Visualizing ensembles in structural biology

Allosteric Modulation of Thrombin by Thrombomodulin: Insights from Logistic Regression and Statistical Analysis of Molecular Dynamics Simulations

Thrombomodulin (TM), a transmembrane receptor integral to the anticoagulant pathway, governs thrombin's substrate specificity via interaction with thrombin's anion-binding exosite I. Despite its established role, the precise mechanisms underlying this regulatory function are yet to be fully unraveled. In this study, we deepen the understanding of these mechanisms through eight independent 1 μs all-atom simulations, analyzing thrombin both in its free form and when bound to TM fragments TM456 and TM56. Our investigations revealed distinct and significant conformational changes in thrombin mediated by the binding of TM56 and TM456. While TM56 predominantly influences motions within exosite I, TM456 orchestrates coordinated alterations across various loop regions, thereby unveiling a multifaceted modulatory role that extends beyond that of TM56. A highlight of our study is the identification of critical hydrogen bonds that undergo transformations during TM56 and TM456 binding, shedding light on the pivotal allosteric influence exerted by TM4 on thrombin's structural dynamics. This work offers a nuanced appreciation of TM's regulatory role in blood coagulation, paving the way for innovative approaches in the development of anticoagulant therapies and expanding the horizons in oncology therapeutics through a deeper understanding of molecular interactions in the coagulation pathway.

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.

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.

Quality Threshold Clustering of Molecular Dynamics: A Word of Caution

Clustering Molecular Dynamics trajectories is a common analysis that allows grouping together similar conformations. Several algorithms have been designed and optimized to perform this routine task, and among them, Quality Threshold stands as a very attractive option. This algorithm guarantees that in retrieved clusters no pair of frames will have a similarity value greater than a specified threshold, and hence, a set of strongly correlated frames are obtained for each cluster. In this work, it is shown that various commonly used software implementations are flawed by confusing Quality Threshold with another simplistic well-known clustering algorithm published by Daura et al. (Daura, X.; van Gunsteren, W. F.; Jaun, B.; Mark, A. E.; Gademann, K.; Seebach, D. Peptide Folding: When Simulation Meets Experiment. Angew. Chemie Int. Ed. 1999, 38 (1/2), 236-240). Daura's algorithm does not impose any quality threshold for the frames contained in retrieved clusters, bringing unrelated structural configurations altogether. The advantages of using Quality Threshold whenever possible to explore Molecular Dynamic trajectories is exemplified. An in-house implementation of the original Quality Threshold algorithm has been developed in order to illustrate our comments, and its code is freely available for further use by the scientific community.

Structural characterization of EGFR exon 19 deletion mutation using molecular dynamics simulation

Epidermal growth factor receptor (EGFR) is a tyrosine kinase receptor important in diverse biological processes including cell proliferation and survival. Upregulation of EGFR activity due to over-expression or mutation is widely implicated in cancer. Activating somatic mutations of the EGFR kinase are postulated to affect the conformation and/or stability of the protein, shifting the EGFR inactive-active state equilibrium towards the activated state. Here, we examined a common EGFR deletion mutation, Δ⁷⁴⁶ELREA⁷⁵⁰, which is frequently observed in non-small cell lung cancer patients. By using molecular dynamics simulation, we investigated the structural effects of the mutation that lead to the experimentally reported increases in kinase activity. Simulations of the active form wild-type and ΔELREA EGFRs revealed the deletion stabilizes the αC helix of the kinase domain, which is located adjacent to the deletion site, by rigidifying the flexible β3-αC loop that accommodates the ELREA sequence. Consequently, the αC helix is stabilized in the “αC-in” active conformation that would prolong the time of the activated state. Moreover, in the mutant kinase, a salt bridge between E762 and K745, which is key for EGFR activity, was also stabilized during the simulation. Additionally, the interaction between EGFR and ATP was favored by ΔELREA EGFR over wild-type EGFR, as reflected by the number of hydrogen bonds formed and the free energy of binding. Simulation of inactive EGFR suggested the deletion would promote a shift from the inactive conformation towards active EGFR, which is supported by the inward movement of the αC helix. The MDS results also align with the effects of tyrosine kinase inhibitors on ΔELREA and wild-type EGFR lung cancer cell lines, where more pronounced inhibition was observed against ΔELREA than for wild-type EGFR by inhibitors recognizing the active kinase conformation.

