Optimal design of thermally stable proteins

Motivation: For many biotechnological purposes, it is desirable to redesign proteins to be more structurally and functionally stable at higher temperatures. For example, chemical reactions are intrinsically faster at higher temperatures, so using enzymes that are stable at higher temperatures would lead to more efficient industrial processes. We describe an innovative and computationally efficient method called Improved Configurational Entropy (ICE), which can be used to redesign a protein to be more thermally stable (i.e. stable at high temperatures). This can be accomplished by systematically modifying the amino acid sequence via local structural entropy (LSE) minimization. The minimization problem is modeled as a shortest path problem in an acyclic graph with nonnegative weights and is solved efficiently using Dijkstra's method

Identification of Morpholino Thiophenes as Novel Mycobacterium tuberculosis Inhibitors, Targeting QcrB

With the emergence of multidrug-resistant strains of <i>Mycobacterium tuberculosis</i> 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 <i>M. tuberculosis</i> 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 <i>c</i> oxidoreductase, part of the bc1-aa3-type cytochrome <i>c</i> oxidase complex that is responsible for driving oxygen-dependent respiration

Prots: A fragment based protein thermo‐stability potential

Designing proteins with enhanced thermo‐stability has been a main focus of protein engineering because of its theoretical and practical significance. Despite extensive studies in the past years, a general strategy for stabilizing proteins still remains elusive. Thus effective and robust computational algorithms for designing thermo‐stable proteins are in critical demand. Here we report PROTS, a sequential and structural four‐residue fragment based protein thermo‐stability potential. PROTS is derived from a nonredundant representative collection of thousands of thermophilic and mesophilic protein structures and a large set of point mutations with experimentally determined changes of melting temperatures. To the best of our knowledge, PROTS is the first protein stability predictor based on integrated analysis and mining of these two types of data. Besides conventional cross validation and blind testing, we introduce hypothetical reverse mutations as a means of testing the robustness of protein thermo‐stability predictors. In all tests, PROTS demonstrates the ability to reliably predict mutation induced thermo‐stability changes as well as classify thermophilic and mesophilic proteins. In addition, this white‐box predictor allows easy interpretation of the factors that influence mutation induced protein stability changes at the residue level. Proteins 2012; © 2011 Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/89526/1/23163_ftp.pd

Rapid detection of similarity in protein structure and function through contact metric distances

The characterization of biological function among newly determined protein structures is a central challenge in structural genomics. One class of computational solutions to this problem is based on the similarity of protein structure. Here, we implement a simple yet efficient measure of protein structure similarity, the contact metric. Even though its computation avoids structural alignments and is therefore nearly instantaneous, we find that small values correlate with geometrical root mean square deviations obtained from structural alignments. To test whether the contact metric detects functional similarity, as defined by Gene Ontology (GO) terms, it was compared in large-scale computational experiments to four other measures of structural similarity, including alignment algorithms as well as alignment independent approaches. The contact metric was the fastest method and its sensitivity, at any given specificity level, was a close second only to Fast Alignment and Search Tool—a structural alignment method that is slower by three orders of magnitude. Critically, nearly 40% of correct functional inferences by the contact metric were not identified by any other approach, which shows that the contact metric is complementary and computationally efficient in detecting functional relationships between proteins. A public ‘Contact Metric Internet Server’ is provided

Algorithm for backrub motions in protein design

Motivation: The Backrub is a small but kinematically efficient side-chain-coupled local backbone motion frequently observed in atomic-resolution crystal structures of proteins. A backrub shifts the Cα–Cβ orientation of a given side-chain by rigid-body dipeptide rotation plus smaller individual rotations of the two peptides, with virtually no change in the rest of the protein. Backrubs can therefore provide a biophysically realistic model of local backbone flexibility for structure-based protein design. Previously, however, backrub motions were applied via manual interactive model-building, so their incorporation into a protein design algorithm (a simultaneous search over mutation and backbone/side-chain conformation space) was infeasible

