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Record W89172109 · doi:10.14264/158815

Structure-activity relationships in biotechnology : science and business perspectives

2007· dissertation· en· W89172109 on OpenAlexaboutno aff
David C. Ireland

Bibliographic record

VenueThe University of Queensland · 2007
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiochemical and Structural Characterization
Canadian institutionsnot available
Fundersnot available
KeywordsNexus (standard)Complementarity (molecular biology)BiotechnologyCompetition (biology)BusinessEngineeringBiologyEcology

Abstract

fetched live from OpenAlex

This PhD offers a new approach to addressing a fundamental gap in our knowledge on the composition and growth of the biotechnology firm and industry. Previous investigations into biotechnology have generally focused on either the scientific or business components and have ignored the inter-disciplinarity forces at play in biotechnology, particularly the overlap between the science and business agendas that lead to either complementarity or competition between these agendas. Understanding and accounting for this relationship is necessary for advancing biotechnology theory and practice, as it is within this nexus that firms derive their competitive advantage and find solutions to their technological and business challenges. Recognising the need to understand this relationship, I sought to encapsulate all the components of biotechnology by mimicking its dyadic design. A dual science-business PhD, an inter-faculty project combining the Institute for Molecular Bioscience and UQ Business School, presented an opportunity to explore the intricate networks and embedded knowledge that lie within the important science-business relationship. But devising a means to incorporate all the science and business components of biotechnology under a single PhD project posed a number of problems. The most enduring and pertinent problem was finding and maintaining a link between the two disciplines so that the thesis presented a coherent story. The solution was found in my science supervisor’s startup biotechnology company Kalthera. Kalthera became the reference point for analysis in a multiple-case, longitudinal, crossnational study. The case-study research examined the development of ten biotechnology firms from Australia, USA, Canada, England and Switzerland in depth over two-years. To ensure credibility, transferability, dependability and conformability of the data generated, the companies ranged in maturity, geographical location, size and market focus. Throughout the study I sought to capture the various developmental changes and challenges these firms encountered as they progressed along their development paths. Kalthera was also the focus of the scientific research. The scientific laboratory-based research component of the thesis was aimed at developing and enhancing Kalthera’s proprietary technology, cyclic cystine knots (CCK). Kalthera is using cyclotides (cyclopeptides), naturally occurring plant-derived peptides that contain this fascinating CCK motif, to develop a novel class of human therapeutics. Cyclotides offer the opportunity to combine the specificity and potency of peptides with the stability and bioavailability of traditional small molecule drugs. To develop the CCK technology, the plasticity, that is how amenable the CCK motif is to variations in the amino acid sequence, and the structure-activity relationships, that is how structure affects function, of the cyclotide framework must be understood. Chapter 2 presents a detailed analysis of Viola odorata, a plant previously shown to contain cyclotides. In this analysis, 13 novel cyclotides are characterised, contributing an additional 1/5th to the total number of cyclotides characterised prior to the study. The study also solves the structure of cycloviolacin O14, tests the haemolytic activity of four novel cyclotides, and the resistance to proteolysis of twelve novel cyclotides. This structure-activity analysis shows that some loops, such as loop 2, of cyclotides are extremely amenable to variations in amino acid sequence but that biological activity is affected by these changes. The relationship between hydrophobicity and haemolytic activity is also explored. During the analysis of V. odorata the first example of a naturally occurring linear cyclotide was discovered. Described in Chapter 3, an analysis of the linear cyclotide violacin A shows that the stability and structure of cyclotides is a consequence of the cystine knot, rather than the cyclic peptide backbone. Structure determination of violacin A reveals that the loop 2–loop 5 hydrophobic patch, common to cyclotides and thought to be implicated in membrane binding, can become flexible by the presence of positive charged residues in loop 2. Given the recent interest in linear cystine knot peptides such as Ecballium elaterium trypsin inhibitor-II (EETI-II) in drug design, the discovery of a naturally occurring linear cyclotide offers exciting opportunities in drug design and development. Chapter 4 presents the results of a field trip where 14 Hawaiian plants were collected and analysed. From the field trip seven new Rubiaceae plant species were discovered to contain cyclotides, and these plants were shown to contain upwards of 38 novel cyclotides. The data suggest that the distribution of cyclotides in the Rubiaceae may not be as sparse as previously thought. Using the fundamental knowledge gathered from the work presented in the previous chapters, Chapter 5 presents two different approaches for developing commercial outcomes for the CCK technology. Firstly, a novel cyclotide-epitope grafted drug, targeting a viral oncogene implicated in activating a range of cancers, was designed and developed. The second drug design approach was aimed at improving our understanding of how cyclotides exhibit their anti-HIV activity. This work provides the foundation for future studies aimed at improving the anti-HIV therapeutic index of cyclotides. As a link between the science and business studies, Chapter 6 explores the relationship between the scientific community and society. This chapter examines the causes of the communication failings and describes the various effects on the scientific community and on society. The chapter discusses how it is not only commercial science that is affected by society’s emotions, but also academic science, as much of the funding that supports academic science comes from the government, society’s representative. Chapters 7 and 8 constitute the formal business component of the thesis. They report on the results of a two year multiple case study that found that the development of new biotechnology firms (NBFs) critically hinges on effective resource organisation, recognition and utilisation of core competencies, the readiness and capacity of the organisation to learn and adapt to change, the management of the science and business agendas, and the ability to refocus these over time to reflect the changing internal and external environments. From this information, and as described in Chapter 8, an ideal growth model that describes the optimal combination of an NBF’s components is presented. This model can be thought of as a growth framework for biotechnology practitioners. In conclusion, this thesis is a “living” example of the inter-disciplinarity in biotechnology. Not only are the difficulties and opportunities associated with the inter-disciplinarity encapsulated in the content and processes that formed the foundation of the thesis, but the results constitute data that may equally impact scientific and business fields. Finally, the findings in this thesis have contributed to a better understanding of the relationship between structure and activity in biotechnology, using cyclotides and NBFs as examples of science and business perspectives respectively.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.751
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.222
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2007
Admission routes1
Has abstractyes

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