General Protocol for Constructing Molecular Models of Nanodiscs.

Nanodisc technology is increasingly being applied for structural and biophysical studies of membrane proteins. In this work, we present a general protocol for constructing molecular models of nanodiscs for molecular dynamics simulations. The protocol is written in python and based on geometric equations, making it fast and easy to modify, enabling automation and customization of nanodiscs in silico. The novelty being the ability to construct any membrane scaffold protein (MSP) variant fast and easy given only an input sequence. We validated and tested the protocol by simulating seven different nanodiscs of various sizes and with different membrane scaffold proteins, both circularized and noncircularized. The structural and biophysical properties were analyzed and shown to be in good agreement with previously reported experimental data and simulation studies.

Martini 3: a general purpose force field for coarse-grained molecular dynamics.

The coarse-grained Martini force field is widely used in biomolecular simulations. Here we present the refined model, Martini 3 ( http://cgmartini.nl ), with an improved interaction balance, new bead types and expanded ability to include specific interactions representing, for example, hydrogen bonding and electronic polarizability. The updated model allows more accurate predictions of molecular packing and interactions in general, which is exemplified with a vast and diverse set of applications, ranging from oil/water partitioning and miscibility data to complex molecular systems, involving protein-protein and protein-lipid interactions and material science applications as ionic liquids and aedamers.

A Coarse-Grained Methodology Identifies Intrinsic Mechanisms That Dissociate Interacting Protein Pairs.

We address the problem of triggering dissociation events between proteins that have formed a complex. We have collected a set of 25 non-redundant, functionally diverse protein complexes having high-resolution three-dimensional structures in both the unbound and bound forms. We unify elastic network models with perturbation response scanning (PRS) methodology as an efficient approach for predicting residues that have the propensity to trigger dissociation of an interacting protein pair, using the three-dimensional structures of the bound and unbound proteins as input. PRS reveals that while for a group of protein pairs, residues involved in the conformational shifts are confined to regions with large motions, there are others where they originate from parts of the protein unaffected structurally by binding. Strikingly, only a few of the complexes have interface residues responsible for dissociation. We find two main modes of response: In one mode, remote control of dissociation in which disruption of the electrostatic potential distribution along protein surfaces play the major role; in the alternative mode, mechanical control of dissociation by remote residues prevail. In the former, dissociation is triggered by changes in the local environment of the protein, e.g., pH or ionic strength, while in the latter, specific perturbations arriving at the controlling residues, e.g., via binding to a third interacting partner is required for decomplexation. We resolve the observations by relying on an electromechanical coupling model which reduces to the usual elastic network result in the limit of the lack of coupling. We validate the approach by illustrating the biological significance of top residues selected by PRS on select cases where we show that the residues whose perturbation leads to the observed conformational changes correspond to either functionally important or highly conserved residues in the complex.

Titratable Martini model for constant pH simulations.

In this work, we deliver a proof of concept for a fast method that introduces pH effects into classical coarse-grained (CG) molecular dynamics simulations. Our approach is based upon the latest version of the popular Martini CG model to which explicit proton mimicking particles are added. We verify our approach against experimental data involving several different molecules and different environmental conditions. In particular, we compute titration curves, pH dependent free energies of transfer, and lipid bilayer membrane affinities as a function of pH. Using oleic acid as an example compound, we further illustrate that our method can be used to study passive translocation in lipid bilayers via protonation. Finally, our model reproduces qualitatively the expansion of the macromolecule dendrimer poly(propylene imine) as well as the associated pKa shift of its different generations. This example demonstrates that our model is able to pick up collective interactions between titratable sites in large molecules comprising many titratable functional groups.

Membrane mediated toppling mechanism of the folate energy coupling factor transporter.

Energy coupling factor (ECF) transporters are responsible for the uptake of micronutrients in bacteria and archaea. They consist of an integral membrane unit, the S-component, and a tripartite ECF module. It has been proposed that the S-component mediates the substrate transport by toppling over in the membrane when docking onto an ECF module. Here, we present multi-scale molecular dynamics simulations and in vitro experiments to study the molecular toppling mechanism of the S-component of a folate-specific ECF transporter. Simulations reveal a strong bending of the membrane around the ECF module that provides a driving force for toppling of the S-component. The stability of the toppled state depends on the presence of non-bilayer forming lipids, as confirmed by folate transport activity measurements. Together, our data provide evidence for a lipid-dependent toppling-based mechanism for the folate-specific ECF transporter, a mechanism that might apply to other ECF transporters.

High-Order Epistasis in Catalytic Power of Dihydrofolate Reductase Gives Rise to a Rugged Fitness Landscape in the Presence of Trimethoprim Selection.

