The naturally occurring mineral of Cu2ZnSnS4 (CZTS) is a promising alternative absorber layer for thin film based photovoltaic devices. It has the remarkable advantage that it consists of abundant, inexpensive and non-toxic elements compared to its crystallographically related and highly successful counterparts: the Cu(In,Ga)(S,Se)2 (CIGSSe) and CuIn(S, Se)2 (CISSe) material systems. Therefore, there is real commercial potential for reduced material costs and improved device efficiencies. A two-stage high throughput combinatorial process for the fabrication of Cu-Zn-Sn-S thin film libraries is presented, which consists of either sequentially stacking or co-depositing Cu,Sn and Zn precursor layers by DC magnetron sputtering followed by a sulphurisation process. Sputtering conditions and target-substrate geometry are developed to give compositionally graded Cu-Zn-Sn precursor layers spanning a wide spatial region around the point of stoichiometry. Conversion into Cu-Zn-Sn-S libraries is achieved by thermally evaporating a uniform layer of sulphur directly onto the metal alloy and annealing the sample at 500 °C in a furnace. Effects of the precursor composition on the structural properties of the films prior to the incorporation of sulphur are investigated. The sulphurised libraries are then studied by Scanning electron microscopy (SEM), X-ray diffraction (XRD) and Raman spectroscopy as a function of composition, to assess the effects on morphology and phase formation. Observations of changes in lattice parameters and crystallinity are clear. The opto-electronic and electrical properties of the CZTS film libraries are measured using photoconductivity and hot point probe techniques, respectively. Changes in the band gap and conductivity type are studied as a function of atomic ratios. Based on high performing compositions, devices have been fabricated with the highest achieving cell at 1.26 %. The observations are discussed in the context of the particular compositions and synthesis conditions, and recommendations are made for further work.

No description available.

The naturally occurring mineral of Cu2ZnSnS4 (CZTS) is a promising alternative absorber layer for thin film based photovoltaic devices. It has the remarkable advantage that it consists of abundant, inexpensive and non-toxic elements compared to its crystallographically related and highly successful counterparts: the Cu(In,Ga)(S,Se)2 (CIGSSe) and CuIn(S, Se)2 (CISSe) material systems. Therefore, there is real commercial potential for reduced material costs and improved device efficiencies. A two-stage high throughput combinatorial process for the fabrication of Cu-Zn-Sn-S thin film libraries is presented, which consists of either sequentially stacking or co-depositing Cu,Sn and Zn precursor layers by DC magnetron sputtering followed by a sulphurisation process. Sputtering conditions and target-substrate geometry are developed to give compositionally graded Cu-Zn-Sn precursor layers spanning a wide spatial region around the point of stoichiometry. Conversion into Cu-Zn-Sn-S libraries is achieved by thermally evaporating a uniform layer of sulphur directly onto the metal alloy and annealing the sample at 500 °C in a furnace. Effects of the precursor composition on the structural properties of the films prior to the incorporation of sulphur are investigated. The sulphurised libraries are then studied by Scanning electron microscopy (SEM), X-ray diffraction (XRD) and Raman spectroscopy as a function of composition, to assess the effects on morphology and phase formation. Observations of changes in lattice parameters and crystallinity are clear. The opto-electronic and electrical properties of the CZTS film libraries are measured using photoconductivity and hot point probe techniques, respectively. Changes in the band gap and conductivity type are studied as a function of atomic ratios. Based on high performing compositions, devices have been fabricated with the highest achieving cell at 1.26 %. The observations are discussed in the context of the particular compositions and synthesis conditions, and recommendations are made for further work.

Engineered affinity proteins have together with naturally derived antibodies becomeindispensable tools in many areas of life-science and with the increasing number ofapplications, the need for high-throughput methods for generation of such different affinityproteins is evident. Today, combinatorial protein engineering is the most successful strategy toisolate novel non-immunoglobulin affinity proteins. In this approach, generally termed directedevolution, high-complexity combinatorial libraries are created from which affinity proteins areisolated using an appropriate selection method, thus circumventing the need for detailedknowledge of the protein structure or the binding mechanism, often necessary in more rationalapproaches. Since the introduction of the phage display technology that pioneered the field ofcombinatorial engineering, several alternative selection systems have been developed for thispurpose.This thesis describes the development of a novel selection system based onstaphylococcal surface display and its implementation in directed evolution approaches. In thefirst study, the transformation efficiency to the gram-positive bacteria Staphylococcus carnosus wassuccessfully improved around 10,000-fold to a level that would allow cell surface display ofcomplex combinatorial protein libraries. In two separate studies, the staphylococcal displaysystem was investigated for the applicability in both de novo selection and affinity maturation ofaffibody molecules. First, using a pre-selection strategy with one round of phage display, ahigh-complexity affibody library was displayed on staphylococcal cells. Using fluorescenceactivatedcell sorting, binders with sub-nanomolar affinity to tumor necrosis factor-alpha(TNF-α) were isolated. Second, a combined approach using phage display for de novo selectionof first-generation affibody binders and staphylococcal display in a subsequent affinitymaturation selection was applied to generate binders with low nanomolar affinity to the humanepidermal growth factor receptor-3 (ErbB3). Moreover, in an additional study, thestaphylococcal surface display system was improved by the introduction of a protease 3Ccleavage sequence in the displayed fusion products in order to facilitate straightforwardproduction of soluble proteins for further downstream characterization.Altogether, the presented studies demonstrate that the staphylococcal selection systemindeed is a powerful tool for selection and characterization of novel affinity proteins and couldbecome an attractive alternative to existing selection techniques. / <p>QC 20100726</p>

