Plant Extracts and Natural Products - Predictive Structural and Biodiversity- Based Analyses of Uses, Bioactivity, and 'Research and Development' Potential
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Plant extracts and natural products - Predictive structural and biodiversity- based analyses of uses, bioactivity, and 'research and development' potential Vafa Amirkia Thesis submitted in accordance with the requirements of the UCL School of Pharmacy for the degree of Doctor of Philosophy November 2016 UCL SCHOOL OF PHARMACY 29-39 Brunswick Square London WC1N 1AX 1 Declaration This thesis describes research conducted in the School of Pharmacy, University College London from February 2013 to February 2016 under the supervision of Professor Michael Heinrich and Dr Jose M. Prieto. I certify that the research described is original and that I have written all the text herein and have clearly indicated by suitable citation any part of this dissertation that has already appeared in publication. ____________________________ 1 November 2016 Vafa Amirkia 2 Abstract The process of drug discovery and development over the last 30 years has been increasingly shaped by formulaic approaches and natural products – integral to the drug discovery process and widely recognized as the most successful class of drug leads – have significantly been deprioritized by a struggling worldwide pharmaceutical industry. Alkaloids - historically the most important superclass of medically important secondary metabolites - have been used worldwide as a source of remedies to treat a wide variety of illnesses yet, there exists a wide discrepancy between their historical and modern significances. To understand these trends from an insider‘s perspective, 52 senior-stakeholders in industry and academia were engaged to provide insights on a series of qualitative and quantitative aspects related to developments in the process of drug discovery from natural products. Stakeholders highlighted the dissonance between the perceived high potential of natural products as drug leads and overall industry and company level strategies. Many industry contacts were highly critical to prevalent company and industry-wide drug discovery strategies indicating a high level of dissatisfaction within the industry. One promising strategy which respondents highlighted was virtual screening which, to a large extent has not been explored in natural products research strategies. Furthermore, the physicochemical features of 27,783 alkaloids from the Dictionary of Natural Products were cross-referenced to pharmacologically significant and other metrics from various databases including the European Bioinformatics Institute‘s ChEMBL and Global Biodiversity Information Facility‘s GBIF biodiversity data. The combined dataset revealed that a compound's likelihood of medicinal use can be linked to its host species‘ abundance and was input into target- independent machine learning algorithms to predict likelihood of pharmaceutical use. The neural network model demonstrated an accuracy of >57% for all pharmaceutical alkaloids and 98% of all alkaloids. This study is the first to incorporate the biodiversity of host organisms in a machine learning scheme characterizing druglikeness and thus demonstrates the link between host species‘ abundance and druglikeness. These findings yield new insights into cost-effective, real-world indicators of drug development potential across the diverse field of natural products. 3 Acknowledgements This doctoral thesis would not have been possible without the support of many people. Firstly, I wish to express my gratitude to my primary supervisor Professor Michael Heinrich, who was generously, abundantly, and consistently encouraging and offered irreplaceable guidance throughout the course of this research. There is no doubt that this research could not be completed without his constant and wise encouragement (often in the form gentle nudges to stretch my intellectual capacities each of the many times we encountered awkward pauses during our discussions). I also wish to express my gratitude to my secondary supervisor Dr Jose M. Prieto whose scientific proficiency and high standard of excellence has propelled this research forward in an invaluable way; he is a rising star in the field of pharmacognosy. Furthermore, I wish to thank my classmates and colleagues at UCL which have provided a highly enriching experience during my studies and upheld the UCL value of ‗collegiality and community-building‘ throughout the years. Outside the UCL community, I must acknowledge the encouragement from a wide range of acquaintances over the years; many of which are scattered across the globe working to enrich the collective life of society. Moreover, I am deeply appreciative of the loyal support from a smaller circle of true friends who have stood shoulder-to-shoulder with me throughout various developments and exemplified excellence in various aspects of life. Lastly, I would like to thank my parents whom been unconditionally supportive and infinitely trusting throughout the successive stages of my life. The profound friendship and deep spiritual bond we have nurtured, has, and will continue to guide my life. This research could not be possible if my father did not enable me ‗to receive training at school and to be instructed in such arts and sciences as are deemed useful and necessary‘ and my mother had not always strived create ‗conditions as would be most conducive to both [my] material and spiritual welfare and advancement‘. 4 Publications Resulting from the Thesis Journal articles: 1. Amirkia, V., & Heinrich, M. (2014). Alkaloids as drug leads– A predictive structural and biodiversity-based analysis. Phytochemistry Letters, 10, xlviii-liii. 2. Amirkia, V., & Heinrich, M. (2015). Natural products and drug discovery: a survey of stakeholders in industry and academia. Frontiers in Pharmacology, 6. 3. Amirkia, V., & Heinrich, M. (2016). Machine learning ‗drug-likeness‘ in pure alkaloids (Unpublished Manuscript) Conference proceedings: 1. Amirkia, V., & Heinrich, M. (2014) Alakaloids as drug leads- A predictive structural and biodiversity-based analysis. Poster presentation. 13th Meeting of Consortium for Globalization of Chinese Medicine (CGCM). 27- 29 August 2014, Beijing, China. 2. Amirkia, V., & Heinrich, M. (2014) Alakaloids as drug leads- A predictive structural and biodiversity-based analysis. Poster presentation. 62nd International Congress and Annual Meeting of the Society for Medicinal Plant and Natural Product Research (GA). 31 August–4 September 2014, Guimaraes, Portugal. 3. Amirkia, V., & Heinrich, M. (2015) Natural product development: current industry and academia insights. Oral presentation. APS PharmSci 2015 – The Science of Medicines. 7–9 September 2015, Nottingham, UK. 5 Table of Contents Abstract ......................................................................................................... 3 Acknowledgements ...................................................................................... 4 Publications Resulting from the Thesis ...................................................... 5 Table of Figures ............................................................................................ 8 Table of Tables ............................................................................................ 10 List of Abbreviations .................................................................................. 12 1. General introduction ................................................................................ 15 1.1. Defining the field of natural products ...................................................15 1.1.1. Humans, nature, and natural products ................................................. 15 1.1.2. Classifying natural products ................................................................. 18 1.2. Significance in modern pharmaceutics ................................................20 1.3. Evolving attitudes towards their use as drugs ......................................23 1.4. Objectives ...........................................................................................28 2. Strategies, challenges and perceptions in modern drug discovery ..... 30 2.1. Prevalent trends – a review of the literature.........................................30 2.1.1. Macro trends: Industry ......................................................................... 30 2.1.2. Micro trends: Industry and academia ................................................... 38 2.1.3. Rise and fall of interest/funding/etc. of natural products ....................... 46 2.2. A study into perceptions of natural products: industry and academia ..54 2.2.1. Results from insider perspectives ........................................................ 54 2.2.2. Perceived ‗hit rates‘ by compound class .............................................. 63 2.3. Insights derived from the survey: .........................................................66 2.3.1. Can cost-effectiveness and natural products research coexist? ........... 66 2.3.2. Efforts to augment supply of natural products ...................................... 69 3. Alkaloids as a historical and modern source of medicines .................. 75 3.1. History of alkaloids ..............................................................................75 3.1.1. Discovery and isolation ........................................................................ 75 3.1.2. Definition and distribution ..................................................................... 76 3.1.3. Use as non-medicines ......................................................................... 78 3.2. Alkaloids in modern medicine ..............................................................80