Protein folding on the ribosome studied using NMR spectroscopy

NMR spectroscopy is a powerful tool for the investigation of protein folding and misfolding, providing a characterization of molecular structure, dynamics and exchange processes, across a very wide range of timescales and with near atomic resolution. In recent years NMR methods have also been developed to study protein folding as it might occur within the cell, in a de novo manner, by observing the folding of nascent polypeptides in the process of emerging from the ribosome during synthesis. Despite the 2.3 MDa molecular weight of the bacterial 70S ribosome, many nascent polypeptides, and some ribosomal proteins, have sufficient local flexibility that sharp resonances may be observed in solution-state NMR spectra. In providing information on dynamic regions of the structure, NMR spectroscopy is therefore highly complementary to alternative methods such as X-ray crystallography and cryo-electron microscopy, which have successfully characterized the rigid core of the ribosome particle. However, the low working concentrations and limited sample stability associated with ribosome-nascent chain complexes means that such studies still present significant technical challenges to the NMR spectroscopist. This review will discuss the progress that has been made in this area, surveying all NMR studies that have been published to date, and with a particular focus on strategies for improving experimental sensitivity

A Continuum Poisson-Boltzmann Model for Membrane Channel Proteins

Membrane proteins constitute a large portion of the human proteome and perform a variety of important functions as membrane receptors, transport proteins, enzymes, signaling proteins, and more. The computational studies of membrane proteins are usually much more complicated than those of globular proteins. Here we propose a new continuum model for Poisson-Boltzmann calculations of membrane channel proteins. Major improvements over the existing continuum slab model are as follows: 1) The location and thickness of the slab model are fine-tuned based on explicit-solvent MD simulations. 2) The highly different accessibility in the membrane and water regions are addressed with a two-step, two-probe grid labeling procedure, and 3) The water pores/channels are automatically identified. The new continuum membrane model is optimized (by adjusting the membrane probe, as well as the slab thickness and center) to best reproduce the distributions of buried water molecules in the membrane region as sampled in explicit water simulations. Our optimization also shows that the widely adopted water probe of 1.4 {\AA} for globular proteins is a very reasonable default value for membrane protein simulations. It gives an overall minimum number of inconsistencies between the continuum and explicit representations of water distributions in membrane channel proteins, at least in the water accessible pore/channel regions that we focus on. Finally, we validate the new membrane model by carrying out binding affinity calculations for a potassium channel, and we observe a good agreement with experiment results.Comment: 40 pages, 6 figures, 5 table

Using a desktop grid to support simulation modelling

Simulation is characterized by the need to run multiple sets of computationally intensive experiments. We argue that Grid computing can reduce the overall execution time of such experiments by tapping into the typically underutilized network of departmental desktop PCs, collectively known as desktop grids. Commercial-off-the-shelf simulation packages (CSPs) are used in industry to simulate models. To investigate if Grid computing can benefit simulation, this paper introduces our desktop grid, WinGrid, and discusses how this can be used to support the processing needs of CSPs. Results indicate a linear speed up and that Grid computing does indeed hold promise for simulation

Simulating chemistry using quantum computers

The difficulty of simulating quantum systems, well-known to quantum chemists, prompted the idea of quantum computation. One can avoid the steep scaling associated with the exact simulation of increasingly large quantum systems on conventional computers, by mapping the quantum system to another, more controllable one. In this review, we discuss to what extent the ideas in quantum computation, now a well-established field, have been applied to chemical problems. We describe algorithms that achieve significant advantages for the electronic-structure problem, the simulation of chemical dynamics, protein folding, and other tasks. Although theory is still ahead of experiment, we outline recent advances that have led to the first chemical calculations on small quantum information processors.Comment: 27 pages. Submitted to Ann. Rev. Phys. Che