Even though our understanding of mechanisms such as protein folding and molecular recognition is relatively poor, antibodies and alternative affinity proteins with entirely novel functions are today generated in a routine manner. The reason for this success is an engineering approach generally known as directed evolution. Directed evolution has provided researchers with a tool for circumventing our limited knowledge and hence the possibility to create novel molecules that by no means could have been designed today. The approach is based on construction of high-complexity combinatorial libraries from which protein variants with desired properties can be selected. Engineered proteins are already indispensable tools in nearly all areas of life science and the recent advent of mainly monoclonal antibodies as therapeutic agents has directed even more attention to the field of combinatorial protein engineering. In this thesis, I present the underlying research efforts of six original papers. The overall objective of the studies has been to develop and investigate a new staphylococcal surface display method for protein engineering and protein characterization. The technology is based on display of recombinant proteins on surface of the Gram-positive bacteria Staphylococcus carnosus. In two initial studies, two key issues were addressed in order to improve the protein engineering method in regard to affinity discrimination ability and transformation efficiency. The successful results enabled investigation of the staphylococcal display system for de novo generation of affibody molecules from large combinatorial libraries. In this study, a high-complexity protein library was for the first time displayed on surface of Gram-positive bacteria and by means of fluorescence-activated cell sorting, specific affinity proteins for tumor necrosis factor-alpha were isolated. Moreover, in following papers, the staphylococcal display method was further improved and investigated for affinity determination, soluble protein production and epitope mapping purposes in order to facilitate downstream characterizations of generated affinity proteins. Taken together, in these studies we have demonstrated that the staphylococcal display system is a powerful alternative to existing technologies for protein engineering and protein characterization. / QC 20100809

Cancer cells display aberrant receptors on their surface that can serve as targets for the development of directed drug therapies. As such, our group has utilized two parallel approaches to redirect the cytotoxic properties of a ribosome-inactivating protein (RIP), Shiga-Like Toxin 1 (SLT 1), by altering its receptor specificity to target and kill cancer cells. The first combinatorial protein library was constructed such that a randomized 7 AA long peptide was inserted within the cytotoxic domain (A chain) of SLT-1. A high-throughput protein-based screening campaign identified a novel A chain toxin variant (named SLT 1AIYSNKLM) capable of targeting and killing human melanoma cells. This variant harbours a peptide insert (IYSNKLM) that directs the A chain to kill human melanoma cell lines. Equilibrium binding studies using 125I-radiolabeled SLT-1AIYSNKLM were conducted to determine the equilibrium binding constant and receptor density on 518-A2 human melanoma cells. When injected into SCID mice bearing a human melanoma xenograft, nanoSPECT/CT imaging as well as the biodistribution profile showed marked tumour uptake and retention of the radiolabeled toxin variant. Furthermore, preliminary experiments have shown that the SLT-1AIYSNKLM receptor is a protein, highlighting the potential for this method to be used in the discovery of novel biomarkers. A second approach was employed to demonstrate that our toxin-based combinatorial library system can be adapted to target known cancer biomarkers. Specifically, SLT-1 A chain variants harbouring 12-residue inserts were expressed in a phage display library. The library was screened against cell lines expressing the human colon cancer marker carcinoembryonic antigen (CEA; CD66e; CEACAM-5) to identify candidates that not only targeted, but internalized into cancer cells within a 1 h period. Variant, CSTA-10, was found to kill CEA-expressing BxPC-3 cells. Overall, the directed evolution of an RIP template such as SLT-1 represents a novel and powerful strategy for the identification of tumour-targeted toxin variants.