Evolutionary fitness landscapes of several antibiotic target proteins have been comprehensively mapped showing strong high-order epistasis between mutations, but understanding these effects at the biochemical and structural levels remained open. Here, we carried out an extensive experimental and computational study to quantitatively understand the evolutionary dynamics of Escherichia coli dihydrofolate reductase (DHFR) enzyme in the presence of trimethoprim-induced selection. To facilitate this, we developed a new in vitro assay for rapidly characterizing DHFR steady-state kinetics. Biochemical and structural characterization of resistance-conferring mutations targeting a total of ten residues spanning the substrate binding pocket of DHFR revealed distinct changes in the catalytic efficiencies of mutated DHFR enzymes. Next, we measured biochemical parameters (Km, Ki, and kcat) for a mutant library carrying all possible combinations of six resistance-conferring DHFR mutations and quantified epistatic interactions between them. We found that the high-order epistasis in catalytic power of DHFR (kcat and Km) creates a rugged fitness landscape under trimethoprim selection. Taken together, our data provide a concrete illustration of how epistatic coupling at the level of biochemical parameters can give rise to complex fitness landscapes, and suggest new strategies for developing mutant specific inhibitors.

Emerging Diversity in Lipid-Protein Interactions.

Membrane lipids interact with proteins in a variety of ways, ranging from providing a stable membrane environment for proteins to being embedded in to detailed roles in complicated and well-regulated protein functions. Experimental and computational advances are converging in a rapidly expanding research area of lipid-protein interactions. Experimentally, the database of high-resolution membrane protein structures is growing, as are capabilities to identify the complex lipid composition of different membranes, to probe the challenging time and length scales of lipid-protein interactions, and to link lipid-protein interactions to protein function in a variety of proteins. Computationally, more accurate membrane models and more powerful computers now enable a detailed look at lipid-protein interactions and increasing overlap with experimental observations for validation and joint interpretation of simulation and experiment. Here we review papers that use computational approaches to study detailed lipid-protein interactions, together with brief experimental and physiological contexts, aiming at comprehensive coverage of simulation papers in the last five years. Overall, a complex picture of lipid-protein interactions emerges, through a range of mechanisms including modulation of the physical properties of the lipid environment, detailed chemical interactions between lipids and proteins, and key functional roles of very specific lipids binding to well-defined binding sites on proteins. Computationally, despite important limitations, molecular dynamics simulations with current computer power and theoretical models are now in an excellent position to answer detailed questions about lipid-protein interactions.

Mechanisms by Which Salt Concentration Moderates the Dynamics of Human Serum Transferrin.

The dynamical and thermodynamic behavior of human transferrin (hTf) protein in saline aqueous solution of various concentrations is studied. hTf is an essential transport protein circulating iron in the blood and delivering it to tissues. It displays highly pH dependent cooperativity between the two lobes, each carrying an iron, and forms a tight complex with the receptor during endocytosis, eventually recycled to the serum after iron release. Molecular dynamics simulations are used to investigate the effects of the amount of salt on protein conformation and dynamics to analyze the structure-function relationship in free hTf at serum pH. To monitor the ionic strength dependence, four different ionic concentrations, 0, 50, 130, and 210 mM NaCl for two protonation states of the iron coordination site is considered. Two mechanisms by which salt affects hTf are disclosed. In the totally closed state where iron coordinating tyrosines are deprotonated, the addition of even 50 mM of salt alters the electrostatic potential distribution around the protein, opening energetic pathways for tyrosine protonation from nearby charged residues as a required first step for iron release. Once domain opening is observed, conformational plasticity renders the iron binding site more accessible by the solvent. At this second stage of iron release, R124 in the N-lobe is identified as kinetically significant anion binding site that accommodates chloride ions and allosterically communicates with the iron binding residues. Opening motions are maximized at 150 mM IS in the N-lobe, and at 210 mM in the C-lobe. The extra mobility in the latter is thought to preclude binding of hTf to its receptor. Thus, the physiological IS is optimal for exposing iron for release from hTf. However, the calculated binding affinities of iron show that even in the most open conformations, iron dissociation needs to be accompanied by chelators.

Increased substrate affinity in the Escherichia coli L28R dihydrofolate reductase mutant causes trimethoprim resistance.

