1,564 research outputs found
Tackling Exascale Software Challenges in Molecular Dynamics Simulations with GROMACS
GROMACS is a widely used package for biomolecular simulation, and over the
last two decades it has evolved from small-scale efficiency to advanced
heterogeneous acceleration and multi-level parallelism targeting some of the
largest supercomputers in the world. Here, we describe some of the ways we have
been able to realize this through the use of parallelization on all levels,
combined with a constant focus on absolute performance. Release 4.6 of GROMACS
uses SIMD acceleration on a wide range of architectures, GPU offloading
acceleration, and both OpenMP and MPI parallelism within and between nodes,
respectively. The recent work on acceleration made it necessary to revisit the
fundamental algorithms of molecular simulation, including the concept of
neighborsearching, and we discuss the present and future challenges we see for
exascale simulation - in particular a very fine-grained task parallelism. We
also discuss the software management, code peer review and continuous
integration testing required for a project of this complexity.Comment: EASC 2014 conference proceedin
Advances in Human-Protein Interaction - Interactive and Immersive Molecular Simulations
International audienc
Outcome of the First wwPDB Hybrid / Integrative Methods Task Force Workshop
Structures of biomolecular systems are increasingly computed by integrative modeling that relies on varied types of experimental data and theoretical information. We describe here the proceedings and conclusions from the first wwPDB Hybrid/Integrative Methods Task Force Workshop held at the European Bioinformatics Institute in Hinxton, UK, on October 6 and 7, 2014. At the workshop, experts in various experimental fields of structural biology, experts in integrative modeling and visualization, and experts in data archiving addressed a series of questions central to the future of structural biology. How should integrative models be represented? How should the data and integrative models be validated? What data should be archived? How should the data and models be archived? What information should accompany the publication of integrative models
Computational techniques to illuminate secrets of the monoamine transporters
The solute carrier family regulates the flow of various substances such as drugs, amino acids, sugars and inorganic ions across the cell membrane. In particular, the monoamine transporters (MATs) are responsible for the regulation of synaptic neurotransmitter levels. Their structures and conformational rearrangements associated with transport remain unsolved. We employed novel computational techniques to identify the binding pocket of cocaine in the dopamine transporter (DAT) and two intracellular pathways for substrate egress in LeuT and DAT. We review possible coarse grained molecular dynamics techniques to extend the temporal scale accessible in simulations of the MATs. Finally, we present the first computational study of DAT in the presence of an explicit electrochemical gradient. In these simulations, we identify a water wire in DAT that may suggest that DAT does not follow an alternating access mechanism
Identifying prospective inhibitors against LdtMt5 from Mycobacterium tuberculosis as a potential drug target.
Masters Degree. University of KwaZulu-Natal, Durban.Tuberculosis (TB) caused by the bacterium, Mycobacterium tuberculosis (M.tb) has resulted in an unprecedented number of deaths over centuries. L,D-transpeptidase enzymes are known to play a crucial role in the biosynthesis of the cell wall, which confers resistance to most antibiotics. These enzymes catalyze the 3â3 peptidoglycan cross-links of the M.tb cell wall. Specific ÎČ-lactam antibiotics (carbapenems) have been reported to inhibit cell wall polymerization of M.tb and they inactivate L,D-transpeptidases through acylation. L,Dtranspeptidase 5 (LdtMt5) is a unique paralog and a vital protein in maintaining integrity of the cell wall specifically in peptidoglycan metabolism therefore making it an important protein target. Carbapenems inhibit LdtMt2, but do not show reasonable inhibitory activities against LdtMt5. We therefore sought to perform virtual screening in order to acquire potential inhibitors against LdtMt5 and to investigate the affinity and to calculate the binding free energies between LdtMt5 and potential inhibitors. Furthermore, we sought to investigate the nature of the transition state involved in the catalytic reaction mechanism; to determine the activation free energies of the mechanism using ONIOM through the thermodynamics and energetics of the reaction path and lastly to express, purify and perform inhibition studies on LdtMt5.
