Thrombin - A Molecular Dynamics Perspective.

Thrombin is a crucial enzyme involved in blood coagulation, essential for maintaining circulatory system integrity and preventing excessive bleeding. However, thrombin is also implicated in pathological conditions such as thrombosis and cancer. Despite the application of various experimental techniques, including X-ray crystallography, NMR spectroscopy, and HDXMS, none of these methods can precisely detect thrombin's dynamics and conformational ensembles at high spatial and temporal resolution. Fortunately, molecular dynamics (MD) simulation, a computational technique that allows the investigation of molecular functions and dynamics in atomic detail, can be used to explore thrombin behavior. This review summarizes recent MD simulation studies on thrombin and its interactions with other biomolecules. Specifically, the 17 studies discussed here provide insights into thrombin's switch between 'slow' and 'fast' forms, active and inactive forms, the role of Na+ binding, the effects of light chain mutation, and thrombin's interactions with other biomolecules. The findings of these studies have significant implications for developing new therapies for thrombosis and cancer. By understanding thrombin's complex behavior, researchers can design more effective drugs and treatments that target thrombin.

Unraveling the Role of Hydrogen Bonds in Thrombin via Two Machine Learning Methods.

Hydrogen bonds play a critical role in the folding and stability of proteins, such as proteins and nucleic acids, by providing strong and directional interactions. They help to maintain the secondary and 3D structure of proteins, and structural changes in these molecules often result from the formation or breaking of hydrogen bonds. To gain insights into these hydrogen bonding networks, we applied two machine learning models - a logistic regression model and a decision tree model - to study four variants of thrombin: wild-type, ΔK9, E8K, and R4A. Our results showed that both models have their unique advantages. The logistic regression model highlighted potential key residues (GLU295) in thrombin's allosteric pathways, while the decision tree model identified important hydrogen bonding motifs. This information can aid in understanding the mechanisms of folding in proteins and has potential applications in drug design and other therapies. The use of these two models highlights their usefulness in studying hydrogen bonding networks in proteins.

Impact of A2T and D23N mutations on C99 homodimer conformations.

The proteolytic cleavage of C99 by γ-secretase is the last step in the production of amyloid-ß (Aß) peptides. Previous studies have shown that membrane lipid composition, cholesterol concentration, and mutation in the transmembrane helix modified the structures and fluctuations of C99. In this study, we performed atomistic molecular dynamics simulations of the homodimer of the 55-residue congener of the C-terminal domain of the amyloid protein precursor, C99(1-55), in a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine-cholesterol lipid bilayer and compared the conformational ensemble of wild-type (WT) sequence to those of the A2T and D23N variants. These mutations are particularly interesting as the protective Alzheimer's disease (AD) A2T mutation is known to decrease Aß production, whereas the early onset AD D23N mutation does not affect Aß production. We found noticeable differences in the structural ensembles of the three sequences. In particular, A2T varies from both WT and D23N by having long-range effects on the population of the extracellular juxtamembrane helix, the interface between the G29xxx-G33xxx-G37 motifs, and the fluctuations of the transmembrane helical topologies.

Simulations suggest double sodium binding induces unexpected conformational changes in thrombin.

Thrombin is a Na[Formula: see text]-activated serine protease existing in two forms targeted to procoagulant and anticoagulant activities, respectively. There is one Na[Formula: see text]-binding site that has been the focus of the study of the thrombin. However, molecular dynamics (MD) simulations suggest that there might be actually two Na[Formula: see text]-binding sites in thrombin and that Na[Formula: see text] ions can even bind to two sites simultaneously. In this study, we performed 12 independent 2-µs all-atom MD simulations for the wild-type (WT) thrombin and we studied the effects of the different Na[Formula: see text] binding modes on thrombin. From the root-mean-square fluctuations (RMSF) for the [Formula: see text]-carbons, we see that the atomic fluctuations mainly change in the 60s, 170s, and 220s loops, and the connection (residue 167 to 170). The correlation matrices for different binding modes suggest regions that may play an important role in thrombin's allosteric response and provide us a possible allosteric pathway for the sodium binding. Amorim-Hennig (AH) clustering tells us how the structure of the regions of interest changes on sodium binding. Principal component analysis (PCA) shows us how the different regions of thrombin change conformation together with sodium binding. Solvent-accessible surface area (SASA) exposes the conformational change in exosite I and catalytic triad. Finally, we argue that the double binding mode might be an inactive mode and that the kinetic scheme for the Na[Formula: see text] binding to thrombin might be a multiple-step mechanism rather than a 2-step mechanism.

