Lin-Tai Da

Monitoring and Inhibition of Insulin Fibrillation by a Small Organic Fluorogen with Aggregation-Induced Emission Characteristics

Amyloid fibrillation of proteins is associated with a great variety of pathologic conditions. Development of new molecules that can monitor amyloidosis kinetics and inhibit fibril formation is of great diagnostic and therapeutic value. In this work, we have developed a biocompatible molecule that functions as an ex situ monitor and an in situ inhibitor for protein fibrillation, using insulin as a model protein. 1,2-Bis[4-(3-sulfonatopropoxyl)phenyl]-1,2-diphenylethene salt (BSPOTPE) is nonemissive when it is dissolved with native insulin in an incubation buffer but starts to fluoresce when it is mixed with preformed insulin fibril, enabling ex situ monitoring of amyloidogenesis kinetics and high-contrast fluorescence imaging of protein fibrils. Premixing BSPOTPE with insulin, on the other hand, inhibits the nucleation process and impedes the protofibril formation. Increasing the dose of BSPOTPE boosts its inhibitory potency. Theoretical modeling using molecular dynamics simulations and docking reveals that BSPOTPE is prone to binding to partially unfolded insulin through hydrophobic interaction of the phenyl rings of BSPOTPE with the exposed hydrophobic residues of insulin. Such binding is assumed to have stabilized the partially unfolded insulin and obstructed the formation of the critical oligomeric species in the protein fibrillogenesis process.

Dynamics of pyrophosphate ion release and its coupled trigger loop motion from closed to open state in RNA polymerase II.

Pyrophosphate ion (PP(i)) release after nucleotide incorporation is a necessary step for RNA polymerase II (pol II) to enter the next nucleotide addition cycle during transcription elongation. However, the role of pol II residues in PP(i) release and the mechanistic relationship between PP(i) release and the conformational change of the trigger loop remain unclear. In this study, we constructed a Markov state model (MSM) from extensive all-atom molecular dynamics (MD) simulations in the explicit solvent to simulate the PP(i) release process along the pol II secondary channel. Our results show that the trigger loop has significantly larger intrinsic motion after catalysis and formation of PP(i), which in turn aids PP(i) release mainly through the hydrogen bonding between the trigger loop residue H1085 and the (Mg-PP(i))(2-) group. Once PP(i) leaves the active site, it adopts a hopping model through several highly conserved positively charged residues such as K752 and K619 to release from the pol II pore region of the secondary channel. These positive hopping sites form favorable interactions with PP(i) and generate four kinetically metastable states as identified by our MSM. Furthermore, our single-mutant simulations suggest that H1085 and K752 aid PP(i) exit from the active site after catalysis, whereas K619 facilitates its passage through the secondary channel. Finally, we suggest that PP(i) release could help the opening motion of the trigger loop, even though PP(i) release precedes full opening of the trigger loop due to faster PP(i) dynamics. Our simulations provide predictions to guide future experimental tests.

A two-state model for the dynamics of the pyrophosphate ion release in bacterial RNA polymerase.

The dynamics of the PPi release during the transcription elongation of bacterial RNA polymerase and its effects on the Trigger Loop (TL) opening motion are still elusive. Here, we built a Markov State Model (MSM) from extensive all-atom molecular dynamics (MD) simulations to investigate the mechanism of the PPi release. Our MSM has identified a simple two-state mechanism for the PPi release instead of a more complex four-state mechanism observed in RNA polymerase II (Pol II). We observed that the PPi release in bacterial RNA polymerase occurs at sub-microsecond timescale, which is ∼3-fold faster than that in Pol II. After escaping from the active site, the (Mg-PPi)2− group passes through a single elongated metastable region where several positively charged residues on the secondary channel provide favorable interactions. Surprisingly, we found that the PPi release is not coupled with the TL unfolding but correlates tightly with the side-chain rotation of the TL residue R1239. Our work sheds light on the dynamics underlying the transcription elongation of the bacterial RNA polymerase.

