50Publications

2,990Citation Statements Received

3,208Citation Statements Given

How they've been cited

2,705

113

2,870

7

How they cite others

2,219

159

3,043

6

Publications

Order By: Most citations

The dynamical solution of a well-mixed, nonlinear stochastic chemical kinetic system, described by the Master equation, may be exactly computed using the stochastic simulation algorithm. However, because the computational cost scales with the number of reaction occurrences, systems with one or more "fast" reactions become costly to simulate. This paper describes a hybrid stochastic method that partitions the system into subsets of fast and slow reactions, approximates the fast reactions as a continuous Markov process, using a chemical Langevin equation, and accurately describes the slow dynamics using the integral form of the "Next Reaction" variant of the stochastic simulation algorithm. The key innovation of this method is its mechanism of efficiently monitoring the occurrences of slow, discrete events while simultaneously simulating the dynamics of a continuous, stochastic or deterministic process. In addition, by introducing an approximation in which multiple slow reactions may occur within a time step of the numerical integration of the chemical Langevin equation, the hybrid stochastic method performs much faster with only a marginal decrease in accuracy. Multiple examples, including a biological pulse generator and a large-scale system benchmark, are simulated using the exact and proposed hybrid methods as well as, for comparison, a previous hybrid stochastic method. Probability distributions of the solutions are compared and the weak errors of the first two moments are computed. In general, these hybrid methods may be applied to the simulation of the dynamics of a system described by stochastic differential, ordinary differential, and Master equations.

Results of atomistic molecular dynamics simulations of dipalmitoylphosphatidylcholine and dipalmitoylphosphatidylglycerol monolayers at the air/water interface are presented. Dipalmitoylphosphatidylcholine is zwitterionic and dipalmitoylphosphatidylglycerol is anionic at physiological pH. NaCl and CaCl2 water subphases are simulated. The simulations are carried out at different surface densities, and a simulation cell geometry is chosen that greatly facilitates the investigation of phospholipid monolayer properties. Ensemble average monolayer properties calculated from simulation are in agreement with experimental measurements. The dependence of the properties of the monolayers on the surface density, the type of the headgroup, and the ionic environment are explained in terms of atomistically detailed pair distribution functions and electron density profiles, demonstrating the strength of simulations in investigating complex, multicomponent systems of biological importance.

Convergent gene pairs with head-to-head configurations are widespread in both eukaryotic and prokaryotic genomes and are speculated to be involved in gene regulation. Here we present a unique mechanism of gene regulation due to convergent transcription from the antagonistic prgX/prgQ operon in Enterococcus faecalis controlling conjugative transfer of the antibiotic resistance plasmid pCF10 from donor cells to recipient cells. Using mathematical modeling and experimentation, we demonstrate that convergent transcription in the prgX/prgQ operon endows the system with the properties of a robust genetic switch through premature termination of elongating transcripts due to collisions between RNA polymerases (RNAPs) transcribing from opposite directions and antisense regulation between complementary counter-transcripts. Evidence is provided for the presence of truncated RNAs resulting from convergent transcription from both the promoters that are capable of sense-antisense interactions. A mathematical model predicts that both RNAP collision and antisense regulation are essential for a robust bistable switch behavior in the control of conjugation initiation by prgX/prgQ operons. Moreover, given that convergent transcription is conserved across species, the mechanism of coupling RNAP collision and antisense interaction is likely to have a significant regulatory role in gene expression.inverse expression | overlapping DNA | gene-regulatory network

