1,721,161 research outputs found
Challenges and perspective in biomolecular simulations: from the atomistic picture to multiscale modeling
Full text linkWe review the state-of-the-art in computational molecular simulations for biological systems. We limit our discussion to three fields: all-atom simulations, coarse-grained models, and novel multiscale approaches. While molecular dynamics simulations are broadly used in the community, major efforts continue to be spent in pushing the boundaries in both size and time limits as well as in improvement of commonly-used force fields. Parallel to all-atom simulations, in recent times the development of coarse-grained methods has flourished. Such techniques are able to describe biophysical features of macromolecular complexes through the use of simplified model potentials. Finally, multiscale models are introduced, giving some perspective about possible future developments in this new field.UPDALP
Topologically based multipolar reconstruction of electrostatic interactions in multiscale simulations of proteins
No full textWe present a new method to incorporate electrostatic interactions in coarse-grained representations of proteins. The model is based on a topologically reconstructed multipolar expansion of the all-atom centers of charge, specifically of the backbone dipoles and the polar or charged side chains. The reliability of the model is checked by studying different test cases, namely protein−cofactor/substrate interactions, protein large conformational changes, and protein−protein complexes. In all cases, the model quantitatively reproduces the all-atom electrostatic field in both a static and a dynamic framework. The model is of general applicability and can be used to improve both full coarse-grained simulations and hybrid all-atom/coarse-grained multiscale approaches.UPDALP
A Nonradial Coarse-Grained Potential for Proteins Produces Naturally Stable Secondary Structure Elements
No full textWe introduce a nonradial potential term for coarse-grained (CG) molecular simulations of proteins. This term mimics the backbone dipole−dipole interactions and accounts for the needed directionality to form stable folded secondary structure elements. We show that α-helical and β-sheet peptide chains are correctly described in dynamics without the need of introducing any a priori bias potentials or ad hoc parametrizations, which limit broader applicability of CG simulations for proteins. Moreover, our model is able to catch the formation of supersecondary structural motifs, like transitions from long single α-helices to helix−coil−helix or β-hairpin assemblies. This novel scheme requires the structural information of Cα beads only; it does not introduce any additional degrees of freedom to the system and has a general formulation, which allows it to be used in synergy with various CG protocols, leading to an improved description of the structural and dynamic properties of protein assemblies and networks.UPDALP
A dimerization interface mediated by functionally critical residues creates interfacial disulfide bonds and copper sites in CueP
Full text linkCueP confers bacterial copper resistance in the periplasm, particularly under anaerobic conditions, through an unknown mechanism. The only available structure and limited solution data suggest that CueP forms noncovalent dimers in solution, whereas sequence conservation suggests important roles for three cysteines and two histidines as copper ligands. Here we report evidence of a dimerization equilibrium mediated by a newly identified interface of functional relevance, which occludes internal copper sites and disulfide bonds but allows for intra- and interchain disulfide bonding, an extensive disulfide relay, and interfacial copper sites. Our results suggest a role for CueP linking redox-state sensing and copper detoxification.Fil: Abriata, Luciano Andres. Swiss Institute Of Bioinformatics, Lausanne; SuizaFil: Pontel, Lucas Blas. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Instituto de Biología Molecular y Celular de Rosario; ArgentinaFil: Vila, Alejandro Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Instituto de Biología Molecular y Celular de Rosario; ArgentinaFil: Dal Peraro, Matteo. Swiss Institute Of Bioinformatics, Lausanne; SuizaFil: Soncini, Fernando Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Instituto de Biología Molecular y Celular de Rosario; Argentin
Characterization of Protein-Membrane Interfaces through a Synergistic Computational-Experimental Approach
No full textThe characterization of biological interfaces is widely recognized as one of the main challenges for modern biology. In particular, biological membranes are nowadays known to be an active environment that allows membrane proteins to perform their work and modulates their function. Integral and peripheral membrane proteins constitute 1/3 of the human proteome, and account for about 50% of the targets
of modern medicinal drugs. Despite their remarkable role, their interplay with the membrane is often poorly characterized, mainly because
of the limits that the currently available experimental techniques encounter when treating hydrophobic environments. In particular, peripheral membrane proteins are often studied in their soluble version: this approach is highly limiting, as the interaction with the membrane is essential for the activity of these biomolecules.
