143 research outputs found
Using Energy Landscape Theory to Uncover the Organization of Conformational Space of Proteins in Their Native States.
The functional motions of proteins navigate on rugged energy landscapes. Hence, mapping of these multidimensional landscapes into lower dimensional manifolds is imperative for gaining deeper insights into the functional dynamics. In the present work we implement novel computational schemes and means of analysis to characterize the topography of conformational space of selected proteins and also to elucidate their functional implications. The present thesis is divided into two parts, where we focus on the case studies of the intrinsically disordered histone tails and the representative allosteric protein Adenlyate Kinase. In particular, analyzing the energy landscapes of histone tails, we find preferential clustering of transient secondary structural elements in the conformational ensembles, which have a dramatic impact on the chain statistics, conformational dynamics and the binding pathways. In the study of Adenylate Kinase we use a novel nonlinear order parameter to rigorously estimate the free energy difference between allosteric states and map out the plausible pathway of transition, which reveals important structural and thermodynamic insights about the mechanism of allostery in Adenylate Kinase. Taken together our findings indicate that the organization of conformational space of functional proteins is delicately crafted to ensure efficient functional regulation and robust response to external signals
Dichotomous noise models of gene switches
Molecular noise in gene regulatory networks has two intrinsic components, one part being due to fluctuations caused by the birth and death of protein or mRNA molecules which are often present in small numbers and the other part arising from gene state switching, a single molecule event. Stochastic dynamics of gene regulatory circuits appears to be largely responsible for bifurcations into a set of multi-attractor states that encode different cell phenotypes. The interplay of dichotomous single molecule gene noise with the nonlinear architecture of genetic networks generates rich and complex phenomena. In this paper, we elaborate on an approximate framework that leads to simple hybrid multi-scale schemes well suited for the quantitative exploration of the steady state properties of large-scale cellular genetic circuits. Through a path sum based analysis of trajectory statistics, we elucidate the connection of these hybrid schemes to the underlying master equation and provide a rigorous justification for using dichotomous noise based models to study genetic networks. Numerical simulations of circuit models reveal that the contribution of the genetic noise of single molecule origin to the total noise is significant for a wide range of kinetic regimes
Impact of Covalent Modifications on Binding and Conformational Propensities of Histone Tails
A stochastic and dynamical view of pluripotency in mouse embryonic stem cells
Pluripotent embryonic stem cells are of paramount importance for biomedical
research thanks to their innate ability for self-renewal and differentiation
into all major cell lines. The fateful decision to exit or remain in the
pluripotent state is regulated by complex genetic regulatory network. Latest
advances in transcriptomics have made it possible to infer basic topologies of
pluripotency governing networks. The inferred network topologies, however, only
encode boolean information while remaining silent about the roles of dynamics
and molecular noise in gene expression. These features are widely considered
essential for functional decision making. Herein we developed a framework for
extending the boolean level networks into models accounting for individual
genetic switches and promoter architecture which allows mechanistic
interrogation of the roles of molecular noise, external signaling, and network
topology. We demonstrate the pluripotent state of the network to be a broad
attractor which is robust to variations of gene expression. Dynamics of exiting
the pluripotent state, on the other hand, is significantly influenced by the
molecular noise originating from genetic switching events which makes cells
more responsive to extracellular signals. Lastly we show that steady state
probability landscape can be significantly remodeled by global gene switching
rates alone which can be taken as a proxy for how global epigenetic
modifications exert control over stability of pluripotent states.Comment: 11 pages, 7 figure
An IBM 1800 Program Package for On-Line and Off-Line Operation of a Calcomp Digital Incremental Plotter. EUR 4225.
Supplementary Materials. (PDF 1263 kb
Computing free energies of protein conformations from explicit solvent simulations
We report a fully general technique addressing a long standing challenge of calculating conformational free energy differences between various states of a polymer chain from simulations using explicit solvent force fields. The main feature of our method is a special mapping variable, a path coordinate, which continuously connects two conformations. The path variable has been designed to preserve locality in the phase space near the path endpoints. We avoid the problem of sampling the unfolded states by creating an artificial confinement “tube” in the phase space that prevents the molecule from unfolding without affecting the calculation of the desired free energy difference. We applied our technique to compute the free energy difference between two native-like conformations of the small protein Trp-cage using the CHARMM force field with explicit solvent. We verified this result by comparing it with an independent, significantly more expensive calculation. Overall, the present study suggests that the new method of computing free energy differences between polymer chain conformations is accurate and highly computationally efficient
Computational modeling to elucidate molecular mechanisms of epigenetic memory
How do mammalian cells that share the same genome exist in notably distinct
phenotypes, exhibiting differences in morphology, gene expression patterns, and
epigenetic chromatin statuses? Furthermore how do cells of different phenotypes
differentiate reproducibly from a single fertilized egg? These are fundamental
problems in developmental biology. Epigenetic histone modifications play an
important role in the maintenance of different cell phenotypes. The exact
molecular mechanism for inheritance of the modification patterns over cell
generations remains elusive. The complexity comes partly from the number of
molecular species and the broad time scales involved. In recent years
mathematical modeling has made significant contributions on elucidating the
molecular mechanisms of DNA methylation and histone covalent modification
inheritance. We will pedagogically introduce the typical procedure and some
technical details of performing a mathematical modeling study, and discuss
future developments.Comment: 36 pages, 4 figures, 2 tables, book chapte
- …