Grid-enabling FIRST: Speeding up simulation applications using WinGrid

The vision of grid computing is to make computational power, storage capacity, data and applications available to users as readily as electricity and other utilities. Grid infrastructures and applications have traditionally been geared towards dedicated, centralized, high performance clusters running on UNIX flavour operating systems (commonly referred to as cluster-based grid computing). This can be contrasted with desktop-based grid computing which refers to the aggregation of non-dedicated, de-centralized, commodity PCs connected through a network and running (mostly) the Microsoft Windowstrade operating system. Large scale adoption of such Windowstrade-based grid infrastructure may be facilitated via grid-enabling existing Windows applications. This paper presents the WinGridtrade approach to grid enabling existing Windowstrade based commercial-off-the-shelf (COTS) simulation packages (CSPs). Through the use of a case study developed in conjunction with Ford Motor Company, the paper demonstrates how experimentation with the CSP Witnesstrade and FIRST can achieve a linear speedup when WinGridtrade is used to harness idle PC computing resources. This, combined with the lessons learned from the case study, has encouraged us to develop the Web service extensions to WinGridtrade. It is hoped that this would facilitate wider acceptance of WinGridtrade among enterprises having stringent security policies in place

MGOS: A library for molecular geometry and its operating system

The geometry of atomic arrangement underpins the structural understanding of molecules in many fields. However, no general framework of mathematical/computational theory for the geometry of atomic arrangement exists. Here we present "Molecular Geometry (MG)'' as a theoretical framework accompanied by "MG Operating System (MGOS)'' which consists of callable functions implementing the MG theory. MG allows researchers to model complicated molecular structure problems in terms of elementary yet standard notions of volume, area, etc. and MGOS frees them from the hard and tedious task of developing/implementing geometric algorithms so that they can focus more on their primary research issues. MG facilitates simpler modeling of molecular structure problems; MGOS functions can be conveniently embedded in application programs for the efficient and accurate solution of geometric queries involving atomic arrangements. The use of MGOS in problems involving spherical entities is akin to the use of math libraries in general purpose programming languages in science and engineering. (C) 2019 The Author(s). Published by Elsevier B.V

GraphCombEx: A Software Tool for Exploration of Combinatorial Optimisation Properties of Large Graphs

We present a prototype of a software tool for exploration of multiple combinatorial optimisation problems in large real-world and synthetic complex networks. Our tool, called GraphCombEx (an acronym of Graph Combinatorial Explorer), provides a unified framework for scalable computation and presentation of high-quality suboptimal solutions and bounds for a number of widely studied combinatorial optimisation problems. Efficient representation and applicability to large-scale graphs and complex networks are particularly considered in its design. The problems currently supported include maximum clique, graph colouring, maximum independent set, minimum vertex clique covering, minimum dominating set, as well as the longest simple cycle problem. Suboptimal solutions and intervals for optimal objective values are estimated using scalable heuristics. The tool is designed with extensibility in mind, with the view of further problems and both new fast and high-performance heuristics to be added in the future. GraphCombEx has already been successfully used as a support tool in a number of recent research studies using combinatorial optimisation to analyse complex networks, indicating its promise as a research software tool

Disc antenna enhanced infrared spectroscopy: From felf-assembled monolayers to membrane proteins

Plasmonic surfaces have emerged as a powerful platform for biomolecular sensing applications and can be designed to optimize the plasmonic resonance for probing molecular vibrations at utmost sensitivity. Here, we present a facile procedure to generate metallic microdisc antenna arrays that are employed in surface-enhanced infrared absorption (SEIRA) spectroscopy of biomolecules. Transmission electron microscopy (TEM) grids are used as shadow mask deployed during physical vapor deposition of gold. The resulting disc-shaped antennas exhibit enhancement factors of the vibrational bands of 4 × 104 giving rise to a detection limit <1 femtomol (10–15 mol) of molecules. Surface-bound monolayers of 4-mercaptobenzoic acid show polyelectrolyte behavior when titrated with cations in the aqueous medium. Conformational rigidity of the self-assembled monolayer is validated by density functional theory calculations. The membrane protein sensory rhodopsin II is tethered to the disc antenna arrays and is fully functional as inferred from the light-induced SEIRA difference spectra. As an advance to previous studies, the accessible frequency range is improved and extended into the fingerprint region