RosettaScripts: A Scripting Language Interface to the Rosetta Macromolecular Modeling Suite

Macromolecular modeling and design are increasingly useful in basic research, biotechnology, and teaching. However, the absence of a user-friendly modeling framework that provides access to a wide range of modeling capabilities is hampering the wider adoption of computational methods by non-experts. RosettaScripts is an XML-like language for specifying modeling tasks in the Rosetta framework. RosettaScripts provides access to protocol-level functionalities, such as rigid-body docking and sequence redesign, and allows fast testing and deployment of complex protocols without need for modifying or recompiling the underlying C++ code. We illustrate these capabilities with RosettaScripts protocols for the stabilization of proteins, the generation of computationally constrained libraries for experimental selection of higher-affinity binding proteins, loop remodeling, small-molecule ligand docking, design of ligand-binding proteins, and specificity redesign in DNA-binding proteins

Role of Active Site Rigidity in Activity: MD Simulation and Fluorescence Study on a Lipase Mutant

Relationship between stability and activity of enzymes is maintained by underlying conformational flexibility. In thermophilic enzymes, a decrease in flexibility causes low enzyme activity while in less stable proteins such as mesophiles and psychrophiles, an increase in flexibility is associated with enhanced enzyme activity. Recently, we identified a mutant of a lipase whose stability and activity were enhanced simultaneously. In this work, we probed the conformational dynamics of the mutant and the wild type lipase, particularly flexibility of their active site using molecular dynamic simulations and time-resolved fluorescence techniques. In contrast to the earlier observations, our data show that active site of the mutant is more rigid than wild type enzyme. Further investigation suggests that this lipase needs minimal reorganization/flexibility of active site residues during its catalytic cycle. Molecular dynamic simulations suggest that catalytically competent active site geometry of the mutant is relatively more preserved than wild type lipase, which might have led to its higher enzyme activity. Our study implies that widely accepted positive correlation between conformation flexibility and enzyme activity need not be stringent and draws attention to the possibility that high enzyme activity can still be accomplished in a rigid active site and stable protein structures. This finding has a significant implication towards better understanding of involvement of dynamic motions in enzyme catalysis and enzyme engineering through mutations in active site

Engineering yeast cytosine deaminase for improved efficacy in cancer gene directed enzyme prodrug therapy

Thesis (Ph. D.)--University of Washington, 2007.Conventional treatment of cancer typically involves some combination of surgery coupled with radio- or chemotherapy. Prognosis in cases of tumor metastasis or inoperable solid-tumors remains grim as cancer cells are often refractory to the DNA damage caused by these treatments due to the loss of cell cycle regulatory proteins during oncogenesis. Higher dosages of either radiation or chemotherapeutic agents can compensate, however, lack of cancer cell specificity and low therapeutic index put strict limitations on dosages that can be administered safely.Growing understanding of oncogenesis and molecular biology has lead to the development of vectors capable of targeting and transducing tumors with high specificity. One of the most successful applications of this technology has been a form of targeted chemotherapy called gene-directed enzyme/prodrug therapy (GDEPT), in which tumor cells are transduced with a suicide gene encoding a non-endogenous enzyme that later metabolically converts a systemically administered prodrug into a potent cytotoxin locally within the tumor. These enzymes are often non-ideal due to both lack of stability and low catalytic efficiency. Protein engineering methods could be used in order to tailor the pharmacokinetic profiles of these enzymes for improved therapeutic use.Our work focused on the re-engineering the enzyme yeast cytosine deaminase for improved efficacy in GDEPT. Two distinct enzyme engineering strategies were employed: regiospecific random mutagenesis was used in order to select for mutants with increased sensitization to the prodrug 5-fluorocytosine while computational design was used to select thermostabilizing mutations. Both approaches lead to independent mutations that conferred improved pharmacokinetics in in vivo mouse tumor xenograph models. Additional study revealed that in both cases the biochemical cause of improvement appeared to be thermostabilization of the enzyme and not an improvement in catalytic efficiency