Bridge helix bending promotes RNA polymerase II backtracking through a critical and conserved threonine residue

The dynamics of the RNA polymerase II (Pol II) backtracking process is poorly understood. We built a Markov State Model from extensive molecular dynamics simulations to identify metastable intermediate states and the dynamics of backtracking at atomistic detail. Our results reveal that Pol II backtracking occurs in a stepwise mode where two intermediate states are involved. We find that the continuous bending motion of the Bridge helix (BH) serves as a critical checkpoint, using the highly conserved BH residue T831 as a sensing probe for the 3′-terminal base paring of RNA:DNA hybrid. If the base pair is mismatched, BH bending can promote the RNA 3′-end nucleotide into a frayed state that further leads to the backtracked state. These computational observations are validated by site-directed mutagenesis and transcript cleavage assays, and provide insights into the key factors that regulate the preferences of the backward translocation.

Application of Markov State Models to Simulate Long Timescale Dynamics of Biological Macromolecules

Conformational changes of proteins are an*Author contributed equally with all other contributors. essential part of many biological processes such as: protein folding, ligand binding, signal transduction, allostery, and enzymatic catalysis. Molecular dynamics (MD) simulations can describe the dynamics of molecules at atomic detail, therefore providing a much higher temporal and spatial resolution than most experimental techniques. Although MD simulations have been widely applied to study protein dynamics, the timescales accessible by conventional MD methods are usually limited to timescales that are orders of magnitude shorter than the conformational changes relevant for most biological functions. During the past decades great effort has been devoted to the development of theoretical methods that may enhance the conformational sampling. In recent years, it has been shown that the statistical mechanics framework provided by discrete-state and -time Markov State Models (MSMs) can predict long timescale dynamics from a pool of short MD simulations. In this chapter we provide the readers an account of the basic theory and selected applications of MSMs. We will first introduce the general concepts behind MSMs, and then describe the existing procedures for the construction of MSMs. This will be followed by the discussions of the challenges of constructing and validating MSMs, Finally, we will employ two biologically-relevant systems, the RNA polymerase and the LAO-protein, to illustrate the application of Markov State Models to elucidate the molecular mechanisms of complex conformational changes at biologically relevant timescales.

Constructing kinetic models to elucidate structural dynamics of a complete RNA polymerase II elongation cycle

The RNA polymerase II elongation is central in eukaryotic transcription. Although multiple intermediates of the elongation complex have been identified, the dynamical mechanisms remain elusive or controversial. Here we build a structure-based kinetic model of a full elongation cycle of polymerase II, taking into account transition rates and conformational changes characterized from both single molecule experimental studies and computational simulations at atomistic scale. Our model suggests a force-dependent slow transition detected in the single molecule experiments corresponds to an essential conformational change of a trigger loop (TL) opening prior to the polymerase translocation. The analyses on mutant study of E1103G and on potential sequence effects of the translocation substantiate this proposal. Our model also investigates another slow transition detected in the transcription elongation cycle which is independent of mechanical force. If this force-independent slow transition happens as the TL gradually closes upon NTP binding, the analyses indicate that the binding affinity of NTP to the polymerase has to be sufficiently high. Otherwise, one infers that the slow transition happens pre-catalytically but after the TL closing. Accordingly, accurate determination of intrinsic properties of NTP binding is demanded for an improved characterization of the polymerase elongation. Overall, the study provides a working model of the polymerase II elongation under a generic Brownian ratchet mechanism, with most essential structural transition and functional kinetics elucidated.

A critical residue selectively recruits nucleotides for t7 RNA polymerase transcription fidelity control.

Nucleotide selection is essential for fidelity control in gene replication and transcription. Recent work on T7 RNA polymerase suggested that a small posttranslocation free energy bias stabilizes Tyr639 in the active site to aid nucleotide selection. However, it was not clear exactly how Tyr639 assists the selection. Here we report a molecular-dynamics simulation study revealing atomistic detail of this critical selectivity. The study shows first that Tyr639 blocks the active site at posttranslocation by marginally stacking to the end basepair of the DNA-RNA hybrid. The study then demonstrates that at the nucleotide preinsertion state, a cognate RNA nucleotide does not affect the local Tyr639 stabilization, whereas a noncognate nucleotide substantially stabilizes Tyr639 so that Tyr639 keeps blocking the active site. As a result, further nucleotide insertion into the active site, which requires moving Tyr639 out of the site, would be hindered for the noncognate nucleotide, but not for the cognate nucleotide. In particular, we note that water molecules assist the ribose recognition in the RNA nucleotide preinsertion, and help Tyr639 stacking to the end basepair in the case of a DNA nucleotide. It was also seen that a base-mismatched nucleotide at preinsertion directly grabs Tyr639 for the active site stabilization. We also find that in a mutant polymerase Y639F the strong stabilization of residue 639 in the active site cannot establish upon the DNA nucleotide preinsertion. The finding explains the reduced differentiation between ribo- and deoxyribonucleotides that has been recorded experimentally for the mutant polymerase.

