Refine
Year of publication
Document Type
- Article (112)
- ZIB-Report (40)
- In Proceedings (5)
- Book chapter (4)
- In Collection (3)
- Other (3)
- Research data (3)
- Doctoral Thesis (2)
- Poster (2)
- Book (1)
Is part of the Bibliography
- no (176)
Keywords
- Markov State Models (5)
- metastability (5)
- cluster analysis (4)
- molecular dynamics (4)
- rare events (4)
- Conformation Dynamics (3)
- MSM (3)
- Perron cluster analysis (3)
- Schur decomposition (3)
- dynamical systems (3)
Institute
- Numerical Mathematics (136)
- Computational Molecular Design (117)
- Modeling and Simulation of Complex Processes (39)
- ZIB Allgemein (15)
- Computational Systems Biology (13)
- Mathematics for Life and Materials Science (7)
- Parallel and Distributed Computing (3)
- Mathematical Algorithmic Intelligence (2)
- Mathematical Optimization (2)
- Mathematical Optimization Methods (2)
The Wiseman fitting can be used to extract binding parameters from ITC data sets, such as heat of binding, number of binding sites, and the overall dissociation rate. The classical Wiseman fitting assumes a direct binding process and neglects the possibility of intermediate binding steps. In principle, it only provides thermodynamic information and not the kinetics of the process. In this article we show that a concentration dependent dissociation constant could possibly stem from intermediate binding steps. The mathematical form of this dependency can be exploited with the aid of the Robust Perron Cluster Cluster Analysis method. Our proposed extension of the Wiseman fitting rationalizes the concentration dependency, and can probably also be used to determine the kinetic parameters of intermediate binding steps of a multivalent binding process. The novelty of this paper is to assume that the binding rate varies per titration step due to the change of the ligand concentration and to use this information in the Wiseman fitting. We do not claim to produce the most accurate values of the binding parameters, we rather present a novel method of how to approach multivalent bindings from a different angle.
The rebinding effect is a phenomenon which occurs when observing a ligand-receptor binding process. On the macro scale this process comprises the Markov property. This Makovian view is spoiled when switching to the atomistic scale of a binding process. We therefore suggest a model which accurately describes the rebinding effect on the atomistic scale by allowing ''intermediate'' bound states. This allows us to define an indicator for the magnitude of rebinding and to formulate an optimization problem. The results form our examples show good agreement with data form laboratory.
The rebinding effect is a phenomenon which occurs when observing a ligand-receptor binding process.
On the macro scale this process comprises the Markov property.
This Makovian view is spoiled when switching to the atomistic scale of a binding process.
We therefore suggest a model which accurately describes the rebinding effect on the atomistic scale by allowing ''intermediate'' bound states.
This allows us to define an indicator for the magnitude of rebinding and to formulate an optimization problem.
The results form our examples show good agreement with data form laboratory.
We consider two disjoint sets of points with a distance metric, or a
proximity function, associated with each set. If each set can be separately
embedded into separate Euclidean spaces, then we provide sufficient conditions
for the two sets to be jointly embedded in one Euclidean space. In this joint
Euclidean embedding, the distances between the points are generated by a
specific relation-preserving function. Consequently, the mutual distances
between two points of the same set are specific qualitative transformations of
their mutual distances in their original space; the pairwise distances between
the points of different sets can be constructed from an arbitrary proximity
function (might require scaling).