Temperature and detection-wavelength dependence of the electron transfer rates in initial stages of photosynthesis

Weak temperature dependence of P (+) H A (-) recombination in mutant Rhodobacter sphaeroides reaction centers

In contrast with findings on the wild-type Rhodobacter sphaeroides reaction center, biexponential P (+) H A (-)  → PH A charge recombination is shown to be weakly dependent on temperature between 78 and 298 K in three variants with single amino acids exchanged in the vicinity of primary electron acceptors. These mutated reaction centers have diverse overall kinetics of charge recombination, spanning an average lifetime from ~2 to ~20 ns. Despite these differences a protein relaxation model applied previously to wild-type reaction centers was successfully used to relate the observed kinetics to the temporal evolution of the free energy level of the state P (+) H A (-) relative to P (+) B A (-) . We conclude that the observed variety in the kinetics of charge recombination, together with their weak temperature dependence, is caused by a combination of factors that are each affected to a different extent by the point mutations in a particular mutant complex. These are as follows: (1) the initial free energy gap between the states P (+) B A (-) and P (+) H A (-) , (2) the intrinsic rate of P (+) B A (-)  → PB A charge recombination, and (3) the rate of protein relaxation in response to the appearance of the charge separated states. In the case of a mutant which displays rapid P (+) H A (-) recombination (ELL), most of this recombination occurs in an unrelaxed protein in which P (+) B A (-) and P (+) H A (-) are almost isoenergetic. In contrast, in a mutant in which P (+) H A (-) recombination is relatively slow (GML), most of the recombination occurs in a relaxed protein in which P (+) H A (-) is much lower in energy than P (+) H A (-) . The weak temperature dependence in the ELL reaction center and a YLH mutant was modeled in two ways: (1) by assuming that the initial P (+) B A (-) and P (+) H A (-) states in an unrelaxed protein are isoenergetic, whereas the final free energy gap between these states following the protein relaxation is large (~250 meV or more), independent of temperature and (2) by assuming that the initial and final free energy gaps between P (+) B A (-) and P (+) H A (-) are moderate and temperature dependent. In the case of the GML mutant, it was concluded that the free energy gap between P (+) B A (-) and P (+) H A (-) is large at all times.

RaTrav: a tool for calculating mean first-passage times on biochemical networks

BACKGROUND

The concept of mean first-passage times (MFPTs) occupies an important place in the theory of stochastic processes, with the methods of their calculation being equally important in theoretical physics, chemistry and biology. We present here a software tool designed to support computational biology studies where Markovian dynamics takes place and MFPTs between initial and single or multiple final states in network-like systems are used. Two methods are made available for which their efficiency is strongly dependent on the topology of the defined network: the combinatorial Hill technique and the Monte Carlo simulation method.

RESULTS

After a brief introduction to RaTrav, we highlight the utility of MFPT calculations by providing two examples (accompanied by Additional file 1) where they are deemed to be of importance: analysis of a protein-protein docking funnel and interpretation of the free energy transduction between two coupled enzymatic reactions controlled by the dynamics of transition between enzyme conformational states.

CONCLUSIONS

RaTrav is a versatile and easy to use software tool for calculating MFPTs across biochemical networks. The user simply prepares a text file with the structure of a given network, along with some additional basic parameters such as transition probabilities, waiting probabilities (if any) and local times (weights of edges), which define explicitly the stochastic dynamics on the network. The RaTrav tool can then be applied in order to compute desired MFPTs. For the provided examples, we were able to find the favourable binding path within a protein-protein docking funnel and to calculate the degree of coupling for two chemical reactions catalysed simultaneously by the same protein enzyme. However, the list of possible applications is much wider.