PARENT: A Parallel Software Suite for the Calculation of Configurational Entropy in Biomolecular Systems

Accurate estimation of configurational entropy from the <i>in silico</i>-generated biomolecular ensembles, e.g., from molecular dynamics (MD) trajectories, is dependent strongly on exhaustive sampling for physical reasons. This, however, creates a major computational problem for the subsequent estimation of configurational entropy using the Maximum Information Spanning Tree (MIST) or Mutual Information Expansion (MIE) approaches for internal molecular coordinates. In particular, the available software for such estimation exhibits serious limitations when it comes to molecules with hundreds or thousands of atoms, because of its reliance on a serial program architecture. To overcome this problem, we have developed a parallel, hybrid MPI/openMP C++ implementation of MIST and MIE, called PARENT, which is particularly optimized for high-performance computing and provides efficient estimation of configurational entropy in different biological processes (e.g., protein–protein interactions). In addition, PARENT also allows for a detailed mapping of intramolecular allosteric networks. Here, we benchmark the program on a set of 1-μs-long MD trajectories of 10 different protein complexes and their components, demonstrating robustness and good scalability. A direct comparison between MIST and MIE on the same dataset demonstrates a superior convergence behavior for the former approach, when it comes to total simulation length and configurational-space binning

Self-Consistent Framework Connecting Experimental Proxies of Protein Dynamics with Configurational Entropy

The recently developed NMR techniques enable estimation of protein configurational entropy change from the change in the average methyl order parameters. This experimental observable, however, does not directly measure the contribution of intramolecular couplings, protein main-chain motions, or angular dynamics. Here, we carry out a self-consistent computational analysis of the impact of these missing contributions on an extensive set of molecular dynamics simulations of different proteins undergoing binding. Specifically, we compare the configurational entropy change in protein complex formation as obtained by the maximum information spanning tree approximation (MIST), which treats the above entropy contributions directly, and the change in the average NMR methyl and NH order parameters. Our parallel implementation of MIST allows us to treat hard angular degrees of freedom as well as couplings up to full pairwise order explicitly, while still involving a high degree of sampling and tackling molecules of biologically relevant sizes. First, we demonstrate a remarkably strong linear relationship between the total configurational entropy change and the average change in both methyl and backbone-NH order parameters. Second, in contrast to canonical assumptions, we show that the main-chain and angular terms contribute significantly to the overall configurational entropy change and also scale linearly with it. Consequently, linear models starting from the average methyl order parameters are able to capture the contribution of main-chain and angular terms well. After applying the quantum-mechanical harmonic oscillator entropy formalism, we establish a similarly strong linear relationship for X-ray crystallographic B-factors. Finally, we demonstrate that the observed linear relationships remain robust against drastic undersampling and argue that they reflect an intrinsic property of compact proteins. Despite their remarkable strength, however, the above linear relationships yield estimates of configurational entropy change whose accuracy appears to be sufficient for qualitative applications only

Multistate Organization of Transmembrane Helical Protein Dimers Governed by the Host Membrane

Association of transmembrane (TM) helices taking place in the cell membrane has an important contribution to the biological function of bitopic proteins, among which receptor tyrosine kinases represent a typical example and a potent target for medical applications. Since this process depends on a complex interplay of different factors (primary structures of TM domains and juxtamembrane regions, composition and phase of the local membrane environment, etc.), it is still far from being fully understood. Here, we present a computational modeling framework, which we have applied to systematically analyze dimerization of 18 TM helical homo- and heterodimers of different bitopic proteins, including the family of epidermal growth factor receptors (ErbBs). For this purpose, we have developed a novel surface-based modeling approach, which not only is able to predict particular conformations of TM dimers in good agreement with experiment but also provides screening of their conformational heterogeneity. Using all-atom molecular dynamics simulations of several of the predicted dimers in different model membranes, we have elucidated a putative role of the environment in selection of particular conformations. Simulation results clearly show that each particular bilayer preferentially stabilizes one of possible dimer conformations, and that the energy gain depends on the interplay between structural properties of the protein and the membrane. Moreover, the character of protein-driven perturbations of the bilayer is reflected in the contribution of a particular membrane to the free energy gain. We have found that the approximated dimerization strength for ErbBs family can be related to their oncogenic ability

