Development & Application of Constant pH Molecular Dynamics (CPHMD ) for Investigating pH-mediated Transient Conformational States and Their Effects on Nucleic Acid & Protein Activity.

pH is a ubiquitous regulator of biological activity, with widespread impact ranging from its role in catalysis to carcinogenesis. Traditionally, a combination of biophysical and computational methods are used to measure pH-dependent activity profiles, and protonation equilibria (i.e. pKa values) of specific residues, and these data are used in conjunction with structural data to provide mechanistic understanding of pH-mediated biological function. More recent developments have also demonstrated the role of transient conformational states in a wide range of biological activities, which naturally leads to the question of how pH affects such transient states, and in turn, their resulting functional activity. In the study of biomolecular transient states, the detection limit is the key limitation of most experimental techniques. To bridge the gap in detection limit, we have developed an appropriate molecular dynamics based computational method, where protonation states are dynamically adjusted as a function of an external pH bath and the local environment surrounding the titrating site. Also known as the explicit solvent constant pH molecular dynamics (CPHMD^MSλD) framework, we use CPHMD^MSλD simulations and enhanced sampling methods to demonstrate the role of pH-regulated transient states in both nucleic acid and protein activity. First, we demonstrate the utility of CPHMD^MSλD simulations in conjunction with NMR experiments to characterize transiently populated Hoogsteen GC+ base pairs in DNA duplexes. The role of pH-dependent transient states is then generalized to RNA activity, including that of the catalytic mechanism of the hairpin ribozyme, where the existence of pH-dependent transient states can be used to reconcile a collection of seemingly inconsistent experimental observations in the literature. In addition, our CPHMD^MSλD simulations of proteins have elucidated the role of pH-dependent transient states in residues that are buried or occluded from solvent, including that of the pH-dependent optical properties of a cyan fluorescent protein mutant, where the existence of pH-dependent transient states can be used to explain its non-monotonic spectroscopic behavior.PHDChemistryUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113562/1/gbgoh_1.pd

Constant pH molecular dynamics of proteins in explicit solvent with proton tautomerism

pH is a ubiquitous regulator of biological activity, including protein‐folding, protein‐protein interactions, and enzymatic activity. Existing constant pH molecular dynamics (CPHMD) models that were developed to address questions related to the pH‐dependent properties of proteins are largely based on implicit solvent models. However, implicit solvent models are known to underestimate the desolvation energy of buried charged residues, increasing the error associated with predictions that involve internal ionizable residue that are important in processes like hydrogen transport and electron transfer. Furthermore, discrete water and ions cannot be modeled in implicit solvent, which are important in systems like membrane proteins and ion channels. We report on an explicit solvent constant pH molecular dynamics framework based on multi‐site λ‐dynamics (CPHMD MSλD ). In the CPHMD MSλD framework, we performed seamless alchemical transitions between protonation and tautomeric states using multi‐site λ‐dynamics, and designed novel biasing potentials to ensure that the physical end‐states are predominantly sampled. We show that explicit solvent CPHMD MSλD simulations model realistic pH‐dependent properties of proteins such as the Hen‐Egg White Lysozyme (HEWL), binding domain of 2‐oxoglutarate dehydrogenase (BBL) and N‐terminal domain of ribosomal protein L9 (NTL9), and the p K a predictions are in excellent agreement with experimental values, with a RMSE ranging from 0.72 to 0.84 p K a units. With the recent development of the explicit solvent CPHMD MSλD framework for nucleic acids, accurate modeling of pH‐dependent properties of both major class of biomolecules—proteins and nucleic acids is now possible. Proteins 2014; 82:1319–1331. © 2013 Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/107513/1/prot24499-sup-0002-suppinfo02.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/107513/2/prot24499-sup-0001-suppinfo01.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/107513/3/prot24499.pd

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Search for heavy resonances decaying to two Higgs bosons in final states containing four b quarks

A search is presented for narrow heavy resonances X decaying into pairs of Higgs bosons (H) in proton-proton collisions collected by the CMS experiment at the LHC at root s = 8 TeV. The data correspond to an integrated luminosity of 19.7 fb(-1). The search considers HH resonances with masses between 1 and 3 TeV, having final states of two b quark pairs. Each Higgs boson is produced with large momentum, and the hadronization products of the pair of b quarks can usually be reconstructed as single large jets. The background from multijet and t (t) over bar events is significantly reduced by applying requirements related to the flavor of the jet, its mass, and its substructure. The signal would be identified as a peak on top of the dijet invariant mass spectrum of the remaining background events. No evidence is observed for such a signal. Upper limits obtained at 95 confidence level for the product of the production cross section and branching fraction sigma(gg -> X) B(X -> HH -> b (b) over barb (b) over bar) range from 10 to 1.5 fb for the mass of X from 1.15 to 2.0 TeV, significantly extending previous searches. For a warped extra dimension theory with amass scale Lambda(R) = 1 TeV, the data exclude radion scalar masses between 1.15 and 1.55 TeV

Search for supersymmetry in events with one lepton and multiple jets in proton-proton collisions at root s=13 TeV

Peer reviewe