TREX1 as a Novel Immunotherapeutic Target.

Mutations in the TREX1 3' → 5' exonuclease are associated with a spectrum of autoimmune disease phenotypes in humans and mice. Failure to degrade DNA activates the cGAS-STING DNA-sensing pathway signaling a type-I interferon (IFN) response that ultimately drives immune system activation. TREX1 and the cGAS-STING DNA-sensing pathway have also been implicated in the tumor microenvironment, where TREX1 is proposed to degrade tumor-derived DNA that would otherwise activate cGAS-STING. If tumor-derived DNA were not degraded, the cGAS-STING pathway would be activated to promote IFN-dependent antitumor immunity. Thus, we hypothesize TREX1 exonuclease inhibition as a novel immunotherapeutic strategy. We present data demonstrating antitumor immunity in the TREX1 D18N mouse model and discuss theory surrounding the best strategy for TREX1 inhibition. Potential complications of TREX1 inhibition as a therapeutic strategy are also discussed.

Light Chain Mutation Effects on the Dynamics of Thrombin.

Thrombin plays an important role in the process of hemostasis and blood coagulation. Studies in thrombin can help us find ways to treat cancer because thrombin is able to reduce the characteristic hypercoagulability of cancer. Thrombin is composed of two chains, the light chain and the heavy chain. The function of the heavy chain has been largely explored, while the function of the light chain was obscured until several disease-associated mutations in the light chain come to light. In this study, we want to explore the dynamic and conformation effects of mutations on the light chain further to determine possible associations between mutation, conformational changes, and disease. The study, which is a follow-up for our studies on apo thrombin and the mutant, ΔK9, mainly focuses on the mutants E8K and R4A. E8K is a disease-associated mutation, and R4A is used to study the role of Arg4, which is suggested experimentally to play a critical role for thrombin's catalytic activities. We performed five all-atom one microsecond-scale molecular dynamics (MD) simulations for both E8K and R4A, and quantified the changes in the conformational ensemble of the mutants. From the root-mean-square fluctuations (RMSF) for the α-carbons, we find that the atomic fluctuations change in the mutants in the 60s loop and γ loop. The correlation coefficients for the α-carbons indicate that the correlation relation for atom-pairs in the protein is also impacted. The clustering analysis and the principal component analysis (PCA) consistently tell us that the catalytic pocket and the regulatory loops are destabilized by the mutations. We also find that there are two binding modes for Na+ by clustering the vector difference between the Na+ ions and the 220s loop. After further analysis, we find that there is a relation between the Na+ binding and the rigidification of the γ loop, which may shed light on the mysterious role of the γ loop in thrombin.

Amyloid-ß(29-42) Dimeric Conformations in Membranes Rich in Omega-3 and Omega-6 Polyunsaturated Fatty Acids.

The omega-3 and omega-6 polyunsaturated fatty acids are two important components of cell membranes in human brains. When incorporated into phospholipids, omega-3 slows the progression of Alzheimer's disease (AD), whereas omega-6 is linked to increased risk of AD. Little is known on the amyloid-ß (Aß) conformations in membranes rich in omega-3 and omega-6 phospholipids. Herein, the structural properties of the Aß29-42 dimer embedded in both fatty acid membranes were comparatively studied to a 1-palmitoyl-2-oleoyl- sn-glycero-3-phosphocholine (POPC) bilayer using all-atom molecular dynamics (MD) simulations. Starting from α-helix, both omega-6 and omega-3 membranes promote new orientations and conformations of the dimer, in agreement with the observed dependence of Aß production upon addition of these two fatty acids. This conformational result is corroborated by atomistic MD simulations of the dimer of the 99 amino acid C-terminal fragment of amyloid precursor protein spanning the residues 15-55. Starting from ß-sheet, omega-6 membrane promotes helical and disordered structures of Aß29-42 dimer, whereas omega-3 membrane preserves the ß-sheet structures differing however from those observed in POPC. Remarkably, the mixture of the two fatty acids and POPC depicts another conformational ensemble of the Aß29-42 dimer. This finding demonstrates that variation in the abundance of the molecular phospholipids, which changes with age, modulates membrane-embedded Aß oligomerization.

