STAR: predicting recombination sites from amino acid sequence

Background: Designing novel proteins with site-directed recombination has enormous prospects. By locating effective recombination sites for swapping sequence parts, the probability that hybrid sequences have the desired properties is increased dramatically. The prohibitive requirements for applying current tools led us to investigate machine learning to assist in finding useful recombination sites from amino acid sequence alone. Results: We present STAR, Site Targeted Amino acid Recombination predictor, which produces a score indicating the structural disruption caused by recombination, for each position in an amino acid sequence. Example predictions contrasted with those of alternative tools, illustrate STAR'S utility to assist in determining useful recombination sites. Overall, the correlation coefficient between the output of the experimentally validated protein design algorithm SCHEMA and the prediction of STAR is very high (0.89). Conclusion: STAR allows the user to explore useful recombination sites in amino acid sequences with unknown structure and unknown evolutionary origin. The predictor service is available from http://pprowler.itee.uq.edu.au/star.

Predicting structural disruption of proteins caused by crossover

We present a machine learning model that predicts a structural disruption score from a protein’s primary structure. SCHEMA was introduced by Frances Arnold and colleagues as a method for determining putative recombination sites of a protein on the basis of the full (PDB) description of its structure. The present method provides an alternative to SCHEMA that is able to determine the same score from sequence data only. Circumventing the need for resolving the full structure enables the exploration of yet unresolved and even hypothetical sequences for protein design efforts. Deriving the SCHEMA score from a primary structure is achieved using a two step approach: first predicting a secondary structure from the sequence and then predicting the SCHEMA score from the predicted secondary structure. The correlation coefficient for the prediction is 0.88 and indicates the feasibility of replacing SCHEMA with little loss of precision. ©2005 IEEE

Design analysis for refolding monomeric protein

Renaturation of protein expressed as inclusion bodies within Escherichia coli is a key step in many bioprocesses. Operating conditions for the refolding step dramatically affect the amount of protein product recovered, and hence profoundly influence the process economics. The first systematic comparison of refolding conducted in batch, fed-batch and continuous stirred-tank reactors is provided Refolding is modeled as kinetic competition between first-order refolding (equilibrium reaction) and irreversible aggregation (second-order). Simulations presented allow direct comparison between different flowsheets and refolding schemes using a dimensionless economic objective. As expected from examination of the reaction kinetics, batch operation is the most inefficient merle. For the base process considered, the overall cost of fed-batch and continuous refolding is virtually identical (less than half that of the batch process). Reactor selection and optimization of refolding using overall economics are demonstrated to be vitally important.

Post translational modifications of recombinant human Papillomavirus type 6b major capsid protein

We have determined the post-translational modifications of the major capsid protein, L1 of human papillomavirus (HPV) type 6b. Since this virus cannot be cultured in the laboratory to obtain sufficient material for a study, a recombinant L1 protein produced in a vaccinia virus expression system was used in this investigation. Our results show that this protein is phosphorylated at serine residues and is also glycosylated. No myristoylation or palmitoylation was detected. The fraction of L1 protein incorporated into virus-like particles was not glycosylated. Since recombinant L1 protein is a potential human vaccine candidate, knowledge of the post-translation modifications of this protein may prove useful for the design of anti-HPV vaccines. (C) 1999 Elsevier Science B.V. All rights reserved.

MiAMP1, a novel protein from Macadamia integrifolia adopts a Greek key beta-barrel fold unique amongst plant antimicrobial proteins

MiAMP1 is a recently discovered 76 amino acid residue, highly basic protein from the nut kernel of:Macadamia integrifolia which possesses no sequence homology to any known protein and inhibits the growth of several microbial plant pathogens in vitro while having no effect on mammalian or plant cells. It is considered to be a potentially useful tool for the genetic engineering of disease resistance in transgenic crop plants and for the design of new fungicides. The three-dimensional structure of MiAMP1 was determined through homonuclear and heteronuclear (N-15) 2D NMR spectroscopy and subsequent simulated annealing calculations with the ultimate aim of understanding the structure-activity relationships of the protein. MiAMP1 is made up of eight beta-strands which are arranged in two Greek key motifs. These Greek key motifs associate to form a Greek key beta-barrel. This structure is unique amongst plant antimicrobial proteins and forms a new class which we term the beta-barrelins. Interestingly, the structure of MiAMP1 bears remarkable similarity to a yeast killer toxin from Williopsis mrakii. This toxin acts by inhibiting beta-glucan synthesis and thereby cell wall construction in sensitive strains of yeast. The structural similarity of MiAMP1 and WmKT, which originate from plant and fungal phyla respectively, may reflect a similar mode of action. (C) 1999 Academic Press.

