We have developed an original method for global optimization of protein side-chain conformations, called the Fast and Accurate Side-Chain Topology and Energy Refinement (FASTER) method. The method operates by systematically overcoming local minima of increasing order. Comparison of the FASTER results with those of the dead-end elimination (DEE) algorithm showed that both methods produce nearly identical results, but the FASTER algorithm is 100-1000 times faster than the DEE method and scales in a stable and favorable way as a function of protein size. We also show that low-order local minima may be almost as accurate as the global minimum when evaluated against experimentally determined structures. In addition, the new algorithm provides significant information about the conformational flexibility of individual side-chains. We observed that strictly rigid side-chains are concentrated mainly in the core of the protein, whereas highly flexible side-chains are found almost exclusively among solvent-oriented residues.
Dead-end elimination (DEE) is a powerful theorem for selecting optimal protein side-chain orientations from a large set of discrete conformations. The present work describes a new approach to dead-end elimination that effectively splits conformational space into partitions to more efficiently eliminate dead-ending rotamers. Split DEE makes it possible to complete protein design calculations that were previously intractable due to the combinatorial explosion of intermediate conformations generated during the convergence process.
The role of computers in the monitoring and control of fermentation processes has increased steadfastly. The ultimate utility of the machines will not depend on the availability of online sensors but also on the availability of techniques that combine direct measurements, leading towards estimates of variable closely related to the microbial process or its control. In this article, a methodology for on-line and noninterfering evaluation of the volumetric mass-transfer coefficient K(l)a is developed. A detailed presentation of the procedure, called "the static method," is given. Its feasibility is proved through implementation of the method on an antibiotic fermentation process. These experiments indicate that operator actions meant to modify the oxygen-transfer conditions can be checked on-line. The quantitative value of the static method is ascertained by comparing the experimental results with K(l)a estimates obtained with the "gassing-out" method. A sensitivity analysis was carried out, revealing the need for temperature and pressure corrections and showing that the precision of the oxygen analyzer determines the precision of the static method.
SUMMARYThis paper presents the application of optimal control theory in determining the optimal feed rate profile for the penicillin G fed-batch fermentation, using a mathematical model based on balancing methods. Since this model does not fulfil all requisites for standard optimal control, we propose a sequence of new models -that converges to the original one in a smooth way -to which the standard techniques are applicable. The unusual optimization of some initial conditions is included. We then state the conjecture that allows us to obtain the optimal control for the original model. The enormous gains in production and the vanishing of the characteristic biphasic behaviour through feed rate profile optimization raise some questions concerning the validity of this model. In this way this optimal control study can prove to be very useful for model discrimination purposes. Furthermore, mathematical and microbial insights lead to the construction of a suboptimal heuristic strategy -which we show to be a limiting case of the optimal scheme -that can serve as a basis for the development of robust, model-independent, optimal adaptive control schemes.
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