Adaptable Lipid Matrix Promotes Protein–Protein Association in Membranes

The cell membrane is “stuffed” with proteins, whose transmembrane (TM) helical domains spontaneously associate to form functionally active complexes. For a number of membrane receptors, a modulation of TM domains’ oligomerization has been shown to contribute to the development of severe pathological states, thus calling for detailed studies of the atomistic aspects of the process. Despite considerable progress achieved so far, several crucial questions still remain: How do the helices recognize each other in the membrane? What is the driving force of their association? Here, we assess the dimerization free energy of TM helices along with a careful consideration of the interplay between the structure and dynamics of protein and lipids using atomistic molecular dynamics simulations in the hydrated lipid bilayer for three different model systems – TM fragments of glycophorin A, polyalanine and polyleucine peptides. We observe that the membrane driven association of TM helices exhibits a prominent entropic character, which depends on the peptide sequence. Thus, a single TM peptide of a given composition induces strong and characteristic perturbations in the hydrophobic core of the bilayer, which may facilitate the initial “communication” between TM helices even at the distances of 20–30 Å. Upon tight helix–helix association, the immobilized lipids accommodate near the peripheral surfaces of the dimer, thus disturbing the packing of the surrounding. The dimerization free energy of the modeled peptides corresponds to the strength of their interactions with lipids inside the membrane being the lowest for glycophorin A and similarly higher for both homopolymers. We propose that the ability to accommodate lipid tails determines the dimerization strength of TM peptides and that the lipid matrix directly governs their association

Role of Dimerization Efficiency of Transmembrane Domains in Activation of Fibroblast Growth Factor Receptor 3

Mutations in transmembrane (TM) domains of receptor tyrosine kinases are shown to cause a number of inherited diseases and cancer development. Here, we use a combined molecular modeling approach to understand molecular mechanism of effect of G380R and A391E mutations on dimerization of TM domains of human fibroblast growth factor receptor 3 (FGFR3). According to results of Monte Carlo conformational search in the implicit membrane and further molecular dynamics simulations, TM dimer of this receptor is able to form a number of various conformations, which differ significantly by the free energy of association in a full-atom model bilayer. The aforementioned mutations affect dimerization efficiency of TM segments and lead to repopulation of conformational ensemble for the dimer. Particularly, both mutations do not change the dimerization free energy of the predominant (putative “non-active”) symmetric conformation of TM dimer, while affect dimerization efficiency of its asymmetric (“intermediate”) and alternative symmetric (putative “active”) models. Results of our simulations provide novel atomistic prospective of the role of G380 and A391E mutations in dimerization of TM domains of FGFR3 and their consecutive contributions to the activation pathway of the receptor

Antimicrobial Peptides Induce Growth of Phosphatidylglycerol Domains in a Model Bacterial Membrane

We performed microsecond long coarse-grained molecular dynamics simulations to elucidate the lateral structure and domain dynamics of a phosphatidylethanolamine (PE)/phosphatidylglycerol (PG) mixed bilayer (7/3), mimicking the inner membrane of gram-negative bacteria. Specifically, we address the effect of surface bound antimicrobial peptides (AMPs) on the lateral organization of the membrane. We find that, in the absence of the peptides, the minor PG fraction only forms small clusters, but that these clusters grow in size upon binding of the cationic AMPs. The presence of AMPs systematically affects the dynamics and induces long-range order in the structure of PG domains, stabilizing the separation between the two lipid fractions. Our results help in understanding the initial stages of destabilization of cytoplasmic bacterial membranes below the critical peptide concentration necessary for disruption, and provide a possible explanation for the multimodal character of AMP activity

The Conformation of the Epidermal Growth Factor Receptor Transmembrane Domain Dimer Dynamically Adapts to the Local Membrane Environment

The epidermal growth factor receptor (EGFR) family is an important class of receptor tyrosine kinases, mediating a variety of cellular responses in normal biological processes and in pathological states of multicellular organisms. Different modes of dimerization of the human EGFR transmembrane domain (TMD) in different membrane mimetics recently prompted us to propose a novel signal transduction mechanism based on protein–lipid interaction. However, the experimental evidence for it was originally obtained with slightly different TMD fragments used in the two different mimetics, compromising the validity of the comparison. To eliminate ambiguity, we determined the nuclear magnetic resonance (NMR) structure of the bicelle-incorporated dimer of the EGFR TMD fragment identical to the one previously used in micelles. The NMR results augmented by molecular dynamics simulations confirm the mutual influence of the TMD and lipid environment, as is required for the proposed lipid-mediated activation mechanism. They also reveal the possible functional relevance of a subtle interplay between the concurrent processes in the lipid and protein during signal transduction