Simulation tools for particle-based reaction-diffusion dynamics in continuous space

Particle-based reaction-diffusion algorithms facilitate the modeling of the diffusional motion of individual molecules and the reactions between them in cellular environments. A physically realistic model, depending on the system at hand and the questions asked, would require different levels of modeling detail such as particle diffusion, geometrical confinement, particle volume exclusion or particle-particle interaction potentials. Higher levels of detail usually correspond to increased number of parameters and higher computational cost. Certain systems however, require these investments to be modeled adequately. Here we present a review on the current field of particle-based reaction-diffusion software packages operating on continuous space. Four nested levels of modeling detail are identified that capture incrementing amount of detail. Their applicability to different biological questions is discussed, arching from straight diffusion simulations to sophisticated and expensive models that bridge towards coarse grained molecular dynamics

ReaDDyMM: fast interacting-particle reaction-diffusion simulations using graphical processing units

AbstractReaDDy is a modular particle simulation package combining off-lattice reaction kinetics with arbitrary particle interaction forces. Here we present a graphical processing unit implementation of ReaDDy that employs the fast multiplatform molecular dynamics package OpenMM. A speedup of up to two orders of magnitude is demonstrated, giving us access to timescales of multiple seconds on single graphical processing units. This opens up the possibility of simulating cellular signal transduction events while resolving all protein copies

Interrogating how we know the world - Starting the conversation ...

How do we ‘know’ the world? It is so vast a question that it feels, perhaps ironically, almost unknowable. Why does it matter? It is not a call to take an inventory of specific facts or perspectives, but is a question we ask in order to help frame a more critical and reflexive approach to the assumptions that underpin (academic) perceptions of WHAT counts as knowledge, HOW we capture and communicate that knowledge and WHO gets to both shape and present ideas as academic (read: expert) knowledge. Taken together, these reflections can, we believe, be very instructive and support more nuanced and critical approaches to social science scholarship

Runaway dilaton models: improved constraints from the full cosmological evolution

One of the few firm predictions of string theory is the existence of a massless scalar field coupled to gravity, the dilaton. In its presence, the value of the fundamental constants of the universe, such as the fine-structure constant, will vary with the time-dependent vacuum expectation value of this field, in direct violation of the Einstein Equivalence Principle. The \emph{runaway dilaton} proposed by Damour, Piazza, and Veneziano provides a physically motivated cosmological scenario which reconciles the existence of a massless dilaton with observations, while still providing non-standard and testable predictions. Furthermore, the field can provide a natural candidate for dynamical dark energy. While this model has been previously constrained from local laboratory experiments and low-redshift observations, we provide here the first full self-consistent constraints, also including high redshift data, in particular from the cosmic microwave background. We consider various possible scenarios in which the field could act as quintessence. Despite the wider parameter space, we make use of recent observational progress to significantly improve constraints on the model's coupling parameters, showing that order unity couplings (which would be natural in string theory) are ruled out.Comment: Published in Phys. Rev.

News from the Swampland -- Constraining string theory with astrophysics and cosmology

Our current best guess for a unified theory of gravitation and quantum field theory (string theory) generically predicts a set of requirements for a consistently quantized theory, the Swampland criteria. Refined versions of these criteria have recently been shown to be in mild tension with cosmological observations. We summarize the status of the current impact of and constraints on the Swampland conjectures from cosmology, and subject a variety of dark energy quintessence models to recently released cosmological datasets. We find that instead of tightening the tension, the new data allows for slightly more freedom in the Swampland criteria. We further demonstrate that if there is no theoretical argument made to prevent interactions of the moduli fields with the electromagnetic sector, a novel fine-tuning argument arises from the extremely tight current constraints on such interactions. Finally, we conclude with a cautionary tale on model-independent reconstructions of the Swampland criteria from expansion rate data.Comment: 35 pages, 20 figures, 4 tables. All comments are welcome! [v2: Added citations, corrected eq. 2.6

Protein-peptide association kinetics beyond the seconds timescale from atomistic simulations

