Previous studies demonstrated the efficiency of the Molecular Dynamics with excited Normal Modes (MDeNM) method on the characterization of large structural changes at a low computational cost. We ...present here MDeNM-EMfit, an extension of the original method designed to the flexible fit of structures into cryo-EM maps. Here, instead of a uniform exploration of the collective motions described by normal modes, sampling is directed toward conformations with increased correlations with the experimental map. Future perspectives to improve the accuracy of fitting and speed of calculations are discussed in light of the results.
Adaptive metabolic reprogramming gives cancer cells a proliferative advantage. Tumour cells extensively use glycolysis to sustain anabolism and produce serine, which not only refuels the one‐carbon ...units necessary for the synthesis of nucleotide precursors and for DNA methylation, but also affects the cellular redox homeostasis. Given its central role in serine metabolism, serine hydroxymethyltransferase (SHMT), a pyridoxal 5′‐phosphate (PLP)‐dependent enzyme, is an attractive target for tumour chemotherapy. In humans, the cytosolic isoform (SHMT1) and the mitochondrial isoform (SHMT2) have distinct cellular roles, but high sequence identity and comparable catalytic properties, which may complicate development of successful therapeutic strategies. Here, we investigated how binding of the cofactor PLP controls the oligomeric state of the human isoforms. The fact that eukaryotic SHMTs are tetrameric proteins while bacterial SHMTs function as dimers may suggest that the quaternary assembly in eukaryotes provides an advantage to fine‐tune SHMT function and differentially regulate intertwined metabolic fluxes, and may provide a tool to address the specificity problem. We determined the crystal structure of SHMT2, and compared it to the apo‐enzyme structure, showing that PLP binding triggers a disorder‐to‐order transition accompanied by a large rigid‐body movement of the two cofactor‐binding domains. Moreover, we demonstrated that SHMT1 exists in solution as a tetramer, both in the absence and presence of PLP, while SHMT2 undergoes a dimer‐to‐tetramer transition upon PLP binding. These findings indicate an unexpected structural difference between the two human SHMT isoforms, which opens new perspectives for understanding their differing behaviours, roles or regulation mechanisms in response to PLP availability in vivo.
Serine proteinase inhibitors (serpins), typically fold to a metastable native state and undergo a major conformational change in order to inhibit target proteases. However, conformational lability of ...the native serpin fold renders them susceptible to misfolding and aggregation, and underlies misfolding diseases such as α
-antitrypsin deficiency. Serpin specificity towards its protease target is dictated by its flexible and solvent exposed reactive centre loop (RCL), which forms the initial interaction with the target protease during inhibition. Previous studies have attempted to alter the specificity by mutating the RCL to that of a target serpin, but the rules governing specificity are not understood well enough yet to enable specificity to be engineered at will. In this paper, we use conserpin, a synthetic, thermostable serpin, as a model protein with which to investigate the determinants of serpin specificity by engineering its RCL. Replacing the RCL sequence with that from α1-antitrypsin fails to restore specificity against trypsin or human neutrophil elastase. Structural determination of the RCL-engineered conserpin and molecular dynamics simulations indicate that, although the RCL sequence may partially dictate specificity, local electrostatics and RCL dynamics may dictate the rate of insertion during protease inhibition, and thus whether it behaves as an inhibitor or a substrate. Engineering serpin specificity is therefore substantially more complex than solely manipulating the RCL sequence, and will require a more thorough understanding of how conformational dynamics achieves the delicate balance between stability, folding and function required by the exquisite serpin mechanism of action.
Proteins are found in solution as ensembles of conformations in dynamic equilibrium. Exploration of functional motions occurring on micro- to millisecond time scales by molecular dynamics (MD) ...simulations still remains computationally challenging. Alternatively, normal mode (NM) analysis is a well-suited method to characterize intrinsic slow collective motions, often associated with protein function, but the absence of anharmonic effects preclude a proper characterization of conformational distributions in a multidimensional NM space. Using both methods jointly appears to be an attractive approach that allows an extended sampling of the conformational space. In line with this view, the MDeNM (molecular dynamics with excited normal modes) method presented here consists of multiple-replica short MD simulations in which motions described by a given subset of low-frequency NMs are kinetically excited. This is achieved by adding additional atomic velocities along several randomly determined linear combinations of NM vectors, thus allowing an efficient coupling between slow and fast motions. The relatively high-energy conformations generated with MDeNM are further relaxed with standard MD simulations, enabling free energy landscapes to be determined. Two widely studied proteins were selected as examples: hen egg lysozyme and HIV-1 protease. In both cases, MDeNM provides a larger extent of sampling in a few nanoseconds, outperforming long standard MD simulations. A high degree of correlation with motions inferred from experimental sources (X-ray, EPR, and NMR) and with free energy estimations obtained by metadynamics was observed. Finally, the large sets of conformations obtained with MDeNM can be used to better characterize relevant dynamical populations, allowing for a better interpretation of experimental data such as SAXS curves and NMR spectra.
