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Dissertations / Theses on the topic 'Drug-target interactions'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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1

Vögtli, M. "Nanomechanical detection of drug-target interactions using cantilever sensors." Thesis, University College London (University of London), 2011. http://discovery.ucl.ac.uk/1307082/.

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The alarming growth of antibiotic-resistant superbugs including methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococci (VRE) is driving the development of new technologies to investigate antibiotics and their modes of action. Novel cantilever array sensors offer a tool to probe the nanomechanics of biomolecular reactions and have recently attracted much attention as a ’label-free’ biosensor as they require no fluorescent or radioactive tags and so biomolecules can be rapidly assayed in a single step reaction. Thereby, cantilever-based sensors are unique in the

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2

Frank, Annika [Verfasser]. "From natural scaffolds to detailed drug-target interactions on biogenic amines / Annika Frank." Düsseldorf : Universitäts- und Landesbibliothek der Heinrich-Heine-Universität Düsseldorf, 2020. http://d-nb.info/1203872461/34.

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3

Smith, Adam Joel Taylor. "Computational investigations of enzyme catalysis, design, and conformational aspects of drug-target interactions." Diss., Restricted to subscribing institutions, 2008. http://proquest.umi.com/pqdweb?did=1679378381&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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4

Wang, Chen. "High-throughput prediction and analysis of drug-protein interactions in the druggable human proteome." VCU Scholars Compass, 2018. https://scholarscompass.vcu.edu/etd/5509.

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Drugs exert their (therapeutic) effects via molecular-level interactions with proteins and other biomolecules. Computational prediction of drug-protein interactions plays a significant role in the effort to improve our current and limited knowledge of these interactions. The use of the putative drug-protein interactions could facilitate the discovery of novel applications of drugs, assist in cataloging their targets, and help to explain the details of medicinal efficacy and side-effects of drugs. We investigate current studies related to the computational prediction of drug-protein interaction

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5

Martínez-Jiménez, Francisco 1988. "Structural study of the therapeutic potential of protein-ligand interactions." Doctoral thesis, Universitat Pompeu Fabra, 2016. http://hdl.handle.net/10803/565402.

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Most of the cellular functions are driven by small-molecules that selectively bind to their protein targets. Is such their importance, that the pharmacological intervention of proteins by small molecule drugs is frequently used to treat multiple conditions. Herein I present a thesis that leverages a threedimensional study of small molecule protein interactions to improve their therapeutic relevance. More specifically, it introduces nAnnolyze, a method for predicting structurally detailed protein-ligand interactions at proteome scale. The method exemplified its applicability by predictin

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6

Penkler, David Lawrence. "In silico analysis of human Hsp90 for the identification of novel anti-cancer drug target sites and natural compound inhibitors." Thesis, Rhodes University, 2015. http://hdl.handle.net/10962/d1018938.

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The 90-KDa heat shock protein (Hsp90) is part of the molecular chaperone family, and as such it is involved in the regulation of protein homeostasis within cells. Specifically, Hsp90 aids in the folding of nascent proteins and re-folding of denatured proteins. It also plays an important role in the prevention of protein aggregation. Hsp90’s functionality is attributed to its several staged, multi-conformational ATPase cycle, in which associated client proteins are bound and released. Hsp90 is known to be associated with a wide array of client proteins, some of which are thought to be involved

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7

Coelho, Edgar Duarte de Jesus Valente Marques. "Computational prediction of inter-species protein-protein interactions." Doctoral thesis, Universidade de Aveiro, 2017. http://hdl.handle.net/10773/19165.

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Doutoramento em Ciências da Computação<br>O estudo em larga escala de proteínas e das suas eventuais interações tem sido alvo de bastante atenção pela comunidade científica. Os métodos de análise experimentais têm produzido uma quantidade imensa de dados, que têm sido armazenados em diferentes repositórios. A disponibilidade destes dados, muitos deles curados por especialistas, abre um leque de oportunidades de investigação. Dado que as técnicas experimentais de identificação de interações proteína- proteína (PPIs) são dispendiosas, demoradas e requerem análise de um perito, os métodos comput

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8

au, low@wehi edu, and CK Andrew Low. "Characterisation and Evaluation of Novel Potential Target (Tubulin) for Antimalarial Chemotherapy." Murdoch University, 2004. http://wwwlib.murdoch.edu.au/adt/browse/view/adt-MU20050930.125714.