Here, we show the potential of a combined computational-experimental approach in order to overcome the aforementioned limits. In
particular, we use molecular modeling to study two peripheral membrane proteins of interest, and successively design ad hoc wet lab experiments to verify the outcomes and predictions of the simulations. This approach allows to bypass the technical limits and high costs of the wet lab techniques, by guiding the experiments with the data of the computational simulations.
We focused our attention on the following peripheral membrane proteins:
New Delhi metallo-beta-lactamase (NDM-1). NDM-1 is a bacterial enzyme that causes antibiotic resistance. Within the class of metallo-beta-lactamases, it represents the most serious threat to global health. The larger resistance of NDM-1 with respect to other proteins of the same class, has been linked to its post-translational modification, which connects it to the outer bacterial membrane of Gram-negative bacteria: this event can significantly increase the chances of NDM-1 to spread through the infection through vesicles excretion. In the present work, we elucidated the mechanistic aspects of the NDM-1/bacterial membrane interaction, and identified the features that contribute to the efficiency of this mechanism.
Golgi phosphorylated protein 3 (Golph3). Golph3 is a peripheral membrane protein present at the Golgi apparatus of most eukaryotic cells. Its normal function consists in binding glycosylating enzymes, and transport them through the Golgi cisternae. In humans, Golph3 has been found to be overexpressed in several forms of cancer: however, no Golph3 inhibitors are currently present in the pharmaceutical market. This is mainly due to the lack of structural information regarding the molecular mechanism of Golph3. Here, we clarify the features of Golph3 that allow it to bind to the Golgi, and elucidate the mechanism of membrane binding. We also propose a recognition mechanism between Golph3 and the glycoenzymes, based on events predicted by the computer simulations.
Overall, in the present work we demonstrate the potential of computational-experimental approaches in structural biology, and in particular
in the study of peripheral membrane proteins. We show that a combined approach constitutes the best way of overcoming the limits of each
technique, and we discuss the repercussions on the study of systems of biological interest.UPDALPE1UPDALP
Constrained optimization applied to multiscale integrative modeling
Full text linkMultiscale integrative modeling stands at the intersection between experimental and computational techniques to predict the atomistic structures of important macromolecules. In the integrative modeling process, the experimental information is often integrated with energy potential and macromolecular substructures in order to derive realistic structural models. This heterogeneous information is often combined into a global objective function that quantifies the quality of the structural models and that is minimized through optimization. In order to balance the contribution of the relative terms concurring to the global function, weight constants are assigned to each term through a computationally demanding process. In order to alleviate this common issue, we suggest to switch from the traditional paradigm of using a single unconstrained global objective function to a constrained optimization scheme. The work presented in this thesis describes the different applications and methods associated with the development of a general constrained optimization protocol for multiscale integrative modeling. The initial implementation concerned the prediction of symmetric macromolecular assemblies throught the incorporation of a recent efficient constrained optimizer nicknamed mViE (memetic Viability Evolution) to our integrative modeling protocol power (parallel optimization workbench to enhance resolution). We tested this new approach through rigorous comparisons against other state-of-the-art integrative modeling methods on a benchmark set of solved symmetric macromolecular assemblies. In this process, we validated the robustness of the constrained optimization method by obtaining native-like structural models. This constrained