Molecular dynamics with excited normal modes (MDeNM) is an enhanced sampling method for exploring conformational changes in proteins with minimal biases. The excitation corresponds to injecting ...kinetic energy along normal modes describing intrinsic collective motions. Herein, we developed a new automated open-source implementation, MDexciteR (https://github.com/mcosta27/MDexciteR), enabling the integration of MDeNM with two commonly used simulation programs with GPU support. Second, we generalized the method to include the excitation of principal components calculated from experimental ensembles. Finally, we evaluated whether the use of coarse-grained normal modes calculated with elastic network representations preserved the performance and accuracy of the method. The advantages and limitations of these new approaches are discussed based on results obtained for three different protein test cases: two globular and a protein/membrane system.
MicroRNAs (miRs) play critical roles in regulation of numerous biological events, including cardiac electrophysiology and arrhythmia, through a canonical RNA interference mechanism. It remains ...unknown whether endogenous miRs modulate physiologic homeostasis of the heart through noncanonical mechanisms.
We focused on the predominant miR of the heart (miR1) and investigated whether miR1 could physically bind with ion channels in cardiomyocytes by electrophoretic mobility shift assay, in situ proximity ligation assay, RNA pull down, and RNA immunoprecipitation assays. The functional modulations of cellular electrophysiology were evaluated by inside-out and whole-cell patch clamp. Mutagenesis of miR1 and the ion channel was used to understand the underlying mechanism. The effect on the heart ex vivo was demonstrated through investigating arrhythmia-associated human single nucleotide polymorphisms with miR1-deficient mice.
We found that endogenous miR1 could physically bind with cardiac membrane proteins, including an inward-rectifier potassium channel Kir2.1. The miR1-Kir2.1 physical interaction was observed in mouse, guinea pig, canine, and human cardiomyocytes. miR1 quickly and significantly suppressed I
at sub-pmol/L concentration, which is close to endogenous miR expression level. Acute presence of miR1 depolarized resting membrane potential and prolonged final repolarization of the action potential in cardiomyocytes. We identified 3 miR1-binding residues on the C-terminus of Kir2.1. Mechanistically, miR1 binds to the pore-facing G-loop of Kir2.1 through the core sequence AAGAAG, which is outside its RNA interference seed region. This biophysical modulation is involved in the dysregulation of gain-of-function Kir2.1-M301K mutation in short QT or atrial fibrillation. We found that an arrhythmia-associated human single nucleotide polymorphism of miR1 (hSNP14A/G) specifically disrupts the biophysical modulation while retaining the RNA interference function. It is remarkable that miR1 but not hSNP14A/G relieved the hyperpolarized resting membrane potential in miR1-deficient cardiomyocytes, improved the conduction velocity, and eliminated the high inducibility of arrhythmia in miR1-deficient hearts ex vivo.
Our study reveals a novel evolutionarily conserved biophysical action of endogenous miRs in modulating cardiac electrophysiology. Our discovery of miRs' biophysical modulation provides a more comprehensive understanding of ion channel dysregulation and may provide new insights into the pathogenesis of cardiac arrhythmias.
Molecular Dynamics Flexible Fitting (MDFF) is a widely used tool to refine high-resolution structures into cryo-EM density maps. Despite many successful applications, MDFF is still limited by its ...high computational cost, overfitting, accuracy, and performance issues due to entrapment within wrong local minima. Modern ensemble-based MDFF tools have generated promising results in the past decade. In line with these studies, we present MDFF_NM, a stochastic hybrid flexible fitting algorithm combining Normal Mode Analysis (NMA) and simulation-based flexible fitting. Initial tests reveal that, besides accelerating the fitting process, MDFF_NM increases the diversity of fitting routes leading to the target, uncovering ensembles of conformations in closer agreement with experimental data. The potential integration of MDFF_NM with other existing methods and integrative modeling pipelines is also discussed.