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Malaria has long affected the world both socially and economically. Annually, there are 1.5-2.7 million deaths and 300-500 million clinical infections (WHO, 1998). Several antimalarial agents (such as chloroquine, quinine, pyrimethamine, cycloguanil, sulphadoxine and others) have lost their effectiveness against this disease through drug resistance being developed by the malarial parasites (The- Wellcome-Trust, 1999). Although there is no hard-core evidence of drug resistance shown on the new antimalarial compounds (artemisinin and artesunate), induced resistant studies in animal models have d

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9

Koptelov, Maksim. "Link prediction in bipartite multi-layer networks, with an application to drug-target interaction prediction." Thesis, Normandie, 2020. http://www.theses.fr/2020NORMC211.

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De nombreux problèmes réels relèvent d’une structure bi-relationnelle et peuvent être modélisés suivant des réseaux bipartis. Une telle modélisation permet l'utilisation de solutions standards pour la prédiction et/ou la recommandation de nouvelles relations entre objets de ces réseaux. La tâche de prédiction de liens est un problème largement étudié dans les réseaux simples, c’est-à-dire les réseaux avec un seul type d'interaction entre sommets. Cependant, pour les réseaux multicouche (i.e. réseaux avec plusieurs types d'arêtes entre sommets), ce problème n'est pas encore entièrement résolu.C

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10

Nadal, Bufi Ferran. "Peptide-based drugs to inhibit LDH5, a potential target for cancer therapy." Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/232526/1/Ferran_Nadal%20Bufi_Thesis.pdf.

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This thesis investigates novel strategies to target lactate dehydrogenase 5 (LDH5), a protein involved in cancer. After decades of research without success, this thesis reports the development of the first molecules able to inhibit the activity of LDH5 with an alternative mechanism of action: disrupting its structure. To do that, an emerging class of drugs called peptides are explored. The lead peptide of this work successfully kills breast cancer cells via LDH5 inhibition. The validation of this strategy is relevant because it can be applied to many other cancer targets that have been traditi

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11

Zhang, Minlu. "Discovery and Analysis of Patterns in Molecular Networks: Link Prediction, Network Analysis, and Applications to Novel Drug Target Discovery." University of Cincinnati / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1330024618.

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12

López, Muñoz Laura. "Homology modeling and structural analysis of the antipsychotic drugs receptorome." Doctoral thesis, Universitat Pompeu Fabra, 2010. http://hdl.handle.net/10803/7228.

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Classically it was assumed that the compounds with therapeutic effect exert their action interacting with a single receptor. Nowadays it is widely recognized that the pharmacological effect of most drugs is more complex and involves a set of receptors, some associated to their positive effects and some others to the side effects and toxicity. Antipsychotic drugs are an example of effective compounds characterized by a complex pharmacological profile binding to several receptors (mainly G protein-coupled-receptors, GPCR). In this work we will present a detailed study of known antipsychotic drug

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13

Loguercio, Salvatore. "Reductionist and Integrative approaches to explore the H.pylori genome." Doctoral thesis, Università degli studi di Padova, 2008. http://hdl.handle.net/11577/3425099.

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The reductionist approach of decomposing biological systems into their constituent parts has dominated molecular biology for half a century. Since organisms are composed solely of atoms and molecules without the participation of extraneous forces, it has been assumed that it should be possible to explain biological systems on the basis of the physico-chemical properties of their individual components, down to the atomic level. However, despite the remarkable success of methodological reductionism in analyzing individual cellular components, it is now generally accepted that the behavior of com

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14

Wu, I.-Ching, and 吳依青. "In silico Investigation of Drug-Target Interactions for N1 Neuraminidase." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/63244554536870783405.

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碩士<br>國立陽明大學<br>生物醫學資訊研究所<br>96<br>H5N1 avian influenza have caused a severe and overwhelming epidemic among birds and humans. To develop new drugs against the pathogen, an easily-mutated virus, much more efforts have been putting on fully understanding the viral entry and leave the cell, especially on neuraminidases and hemagglutinins. Here we used molecular dynamics simulations to test different ligands, including sialic acid, Peramivir, Oseltamivir and Zanamivir binding to N1 neuraminidases and to compare Oseltamivir binding to wild type and mutant N1 neuraminidases. Binding energy and bind

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15

Chen, Yuzong, Zerong Li, and C. Y. Ung. "Computational Method for Drug Target Search and Application in Drug Discovery." 2003. http://hdl.handle.net/1721.1/3777.