A total of 12766 compounds were computationally screened from the ZINC database to
identify potential leads against LdtMt5. Docking was performed using two different software
programs. Molecular dynamics (MD) simulations were subsequently performed on
compounds obtained through virtual screening. Density functional theory (DFT) calculations
were then carried out to understand the catalytic mechanism of LdtMt5 with respect to ÎČ-lactam
derivatives using a hybrid ONIOM quantum mechanics/molecular mechanics (QM/MM)
method. LdtMt5 complexes with six selected ÎČ-lactam compounds were evaluated. Finally, a
lyophilised pET28a-LdtMt5 was used to transform E. coli strain BL21 (DE3) and SDS-PAGE
was used to verify the purity, molecular weight and protein profile determination. Finally, an
in vitro binding thermodynamics analysis using isothermal titration calorimetry (ITC) was later
on performed on a single compound (the strongest binder) from the final set, in a bid to further
validate the calculated binding energy values.
A number of compounds from four different antimicrobial classes (n = 98) were obtained from
the virtual screening and those with docking scores ranging from -7.2 to -9.9 kcal mol-1 were
considered for MD analysis (n = 37). A final set of 10 compounds which exhibited the greatest
affinity, from four antibiotic classes was selected and Molecular Mechanics/Generalized Born
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Surface Area (MM-GBSA) binding free energies (ÎGbind) from the set were characterised. The
calculated binding free energies ranged from -30.68 to -48.52 kcal mol-1
. The ÎČ-lactam class
of compounds demonstrated the highest ÎGbind and also the greatest number of potential
inhibitors. The DFT activation energies (âG
#
) obtained for the acylation of LdtMt5 by the six
selected ÎČ-lactams were calculated as 13.67, 20.90, 22.88, 24.29, 27.86 and 28.26 kcal mol-1
.
The âG# results from the 6-membered ring transition state (TS) revealed that all selected six ÎČlactams were thermodynamically more favourable than previously calculated activation energy
values for imipenem and meropenem complexed with LdtMt5. The results are also comparable
to those observed for LdtMt2, however for compound 1 the values are considerably lower than
those obtained for meropenem and imipenem in complex with LdtMt2, thus suggesting in theory
that compound 1 is a more potent inhibitor of LdtMt5. We also report the successful expression
and and purification of LdtMt5, however the molecule selected for the in vitro inhibition study
gave a poor result. On further review, we concluded that the main cause of this outcome was
due to the relatively low insolubility of the compound.
The outcome of this study provides insight into the design of potential novel leads for LdtMt5.
Our screening obtained ten novel compounds from four different antimicrobial classes. We
suggest that further in vitro binding thermodynamics analysis of the novel compounds from
the four classes, including the carbapenems be performed to evaluate inhibition of these
compounds on LdtMt5. If the experimental observations suggest binding affinity to the protein,
catalytic mechanistic studies can be undertaken. These results will also be used to verify or
modify our computational model
On the development of slime mould morphological, intracellular and heterotic computing devices
The use of live biological substrates in the fabrication of unconventional computing (UC) devices is steadily transcending the barriers between science fiction and reality, but efforts in this direction are impeded by ethical considerations, the fieldâs restrictively broad multidisciplinarity and our incomplete knowledge of fundamental biological processes. As such, very few functional prototypes of biological UC devices have been produced to date. This thesis aims to demonstrate the computational polymorphism and polyfunctionality of a chosen biological substrate â slime mould Physarum polycephalum, an arguably âsimpleâ single-celled organism â and how these properties can be harnessed to create laboratory experimental prototypes of functionally-useful biological UC prototypes. Computing devices utilising live slime mould as their key constituent element can be developed into a) heterotic, or hybrid devices, which are based on electrical recognition of slime mould behaviour via machine-organism interfaces, b) whole-organism-scale morphological processors, whose output is the organismâs morphological adaptation to environmental stimuli (input) and c) intracellular processors wherein data are represented by energetic signalling events mediated by the cytoskeleton, a nano-scale protein network. It is demonstrated that each category of device is capable of implementing logic and furthermore, specific applications for each class may be engineered, such as image processing applications for morphological processors and biosensors in the case of heterotic devices. The results presented are supported by a range of computer modelling experiments using cellular automata and multi-agent modelling. We conclude that P. polycephalum is a polymorphic UC substrate insofar as it can process multimodal sensory input and polyfunctional in its demonstrable ability to undertake a variety of computing problems. Furthermore, our results are highly applicable to the study of other living UC substrates and will inform future work in UC, biosensing, and biomedicine
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