Network theory methods and molecular dynamics (MD) simulations are accepted tools to study allosteric regulation. Indeed, dynamic networks built upon correlation analysis of MD trajectories provide ...detailed information about communication paths between distant sites. In this context, we aimed to understand whether the efficiency of intramolecular communication could be used to predict the allosteric potential of a given site. To this end, we performed MD simulations and network theory analyses in cathepsin K (catK), whose allosteric sites are well defined. To obtain a quantitative measure of the efficiency of communication, we designed a new protocol that enables the comparison between properties related to ensembles of communication paths obtained from different sites. Further, we applied our strategy to evaluate the allosteric potential of different catK cavities not yet considered for drug design. Our predictions of the allosteric potential based on intramolecular communication correlate well with previous catK experimental and theoretical data. We also discuss the possibility of applying our approach to other proteins from the same family.
There is a variety of experimental and computational techniques available to explore protein dynamics, each presenting advantages and limitations. One promising experimental technique that is driving ...the development of computational methods is cryo‐electron microscopy (cryo‐EM). Cryo‐EM provides molecular‐level structural data and first estimates of conformational landscape from single particle analysis but cannot track real‐time protein dynamics and may contain uncertainties in atomic positions especially at highly dynamic regions. Molecular simulations offer atomic‐level insights into protein dynamics; however, their computing time requirements limit the conformational sampling accuracy, and it is often hard, to assess by full‐atomic simulations the cooperative movements of biological interest for large assemblies such as those resolved by cryo‐EM. Coarse‐grained (CG) simulations permit us to explore such systems, but at the costs of lower resolution and potentially incomplete sampling of conformational space. On the other hand, analytical methods may circumvent sampling limitations. In particular, elastic network models‐based normal mode analyses (ENM‐NMA) provide unique solutions for the complete mode spectra near equilibrium states, even for systems of megadaltons, and may thus deliver information on mechanisms of motions relevant to biological function. Yet, they lack atomic resolution as well as temporal information for non‐equilibrium systems. Given the complementary nature of these methods, the integration of molecular simulations and ENM‐NMA into hybrid methodologies has gained traction. This review presents the current state‐of‐the‐art in structure‐based computations and how they are helping us gain a deeper understanding of biological mechanisms, with emphasis on the development of hybrid methods accompanying the advances in cryo‐EM.
This article is categorized under:
Structure and Mechanism > Computational Biochemistry and Biophysics
Synergy of global motions from analytical approaches such as Normal Mode analysis together with coarse‐grained models (e.g. ENMs) (top left) and local details from molecular simulations at atomic resolution (top right) with Cryo‐EM structural data (top middle) leads to a range of hybrid methods covering a broad range of length and time scales and applications (bottom).
The human neuroendocrine enzyme glutamate decarboxylase (GAD) catalyses the synthesis of the inhibitory neurotransmitter gamma-aminobutyric acid (GABA) using pyridoxal 5'-phosphate as a cofactor. GAD ...exists as two isoforms named according to their respective molecular weights: GAD65 and GAD67. Although cytosolic GAD67 is typically saturated with the cofactor (holoGAD67) and constitutively active to produce basal levels of GABA, the membrane-associated GAD65 exists mainly as the inactive apo form. GAD65, but not GAD67, is a prevalent autoantigen, with autoantibodies to GAD65 being detected at high frequency in patients with autoimmune (type 1) diabetes and certain other autoimmune disorders. The significance of GAD65 autoinactivation into the apo form for regulation of neurotransmitter levels and autoantibody reactivity is not understood. We have used computational and experimental approaches to decipher the nature of the holo → apo conversion in GAD65 and thus, its mechanism of autoinactivation. Molecular dynamics simulations of GAD65 reveal coupling between the C-terminal domain, catalytic loop, and pyridoxal 5'-phosphate-binding domain that drives structural rearrangement, dimer opening, and autoinactivation, consistent with limited proteolysis fragmentation patterns. Together with small-angle X-ray scattering and fluorescence spectroscopy data, our findings are consistent with apoGAD65 existing as an ensemble of conformations. Antibody-binding kinetics suggest a mechanism of mutually induced conformational changes, implicating the flexibility of apoGAD65 in its autoantigenicity. Although conformational diversity may provide a mechanism for cofactor-controlled regulation of neurotransmitter biosynthesis, it may also come at a cost of insufficient development of immune self-tolerance that favors the production of GAD65 autoantibodies.
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