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Ligand-protein inverse docking has recently been introduced as a computer method for identification of potential protein targets of a drug. A protein structure database is searched to find proteins to which a drug can bind or weakly bind. Examples of potential applications of this method in facilitating drug discovery include: (1) identification of unknown and secondary therapeutic targets of a drug, (2) prediction of potential toxicity and side effect of an investigative drug, and (3) probing molecular mechanism of bioactive herbal compounds such as those extracted from plants used in traditi

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16

Liao, Pei-Han, and 廖珮函. "Inferring Drug-Target Interactions Based on Perturbational Profiles in LINCS L1000 Data." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/dw9egx.

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碩士<br>國立臺灣大學<br>生醫電子與資訊學研究所<br>106<br>The journey of a drug, from being selected in the laboratory to finally be sold on the market, is tedious, money-consuming and full of risks. It is an urgent need to shorten the process of drug discovery and development. Either accelerating the initial phase – drug discovery or repurposing existing drugs for new indications could be beneficial to achieve the goal. In this study, we have developed an analysis pipeline for predicting potential targets of drugs based on only perturbational profiles in L1000 data. Through analyzing the associations between com

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17

Olayan, Rawan S. "Novel computational methods to predict drug–target interactions using graph mining and machine learning approaches." Diss., 2017. http://hdl.handle.net/10754/626424.

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Computational drug repurposing aims at finding new medical uses for existing drugs. The identification of novel drug-target interactions (DTIs) can be a useful part of such a task. Computational determination of DTIs is a convenient strategy for systematic screening of a large number of drugs in the attempt to identify new DTIs at low cost and with reasonable accuracy. This necessitates development of accurate computational methods that can help focus on the follow-up experimental validation on a smaller number of highly likely targets for a drug. Although many methods have been proposed

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18

(8740836), Guanhui Wu. "Protein and Ligand Interactions of MYC Promoter G-quadruplex." Thesis, 2020.

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<div>G-quadruplexes (G4s) are non-canonical secondary structures formed in single-stranded guanine-rich nucleic acid sequences, such as those found in oncogene promoters and telomeres. <i>MYC</i>, one of the most critical oncogenes, has a DNA G4 (MycG4) in its proximal promoter region that functions as a transcriptional silencer. MycG4 is very stable and the pathological activation of <i>MYC</i> requires its active unfolding. However, it remains unclear what drives MycG4 unfolding in cancer cells. We have studied the interactions of DDX5 with the MycG4 at both molecular and cellular levels and

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19

Coelho, Guilherme Pedro Antunes Carvalhas Gabriel. "Computational discovery of drug-target interaction." Master's thesis, 2018. http://hdl.handle.net/10316/86211.

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Trabalho de Projeto do Mestrado Integrado em Engenharia Biomédica apresentado à Faculdade de Ciências e Tecnologia<br>A descoberta de antibióticos foi rapidamente seguida por um aumento da resistência bacterial aos mesmos. Esta resistência torna necessária a descoberta de novos fármacos, cujo processo requer tempo e esforços financeiros. O reposicionamento de fármacos foi proposto como a abordagem mais adequada para contornar esta dependência e permitir o desenvolvimento de novos fármacos. O maior desafio para o reposicionamento de fármacos prende-se com a identificação da possível interação e

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20

Raman, Karthik. "Systems-Level Modelling And Simulation Of Mycobacterium Tuberculosis : Insights For Drug Discovery." Thesis, 2008. https://etd.iisc.ac.in/handle/2005/685.

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Systems biology adopts an integrated approach to study and understand the function of biological systems, particularly, the response of such systems to perturbations, such as the inhibition of a reaction in a pathway, or the administration of a drug. The complexity and large scale of biological systems make modelling and simulation an essential and critical part of systems-level studies. Systems-level modelling of pathogenic organisms has the potential to significantly enhance drug discovery programmes. In this thesis, we show how systems--level models can positively impact anti-tubercular dr

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Raman, Karthik. "Systems-Level Modelling And Simulation Of Mycobacterium Tuberculosis : Insights For Drug Discovery." Thesis, 2008. http://hdl.handle.net/2005/685.