Computational investigation on effect of mutations in PCNA resulting in structural perturbations and inhibition of mismatch repair pathway

From bacteria to mammals, DNA mismatch repair (MMR) pathway plays an essential role in eliminating mismatched nucleotides and insertion-deletion mismatches during the process of DNA replication. Among many of the proteins which participate in the mismatch repair process, proliferating cell nuclear antigen (PCNA) remains the principal conductor at the replication fork. The pol30-201 and pol30-204 are the two mutated alleles which encode for C22Y and C81R mutant forms of PCNA proteins. We performed long term molecular dynamics (MD) simulations analysis (0.8 μs) to understand the dynamic behavior and alterations in the structure of wild type and mutated forms of PCNA at the atomic level. We observed changes in the structural characteristics like length, radius, rise per residue of alpha helices in both the mutated forms of PCNA. Apart from it, disfigurement of the charge distribution which effects binding with the dsDNA due to mutant C22Y and other structural perturbations were also seen in regions significant for the formation of a biologically active trimeric form of PCNA due to mutant C81R. Our analysis of native and mutated forms of PCNA provides an insight into the essential structural and functional features required for proper and well-coordinated DNA mismatch repair process and consequences of the mutation leading to an impaired process of MMR. These structural characteristics are fundamental for the MMR process and hence our analysis likely contributes to or presents the novel mechanism involved in the process of MMR.Communicated by Ramaswamy H. Sarma.

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.

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.

Molecular dynamics simulations of aptamer-binding reveal generalized allostery in thrombin

Thrombin is an attractive target for antithrombotic therapy due to its central role in thrombosis and hemostasis as well as its role in inducing tumor growth, metastasis, and tumor invasion. The thrombin-binding DNA aptamer (TBA), is under investigation for anticoagulant drugs. Although aptamer binding experiments have been revealed various effects on thrombin's enzymatic activities, the detailed picture of the thrombin's allostery from TBA binding is still unclear. To investigate thrombin's response to the aptamer-binding at the molecular level, we compare the mechanical properties and free energy landscapes of the free and aptamer-bound thrombin using microsecond-scale all-atom GPU-based molecular dynamics simulations. Our calculations on residue fluctuations and coupling illustrate the allosteric effects of aptamer-binding at the atomic level, highlighting the exosite II, 60s, γ and the sodium loops, and the alpha helix region in the light chains involved in the allosteric changes. This level of details clarifies the mechanisms of previous experimentally demonstrated phenomena, and provides a prediction of the reduced autolysis rate after aptamer-binding. The shifts in thrombin's ensemble of conformations and free energy surfaces after aptamer-binding demonstrate that the presence of bound-aptamer restricts the conformational freedom of thrombin suggesting that conformational selection, i.e. generalized allostery, is the dominant mechanism of thrombin-aptamer binding. The profound perturbation on thrombin's mechanical and thermodynamic properties due to the aptamer-binding, which was revealed comprehensively as a generalized allostery in this work, may be exploited in further drug discovery and development.

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.

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.

Binding Site Configurations Probe the Structure and Dynamics of the Zinc Finger of NEMO (NF-κB Essential Modulator)

Zinc-finger proteins are regulators of critical signaling pathways for various cellular functions, including apoptosis and oncogenesis. Here, we investigate how binding site protonation states and zinc coordination influence protein structure, dynamics, and ultimately function, as these pivotal regulatory proteins are increasingly important for protein engineering and therapeutic discovery. To better understand the thermodynamics and dynamics of the zinc finger of NEMO (NF-κB essential modulator), as well as the role of zinc, we present results of 20 μs molecular dynamics trajectories, 5 μs for each of four active site configurations. Consistent with experimental evidence, the zinc ion is essential for mechanical stabilization of the functional, folded conformation. Hydrogen bond motifs are unique for deprotonated configurations yet overlap in protonated cases. Correlated motions and principal component analysis corroborate the similarity of the protonated configurations and highlight unique relationships of the zinc-bound configuration. We hypothesize a potential mechanism for zinc binding from results of the thiol configurations. The deprotonated, zinc-bound configuration alone predominantly maintains its tertiary structure throughout all 5 μs and alludes rare conformations potentially important for (im)proper zinc-finger-related protein-protein or protein-DNA interactions.