We conducted over 150 ns of simulation of a protegrin-1 octamer pore in a lipid bilayer composed of palmitoyloleoyl-phosphatidylethanolamine (POPE) and palmitoyloleoyl-phosphatidylglycerol (POPG) lipids mimicking the inner membrane of a bacterial cell. The simulations improve on a model of a pore proposed from recent NMR experiments and provide a coherent understanding of the molecular mechanism of antimicrobial activity. Although lipids tilt somewhat toward the peptides, the simulated protegrin-1 pore more closely follows the barrel-stave model than the toroidal-pore model. The movement of ions is investigated through the pore. The pore selectively allows negatively charged chloride ions to pass through at an average rate of one ion every two nanoseconds. Only two events are observed of sodium ions crossing through the pore. The potential of mean force is calculated for the water and both ion types. It is determined that the chloride ions move through the pore with ease, similarly to the water molecules with the exception of a zone of restricted movement midway through the pore. In bacteria, ions moving through the pore will compromise the integrity of the transmembrane potential. Without the transmembrane potential as a countermeasure, water will readily flow inside the higher osmolality cytoplasm. We determine that the diffusivity of water through a single PG-1 pore is sufficient to cause fast cell death by osmotic lysis.

Probability reigns in biology, with random molecular events dictating the fate of individual organisms, and propelling populations of species through evolution. In principle, the master probability equation provides the most complete model of probabilistic behavior in biomolecular networks. In practice, master equations describing complex reaction networks have remained unsolved for over 70 years. This practical challenge is a reason why master equations, for all their potential, have not inspired biological discovery. Herein, we present a closure scheme that solves the master probability equation of networks of chemical or biochemical reactions. We cast the master equation in terms of ordinary differential equations that describe the time evolution of probability distribution moments. We postulate that a finite number of moments capture all of the necessary information, and compute the probability distribution and higherorder moments by maximizing the information entropy of the system. An accurate order closure is selected, and the dynamic evolution of molecular populations is simulated. Comparison with kinetic Monte Carlo simulations, which merely sample the probability distribution, demonstrates this closure scheme is accurate for several small reaction networks. The importance of this result notwithstanding, a most striking finding is that the steady state of stochastic reaction networks can now be readily computed in a single-step calculation, without the need to simulate the evolution of the probability distribution in time.stochastic models | information theory | entropy maximization | statistical mechanics T he fabric of all things living is discrete and noisy, individual molecules in perpetual random motion. However, humans, in our effort to understand and manipulate the biological cosmos, have historically perceived and modeled nature as large collections of molecules with behaviors not far from an expected average. Mathematical models, founded on such determinism, may be excellent approximations of reality when the number of molecules is very large, approaching the limit of an infinitely sized molecular population (1-5). Of course, the size of biomolecular systems is far from infinite. And we know that the behavior of a few molecules fluctuating from the average in unexpected ways may forever seal the fate of a living organism. It has thus been commonly recognized that models of small, evolving molecular populations better account for the noisy, probabilistic nature of outcomes (6-8).The most complete model of stochastically evolving molecular populations is one based on the master probability equation (9). The "master" in the name reflects the all-encompassing nature of an equation that purports to govern all possible outcomes for all time. Because of its ambitious character, the master equation has remained unsolved for all but the simplest of molecular interaction networks, even though it is now over seven decades since the first master equations were set up for chemical systems (10,11). Herein we ...

