THE DEAD-END ELIMINATION THEOREM AND ITS USE IN PROTEIN SIDE-CHAIN POSITIONING

THE prediction of a protein's tertiary structure is still a considerable problem because the huge amount of possible conformational space' makes it computationally difficult. With regard to side-chain modelling, a solution has been attempted by the grouping of side-chain conformations into representative sets of rotamers 2-5. Nonetheless, an exhaustive combinatorial search is still limited to carefully identified packing units 5,6 containing a limited number of residues. For larger systems other strategies had to be developed, such as the Monte Carlo Procedure 6,7 and the genetic algorithm and clustering approach 8. Here we present a theorem, referred to as the 'dead-end elimination' theorem, which imposes a suitable condition to identify rotamers that cannot be members of the global minimum energy conformation. Application of this theorem effectively controls the computational explosion of the rotamer combinatorial problem, thereby allowing the determination of the global minimum energy conformation of a large collection of side chains

Entry and exit decisions in flexible teams

The present study identifies a major limitation of current research on multinational enterprises (MNEs). Joint decision-making in a distributed setting is of critical importance in practice, but has received little attention in our theories. To address this gap in knowledge, we examine the effects of flexible decision teams when MNEs assess turbulent markets. Remarkably, flexible teams composed of fallible evaluators can outperform what is usually thought of as an “optimal” decision. Our main result supports the claims advanced in recent empirical studies. Structural flexibility can help MNEs achieve high levels of performance, even in conditions of turbulence. Journal of International Business Studies (2008) 39, 1278–1292. doi:10.1057/palgrave.jibs.8400413