907 research outputs found
Ab initio RNA folding
RNA molecules are essential cellular machines performing a wide variety of
functions for which a specific three-dimensional structure is required. Over
the last several years, experimental determination of RNA structures through
X-ray crystallography and NMR seems to have reached a plateau in the number of
structures resolved each year, but as more and more RNA sequences are being
discovered, need for structure prediction tools to complement experimental data
is strong. Theoretical approaches to RNA folding have been developed since the
late nineties when the first algorithms for secondary structure prediction
appeared. Over the last 10 years a number of prediction methods for 3D
structures have been developed, first based on bioinformatics and data-mining,
and more recently based on a coarse-grained physical representation of the
systems. In this review we are going to present the challenges of RNA structure
prediction and the main ideas behind bioinformatic approaches and physics-based
approaches. We will focus on the description of the more recent physics-based
phenomenological models and on how they are built to include the specificity of
the interactions of RNA bases, whose role is critical in folding. Through
examples from different models, we will point out the strengths of
physics-based approaches, which are able not only to predict equilibrium
structures, but also to investigate dynamical and thermodynamical behavior, and
the open challenges to include more key interactions ruling RNA folding.Comment: 28 pages, 18 figure
Stochastic level-set method for shape optimisation
We present a new method for stochastic shape optimisation of engineering
structures. The method generalises an existing deterministic scheme, in which
the structure is represented and evolved by a level-set method coupled with
mathematical programming. The stochastic element of the algorithm is built on
the methods of statistical mechanics and is designed so that the system
explores a Boltzmann-Gibbs distribution of structures. In non-convex
optimisation problems, the deterministic algorithm can get trapped in local
optima: the stochastic generalisation enables sampling of multiple local
optima, which aids the search for the globally-optimal structure. The method is
demonstrated for several simple geometrical problems, and a proof-of-principle
calculation is shown for a simple engineering structure.Comment: 17 pages, 10 fig
Computation of protein geometry and its applications: Packing and function prediction
This chapter discusses geometric models of biomolecules and geometric
constructs, including the union of ball model, the weigthed Voronoi diagram,
the weighted Delaunay triangulation, and the alpha shapes. These geometric
constructs enable fast and analytical computaton of shapes of biomoleculres
(including features such as voids and pockets) and metric properties (such as
area and volume). The algorithms of Delaunay triangulation, computation of
voids and pockets, as well volume/area computation are also described. In
addition, applications in packing analysis of protein structures and protein
function prediction are also discussed.Comment: 32 pages, 9 figure
Physics of thick polymers
We present the results of analytic calculations and numerical simulations of
the behaviour of a new class of chain molecules which we call thick polymers.
The concept of the thickness of such a polymer, viewed as a tube, is
encapsulated by a special three body interaction and impacts on the behaviour
both locally and non-locally. When thick polymers undergo compaction due to an
attractive self-interaction, we find a new type of phase transition between a
compact phase and a swollen phase at zero temperature on increasing the
thickness. In the vicinity of this transition, short tubes form space filling
helices and sheets as observed in protein native state structures. Upon
increasing the chain length, or the number of chains, we numerically find a
crossover from secondary structure motifs to a quite distinct class of
structures akin to the semi-crystalline phase of polymers or amyloid fibers in
polypeptides.Comment: 41 pages, 20 figures. Accepted for publication in J. Pol. Sci.
Molecular dynamics-based approaches for enhanced sampling of long-time, large-scale conformational changes in biomolecules
The rugged energy landscape of biomolecules together with shortcomings of traditional molecular dynamics (MD) simulations require specialized methods for capturing large-scale, long-time configurational changes along with chemical dynamics behavior. In this report, MD-based methods for biomolecules are surveyed, involving modification of the potential, simulation protocol, or algorithm as well as global reformulations. While many of these methods are successful at probing the thermally accessible configuration space at the expense of altered kinetics, more sophisticated approaches like transition path sampling or Markov chain models are required to obtain mechanistic information, reaction pathways, and/or reaction rates. Divide-and-conquer methods for sampling and for piecing together reaction rate information are especially suitable for readily available computer cluster networks. Successful applications to biomolecules remain a challenge
Using molecular dynamics and enhanced sampling techniques to find cryptic druggable pockets in proteins of pharmaceutical interest
Cryptic pockets are sites on protein targets that are hidden in the unliganded form and only become apparent when drugs bind. These sites provide a promising alternative to classical substrate binding sites for drug development, especially when the latter are not druggable. In this thesis I investigate the nature and dynamical properties of cryptic sites in a number of pharmacologically relevant targets, while comparing the efficacy of various simulation-based approaches in discovering them. I found that the studied cryptic sites do not correspond to local minima in the computed conformational free-energy landscape of the unliganded proteins. They thus promptly close in all of the molecular dynamics simulations performed, irrespective of the force-field used. Temperature-based enhanced sampling approaches, such as parallel tempering, do not improve the situation, as the entropic term does not help in the opening of the sites. The use of fragment probes helps, as in long simulations occasionally it leads to the opening and binding to the cryptic sites. The observed mechanism of cryptic site formation is suggestive of interplay between two classical mechanisms: induced-fit and conformational selection. Employing this insight, I developed a novel Hamiltonian replica exchange-based method SWISH (sampling water interfaces through scaled Hamiltonians), which combined with probes resulted in a promising general approach for cryptic site discovery. In addition, we revisit the rather ill-defined concept of the cryptic pockets in order to propose an alternative measurable interpretation. I outline how the new practical definition can be applied to the ligandable targets reported in the PDB, in order to provide a consistent data-driven view on crypticity and how it may impact the drug discovery. This thesis presents a comprehensive study of the cryptic pocket phenomenon: from understanding the nature of their formation to novel detection methodology, and towards understanding their global significance in drug discovery
Enhanced sampling in molecular dynamics using metadynamics, replica-exchange, and temperature-acceleration
We review a selection of methods for performing enhanced sampling in molecular dynamics simulations. We consider methods based on collective variable biasing and on tempering, and offer both historical and contemporary perspectives. In collective-variable biasing, we first discuss methods stemming from thermodynamic integration that use mean force biasing, including the adaptive biasing force algorithm and temperature acceleration. We then turn to methods that use bias potentials, including umbrella sampling and metadynamics. We next consider parallel tempering and replica-exchange methods. We conclude with a brief presentation of some combination methods. \ua9 2013 by the author; licensee MDPI, Basel, Switzerland
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