Yiannis N. Kaznessis

SynBioSS: The Synthetic Biology Modeling Suite

UNLABELLED SynBioSS (Synthetic Biology Software Suite) is a suite of software for the modeling and simulation of synthetic genetic constructs. SynBioSS utilizes the registry of standard biological parts, a database of kinetic parameters, and both graphical and command-line interfaces to multiscale simulation algorithms. AVAILABILITY SynBioSS is available under the GNU General Public License at http://synbioss.sourceforge.net.

Retrocyclins Kill Bacilli and Germinating Spores of Bacillus anthracis and Inactivate Anthrax Lethal Toxin

θ-defensins are cyclic octadecapeptides encoded by the modified α-defensin genes of certain nonhuman primates. The recent demonstration that human α-defensins could prevent deleterious effects of anthrax lethal toxin in vitro and in vivo led us to examine the effects of θ-defensins on Bacillus anthracis (Sterne). We tested rhesus θ-defensins 1-3, retrocyclins 1-3, and several analogues of RC-1. Low concentrations of θ-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 θ-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 θ-defensins provide molecular templates that could be used to create novel agents effective against B. anthracis and its toxins.

Models for synthetic biology

Synthetic biological engineering is emerging from biology as a distinct discipline based on quantification. The technologies propelling synthetic biology are not new, nor is the concept of designing novel biological molecules. What is new is the emphasis on system behavior.The objective is the design and construction of new biological devices and systems to deliver useful applications. Numerous synthetic gene circuits have been created in the past decade, including bistable switches, oscillators, and logic gates, and possible applications abound, including biofuels, detectors for biochemical and chemical weapons, disease diagnosis, and gene therapies.More than fifty years after the discovery of the molecular structure of DNA, molecular biology is mature enough for real quantification that is useful for biological engineering applications, similar to the revolution in modeling in chemistry in the 1950s. With the excitement that synthetic biology is generating, the engineering and biological science communities appear remarkably willing to cross disciplinary boundaries toward a common goal.

Protegrin structure-activity relationships: using homology models of synthetic sequences to determine structural characteristics important for activity

The protegrin family of antimicrobial peptides is among the shortest in sequence length while remaining very active against a variety of microorganisms. The major goal of this study is to characterize easily calculated molecular properties, which quantitatively show high correlation with antibacterial activity. The peptides studied have high sequence similarity but vary in activity over more than an order of magnitude. Hence, sequence analysis alone cannot be used to predict activity for these peptides. We calculate structural properties of 62 protegrin and protegrin-analogue peptides and correlate them to experimental activities against six microbe species, as well as hemolytic and cytotoxic activities. Natural protegrins structures were compared with synthetic derivatives using homology modeling, and property descriptors were calculated to determine the characteristics that confer their antimicrobial activity. A structure-activity relationship study of all these peptides provides information about the structural properties that affect activity against different microbial species.

Convergent transcription confers a bistable switch in Enterococcus faecalis conjugation

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.

Novel analogues of the therapeutic complement inhibitor compstatin with significantly improved affinity and potency

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-NH(2)) displayed a 1000-fold increase in both potency (IC(50) = 62 nM) and binding affinity for C3b (K(D) = 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.

Prediction of Distant Residue Contacts With the Use of Evolutionary Information

In this work we present a novel correlated mutations analysis (CMA) method that is significantly more accurate than previously reported CMA methods. Calculation of correlation coefficients is based on physicochemical properties of residues (predictors) and not on substitution matrices. This results in reliable prediction of pairs of residues that are distant in protein sequence but proximal in its three dimensional tertiary structure. Multiple sequence alignments (MSA) containing a sequence of known structure for 127 families from PFAM database have been selected so that all major protein architectures described in CATH classification database are represented. Protein sequences in the selected families were filtered so that only those evolutionarily close to the target protein remain in the MSA. The average accuracy obtained for the alpha beta class of proteins was 26.8% of predicted proximal pairs with average improvement over random accuracy (IOR) of 6.41. Average accuracy is 20.6% for the mainly beta class and 14.4% for the mainly alpha class. The optimum correlation coefficient cutoff (cc cutoff) was found to be around 0.65. The first predictor, which correlates to hydrophobicity, provides the most reliable results. The other two predictors give good predictions which can be used in conjunction to those of the first one. When stricter cc cutoff is chosen, the average accuracy increases significantly (38.76% for alpha beta class), but the trade off is a smaller number of predictions. The use of solvent accessible area estimations for filtering false positives out of the predictions is promising. Proteins 2005.

Computational studies of protegrin antimicrobial peptides: A review

Antimicrobial peptides (AMPs) are small, naturally occurring peptides that exhibit strong antibacterial properties generally believed to be a result of selective bacterial membrane disruption. As a result, there has been significant interest in the development of therapeutic antibiotics based on AMPs; however, the poor understanding of the fundamental mechanism of action of these peptides has largely hampered such efforts. We present a summary of computational and theoretical investigations of protegrin, a particularly potent peptide that is both an excellent model for the mechanism of action of AMPs and a promising therapeutic candidate. Experimental investigations have shed light on many of the key steps in the action of protegrin: protegrin monomers are known to dimerize in various lipid environments; protegrin peptides interact strongly with lipid bilayer membranes, particularly anionic lipids; protegrins have been shown to form pores in lipid bilayers, which results in uncontrolled ion transport and may be a key factor in bacterial death. In this work, we present a comprehensive review of the computational and theoretical studies that have complemented and extended the information obtained from experimental work with protegrins, as well as a brief survey of the experimental biophysical studies that are most pertinent to such computational work. We show that a consistent, mechanistic description of the bactericidal mechanism of action of protegrins is emerging, and briefly outline areas where the current understanding is deficient. We hope that the research reviewed herein offers compelling evidence of the benefits of computational investigations of protegrins and other AMPs, as well as providing a useful guide to future work in this area.

A closure scheme for chemical master equations

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 higher-order 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.

On the Nature of Antimicrobial Activity: A Model for Protegrin-1 Pores

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.