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A method is presented for the estimation of the standard Gibbs energies of formation of biochemical compounds (and hence the Gibbs energies and equilibrium constants of biochemical reactions) from the contributions of groups. The method employs a large set of groups and special corrections. The contributions were estimated via multiple linear regression, using screened and weighted literature data. For most of the data employed, the error is less than 2 kcal/mol. The method provides a useful first approximation to Gibbs energies and equilibrium constants in biochemical systems.

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The synthesis of biochemical pathways satisfying stoichiometric constraints is discussed. Stoichiometric constraints arise primarily from designating compounds as required or allowed reactants, and required or allowed products of the pathways; they also arise from similar restrictions on intermediate metabolites and bioreactions participating in the pathways. An algorithm for the complete and correct solution of the problem is presented; the algorithm satisfies each constraint by recursively transforming a base-set of pathways. The algorithm is applied to the problem of lysine synthesis from glucose and ammonia. In addition to the established synthesis routes, the algorithm constructs several alternative pathways that bypass key enzymes, such as malate dehydrogenase and pyruvate dehydrogenase. Apart from the construction of pathways with desired characteristics, the systematic synthesis of pathways can also uncover fundamental constraints in a particular problem, by demonstrating that no pathways exist to meet certain sets of specifications. In the case of lysine, the algorithm shows that oxaloacetate is a necessary intermediate in all pathways leading to lysine from glucose, and that the yield of lysine over glucose cannot exceed 67% in the absence of enzymatic recovery of carbon dioxide.

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A method to efficiently simulate diffusion and reaction in a single-file system is presented. By considering all possible configurations of M species in a length N one-dimensional pore, a deterministic model consisting of (M+1)N variables can be constructed for the system. The order of the system can then be significantly reduced by considering only pairs of adjacent cells, or (M+1)2(N−1) doublets. This lumped model is able to capture the most important correlations between cells when the dominant mode of transport is through single-site hops. Extensions of this method for higher dimensional pores and more complex molecular interactions are discussed. The results of the approximation are compared to results of the full deterministic model, and new situations are investigated. The implications of single-file behavior are discussed for reversible reactions and molecules of different mobilities.

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