Na+-binding modes involved in thrombin's allosteric response as revealed by molecular dynamics simulations, correlation networks and Markov modeling.

The monovalent sodium ion (Na+) is a critical modulator of thrombin. However, the mechanism of thrombin's activation by Na+ has been widely debated for more than twenty years. Details of the linkage between thrombin and Na+ remain vague due to limited temporal and spatial resolution in experiments. In this work, we combine microsecond scale atomic-detailed molecular dynamics simulations with correlation network analyses and hidden Markov modeling to probe the detailed thermodynamic and kinetic picture of Na+-binding events and their resulting allosteric responses in thrombin. We reveal that ASP189 and ALA190 comprise a stable Na+-binding site (referred as "inner" Na+-binding site) along with the previously known one (referred as "outer" Na+-binding site). The corresponding newly identified Na+-binding mode introduces significant allosteric responses in thrombin's regulatory regions by stabilizing selected torsion angles of residues responsive to Na+-binding. Our Markov model indicates that the bound Na+ prefers to transfer between the two Na+-binding sites when an unbinding event takes place. These results suggest a testable hypothesis of a substrate-driven Na+ migration (ΔG ∼ 1.7 kcal mol-1) from the "inner" Na+-binding site to the "outer" one during thrombin's catalytic activities. The binding of a Na+ ion at the "inner" Na+-binding site should be inferred as a prerequisite for thrombin's efficient recognition to the substrate, which opens a new angle for our understanding of Na+-binding's allosteric activation on thrombin and sheds light on detailed processes in thrombin's activation.

Probing light chain mutation effects on thrombin via molecular dynamics simulations and machine learning.

Thrombin is a key component for chemotherapeutic and antithrombotic therapy development. As the physiologic and pathologic roles of the light chain still remain vague, here, we continue previous efforts to understand the impacts of the disease-associated single deletion of LYS9 in the light chain. By combining supervised and unsupervised machine learning methodologies and more traditional structural analyses on data from 10 µs molecular dynamics simulations, we show that the conformational ensemble of the ΔK9 mutant is significantly perturbed. Our analyses consistently indicate that LYS9 deletion destabilizes both the catalytic cleft and regulatory functional regions and result in some conformational changes that occur in tens to hundreds of nanosecond scaled motions. We also reveal that the two forms of thrombin each prefer a distinct binding mode of a Na+ ion. We expand our understanding of previous experimental observations and shed light on the mechanisms of the LYS9 deletion associated bleeding disorder by providing consistent but more quantitative and detailed structural analyses than early studies in literature. With a novel application of supervised learning, i.e. the decision tree learning on the hydrogen bonding features in the wild-type and ΔK9 mutant forms of thrombin, we predict that seven pairs of critical hydrogen bonding interactions are significant for establishing distinct behaviors of wild-type thrombin and its ΔK9 mutant form. Our calculations indicate the LYS9 in the light chain has both localized and long-range allosteric effects on thrombin, supporting the opinion that light chain has an important role as an allosteric effector.

Structure and Dynamics of tRNAMet Containing Core Substitutions.

The fidelity of protein synthesis is largely dominated by the accurate recognition of transfer RNAs (tRNAs) by their cognate aminoacyl-tRNA synthetases. Aminoacylation of each tRNA with its cognate amino acid is necessary to maintain the accuracy of genetic code input. Aminoacylated tRNAMet functions in both initiation and elongation steps during protein synthesis. As a precursor to the investigation of a methionyl-tRNA synthetase-tRNAMet complex, presented here are the results of molecular dynamics (MD) for single nucleotide substitutions in the D-loop of tRNAMet (G15A, G18A, and G19A) probing structure/function relationships. The core of tRNAMet likely mediates an effective communication between the tRNA anticodon and acceptor ends, contributing an acceptor stem rearrangement to fit into the enzyme-active site. Simulations of Escherichia coli tRNAMet were performed for 1 µs four times each. The MD simulations showed changes in tRNA flexibility and long-range communication most prominently in the G18A variant. The results indicate that the overall tertiary structure of tRNAMet remains unchanged with these substitutions; yet, there are perturbations to the secondary structure. Network-based analysis of the hydrogen bond structure and correlated motion indicates that the secondary structure elements of the tRNA are highly intraconnected, but loosely interconnected. Specific nucleotides, including U8 and G22, stabilize the mutated structures and are candidates for substitution in future studies.