Dihydrofolate reductase (DHFR) is a ubiquitous enzyme with an essential role in cell metabolism. DHFR catalyzes the reduction of dihydrofolate to tetrahydrofolate, which is a precursor for purine and thymidylate synthesis. Several DHFR targeting antifolate drugs including trimethoprim, a competitive antibacterial inhibitor, have therefore been developed and are clinically used. Evolution of resistance against antifolates is a common public health problem rendering these drugs ineffective. To combat the resistance problem, it is important to understand resistance-conferring changes in the DHFR structure and accordingly develop alternative strategies. Here, we structurally and dynamically characterize Escherichia coli DHFR in its wild type (WT) and trimethoprim resistant L28R mutant forms in the presence of the substrate and its inhibitor trimethoprim. We use molecular dynamics simulations to determine the conformational space, loop dynamics and hydrogen bond distributions at the active site of DHFR for the WT and the L28R mutant. We also report their experimental kcat, Km, and Ki values, accompanied by isothermal titration calorimetry measurements of DHFR that distinguish enthalpic and entropic contributions to trimethoprim binding. Although mutations that confer resistance to competitive inhibitors typically make enzymes more promiscuous and decrease affinity to both the substrate and the inhibitor, strikingly, we find that the L28R mutant has a unique resistance mechanism. While the binding affinity differences between the WT and the mutant for the inhibitor and the substrate are small, the newly formed extra hydrogen bonds with the aminobenzoyl glutamate tail of DHF in the L28R mutant leads to increased barriers for the dissociation of the substrate and the product. Therefore, the L28R mutant indirectly gains resistance by enjoying prolonged binding times in the enzyme-substrate complex. While this also leads to slower product release and decreases the catalytic rate of the L28R mutant, the overall effect is the maintenance of a sufficient product formation rate. Finally, the experimental and computational analyses together reveal the changes that occur in the energetic landscape of DHFR upon the resistance-conferring L28R mutation. We show that the negative entropy associated with the binding of trimethoprim in WT DHFR is due to water organization at the binding interface. Our study lays the framework to study structural changes in other trimethoprim resistant DHFR mutants.

Predicting long term cooperativity and specific modulators of receptor interactions in human transferrin from dynamics within a single microstate.

Transferrin (Tf) is an essential transport protein circulating iron in the blood and delivering it to tissues. It displays highly pH dependent cooperativity between the two lobes each carrying an iron, and forms a tight complex with the receptor during endocytosis and recycling back to the serum. We explore short-term dynamics within selected microstates of human Tf to identify functional information relevant to long-term dynamics. While the variance-covariance matrix delineates cooperativity between the domains of Tf at serum pH which is lost at endosomal pH, its decomposition does not bring about additional information. We employ perturbation-response scanning (PRS) to extract essential components that contribute to a pre-selected conformational change. Since large-scale motions may require key residues to mediate correlated motions between different regions of the protein, we use PRS to predict those involved in the conformational transitions between the iron bound and free hTf. Physiological and endosomal conditions are mimicked to identify critical residues for holo → apo and apo → holo transitions. Iron binding motions are mainly orchestrated by residues at the synergistic anion uptake sites, a finding also corroborated by additional molecular dynamics simulations where these sites are perturbed by docking the anion. Iron release is not readily accessible at serum pH, while at endosomal pH single residue perturbations on any residue encourage the large transition that involves a complex twisting of the two domains relative to each other, simultaneously opening both lobes. The pH dependent change in the dynamics is traced to the altered electrostatic potential distribution along the surface. The examination of local dynamics in the hTf-receptor pair reveals cooperativity in the quaternary structure and explains resistance to iron release in the complex. Meanwhile, the analysis of the hTf complex with a bacterial receptor that has evolved to sequester iron identifies two regions contacting rapidly evolving residues that mechanically manipulate dissociation from the pathogen.

Detailed molecular dynamics simulations of human transferrin provide insights into iron release dynamics at serum and endosomal pH.

Human serum transferrin (hTf) transports ferric ions in the blood stream and delivers them to cells via receptor-mediated endocytosis. hTf is folded into two homologous lobes; we utilize three of the available crystal structures delineating large conformational changes involved in iron binding/dissociation. We address the problems of whether the release process follows the same trend at serum (~7.4) and endosomal (~5.6) pH, and if there is communication between the lobes. In the absence of the transferrin receptor, we study the dynamics of the full structure as well as the separate lobes in different closed, partially open, and open conformations under neutral and endosomal pH conditions. Results corroborate those experimental observations underscoring the distinguishing effect of pH on the dynamics of hTf. Furthermore, in a total of 2 µs molecular dynamics simulations, residue fluctuations elucidate the cross talk between the lobes correlated by the peptide linker bridging them at serum pH, while their correlations are lost under endosomal conditions. At serum pH, interplay between relative mobility of the lobes is correlated with iron release rates, rendering the initial conformational change an important contributor to the dynamics under these conditions. Interestingly, C-lobe opening lags behind that of the N-lobe as long as there is at least one iron bound, making the more stable C-lobe an attractive target for recognition by receptors. At endosomal pH, both lobes readily open, making irons available for delivery.

Perturbation response scanning specifies key regions in subtilisin serine protease for both function and stability.

Can one infer the amino acids of the enzymes that are responsible for the stability or the level of the catalytic activity by computationally experimenting on the inhibited enzyme in the enzyme-inhibitor complex? In this article, we answer this question positively both by designing molecular dynamics simulations and by devising coarse-grained methodologies on the subtilisin serine protease. Both methodologies are based on the cross-correlations of the fluctuations of the residues, obtained either by monitoring the trajectories from the simulation or by constructing the inverse Laplacian of the elastic network model, of the complex. A perturbation scanning is applied to the complex using these correlations. The results indicate that the two methods almost point out the same regions on the flexible of the enzyme. These regions are: (i) 50-61, (ii) 155-164 and (iii) 192-194, all of which are designated to be important by experimental studies in the literature.