Approach to designing rotating drum bioreactors for solid-state fermentation on the basis of dimensionless design factors

The development of large-scale solid-stale fermentation (SSF) processes is hampered by the lack of simple tools for the design of SSF bioreactors. The use of semifundamental mathematical models to design and operate SSF bioreactors can be complex. In this work, dimensionless design factors are used to predict the effects of scale and of operational variables on the performance of rotating drum bioreactors. The dimensionless design factor (DDF) is a ratio of the rate of heat generation to the rate of heat removal at the time of peak heat production. It can be used to predict maximum temperatures reached within the substrate bed for given operational variables. Alternatively, given the maximum temperature that can be tolerated during the fermentation, it can be used to explore the combinations of operating variables that prevent that temperature from being exceeded. Comparison of the predictions of the DDF approach with literature data for operation of rotating drums suggests that the DDF is a useful tool. The DDF approach was used to explore the consequences of three scale-up strategies on the required air flow rates and maximum temperatures achieved in the substrate bed as the bioreactor size was increased on the basis of geometric similarity. The first of these strategies was to maintain the superficial flow rate of the process air through the drum constant. The second was to maintain the ratio of volumes of air per volume of bioreactor constant. The third strategy was to adjust the air flow rate with increase in scale in such a manner as to maintain constant the maximum temperature attained in the substrate bed during the fermentation. (C) 2000 John Wiley & Sons, Inc.

Conformational selection of inhibitors and substrates by proteolytic enzymes: Implications for drug design and polypeptide processing

Inhibitors of proteolytic enzymes (proteases) are emerging as prospective treatments for diseases such as AIDS and viral infections, cancers, inflammatory disorders, and Alzheimer's disease. Generic approaches to the design of protease inhibitors are limited by the unpredictability of interactions between, and structural changes to, inhibitor and protease during binding. A computer analysis of superimposed crystal structures for 266 small molecule inhibitors bound to 48 proteases (16 aspartic, 17 serine, 8 cysteine, and 7 metallo) provides the first conclusive proof that inhibitors, including substrate analogues, commonly bind in an extended beta-strand conformation at the active sites of all these proteases. Representative superimposed structures are shown for (a) multiple inhibitors bound to a protease of each class, (b) single inhibitors each bound to multiple proteases, and (c) conformationally constrained inhibitors bound to proteases. Thus inhibitor/substrate conformation, rather than sequence/composition alone, influences protease recognition, and this has profound implications for inhibitor design. This conclusion is supported by NMR, CD, and binding studies for HIV-1 protease inhibitors/ substrates which, when preorganized in an extended conformation, have significantly higher protease affinity. Recognition is dependent upon conformational equilibria since helical and turn peptide conformations are not processed by proteases. Conformational selection explains the resistance of folded/structured regions of proteins to proteolytic degradation, the susceptibility of denatured proteins to processing, and the higher affinity of conformationally constrained 'extended' inhibitors/substrates for proteases. Other approaches to extended inhibitor conformations should similarly lead to high-affinity binding to a protease.

