The thermostabilization of an enzyme while maintaining its activity for industrial or biomedical applications using traditional selection methods can be difficult. We demonstrate a rapid computational approach that identified three mutations within a model enzyme that produce a 10°C increase in apparent T m and a 30-fold increase in half-life at 50°C, with no reduction in catalytic efficiency. The effects of the mutations were synergistic, giving an increase in excess of the sum of their individual effects. The redesigned enzyme induces an increased, temperaturedependent bacterial growth rate under conditions that require its activity, thereby coupling molecular and metabolic engineering.Enzymes are the most efficient catalysts of chemical reactions known, enhancing reaction rates by as much as twenty-three orders of magnitude (1, 2). However, there has been little evolutionary pressure for them to become more thermostable than is required by their native environment. Many studies indicate that enzymes (like most proteins) exhibit closely balanced free energy profiles for folding and unfolding, thereby allowing functionally important dynamic motions and appropriate degradation in vivo (3). However, in a laboratory or industrial setting this lack of thermostability can lead to undesirable loss of activity (4).The physical principles of protein folding that result in a balance of stability and flexibility, while maintaining function, are not perfectly understood and have been difficult to exploit for the development of thermostabilized enzymes (4). For hyperthermophiles, selective pressures have generated proteins with denaturation temperatures upwards of 110° C (5). Their proteins exhibit topologies and stabilizing interactions similar to those from mesophilic and thermophilic organisms (6, 7) leading to diverse hypotheses regarding their relative behaviors (8). However, a key mechanism for thermostabilization appears to be optimization of interactions between amino acids within their core (5), complementing computational design methods which optimize a sequence for a given fold (9-13).The thermostabilization of an enzyme presents additional challenges for computational protein design methods because the active site substrate geometry and the molecular dynamic behavior during an enzymatic reaction often appear fine-tuned for maximum catalytic efficiency (2, 3). Therefore the design method must be capable of predicting thermostabilizing mutations within a given fold while minimizing any shift in the backbone that might structurally disrupt the active site structure or quench its flexibility. In the past several years, methods for computational protein structure prediction and design have improved significantly (10,11,14). Recently, computational design has been used successfully in thermostabilizing non-catalytic proteins (15-18), redesigning binding pockets (19)(20)(21)(22)(23), creating a novel protein fold (24) and designing catalytic activity into a bacterial receptor (25). We use the program RosettaDe...

With the emergence of multidrug-resistant strains of Mycobacterium tuberculosis there is a pressing need for new oral drugs with novel mechanisms of action. Herein, we describe the identification of a novel morpholino–thiophenes (MOT) series following phenotypic screening of the Eli Lilly corporate library against M. tuberculosis strain H37Rv. The design, synthesis, and structure–activity relationships of a range of analogues around the confirmed actives are described. Optimized leads with potent whole cell activity against H37Rv, no cytotoxicity flags, and in vivo efficacy in an acute murine model of infection are described. Mode-of-action studies suggest that the novel scaffold targets QcrB, a subunit of the menaquinol cytochrome c oxidoreductase, part of the bc1-aa3-type cytochrome c oxidase complex that is responsible for driving oxygen-dependent respiration.