Cancer cells display aberrant receptors on their surface that can serve as targets for the development of directed drug therapies. As such, our group has utilized two parallel approaches to redirect the cytotoxic properties of a ribosome-inactivating protein (RIP), Shiga-Like Toxin 1 (SLT 1), by altering its receptor specificity to target and kill cancer cells. The first combinatorial protein library was constructed such that a randomized 7 AA long peptide was inserted within the cytotoxic domain (A chain) of SLT-1. A high-throughput protein-based screening campaign identified a novel A chain toxin variant (named SLT 1AIYSNKLM) capable of targeting and killing human melanoma cells. This variant harbours a peptide insert (IYSNKLM) that directs the A chain to kill human melanoma cell lines. Equilibrium binding studies using 125I-radiolabeled SLT-1AIYSNKLM were conducted to determine the equilibrium binding constant and receptor density on 518-A2 human melanoma cells. When injected into SCID mice bearing a human melanoma xenograft, nanoSPECT/CT imaging as well as the biodistribution profile showed marked tumour uptake and retention of the radiolabeled toxin variant. Furthermore, preliminary experiments have shown that the SLT-1AIYSNKLM receptor is a protein, highlighting the potential for this method to be used in the discovery of novel biomarkers. A second approach was employed to demonstrate that our toxin-based combinatorial library system can be adapted to target known cancer biomarkers. Specifically, SLT-1 A chain variants harbouring 12-residue inserts were expressed in a phage display library. The library was screened against cell lines expressing the human colon cancer marker carcinoembryonic antigen (CEA; CD66e; CEACAM-5) to identify candidates that not only targeted, but internalized into cancer cells within a 1 h period. Variant, CSTA-10, was found to kill CEA-expressing BxPC-3 cells. Overall, the directed evolution of an RIP template such as SLT-1 represents a novel and powerful strategy for the identification of tumour-targeted toxin variants.

No description available.

The development of recombinant proteins for therapeutic applications has revolutionized the pharmaceutical industry. In particular, monoclonal antibodies are the safest class of all therapeutic molecules and account for the majority of recombinant proteins currently undergoing clinical trials. A variety of technologies exist to engineer antibodies with a desired binding specificity and affinity, both of which are a prerequisite for therapeutic applications. This dissertation describes the implementation of a novel combinatorial library screening technology for the discovery and engineering of antibodies with unique binding properties. Combinatorial library screening technologies are used for the in vitro isolation of antibodies from large ensembles of proteins (libraries) typically produced by microorganisms using molecular biology techniques. Our lab has developed a powerful antibody discovery technology that relies on E. coli display by anchored periplasmic expression, otherwise known as APEx. First, I compared the effects of using combinatorial libraries comprising either smaller, monovalent single-chain antibody fragments (scFv), or the much larger, bifunctional full-length IgG antibodies. These technologies were used to isolate a small panel of antigen specific antibodies from the same library of antibody variable domains amplified from a mouse immunized with the Protective Antigen (PA) component from Bacillus anthracis, the causative agent of anthrax. Overall, IgG display resulted in the isolation of a broader panel of variable domain sequences. Most of these variable domains exhibited substantially reduced affinity when expressed as scFvs, which is consistent with the finding that none of these could be isolated from the equivalent scFv library. These results indicate that the antibody format used during in vitro selection affects which antibody variable domains will be discovered. Second, I developed several modifications of the APEx methodology to allow for more efficient recovery of antibodies with desired properties. Specifically, the system was reengineered to simultaneously account for antibody binding and expression levels in order to isolate the highest affinity antibodies with favorable expression characteristics. Third, the new approach, coupled with optimized fluorescence activated cell sorting (FACS) settings, was used to increase the affinity of an antibody by 35-fold resulting in a K[subscript D] of 100 pM. It was demonstrated that genetic transfer of this high affinity antibody specific for the V antigen of Yersinia pestis, the etiologic agent of the plague, conferred increased protection against intranasal challenge with a 363 LD₅₀ of Y. pestis in mice. / text

This thesis develops an integrated methodology based on the desirability index and QSAR models to virtually optimise molecules. Statistical and algorithmic tools are proposed to search in huge collections of compounds obtained by combinatorial chemistry the most promising ones. First, once the drugability properties of interest have been precisely defined, QSAR models are developed to mimic the relationship between those optimised properties and chemical descriptors of molecules. The literature on QSAR models is reviewed and the statistical tools to validate the models, analyse their fit and their predictive power are detailed. Even if a QSAR model has been validated and sounds highly predictive, we emphasise the importance of measuring extrapolation by the definition of its applicability domain and quantifying the prediction error for a given molecule. Indeed, QSAR models are often massively applied to predict drugability properties for libraries of new compounds without taking care of the reliability of each individual prediction. Then, a desirability index measures the compromise between the multiple estimated drugability properties and allows to rank the molecules in the combinatorial library in preference order. The propagation of the models prediction error on the desirability index is quantified by a confidence interval that can be constructed under general conditions for linear regression, PLS regression or regression tree models. This fulfills an important lack of the desirability index literature that considers it as exact. Finally, a new efficient algorithm (WEALD) is proposed to virtually screen the combinatorial library and retain the molecule with the highest desirability indexes. For each explored molecule, it is checked if it belongs to the applicability domain of each QSAR models. In addition, the uncertainty of the desirability index of each explored molecule is taken into account by gathering molecules that can not be distinguished from the optimal one due to the propagation of QSAR models prediction error. Those molecules do not have a significantly smaller desirability than the optimal molecule found by WEALD. This constitutes another important improvement in the use of desirability index as a tool to compare solutions in a multicriteria optimisation problem. This integrated methodology has been developed in the context of lead optimisation and is illustrated on a real combinatorial library provided by Eli Lilly and Company. This is the main application of the thesis. Nevertheless, as the results on desirability index uncertainty are applicable under general conditions, they can be applied to any multicriteria optimisation problem, like it often occurs in industry.