Physicochemical characteristics of LR3-IGF1 protein inclusion bodies: Electrophoretic mobility studies

A knowledge of the physicochemical properties of inclusion bodies is important for the rational design of potential recovery processes such as flotation and precipitation. In this study, measurement of the size and electrophoretic mobility of protein inclusion bodies and cell debris was undertaken. SDS-PAGE analysis of protein inclusion bodies subjected to different cleaning regimes suggested that electrophoretic mobility provides a qualitative measure of protein inclusion body purity. Electrophoretic mobility as a function of electrolyte type and ionic strength was investigated. The presence of divalent ions produced a stronger effect on electrophoretic mobility compared with monovalent ions. The isoelectric point of cell debris was significantly lower than that for the inclusion bodies. Hence, the contaminating cell debris may be separated from inclusion bodies using flotation by exploiting this difference in isoelectric points. Separation by this method is simple, convenient, and a possible alternative to the conventional route of centrifugation.

Measuring the interaction forces between protein inclusion bodies and an air bubble using an atomic force microscope

Interaction forces between protein inclusion bodies and an air bubble have been quantified using an atomic force microscope (AFM). The inclusion bodies were attached to the AFM tip by covalent bonds. Interaction forces measured in various buffer concentrations varied from 9.7 nN to 25.3 nN (+/- 4-11%) depending on pH. Hydrophobic forces provide a stronger contribution to overall interaction force than electrostatic double layer forces. It also appears that the ionic strength affects the interaction force in a complex way that cannot be directly predicted by DLVO theory. The effects of pH are significantly stronger for the inclusion body compared to the air bubble. This study provides fundamental information that will subsequently facilitate the rational design of flotation recovery system for inclusion bodies. It has also demonstrated the potential of AFM to facilitate the design of such processes from a practical viewpoint.

Bioprocess-centered molecular design (BMD) for the efficient production of an interfacially active peptide

The efficient expression and purification of an interfacially active peptide (mLac21) was achieved by using bioprocess-centered molecular design (BMD), wherein key bioprocess considerations are addressed during the initial molecular biology work. The 21 amino acid mLac21 peptide sequence is derived from the lac repressor protein and is shown to have high affinity for the oil-water interface, causing a substantial reduction in interfacial tension following adsorption. The DNA coding for the peptide sequence was cloned into a modified pET-31(b) vector to permit the expression of mLac21 as a fusion to ketosteroid isomerase (KSI). Rational iterative molecular design, taking into account the need for a scaleable bioprocess flowsheet, led to a simple and efficient bioprocess yielding mLac21 at 86% purity following ion exchange chromatography (and >98% following chromatographic polishing). This case study demonstrates that it is possible to produce acceptably pure peptide for potential commodity applications using common scaleable bioprocess unit operations. Moreover, it is shown that BMD is a powerful strategy that can be deployed to reduce bioseparation complexity. (C) 2004 Wiley Periodicals, Inc.

Protein crystallography and examples of its applications in medicinal chemistry

The field of protein crystallography inspires and enthrals, whether it be for the beauty and symmetry of a perfectly formed protein crystal, the unlocked secrets of a novel protein fold, or the precise atomic-level detail yielded from a protein-ligand complex. Since 1958, when the first protein structure was solved, there have been tremendous advances in all aspects of protein crystallography, from protein preparation and crystallisation through to diffraction data measurement and structure refinement. These advances have significantly reduced the time required to solve protein crystal structures, while at the same time substantially improving the quality and resolution of the resulting structures. Moreover, the technological developments have induced researchers to tackle ever more complex systems, including ribosomes and intact membrane-bound proteins, with a reasonable expectation of success. In this review, the steps involved in determining a protein crystal structure are described and the impact of recent methodological advances identified. Protein crystal structures have proved to be extraordinarily useful in medicinal chemistry research, particularly with respect to inhibitor design. The precise interaction between a drug and its receptor can be visualised at the molecular level using protein crystal structures, and this information then used to improve the complementarity and thus increase the potency and selectivity of an inhibitor. The use of protein crystal structures in receptor-based drug design is highlighted by (i) HIV protease, (ii) influenza virus neuraminidase and (iii) prostaglandin H-2-synthetase. These represent, respectively, examples of protein crystal structures that (i) influenced the design of drugs currently approved for use in the treatment of HIV infection, (ii) led to the design of compounds currently in clinical trials for the treatment of influenza infection and (iii) could enable the design of highly specific non-steroidal anti-inflammatory drugs that lack the common side-effects of this drug class.