmic environments.

Phase separation processes are increasingly being recognized as important organizing mechanisms of biological macromolecules in cellular environments. Well-established drivers of phase separation are multi-valency and intrinsic disorder. Here, we show that globular macromolecules may condense simply based on electrostatic complementarity. More specifically, phase separation of mixtures between RNA and positively charged proteins is described from a combination of multiscale computer simulations with microscopy and spectroscopy experiments. Phase diagrams were mapped out as a function of molecular concentrations in experiment and as a function of molecular size and temperature via simulations. The resulting condensates were found to retain at least some degree of internal dynamics varying as a function of the molecular composition. The results suggest a more general principle for phase separation that is based primarily on electrostatic complementarity without invoking polymer properties as in most previous studies. Simulation results furthermore suggest that such phase separation may occur widely in heterogenous cellular environment between nucleic acid and protein components.

Prediction of Membrane Permeation of Drug Molecules by Combining an Implicit Membrane Model with Machine Learning.

Lipid membrane permeation of drug molecules was investigated with Heterogeneous Dielectric Generalized Born (HDGB)-based models using solubility-diffusion theory and machine learning. Free energy profiles were obtained for neutral molecules by the standard HDGB and Dynamic HDGB (DHDGB) to account for the membrane deformation upon insertion of drugs. We also obtained hybrid free energy profiles where the neutralization of charged molecules was taken into account upon membrane insertion. The evaluation of the predictions was done against experimental permeability coefficients from Parallel Artificial Membrane Permeability Assays (PAMPA), and effects of partial charge sets, CGenFF, AM1-BCC, and OPLS, on the performance of the predictions were discussed. (D)HDGB-based models improved the predictions over the two-state implicit membrane models, and partial charge sets seemed to have a strong impact on the predictions. Machine learning increased the accuracy of the predictions, although it could not outperform the physics-based approach in terms of correlations.

Structure refinement of membrane proteins via molecular dynamics simulations.

A refinement protocol based on physics-based techniques established for water soluble proteins is tested for membrane protein structures. Initial structures were generated by homology modeling and sampled via molecular dynamics simulations in explicit lipid bilayer and aqueous solvent systems. Snapshots from the simulations were selected based on scoring with either knowledge-based or implicit membrane-based scoring functions and averaged to obtain refined models. The protocol resulted in consistent and significant refinement of the membrane protein structures similar to the performance of refinement methods for soluble proteins. Refinement success was similar between sampling in the presence of lipid bilayers and aqueous solvent but the presence of lipid bilayers may benefit the improvement of lipid-facing residues. Scoring with knowledge-based functions (DFIRE and RWplus) was found to be as good as scoring using implicit membrane-based scoring functions suggesting that differences in internal packing is more important than orientations relative to the membrane during the refinement of membrane protein homology models.

Determination of Hydrophobic Lengths of Membrane Proteins with the HDGB Implicit Membrane Model.

A protocol for predicting the hydrophobic length of membrane proteins using the heterogeneous dielectric generalized Born (HDGB) implicit membrane model is presented. The method involves optimal positioning in the membrane and identification of lipid-facing and inward-facing residues, followed by energy optimization of the implicit membrane model to obtain the hydrophobic length from the optimal membrane width. The latest HDGB version 3 (HDGBv3) and HDGB van der Waals (HDGBvdW) models were applied to a test set containing 15 proteins (seven ß-barrel and eight α-helical proteins), for which matching membrane widths are available from experiment, and an additional set contains ten α-helical and ten ß-barrel proteins without any experimental data. The results with the HDGB model compare favorably with predictions from methods used in the Orientations of Proteins in Membranes (OPM) and Protein Data Bank of Transmembrane Proteins (PDB-TM) databases.

Discrimination of Native-like States of Membrane Proteins with Implicit Membrane-based Scoring Functions.

A scoring protocol based on implicit membrane-based scoring functions and a new protocol for optimizing the positioning of proteins inside the membrane was evaluated for its capacity to discriminate native-like states from misfolded decoys. A decoy set previously established by the Baker lab (Proteins: Struct., Funct., Genet. 2006, 62, 1010-1025) was used along with a second set that was generated to cover higher resolution models. The Implicit Membrane Model 1 (IMM1), IMM1 model with CHARMM 36 parameters (IMM1-p36), generalized Born with simple switching (GBSW), and heterogeneous dielectric generalized Born versions 2 (HDGBv2) and 3 (HDGBv3) were tested along with the new HDGB van der Waals (HDGBvdW) model that adds implicit van der Waals contributions to the solvation free energy. For comparison, scores were also calculated with the distance-scaled finite ideal-gas reference (DFIRE) scoring function. Z-scores for native state discrimination, energy vs root-mean-square deviation (RMSD) correlations, and the ability to select the most native-like structures as top-scoring decoys were evaluated to assess the performance of the scoring functions. Ranking of the decoys in the Baker set that were relatively far from the native state was challenging and dominated largely by packing interactions that were captured best by DFIRE with less benefit of the implicit membrane-based models. Accounting for the membrane environment was much more important in the second decoy set where especially the HDGB-based scoring functions performed very well in ranking decoys and providing significant correlations between scores and RMSD, which shows promise for improving membrane protein structure prediction and refinement applications. The new membrane structure scoring protocol was implemented in the MEMScore web server ( http://feiglab.org/memscore ).

