Unveiling a novel transient druggable pocket in BACE-1 through molecular simulations: conformational analysis and binding mode of multisite inhibitors

The critical role of BACE-1 in the formation of neurotoxic ß-amyloid peptides in the brain makes it an attractive target for an efficacious treatment of Alzheimer’s disease. However, the development of clinically useful BACE-1 inhibitors has proven to be extremely challeng- ing. In this study we examine the binding mode of a novel potent inhibitor (compound 1, with IC50 80 nM) designed by synergistic combination of two fragments—huprine and rhein— that individually are endowed with very low activity against BACE-1. Examination of crystal structures reveals no appropriate binding site large enough to accommodate 1. Therefore we have examined the conformational flexibility of BACE-1 through extended molecular dynamics simulations, paying attention to the highly flexible region shaped by loops 8–14, 154–169 and 307–318. The analysis of the protein dynamics, together with studies of pocket druggability, has allowed us to detect the transient formation of a secondary binding site, which contains Arg307 as a key residue for the interaction with small molecules, at the edge of the catalytic cleft. The formation of this druggable “floppy” pocket would enable the bind- ing of multisite inhibitors targeting both catalytic and secondary sites. Molecular dynamics simulations of BACE-1 bound to huprine-rhein hybrid compounds support the feasibility of this hypothesis. The results provide a basis to explain the high inhibitory potency of the two enantiomeric forms of 1, together with the large dependence on the length of the oligo- methylenic linker. Furthermore, the multisite hypothesis has allowed us to rationalize the inhibitory potency of a series of tacrine-chromene hybrid compounds, specifically regarding the apparent lack of sensitivity of the inhibition constant to the chemical modifications intro- duced in the chromene unit. Overall, these findings pave the way for the exploration of novel functionalities in the design of optimized BACE-1 multisite inhibitors

Can environment or allergy explain international variation in prevalence of wheeze in childhood?

Asthma prevalence in children varies substantially around the world, but the contribution of known risk factors to this international variation is uncertain. The International Study of Asthma and Allergies in Childhood (ISAAC) Phase Two studied 8–12 year old children in 30 centres worldwide with parent-completed symptom and risk factor questionnaires and aeroallergen skin prick testing. We used multilevel logistic regression modelling to investigate the effect of adjustment for individual and ecological risk factors on the between-centre variation in prevalence of recent wheeze. Adjustment for single individual-level risk factors changed the centre-level variation from a reduction of up to 8.4% (and 8.5% for atopy) to an increase of up to 6.8%. Modelling the 11 most influential environmental factors among all children simultaneously, the centre-level variation changed little overall (2.4% increase). Modelling only factors that decreased the variance, the 6 most influential factors (synthetic and feather quilt, mother’s smoking, heating stoves, dampness and foam pillows) in combination resulted in a 21% reduction in variance. Ecological (centre-level) risk factors generally explained higher proportions of the variation than did individual risk factors. Single environmental factors and aeroallergen sensitisation measured at the individual (child) level did not explain much of the between-centre variation in wheeze prevalence

Anthropogenic Sources and their Environmental Impact to Surface Waters

Abstract Influence of the human beings to the nature initially was inexistent, but it increased continuously until the industri

Utilizing Machine Learning for Efficient Parameterization of Coarse Grained Molecular Force Fields

This work demonstrates the use of open literature data to force field paramterization via a novel approach applying Bayesian optimization. We have selected Dissipative Particle Dynamics (DPD) as the simulation method in this proof-of-concept work

Towards Low Cost Virtual Biological Laboratories: Molecular Modelling Simulation on Commodity Hardware.

Many essential cell processes, such as the conformation of embedded proteins, membrane permeability, interaction with drugs and signalling, are directly connected to the molecular dynamics of cell membranes. The importance of this biology has led to an intensifying demand for hardware and software optimized models and tools, implemented on commodity high performance low-cost hardware, in order to provide the scientific community with virtual low cost laboratories. In the light of these considerations, we implemented an accelerated version of a molecular dynamics coarse-grain lipid bilayers simulator on commodity Graphic Processing Units (GPU) architectures. The characteristics of this molecular dynamics model, such as new force fields for pair potentials that include an unconventional representation for water and charges, were particularly challenging. We introduced new algorithms and data structures required by coarse-grain models compared to atomistic ones, for the modelling of the integration timestep, neighbour list generation, and nonbonded force interactions. We characterized the impact on performance of biological systems of differing complexity in terms of size, particle type and timestep. We also compared the simulations of many particle-type systems against single particle-type systems, to evaluate the overhead of additional structures needed to model more complex molecules. Moreover, we performed a detailed analysis on the profiling of the simulation code and its execution flows due to the computation of the non-bonded forces. Finally, we characterized the acceleration and accuracy of the simulations on three GPUs having different computation capabilities and parallelism, achieving one order of magnitude faster simulation execution times

CoCo-MD: A Simple and Effective Method for the Enhanced Sampling of Conformational Space

CoCo (“complementary coordinates”) is a method for ensemble enrichment based on principal component analysis (PCA) that was developed originally for the investigation of NMR data. Here we investigate the potential of the CoCo method, in combination with molecular dynamics simulations (CoCo-MD), to be used more generally for the enhanced sampling of conformational space. Using the alanine penta-peptide as a model system, we find that an iterative workflow, interleaving short multiple-walker MD simulations with long-range jumps through conformational space informed by CoCo analysis, can increase the rate of sampling of conformational space up to 10 times for the same computational effort (total number of MD timesteps). Combined with the reservoir-REMD method, free energies can be readily calculated. An alternative, approximate but fast and practically useful, alternative approach to unbiasing CoCo-MD generated data is also described. Applied to cyclosporine A, we can achieve far greater conformational sampling than has been reported previously, using a fraction of the computational resource. Simulations of the maltose binding protein, begun from the “open” state, effectively sample the “closed” conformation associated with ligand binding. The PCA-based approach means that optimal collective variables to enhance sampling need not be defined in advance by the user but are identified automatically and are adaptive, responding to the characteristics of the developing ensemble. In addition, the approach does not require any adaptations to the associated MD code and is compatible with any conventional MD package