ADAPTIVE MULTILEVEL SPLITTING IN MOLECULAR DYNAMICS SIMULATIONS

Adaptive Multilevel Splitting (AMS) is a replica-based rare event sampling method that has been used successfully in high-dimensional stochastic simulations to identify trajectories across a high potential barrier separating one metastable state from another, and to estimate the probability of observing such a trajectory. An attractive feature of AMS is that, in the limit of a large number of replicas, it remains valid regardless of the choice of reaction coordinate used to characterize the trajectories. Previous studies have shown AMS to be accurate in Monte Carlo simulations. In this study, we extend the application of AMS to molecular dynamics simulations and demonstrate its effectiveness using a simple test system. Our conclusion paves the way for useful applications, such as molecular dynamics calculations of the characteristic time of drug dissociation from a protein target

The Role of Micronutrients in Graft-VS.-Host Disease: Immunomodulatory Effects of Vitamins A and D

Graft-vs.-host disease (GVHD) remains a major obstacle to the success of allogeneic hematopoietic stem cell transplantation (HSCT). GVHD occurs because donor T cells in the allograft recognize the genetically disparate host as foreign and attack the transplant recipient's tissues. While genetic incompatibility between donor and recipient is the primary determinant for the extent of alloimmune response, GVHD incidence and severity are also influenced by non-genetic factors. Recent advances in immunology establish that environmental factors, including dietary micronutrients, contribute significantly to modulating various immune responses and may influence the susceptibility to autoimmune and inflammatory diseases of experimental animals and humans. Emerging clinical and preclinical evidence indicates that certain micronutrients may participate in regulating GVHD risk after allogeneic HSCT. In this review, we summarize recent advances in our understanding with respect to the potential role of micronutrients in the pathogenesis of acute and chronic GVHD, focusing on vitamins A and D

Detection of Crosslinks within and between Proteins by LC-MALDI-TOFTOF and the Software FINDX to Reduce the MSMS-Data to Acquire for Validation

Lysine-specific chemical crosslinking in combination with mass spectrometry is emerging as a tool for the structural characterization of protein complexes and protein-protein interactions. After tryptic digestion of crosslinked proteins there are thousands of peptides amenable to MSMS, of which only very few are crosslinked peptides of interest. Here we describe how the advantage offered by off-line LC-MALDI-TOF/TOF mass spectrometry is exploited in a two-step workflow to focus the MSMS-acquisition on crosslinks mainly. In a first step, MS-data are acquired and all the peak list files from the LC-separated fractions are merged by the FINDX software and screened for presence of crosslinks which are recognized as isotope-labeled doublet peaks. Information on the isotope doublet peak mass and intensity can be used as search constraints to reduce the number of false positives that match randomly to the observed peak masses. Based on the MS-data a precursor ion inclusion list is generated and used in a second step, where a restricted number of MSMS-spectra are acquired for crosslink validation. The decoupling of MS and MSMS and the peptide sorting with FINDX based on MS-data has the advantage that MSMS can be restricted to and focused on crosslinks of Type 2, which are of highest biological interest but often lowest in abundance. The LC-MALDI TOF/TOF workflow here described is applicable to protein multisubunit complexes and using 14N/15N mixed isotope strategy for the detection of inter-protein crosslinks within protein oligomers

The early mathematical education of Ada Lovelace

Ada, Countess of Lovelace, is remembered for a paper published in 1843, which translated and considerably extended an article about the unbuilt Analytical Engine, a general-purpose computer designed by the mathematician and inventor Charles Babbage. Her substantial appendices, nearly twice the length of the original work, contain an account of the principles of the machine, along with a table often described as ‘the first computer program’. In this paper we look at Lovelace's education before 1840, which encompassed older traditions of practical geometry; newer textbooks influenced by continental approaches; wide reading; and a fascination with machinery. We also challenge judgements by Dorothy Stein and by Doron Swade of Lovelace's mathematical knowledge and skills before 1840, which have impacted later scholarly and popular discourse

Computational and synthetic approaches in the design and development of chemical probes for estrogen receptor function

A member of the nuclear receptor superfamily, the estrogen receptor (ER) is a ligand-regulated transcription factor responsible for the regulation of hundreds of genes. Consequently, ERs are involved in numerous disease states, including cellular proliferation, post-menopausal symptoms, inflammation, and neurodegeneration, all of which represent potential opportunities for endocrine therapies. Sustained efforts in structural biology have led to the deposition of many high resolution x-ray crystal structures of ligand-receptor complexes into the PDB, and provide valuable insight into the key ligand-receptor interactions determining binding affinity and, in some cases, specific macroscopic structural attributes that directly affect ER function. As described herein, we have leveraged selected PDB structures, supplemented by additional unpublished structures obtained from collaborators, to design and develop chemical probes of ER function. The underlying mechanisms driving ligand affinity and selectivity remain a key focus in understanding ER function. Correspondingly, we describe the development of imidazo[1,2-a]pyridine ligands to probe the importance of the core scaffold structure in ligand binding affinity. Computational analysis of ligand and receptor structures has led to the identification of the interaction between their respective dipole moments as an important receptor-ligand interaction. We also set out to discover novel ER scaffolds through a virtual screening approach and follow-up synthetic efforts to identify and further investigate a thiadiazole scaffold bearing an extended alkyl substituent. Docking structures suggest an intriguing binding mode probing the presence of a putative second binding volume reminiscent of that observed for the high affinity and highly selective glucocorticoid receptor (GR) ligand, deacylcortivazol (DAC). The diverse biological roles of ERs also provide opportunities to probe receptor function through alternative mechanisms. We report the use of recent crystal structures to design novel modifications of known ER ligands in probing the molecular basis for receptor crosstalk between ER and NF-??B, and the resulting effect on inflammatory pathways. These ligand modifications are centered on destabilizing helix 12 by disrupting the position of a single histidine residue within the binding pocket, and have been shown to effect antagonist activity on both classical ER pathways and the expression of IL-6, the latter being representative of inflammatory responses, in vivo. Previous work in our labs has also demonstrated that the assessment of ER-dependent targets can provide a better indication of ER function in vivo than assaying ER itself. To this end, we have developed new scoring functions for evaluating docked structures of fluorinated analogues of Tanaproget for the progesterone receptor (PR), whose expression is tightly controlled by ER. These functions have been applied in the design and selection of new synthetic targets for use in imaging ER-positive tumors via positron emission tomography (PET)

Adaptive Multilevel Splitting in Molecular Dynamics Simulations*

Adaptive Multilevel Splitting (AMS) is a replica-based rare event sampling method that has been used successfully in high-dimensional stochastic simulations to identify trajectories across a high potential barrier separating one metastable state from another, and to estimate the probability of observing such a trajectory. An attractive feature of AMS is that, in the limit of a large number of replicas, it remains valid regardless of the choice of reaction coordinate used to characterize the trajectories. Previous studies have shown AMS to be accurate in Monte Carlo simulations. In this study, we extend the application of AMS to molecular dynamics simulations and demonstrate its effectiveness using a simple test system. Our conclusion paves the way for useful applications, such as molecular dynamics calculations of the characteristic time of drug dissociation from a protein target