Understanding and control of structures and rates involved in protein-ligand binding are es- sential for drug design. Unfortunately, atomistic molecular dynamics (MD) simulations cannot di- rectly sample the excessively long residence and rearrangement times of tightly binding complexes. Here we exploit the recently developed multi-ensemble Markov model framework to compute full protein-peptide kinetics of the oncoprotein fragment 25−109Mdm2 and the nano-molar inhibitor peptide PMI. Using this system, we report, for the first time, direct estimates of kinetics beyond the seconds timescales using simulations of an all-atom MD model, with high accuracy and pre- cision. These results only require explicit simulations on the sub-milliseconds timescale and are tested against existing mutagenesis data and our own experimental measurements of the dissoci- ation and association rates. The full kinetic model reveals an overall downhill but rugged binding funnel with multiple pathways. The overall strong binding arises from a variety of conformations with different hydrophobic contact surfaces that interconvert on the milliseconds timescale.Funding is acknowledged by European Commission (ERC StG “pcCells” to F.N.), Deutsche Forschungsgemeinschaft (SFB 1114/C3, SFB 740/D7, and TRR 186/A12 to F.N. and SFB 1114/A4 to F.N. and T.W.). J.C. is a Wellcome Trust Senior Research Fellow (WT 095195MA). J.S. is a Marie Sklodowska-Curie Internationally outgoing fellow. M.D.C. is supported by a Biotechnology and Biological Sciences Research Council (BBSRC) studentship

Disruption of cytoskeletal integrity impairs Gi-mediated signaling due to displacement of Gi proteins

β1 integrins play a crucial role as cytoskeletal anchorage proteins. In this study, the coupling of the cytoskeleton and intracellular signaling pathways was investigated in β1 integrin deficient (−/−) embryonic stem cells. Muscarinic inhibition of the L-type Ca2+ current (ICa) and activation of the acetylcholine-activated K+ current (IK,ACh) was found to be absent in β1 integrin−/− cardiomyocytes. Conversely, β adrenoceptor-mediated modulation of ICa was unaffected by the absence of β1 integrins. This defect in muscarinic signaling was due to defective G protein coupling. This was supported by deconvolution microscopy, which demonstrated that Gi exhibited an atypical subcellular distribution in the β1 integrin−/− cardiomyocytes. A critical role of the cytoskeleton was further demonstrated using cytochalasin D, which displaced Gi and impaired muscarinic signaling. We conclude that cytoskeletal integrity is required for correct localization and function of Gi-associated signaling microdomains

Genomic basis for skin phenotype and cold adaptation in the extinct Steller’s sea cow

Steller’s sea cow, an extinct sirenian and one of the largest Quaternary mammals, was described by Georg Steller in 1741 and eradicated by humans within 27 years. Here, we complement Steller’s descriptions with paleogenomic data from 12 individuals. We identified convergent evolution between Steller’s sea cow and cetaceans but not extant sirenians, suggesting a role of several genes in adaptation to cold aquatic (or marine) environments. Among these are inactivations of lipoxygenase genes, which in humans and mouse models cause ichthyosis, a skin disease characterized by a thick, hyperkeratotic epidermis that recapitulates Steller’s sea cows’ reportedly bark-like skin. We also found that Steller’s sea cows’ abundance was continuously declining for tens of thousands of years before their description, implying that environmental changes also contributed to their extinction

Machine Learning for Mathematical Software

While there has been some discussion on how Symbolic Computation could be used for AI there is little literature on applications in the other direction. However, recent results for quantifier elimination suggest that, given enough example problems, there is scope for machine learning tools like Support Vector Machines to improve the performance of Computer Algebra Systems. We survey the authors own work and similar applications for other mathematical software. It may seem that the inherently probabilistic nature of machine learning tools would invalidate the exact results prized by mathematical software. However, algorithms and implementations often come with a range of choices which have no effect on the mathematical correctness of the end result but a great effect on the resources required to find it, and thus here, machine learning can have a significant impact.Comment: To appear in Proc. ICMS 201