Using correlated motions to determine sufficient sampling times for molecular dynamics.

Here we present a time-dependent correlation method that provides insight into how long a system takes to grow into its equal-time (Pearson) correlation. We also show a usage of an extant time-lagged correlation method that indicates the time for parts of a system to become decorrelated, relative to equal-time correlation. Given a completed simulation (or set of simulations), these tools estimate (i) how long of a simulation of the same system would be sufficient to observe the same correlated motions, (ii) if patterns of observed correlated motions indicate events beyond the timescale of the simulation, and (iii) how long of a simulation is needed to observe these longer timescale events. We view this method as a decision-support tool that will aid researchers in determining necessary sampling times. In principle, this tool is extendable to any multidimensional time series data with a notion of correlated fluctuations; however, here we limit our discussion to data from molecular-dynamics simulations.

Influence of electric field on the amyloid-ß(29-42) peptides embedded in a membrane bilayer.

Alzheimer's disease is linked to various types of aggregates of amyloid-ß (Aß) peptide and their interactions with protein receptors and neuronal cell membranes. Little is known on the impact of the electric field on membrane-embedded Aß. Here we use atomistic molecular dynamics simulations to study the effects of a constant electric field on the conformations of Aß29-42 dimer inside a membrane, where the electric field has a strength of 20 mV/nm which exists across the membrane of a human neuron. Starting from α-helix peptides, the transmembrane electric field (TMEF) accelerates the conversion from the Gly-out substate to the Gly-side and Gly-in substates. Starting from ß-sheet peptides, TMEF induces changes of the kink and tilt angles at Gly33 and Gly37. Overall, in the simulations totaling 10 µs, TMEF establishes new ground states for the dimer, similar to induced-fit in ligand binding. Our findings indicate that TMEF can stabilize rare conformations of amyloid peptides, and this could influence the cleavage of the amyloid precursor protein and the formation of ß-sheet oligomers in membrane bilayers.

All-atom molecular dynamics comparison of disease-associated zinc fingers.

An important regulatory domain of NF-[Formula: see text]B Essential Modulator (NEMO) is a ubiquitin-binding zinc finger, with a tetrahedral CYS3HIS1 zinc-coordinating binding site. Two variations of NEMO's zinc finger are implicated in various disease states including ectodermal dysplasia and adult-onset glaucoma. To discern structural and dynamical differences between these disease states, we present results of 48-[Formula: see text]s of molecular dynamics simulations for three zinc finger systems each in two states, with and without zinc-bound and correspondingly appropriate cysteine thiol/thiolate configurations. The wild-type protein, often studied for its role in cancer, maintains the most rigid and conformationally stable zinc-bound configuration compared with the diseased counterparts. The glaucoma-related protein has persistent loss of secondary structure except within the dominant conformation. Conformational overlap between wild-type and glaucoma isoforms indicate a competitive binding mechanism may be substantial in the malfunctioning configuration, while the alpha-helical disruption of the ectodermal dysplasia suggests a loss of binding selectivity is responsible for aberrant function.

Experimentally Dissecting the Origins of Peroxiredoxin Catalysis.

AIMS: Peroxiredoxins (Prxs) are ubiquitous cysteine-based peroxidases involved in oxidant defense and signal transduction. Despite much study, the precise roles of conserved residues remain poorly defined. In this study, we carried out extensive functional and structural characterization of 10 variants of such residues in a model decameric bacterial Prx. RESULTS: Three active site proximal mutations of Salmonella typhimurium AhpC, T43V, R119A, and E49Q, lowered catalytic efficiency with hydrogen peroxide by 4-5 orders of magnitude, but did not affect reactivity toward their reductant, AhpF. pKa values of the peroxidatic cysteine were also shifted up by 1-1.3 pH units for these and a decamer disruption mutant, T77I. Except for the decamer-stabilizing T77V, all mutations destabilized decamers in the reduced form. In the oxidized form, three mutants-T77V, T43A, and T43S-exhibited stabilized decamers and were more efficiently reduced by AhpF than wild-type AhpC. Crystal structures of most mutants were solved and many showed alterations in stability of the fully folded active site loop. INNOVATION: This is the first study of Prx mutants to comprehensively assess the effects of mutations on catalytic activities, the active site cysteine pKa, and the protein structure and oligomeric status. CONCLUSION: The Arg119 side chain must be properly situated for efficient catalysis, but for other debilitating variants, the functional defects could be explained by structural perturbations and/or associated decamer destabilization rather than direct effects. This underscores the importance of our comprehensive approach. A remarkable new finding was the preference of the reductant for decamers. Antioxid. Redox Signal. 28, 521-536.