Uncovering Large-Scale Conformational Change in Molecular Dynamics without Prior Knowledge

As the length of molecular dynamics (MD) trajectories grows with increasing computational power, so does the importance of clustering methods for partitioning trajectories into conformational bins. Of the methods available, the vast majority require users to either have some a priori knowledge about the system to be clustered or to tune clustering parameters through trial and error. Here we present non-parametric uses of two modern clustering techniques suitable for first-pass investigation of an MD trajectory. Being non-parametric, these methods require neither prior knowledge nor parameter tuning. The first method, HDBSCAN, is fast-relative to other popular clustering methods-and is able to group unstructured or intrinsically disordered systems (such as intrinsically disordered proteins, or IDPs) into bins that represent global conformational shifts. HDBSCAN is also useful for determining the overall stability of a system-as it tends to group stable systems into one or two bins-and identifying transition events between metastable states. The second method, iMWK-Means, with explicit rescaling followed by K-Means, while slower than HDBSCAN, performs well with stable, structured systems such as folded proteins and is able to identify higher resolution details such as changes in relative position of secondary structural elements. Used in conjunction, these clustering methods allow a user to discern quickly and without prior knowledge the stability of a simulated system and identify both local and global conformational changes.

Protein Folding and Structure Prediction from the Ground Up II: AAWSEM for α/β Proteins

The atomistic associative memory, water mediated, structure and energy model (AAWSEM) is an efficient coarse-grained force field with transferable tertiary interactions that incorporates local in sequence energetic biases using structural information derived from all-atom simulations of long segments of the protein. For α helical proteins, the accuracy of structure prediction using AAWSEM has been established previously. In this article, we examine the capability of AAWSEM to predict the structure of α/β proteins. We also elaborate on an iterative approach that uses the structures from a first round of AAWSEM simulation as fragment memories. This iterative scheme improves the quality of the structure prediction and makes the free energy profile more funneled toward native configurations. We explore the use of clustering analyses as a way of evaluating the confidence in various structure prediction models. Clustering using a local relative order parameter (mutual Q) of the predicted structural ensemble turns out to be optimal. The tightest cluster according to mutual Q generally has the most correctly folded structure. Since there is no bioinformatic input, AAWSEM amounts to an ab initio protein structure prediction method that combines the efficiency of coarse-grained simulations with the local structural accuracy that can be achieved from all-atom simulations.

All-Atom Molecular Dynamics Reveals Mechanism of Zinc Complexation with Therapeutic F10

Advancing the use of therapeutic nucleic acids requires understanding the chemical and structural properties that allow these polymers to promote the death of malignant cells. Here we explore Zn²⁺ complexation by the fluoropyrimidine polymer F10, which has strong activities in multiple preclinical models of cancer. Delivery of fluoropyrimidine FdUMP in the 10-residue polymer F10 rather than the nucleobase (5-fluorouracil) allows consideration of metal ion binding effects on drug delivery. The differences in metal ion interactions with fluoropyrimidine compared to normal DNA results in conformation changes that affect protein binding, cell uptake, and codelivery of metals such as zinc, and the cytoxicity thereof. Microsecond-time-scale, all-atom simulations of F10 predict that zinc selectively stabilizes the polymer via interactions with backbone phosphate groups and suggest a mechanism of complexation for the zinc-base interactions shown in previous experimental work. The positive zinc ions are attracted to the negatively charged phosphate groups. Once the Zn²⁺ ions are near F10, they cause the base's N3 nitrogen to deprotonate. Subsequently, magnesium atoms displace zinc from their interactions with phosphate, freeing the zinc ions to interact with the FdU bases by forming weak interactions with the O4 oxygen and the fluorine attached to C5. These interactions of magnesium with phosphate groups and zinc with nucleobases agree with previous experimental results and are seen in MD simulations only when magnesium is introduced after N3 deprotonation, indicating a specific order of metal binding events. Additionally, we predict interactions between zinc and F10's O2 atoms, which were not previously observed. By comparison to 10mers of polyU and polydT, we also predict that the presence of fluorine increases the binding affinity of zinc to F10 relative to analogous strands of RNA and DNA consisting of only native nucleotides.