A Jump-from-Cavity Pyrophosphate Ion Release Assisted by a Key Lysine Residue in T7 RNA Polymerase Transcription Elongation

Pyrophosphate ion (PPi) release during transcription elongation is a signature step in each nucleotide addition cycle. The kinetics and energetics of the process as well as how it proceeds with substantial conformational changes of the polymerase complex determine the mechano-chemical coupling mechanism of the transcription elongation. Here we investigated detailed dynamics of the PPi release process in a single-subunit RNA polymerase (RNAP) from bacteriophage T7, implementing all-atom molecular dynamics (MD) simulations. We obtained a jump-from-cavity kinetic model of the PPi release utilizing extensive nanosecond MD simulations. We found that the PPi release in T7 RNAP is initiated by the PPi dissociation from two catalytic aspartic acids, followed by a comparatively slow jump-from-cavity activation process. Combining with a number of microsecond long MD simulations, we also found that the activation process is hindered by charged residue associations as well as by local steric and hydrogen bond interactions. On the other hand, the activation is greatly assisted by a highly flexible lysine residue Lys472 that swings its side chain to pull PPi out. The mechanism can apply in general to single subunit RNA and DNA polymerases with similar molecular structures and conserved key residues. Remarkably, the flexible lysine or arginine residue appears to be a universal module that assists the PPi release even in multi-subunit RNAPs with charge facilitated hopping mechanisms. We also noticed that the PPi release is not tightly coupled to opening motions of an O-helix on the fingers domain of T7 RNAP according to the microsecond MD simulations. Our study thus supports the Brownian ratchet scenario of the mechano-chemical coupling in the transcription elongation of the single-subunit polymerase.

T7 RNA polymerase translocation is facilitated by a helix opening on the fingers domain that may also prevent backtracking

Abstract Here, we studied the complete process of a viral T7 RNA polymerase (RNAP) translocation on DNA during transcription elongation by implementing extensive all-atom molecular dynamics (MD) simulations to construct a Markov state model (MSM). Our studies show that translocation proceeds in a Brownian motion, and the RNAP thermally transits among multiple metastable states. We observed non-synchronized backbone movements of the nucleic acid (NA) chains with the RNA translocation accomplished first, while the template DNA lagged. Notably, both the O-helix and Y-helix on the fingers domain play key roles in facilitating NA translocation through the helix opening. The helix opening allows a key residue Tyr639 to become inserted into the active site, which pushes the RNA–DNA hybrid forward. Another key residue, Phe644, coordinates the downstream template DNA motions by stacking and un-stacking with a transition nucleotide (TN) and its adjacent nucleotide. Moreover, the O-helix opening at pre-translocation (pre-trans) likely resists backtracking. To test this hypothesis, we computationally designed mutants of T7 RNAP by replacing the amino acids on the O-helix with counterpart residues from a mitochondrial RNAP that is capable of backtracking. The current experimental results support the hypothesis.

THEORETICAL INVESTIGATIONS ON ELUCIDATING FUNDAMENTAL MECHANISMS OF CATALYSIS AND DYNAMICS INVOLVED IN TRANSCRIPTION BY RNA POLYMERASE

RNA polymerase is the enzyme that synthesizes RNA during the transcription process. To understand its mechanism, structural studies have provided us pictures of the series of steps necessary to add a new nucleotide to the nascent RNA chain, the steps altogether known as the nucleotide addition cycle (NAC). However, these static snapshots do not provide dynamic information of these processes involved in NAC, such as the conformational changes of the protein and the atomistic details of the catalysis. Computational studies have made efforts to fill these knowledge gaps. In this review, we provide examples of different computational approaches that have improved our understanding of the transcription elongation process for RNA polymerase, such as normal mode analysis, molecular dynamic (MD) simulations, Markov state models (MSMs). We also point out some unsolved questions that could be addressed using computational tools in the future.