Visualizing correlated motion with HDBSCAN clustering.

Correlated motion analysis provides a method for understanding communication between and dynamic similarities of biopolymer residues and domains. The typical equal-time correlation matrices-frequently visualized with pseudo-colorings or heat maps-quickly convey large regions of highly correlated motion but hide more subtle similarities of motion. Here we propose a complementary method for visualizing correlations within proteins (or general biopolymers) that quickly conveys intuition about which residues have a similar dynamic behavior. For grouping residues, we use the recently developed non-parametric clustering algorithm HDBSCAN. Although the method we propose here can be used to group residues using correlation as a similarity matrix-the most straightforward and intuitive method-it can also be used to more generally determine groups of residues which have similar dynamic properties. We term these latter groups "Dynamic Domains", as they are based not on spatial closeness but rather closeness in the column space of a correlation matrix. We provide examples of this method across three human proteins of varying size and function-the Nf-Kappa-Beta essential modulator, the clotting promoter Thrombin and the mismatch repair protein (dimer) complex MutS-alpha. Although the examples presented here are from all-atom molecular dynamics simulations, this visualization technique can also be used on correlations matrices built from any ensembles of conformations from experiment or computation.

Mechanistic insights into thrombin's switch between "slow" and "fast" forms.

Thrombin is a multifunctional enzyme that plays an important role in blood coagulation, cell growth, and metastasis. Depending upon the binding of sodium ions, thrombin presents significantly different enzymatic activities. In the environment with sodium ions, thrombin is highly active in cleaving the coagulated substrates and this is referred to as the "fast" form; in the environment without sodium ions, thrombin turns catalytically less active and is in the "slow" form. Although many experimental studies over the last two decades have attempted to reveal the structural and kinetic differences between these two forms, it remains vague and disputed how the functional switch between the "fast" and "slow" forms is mediated by Na+ cations. In this work, we employ microsecond-scale all-atom molecular dynamics simulations to investigate the differences in the structural ensembles in sodium-bound/unbound and potassium-bound/unbound thrombin. Our calculations indicate that the regulatory regions, including the 60s, γ loops, and exosite I and II, are primarily affected by both the bound and unbound cations. Conformational free energy surfaces, estimated from principal component analysis, further reveal the existence of multiple conformational states. The binding of a cation introduces changes in the distribution of these states. Through comparisons with potassium-binding, the binding of sodium ions appears to shift the population toward conformational states that might be catalytically favorable. Our study of thrombin in the presence of sodium/potassium ions suggests Na+-mediated generalized allostery is the mechanism of thrombin's functional switch between the "fast" and "slow" forms.

All-atom MD indicates ion-dependent behavior of therapeutic DNA polymer.

Understanding the efficacy of and creating delivery mechanisms for therapeutic nucleic acids requires understanding structural and kinetic properties which allow these polymers to promote the death of cancerous cells. One molecule of interest is a 10 mer of FdUMP (5-fluoro-2'-deoxyuridine-5'-O-monophosphate) - also called F10. Here we investigate the structural and kinetic behavior of F10 in intracellular and extracellular solvent conditions along with non-biological conditions that may be efficacious in in vitro preparations of F10 delivery systems. From our all-atom molecular dynamics simulations totaling 80 microseconds, we predict that F10's phosphate groups form close-range interactions with calcium and zinc ions, with calcium having the highest affinity of the five ions investigated. We also predict that F10's interactions with magnesium, potassium and sodium are almost exclusively long-range interactions. In terms of intramolecular interactions, we find that F10 is least structured (in terms of hydrogen bonds among bases) in the 150 mM NaCl (extracellular-like solvent conditions) and most structured in 150 mM ZnCl2. Kinetically, we see that F10 is unstable in the presence of magnesium, sodium or potassium, finding stable kinetic traps in the presence of calcium or zinc.