optimization protocol was then applied to predict the structure of the elusive human Huntingtin protein. Due to the fact that little structural information was available when the project was initiated, we integrated information from secondary structure prediction and low-resolution experiments, in the form of cryo-electron microscopy maps and crosslinking mass spectrometry data, in order to derive a structural model of Huntingtin. The structure resulting from such integrative modeling approach was used to derive dynamic information about Huntingtin protein. At a finer level of resolution, the constrained optimization protocol was then applied to dock small molecules inside the binding site of protein targets. We converted the classical molecular docking problem from an unconstrained single objective optimization to a constrained one by extracting local and global constraints from pre-computed energy grids. The new approach was tested and validated on standard ligand-receptor benchmark sets widely used by the molecular docking community, and showed comparable results to state-of-the-art molecular docking programs. Altogether, the work presented in this thesis proposed improvements in the field of multiscale integrative modeling which are reflected both in the quality of the models returned by the new constrained optimization protocol and in the simpler way of treating the uncorrelated terms concurring to the global scoring scheme to estimate the quality of the models.UPDALP
Characterization of Coenzyme Q Biosynthesis Proteins through Integrative Modeling at the Protein-Membrane Interface
Full text linkIntegral and peripheral membrane proteins account for one-third of the human proteome, and they are estimated to represent the target for over 50% of modern medicinal drugs. Despite their central role in medicine, the complex, heterogeneous and dynamic nature of biological membranes complicates the investigation of their mechanism of action by both experimental and computational techniques. Among the different membrane bound compartments in eukaryotic cells, mitochondria are highly complex in form and function, and they harbor a unique proteome that remains largely unexplored. A growing number of inherited metabolic diseases are associated with mitochondrial dysfunction, which necessitates the structural and functional elucidation of mitochondrial proteins. In this thesis, we combine experimental and computational methods to explore the activity of COQ8 and COQ9, two functionally elusive proteins of the biosynthetic complex that produces coenzyme Q, a redox-active lipid component of the mitochondrial electron transport chain.
(i) Conserved Lipid Modulation of Ancient Kinase-Like UbiB Family Member COQ8.
We demonstrate that COQ8 has an ATPase function that is activated when it specifically associates with cardiolipin-containing membranes. We identify its interaction surface with the inner mitochondrial membrane, which gives hints about the possible interaction surfaces with other members of the coenzyme Q synthesis machinery and has implications on how it mediates functional interactions with lipids. Collectively, this work reveals how the positioning of COQ8 on the inner mitochondrial membrane is key to its activation, and therefore advances our understanding of the COQ8 function.
(ii) Membrane, Lipid, and Protein Interactions of Coenzyme Q Biosynthesis Protein COQ9.
We explore the lipid binding activity of COQ9, and we reveal that COQ9 repurposes an ancient bacterial fold to selectively bind aromatic isoprenes, including CoQ intermediates that reside within the bilayer. We elucidate the mechanistic details of its membrane binding process, by which COQ9 warps the membrane surface and creates a tightly sealed hydrophobic region to access its lipid cargo. Finally, we establish a potential molecular interface between COQ9 and COQ7, the enzyme that catalyzes the penultimate step in CoQ biosynthesis, suggesting a model whereby COQ9 presents intermediates to CoQ enzymes to overcome the hydrophobic barrier of the membrane. Collectively, our results provide a mechanism for how a lipid binding protein might access, select, and extract specific cargo from a membrane and present it to a peripheral membrane enzyme.
