1,721,093 research outputs found
Structural predictions of HCN/CNG ion channels: Insights on channels' gating
Full text linkEvolution built a membrane around the earliest forms of life in order to isolate them from the external environment. The cell membrane is constituted by two layers of phospholipids, which are molecules having a polar head and non-polar tails. Two films of these molecules are assembled together by hydrophobic forces building a very stable lipid bilayer.
Inserted in this amphiphilic environments are membrane proteins, which have both hydrophobic and hydrophilic regions on their surface. In highly evolved and specified cells this class of proteins carries out a variety of different activities essential for the cell and organism life, like the antibody recognition in lymphocytes and the nervous pulse transmission in neurons.
Although the presence of the membrane helps cells to retain vital ingredients, it prevents the access to necessary ionized substrates and ions, because the hydrophobic core is a high free energy barrier in the diffusion of charged molecules.
Membrane spanning pores are a common feature to ionic channels (Hille, 2001;Chang et al., 1998), and they are presents in different classes of other biological transporter proteins like bacterial porins and aquaporins.
Special membrane proteins, the ionic channels, form holes through the cell membrane, providing a feasible path for ion exchanges
Molecular Modeling of Ion Channels: Structural Predictions
No full textRecent advances in membrane protein crystallography have greatly increased structural information of channels permeating metal ions. Structural bioinformatics techniques and molecular dynamics calculations are providing structural models of ion channels for which the three-dimensional structure is not known. Most of the reported structure prediction studies focus on K(+) channels and are based on the KcsA K(+) channel structure
Structural modeling of G-protein coupled receptors: An overview on automatic web-servers
No full textDespite the significant efforts and discoveries during the last few years in G protein-coupled receptor (GPCR) expression and crystallization, the receptors with known structures to date are limited only to a small fraction of human GPCRs. The lack of experimental three-dimensional structures of the receptors represents a strong limitation that hampers a deep understanding of their function. Computational techniques are thus a valid alternative strategy to model three-dimensional structures. Indeed, recent advances in the field, together with extraordinary developments in crystallography, in particular due to its ability to capture GPCRs in different activation states, have led to encouraging results in the generation of accurate models. This, prompted the community of modelers to render their methods publicly available through dedicated databases and web-servers. Here, we present an extensive overview on these services, focusing on their advantages, drawbacks and their role in successful applications. Future challenges in the field of GPCR modeling, such as the predictions of long loop regions and the modeling of receptor activation states are presented as well
Molecular Mechanics/Coarse-Grained Simulations as a Structural Prediction Tool for GPCRs/Ligand Complexes
No full textA Multimodal Approach for Protein Remote Homology Detection
No full textProtein remote homology detection represents a crucial and challenging task in bioinformatics: even if effective methods appeared in recent years, in several cases a proper characterization of remote evolutionary correlation can not be derived. In such situations, it may be possible that information derived from other sources helps, provided that it is possible to properly integrate such (even partial) information into existing models. In this paper, we provide some evidence that this route is feasible: inspired by the multimodal retrieval literature, we show how it is possible to exploit a simple multimodal approach to improve a model learned from a set of sequences, by using knowledge derived from a partial set of corresponding 3D structures. We investigate (with the SCOP 1.53 benchmark) the suitability of the proposed multimodal scheme, showing that a beneficial effect can be obtained even when a very reduced amount of structures are available. A further detailed analysis on a member of the GPCR superfamily confirms that this multimodal approach can extract information that cannot be obtained from sequence-based techniques
MERMAID: dedicated web server to prepare and run coarse-grained membrane protein dynamics
Full text linkAtomistic molecular dynamics simulations of membrane proteins have been shown to be extremely useful for characterizing the molecular features underlying their function, but require high computational power, limiting the understanding of complex events in membrane proteins, e.g. ion channels gating, GPCRs activation. To overcome this issue, it has been shown that coarse-grained approaches, although requiring less computational power, are still capable of correctly describing molecular events underlying big conformational changes in biological systems. Here, we present the Martini coarse-grained membrane protein dynamics (MERMAID), a publicly available web interface that allows the user to prepare and run coarse-grained molecular dynamics (CGMD) simulations and to analyse the trajectories
Multiscale simulations on human Frizzled and Taste2 GPCRs
No full textRecently, molecular dynamics simulations, from all atom and coarse grained to hybrid methods bridging the two scales, have provided exciting functional insights into class F (Frizzled and Taste2) GPCRs (about 40 members in humans). Findings include: (i) The activation of one member of the Frizzled receptors (FZD4) involves a bending of transmembrane helix TM7 far larger than that in class A GPCRs. (ii) The affinity of an anticancer drug targeting another member (Smoothened receptor) decreases in a specific drug-resistant variant, because the mutation ultimately disrupts the binding cavity and affects TM6. (iii) A novel two-state recognition mechanism explains the very large agonist diversity for at least one member of the Taste2 GPCRs, hTAS2R46
Molecular Mechanics/Coarse-Grained Models
No full textMolecular simulations have proved to be extremely successful in predicting structures and energetics of ligand binding to their target receptors. However standard approaches are challenged when one has to deal with homology models based on templates with low sequence identity. In an effort at facing this challenge we have developed a hybrid molecular mechanics/coarse-grained (MM/CG) simulations approach, aimed at connecting the disparate spatial and temporal scales relevant to complex biological processes. This approach concentrates the efforts in characterizing the binding cavity while renouncing to most of protein details which are likely to be predicted in a rather inaccurate way by bioinformatics techniques. Examples of application of this technique to GPCRs illustrate the power of this approach
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