All-Atom MD Predicts Magnesium-Induced Hairpin in Chemically Perturbed RNA Analog of F10 Therapeutic.

Given their increasingly frequent usage, understanding the chemical and structural properties which allow therapeutic nucleic acids to promote the death of cancer cells is critical for medical advancement. One molecule of interest is a 10-mer of FdUMP (5-fluoro-2'-deoxyuridine-5'-O-monophosphate) also called F10. To investigate causes of structural stability, we have computationally restored the 2' oxygen on each ribose sugar of the phosphodiester backbone, creating FUMP[10]. Microsecond time-scale, all-atom, simulations of FUMP[10] in the presence of 150 mM MgCl2 predict that the strand has a 45% probability of folding into a stable hairpin-like secondary structure. Analysis of 16 µs of data reveals phosphate interactions as likely contributors to the stability of this folded state. Comparison with polydT and polyU simulations predicts that FUMP[10]'s lowest order structures last for one to 2 orders of magnitude longer than similar nucleic acid strands. Here we provide a brief structural and conformational analysis of the predicted structures of FUMP[10], and suggest insights into its stability via comparison to F10, polydT, and polyU.

Small static electric field strength promotes aggregation-prone structures in amyloid-ß(29-42).

The formation of senile plaques in central neural system resulting from the aggregation of the amyloid ß (Aß) of 40 and 42 residues is one of the two hallmarks of Alzheimer's disease. Numerous experiments and computational studies have shown that the aggregation of Aß peptides in vitro is very complex and depends on many factors such as pH, agitation, temperature, and peptide concentration. The impact of a static electric field (EF) on amyloid peptide aggregation has been much less studied, although EFs may have some applications to treat Parkinson's disease symptoms. Here, we study the influence of an EF strength of 20 mV/nm, present in the human brains, on the conformation of the Aß29-42 dimer. Our 7 µs non-equilibrium atomistic simulations in aqueous solution show that this field-strength promotes substantially the formation of ß-hairpins, believed to be a very important intermediate state during aggregation. This work also suggests that structural biology experiments conducted under appropriate EF strengths may help reduce the conformational heterogeneity of Aß1-40/Aß1-42 dimers and provide significant insights into their structures that may be disease-causing.

MutSα's Multi-Domain Allosteric Response to Three DNA Damage Types Revealed by Machine Learning.

MutSα is a key component in the mismatch repair (MMR) pathway. This protein is responsible for initiating the signaling pathways for DNA repair or cell death. Herein we investigate this heterodimer's post-recognition, post-binding response to three types of DNA damage involving cytotoxic, anti-cancer agents-carboplatin, cisplatin, and FdU. Through a combination of supervised and unsupervised machine learning techniques along with more traditional structural and kinetic analysis applied to all-atom molecular dynamics (MD) calculations, we predict that MutSα has a distinct response to each of the three damage types. Via a binary classification tree (a supervised machine learning technique), we identify key hydrogen bond motifs unique to each type of damage and suggest residues for experimental mutation studies. Through a combination of a recently developed clustering (unsupervised learning) algorithm, RMSF calculations, PCA, and correlated motions we predict that each type of damage causes MutSα to explore a specific region of conformation space. Detailed analysis suggests a short range effect for carboplatin-primarily altering the structures and kinetics of residues within 10 angstroms of the damaged DNA-and distinct longer-range effects for cisplatin and FdU. In our simulations, we also observe that a key phenylalanine residue-known to stack with a mismatched or unmatched bases in MMR-stacks with the base complementary to the damaged base in 88.61% of MD frames containing carboplatinated DNA. Similarly, this Phe71 stacks with the base complementary to damage in 91.73% of frames with cisplatinated DNA. This residue, however, stacks with the damaged base itself in 62.18% of trajectory frames with FdU-substituted DNA and has no stacking interaction at all in 30.72% of these frames. Each drug investigated here induces a unique perturbation in the MutSα complex, indicating the possibility of a distinct signaling event and specific repair or death pathway (or set of pathways) for a given type of damage.