We propose a mathematical model for mitochondria-dependent apoptosis, in which kinetic cooperativity in formation of the apoptosome is a key element ensuring bistability. We examine the role of Bax and Bcl-2 synthesis and degradation rates, as well as the number of mitochondrial permeability transition pores (MPTPs), on the cell response to apoptotic stimuli. Our analysis suggests that cooperative apoptosome formation is a mechanism for inducing bistability, much more robust than that induced by other mechanisms, such as inhibition of caspase-3 by the inhibitor of apoptosis (IAP). Simulations predict a pathological state in which cells will exhibit a monostable cell survival if Bax degradation rate is above a threshold value, or if Bax expression rate is below a threshold value. Otherwise, cell death or survival occur depending on initial caspase-3 levels. We show that high expression rates of Bcl-2 can counteract the effects of Bax. Our simulations also demonstrate a monostable (pathological) apoptotic response if the number of MPTPs exceeds a threshold value. This study supports our contention, based on mathematical modeling, that cooperativity in apoptosome formation is critically important for determining the healthy responses to apoptotic stimuli, and helps define the roles of Bax, Bcl-2, and MPTP vis-à-vis apoptosome formation.

No abstract

Despite the suitability of various lattice geometries for coarse-grained modeling of proteins, the actual packing geometry of residues in folded structures has remained largely unexplored. A strong tendency to assume a regular packing geometry is shown here by optimally reorienting and superimposing clusters of neighboring residues from databank structures examined on a coarsegrained (single-site-per-residue) scale. The orientation function (or order parameter) of the examined coordination clusters with respect to fcc lattice directions is found to be 0.82. The observed geometry, which may be termed an incomplete distorted face-centered cubic (fcc) packing, is apparently favored by the drive to maximize packing density, in a fashion analogous to the way identical spheres pack densely and follow fcc geometry. About 2/3 of all residues obey this packing geometry, while the remainder occupy other context-dependent positions. The preferred coordination directions show relatively small variations over the various amino acid types, consistent with uniform residue viewpoint. Both the extremes of solvent-exposed and completely buried residue neighborhoods approximate the same generic packing, the only difference being in the numbers (and not the orientations) of coordination sites that are occupied (or left void for solvent occupancy). We observe the prevalence of a rather uniform (tight) residue packing density throughout the structure, including even the residues packed near solvent-exposed regions. The observed orientation distribution reveals an underlying, intrinsic orientation lattice for proteins. Proteins 2003;52:56 -67.

The high packing density of residues in proteins ought to be manifested in some order; to date this packing order has not been thoroughly characterized. The packing regularity in proteins is important because the internal organization of proteins can have a dominant effect on functional dynamics, and it can aid in the design, simulation and evaluation of structures. Packing metrics could also inform us about normal sequence variability, an issue that, with the accumulating genome data, becomes increasingly important. Other studies, indicating a possible correlation between packing density, sequence conservation, and folding nucleation ͓O. B. Ptitsyn, J. Mol. Biol. 278, 655 ͑1998͔͒, have emphasized the importance of packing. Here, residue clusters from protein databank structures, each comprised of a central residue and all neighbors located within the first coordination shell, have been rigidly re-oriented and superimposed in a self-consistent optimization. About two-thirds of residues are found to follow approximately the relative orientation preferences of face-centered-cubic packing, when examined on a coarse-grained scale ͑one site per residue͒, while the remaining one-third occupy random positions. The observed regularity, which becomes more pronounced after optimal superimposition of core residues, appears to be the result of uniform sampling of the coordination space around each residue on a coarse-grained scale with hydrophobic clustering and volume exclusion, to achieve packing densities close to that of the universal closest packing of identical spheres.

No abstract

Despite the establishment of the important role of nitric oxide (NO) on apoptosis, a molecular- level understanding of the origin of its dichotomous pro- and anti-apoptotic effects has been elusive. We propose a new mathematical model for simulating the effects of nitric oxide (NO) on apoptosis. The new model integrates mitochondria-dependent apoptotic pathways with NO-related reactions, to gain insights into the regulatory effect of the reactive NO species N2O3, non-heme iron nitrosyl species (FeLnNO), and peroxynitrite (ONOO−). The biochemical pathways of apoptosis coupled with NO-related reactions are described by ordinary differential equations using mass-action kinetics. In the absence of NO, the model predicts either cell survival or apoptosis (a bistable behavior) with shifts in the onset time of apoptotic response depending on the strength of extracellular stimuli. Computations demonstrate that the relative concentrations of anti- and pro-apoptotic reactive NO species, and their interplay with glutathione, determine the net anti- or pro-apoptotic effects at long time points. Interestingly, transient effects on apoptosis are also observed in these simulations, the duration of which may reach up to hours, despite the eventual convergence to an anti-apoptotic state. Our computations point to the importance of precise timing of NO production and external stimulation in determining the eventual pro- or anti-apoptotic role of NO.

Apoptosis is an important area of research because of its role in keeping a mature multicellular organism's number of cells constant hence, ensuring that the organism does not have cell accumulation that may transform into cancer with additional hallmarks.Firstly, we have carried out sensitivity analysis on an existing mitochondria-dependent mathematical apoptosis model to find out which parameters have a role in causing monostable cell survival i.e., malfunction in apoptosis. We have then generated three healthy cell models by changing these sensitive parameters while preserving bistability i.e., healthy functioning. For each healthy cell, we varied the proapoptotic production rates, which were found to be among the most sensitive parameters, to yield cells that have malfunctioning apoptosis. We simulated caspase-3 activation, by numerically integrating the governing ordinary differential equations of a mitochondria-dependent apoptosis model, in a hypothetical malfunctioning cell which is treated by four potential

A critical goal in cell biology is to develop a systems-level perspective of eukaryotic cell cycle controls. Among these controls, a complex signaling network (called 'checkpoints') arrests progression through the cell cycle when there is a threat to genomic integrity such as unreplicated or damaged DNA. Understanding the regulatory principles of cell cycle checkpoints is important because loss of checkpoint regulation may be a requisite step on the roadway to cancer. Mathematical modeling has proved to be a useful guide to cell cycle regulation by revealing the importance of bistability, hysteresis and time lags in governing cell cycle transitions and checkpoint mechanisms. In this report, we propose a mathematical model of the frog egg cell cycle including effects of unreplicated DNA on progression into mitosis. By a stepwise approach utilizing parameter estimation tools, we build a model that is grounded in fundamental behaviors of the cell cycle engine (hysteresis and time lags), includes new elements in the signaling network (Myt1 and Chk1 kinases), and fits a large and diverse body of data from the experimental literature. The model provides a validated framework upon which to build additional aspects of the cell cycle checkpoint signaling network, including those control signals in the mammalian cell cycle that are commonly mutated in cancer.