-defensins are cyclic octadecapeptides encoded by the modified ␣-defensin genes of certain nonhuman primates. The recent demonstration that human ␣-defensins could prevent deleterious effects of anthrax lethal toxin in vitro and in vivo led us to examine the effects of -defensins on Bacillus anthracis (Sterne). We tested rhesus -defensins 1-3, retrocyclins 1-3, and several analogues of RC-1. Low concentrations of -defensins not only killed vegetative cells of B. anthracis (Sterne) and rendered their germinating spores nonviable, they also inactivated the enzymatic activity of anthrax lethal factor and protected murine RAW-264.7 cells from lethal toxin, a mixture of lethal factor and protective antigen. Structure-function studies indicated that the cyclic backbone, intramolecular tri-disulfide ladder, and arginine residues of -defensins contributed substantially to these protective effects. Surface plasmon resonance studies showed that retrocyclins bound the lethal factor rapidly and with high affinity. Retrocyclin-mediated inhibition of the enzymatic activity of lethal factor increased substantially if the enzyme and peptide were preincubated before substrate was added. The temporal discrepancy between the rapidity of binding and the slowly progressive extent of lethal factor inhibition suggest that post-binding events, perhaps in situ oligomerization, contribute to the antitoxic properties of retrocyclins. Overall, these findings suggest that -defensins provide molecular templates that could be used to create novel agents effective against B. anthracis and its toxins.Under normal circumstances Bacillus anthracis causes human infections only in individuals exposed to infected farm animals or their spore-contaminated products. The virulence of B. anthracis primarily derives from the hardiness of its spores, an anti-phagocytic capsule that surrounds its vegetative cells (1), and two secreted binary toxins: lethal toxin (LeTx) 3 and edema toxin (EdTx). Both toxins contain protective antigen (PA, 83 kDa). LeTx also contains lethal factor (LF, 90 kDa), and EdTx contains edema factor (EF, 89 kDa). The genes for all three toxin components, PA, LF, and EF, reside on the pXO1 plasmid (2), and those responsible for capsule synthesis exist on the pXO2 plasmid (3). Both of these plasmids are required for in vivo virulence (3).EF is an adenylate cyclase (4) and LF is a zinc-dependent metalloprotease that selectively attacks certain MAPK kinases (5, 6). PA is required to allow both of the other toxin components to enter host cells (7). When PA binds a cellular receptor (8), it is cleaved into PA63 (63 kDa) and PA20 (20 kDa). The PA20 diffuses away, and the residual receptor-bound PA63 molecules self-associate into ring-shaped heptamers (9) that bind EF or LF with high affinity (10 -12). Oligomerization of PA63 leads to endocytosis, which transports the complexes to an acidic compartment (13-15). Here, the heptameric pre-pore changes into an integral-membrane pore (16, 17) that translocates EF or LF into the cytosol (18). Immu...

Inducible utilization pathways reflect widespread microbial strategies to uptake and consume sugars from the environment. Despite their broad importance and extensive characterization, little is known how these pathways naturally respond to their inducing sugar in individual cells. Here, we performed single-cell analyses to probe the behavior of representative pathways in the model bacterium Escherichia coli. We observed diverse single-cell behaviors, including uniform responses (D-lactose, D-galactose, N-acetylglucosamine, N-acetylneuraminic acid), “all-or-none” responses (D-xylose, L-rhamnose), and complex combinations thereof (L-arabinose, D-gluconate). Mathematical modeling and probing of genetically modified pathways revealed that the simple framework underlying these pathways—inducible transport and inducible catabolism—could give rise to most of these behaviors. Sugar catabolism was also an important feature, as disruption of catabolism eliminated tunable induction as well as enhanced memory of previous conditions. For instance, disruption of catabolism in pathways that respond to endogenously synthesized sugars led to full pathway induction even in the absence of exogenous sugar. Our findings demonstrate the remarkable flexibility of this simple biological framework, with direct implications for environmental adaptation and the engineering of synthetic utilization pathways as titratable expression systems and for metabolic engineering.

Compstatin is a 13-residue disulfide-bridged peptide that inhibits a key step in the activation of the human complement system. Compstatin and its derivatives have shown great promise for the treatment of many clinical disorders associated with unbalanced complement activity. To obtain more potent compstatin analogues, we have now performed an N-methylation scan of the peptide backbone and amino acid substitutions at position 13. One analogue (Ac-I[CVW(Me)QDW-Sar-AHRC](NMe)I-NH2) displayed a 1,000-fold increase in both potency (IC50=62 nM) and binding affinity for C3b (KD=2.3 nM) over that of the original compstatin. Biophysical analysis using surface plasmon resonance and isothermal titration calorimetry suggests that the improved binding originates from more favorable free conformation and stronger hydrophobic interactions. This study provides a series of significantly improved drug leads for therapeutic applications in complement-related diseases, and offers new insights into the structure-activity relationships of compstatin analogues.

scite is a Brooklyn-based startup that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

hi@scite.ai

334 Leonard St

Brooklyn, NY 11211

Copyright © 2023 scite Inc. All rights reserved.

Made with 💙 for researchers