In conclusion, our work is a good illustration of the interplay between experiment and modeling in protein research and specifically in understanding how proteins perform their action in direct synergy with membrane environments. We anticipate our integrative methodologies and mechanistic findings will prove relevant to other membrane proteins, whose fine functional modulation at the membrane-water interface has been historically challenging to characterize.UPDALPE1UPDALP
Molecular Modeling of Membrane Embedded Proteins
Full text linkOver the past years, molecular modeling and simulation techniques have had a major impact on experimental life sciences. They are capable of providing accurate insight into microscopic mechanisms, which are usually difficult to investigate experimentally. Moreover, the integration of experimental data with molecular modeling appears to be a promising strategy to better understand complex biological processes. In this thesis, molecular dynamics simulation has been used in combination with experimental data to investigate two transmembrane proteins: (i) the bacterial chemoreceptor PhoQ and (ii) the Amyloid Precursor Protein (APP). (i) Bacterial two-component system PhoQ and bacterial membranes. Two-component systems (TCSs) are signaling complexes essential for bacterial survival and virulence. PhoQ is the histidine kinase chemoreceptor of the PhoQ-PhoP tandem machine that detects the concentration of cationic species at the inner membrane of Gram-negative bacteria. A full understanding of the PhoQ signal transduction mechanism is currently hindered by the lack of a complete atomistic structure. In this thesis project, the first structural model of the transmembrane (TM) portion of PhoQ from Escherichia coli was assembled, by using molecular simulations integrated with cross-linking disulfide scanning data. Its structural and dynamic features induce a concerted displacement of the TM helices at the periplasmic side, which modulates a rotation at the cytoplasmic end. This supports the idea that signal transduction is promoted through a combination of scissoring and rotational movements of the TM helices. Knowledge of this complex mechanism is essential in order to understand how the chemical stimuli sensed by the periplasmic sensor domain trigger, via the relay of the HAMP domain, the histidine auto-phosphorylation and kinase/phosphatase activity at the cytoplasmic end. The PhoQ sensor domain lies in close proximity to the membrane. Interaction with anionic lipids, such as phosphophatidylglycerols (PG) and cardiolipins (CL), are thought to play a key role in PhoQ activity. Present in bacterial and mitochondrial membranes, cardiolipins have a unique dimeric structure, which carries up to two charges, i.e. one per phosphate group, and under physiological conditions, can be unprotonated or singly protonated. Exhaustive models and characterization of cardiolipins are to-date scarce; therefore an ab initio parameterization of cardiolipin species for molecular simulation consistent with commonly used force fields is proposed here. Molecular dynamics (MD) simulations based on these models indicate a protonation-dependent lipid packing. A noteworthy interaction with solvating mono- and divalent cations is also observed. The proposed models will contribute to the biophysical and biochemical characterizations of bacterial and mitochondrial membranes and membrane-embedded proteins. (ii) Structural and dynamic properties of the Amyloid Precursor Protein. The Amyloid Precursor Protein (APP) is a type I membrane glycoprotein present at the neuronal synapsis. The proteolytic cleavage of its C-terminal segment produces amyloid-β (Aβ) peptides of different lengths, the deposition of which is an early indicator of Alzheimer"s disease (AD). Recently, the backbone structure of the APP transmembrane (TM) domain in detergent micelles was determined by nuclear magnetic resonance (NMR, independently by two different experimental groups). The TM conformations of these two structures are however markedly different. One is characterized by a highly kinked α-helix, whereas the other is mainly straight. Molecular dynamics simulations showed that the APP TM region is highly flexible and its secondary structure is influenced by the surrounding lipid environment. The size of the embedding detergent micelles strongly affects the conformation of the APP α-helix, with solvation being the main driving force for the development of a helical curvature. Once embedded in a membrane bilayer, APP systematically prefers a straight helical conformation. This is also confirmed when analyzing in silico the atomistic APP population observed in double electron-electron resonance (DEER) spectroscopy. In summary, the APP transmembrane domain is highly flexible due to the presence of glycine residues and can readily respond to the lipid environment, a property that might be critical for proteolytic processing by γ-secretase enzymes. The presented thesis work clearly shows how molecular simulations and their interplay with available experimental input can help advance the understanding of the mechanism of complex biological systems and processes on a molecular scale. These results, in particular, go well beyond the current understanding of the functioning of two transmembrane proteins relevant for human health. Furthermore, the computational approaches and procedures developed in these projects will hopefully promote novel integrated strategies for investigating biological systems.UPDALP
- …