Heterogeneous dielectric generalized Born model with a van der Waals term provides improved association energetics of membrane-embedded transmembrane helices.

The heterogeneous dielectric generalized Born (HDGB) implicit membrane formalism is extended by the addition of a van der Waals dispersion term to better describe the nonpolar components of the free energy of solvation. The new model, termed HDGBvdW, improves the energy estimates in the hydrophobic interior of the membrane, where polar and charged species are rarely found and nonpolar interactions become significant. The implicit van der Waals term for the membrane environment extends the model from Gallicchio et al. (J. Comput. Chem. 2004, 25, 479) by combining separate contributions from each of the membrane components. The HDGBvdW model is validated with a series of test cases ranging from membrane insertion and pair association profiles of amino acid side chain analogs and transmembrane helices. Overall, the HDGBvdW model leads to increased agreement with explicit membrane simulation results and experimental data. © 2016 Wiley Periodicals, Inc.

Dynamic nuclear polarization-enhanced NMR on aligned lipid bilayers at ambient temperature.

Dynamic nuclear polarization (DNP)-enhanced solid-state NMR spectroscopy has been shown to hold great potential for functional studies of membrane proteins at low temperatures due to its great sensitivity improvement. There are, however, numerous applications for which experiments at ambient temperature are desirable and which would also benefit from DNP signal enhancement. Here, we demonstrate as a proof of concept that a significant signal increase for lipid bilayers under room-temperature conditions can be achieved by utilizing the Overhauser effect. Experiments were carried out on aligned bilayers at 400 MHz/263 GHz using a stripline structure combined with a Fabry-Perot microwave resonator. A signal enhancement of protons of up to -10 was observed. Our results demonstrate that Overhauser DNP at high field provides efficient polarization transfer within insoluble samples, which is driven by fast local molecular fluctuations. Furthermore, our experimental setup offers an attractive option for DNP-enhanced solid-state NMR on ordered membranes and provides a general perspective toward DNP at ambient temperatures.

Ceramide-lipid interactions studied by MD simulations and solid-state NMR.

Ceramides play a key modulatory role in many cellular processes, which results from their effect on the structure and dynamics of biological membranes. In this study, we investigate the influence of C16-ceramide (C16) on the biophysical properties of DMPC lipid bilayers using solid-state NMR and atomistic molecular dynamics (MD) simulations. MD simulations and NMR measurements were carried out for a pure DMPC bilayer and for a 20% DMPC-C16 mixture. Calculated key structural properties, namely area per lipid, chain order parameters, and mass density profiles, indicate that C16 has an ordering effect on the DMPC bilayer. Furthermore, the simulations predict that specific hydrogen-bonds form between DMPC and C16 molecules. Multi-nuclear solid-state NMR was used to verify these theoretical predictions. Chain order parameters extracted from (13)C(1)H dipole couplings were measured for both lipid and ceramide and follow the trend suggested by the MD simulations. Furthermore, (1)H-MAS NMR experiments showed a direct contact between ceramide and lipids.

Structural properties of so-called NSAID-phospholipid-complexes.

So-called NSAID-phospholipid-complexes have been recently reported in literature to reduce local gastrointestinal toxicity. The present work was dedicated to the structural characterization of so-called drug-phospholipid-complexes on the example of diclofenac sodium, ibuprofen and piroxicam complexes with dipalmitoylphosphatidylcholine (DPPC) at different stages of preparation. The applied techniques include (1)H/2D ROESY NMR for the structural characterization in organic solvents, FT-IR and X-ray diffraction for the structural characterization in the solid state and PCS, (31)P NMR, as well as MAS (1)H/2D NOESY NMR for the structural characterization in aqueous media following hydration. Whereas the formation of isolated 1:1 drug-phospholipid-complexes with a preferential location of diclofenac and ibuprofen at the polar head group, stabilized by cation-π interaction, seems reasonable in organic solvents, it was found that mainly liposomal and micellar structures are formed upon hydration of the drug-phospholipid-complexes. Hence the term "NSAID-phospholipid-complex" may be misleading in the context with physiologically relevant aqueous media. Piroxicam did not show significant interaction with DPPC.