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Systems biology adopts an integrated approach to study and understand the function of biological systems, particularly, the response of such systems to perturbations, such as the inhibition of a reaction in a pathway, or the administration of a drug. The complexity and large scale of biological systems make modelling and simulation an essential and critical part of systems-level studies. Systems-level modelling of pathogenic organisms has the potential to significantly enhance drug discovery programmes. In this thesis, we show how systems--level models can positively impact anti-tubercular dru

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22

施翔尹. "Improving Drug-Target Interaction Identification using Integrated Machine Learned Approach." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/n4eas3.

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23

Ciaccioli, Gianmario. "ASYN and tau interaction : new drug target for neurodegenerative diseases." Doctoral thesis, 2014. http://hdl.handle.net/10451/15500.

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Tese de doutoramento, Bioquímica (Biotecnologia), Universidade de Lisboa, Faculdade de Ciências, 2014<br>Neurodegenerative diseases are among the most complex and puzzling human disorders and in the last century the number of people affected by neurodegenerative disorders is increasing year after year. These devastating disorders currently do not have any effective therapies or treatments, thus are a social and economic burden for modern society and novel therapeutic strategies need to be developed for these disease states. Synucleinopathies and tauopathies regroup a wide number of neurodegene

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24

Ba, Alawi Wail. "Novel Methods for Drug-Target Interaction Prediction using Graph Mining." Diss., 2016. http://hdl.handle.net/10754/619165.

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The problem of developing drugs that can be used to cure diseases is important and requires a careful approach. Since pursuing the wrong candidate drug for a particular disease could be very costly in terms of time and money, there is a strong interest in minimizing such risks. Drug repositioning has become a hot topic of research, as it helps reduce these risks significantly at the early stages of drug development by reusing an approved drug for the treatment of a different disease. Still, finding new usage for a drug is non-trivial, as it is necessary to find out strong supporting evidence t

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Lin, Yung-Hsin, and 林永欣. "Application of Data Mining and Statistical Approaches to Adverse Drug-Drug Interaction Prediction in Chemo Drug and Target Drug." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/29375086938046241751.

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碩士<br>國立臺灣大學<br>醫學工程學研究所<br>100<br>Malignant tumors, also known as cancer, according to the World Health Organization[1] announced that cancer is a worldwide major cause of death, accounting for 7.6 million deaths in 2008, around 13% of all deaths[2]. The choice of the treatment of cancer including surgery, chemotherapy and radiation therapy, the emergence of drug targets, has become a cancer treatment is another option. Target drug is a specific chemical role in tumor growth and “target receptor (ligand)” to suppress tumors. The “target receptor”, including tumor growth related receptor (liga

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Monteiro, Nelson Rodrigo Carvalho. "End-to-End Deep Learning Approach for Drug-Target Interaction Prediction." Master's thesis, 2019. http://hdl.handle.net/10316/87296.

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Trabalho de Projeto do Mestrado Integrado em Engenharia Biomédica apresentado à Faculdade de Ciências e Tecnologia<br>A descoberta de potenciais Interações Fármaco-Alvo é uma etapa determinante no processo de descoberta e reposicionamento de fármacos, uma vez que a eficácia do tratamento antibiótico disponível está a diminuir, provocado pelo aumento da sua utilização indevida. Apesar dos esforços colocados nos métodos tradicionais in vivo ou in vitro, o investimento financeiro farmacêutico foi reduzido ao longo dos anos. Desta forma, estabelecer métodos computacionais eficazes, é decisivo para

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27

Chu, Liang-Hui, and 褚亮翬. "Construction of Cancer-Perturbed Protein-Protein Interaction Network of Apoptosis for Drug Target Discovery." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/45671639924443147682.

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碩士<br>國立清華大學<br>電機工程學系<br>95<br>Abstract Background Cancer is known to occur due to mutations of oncogenes or tumor suppressor genes, which alter a series of downstream signal transduction pathways at molecular level. Therefore, inspecting interactive behaviors of proteins in cancer cells and comparing them with those in normal cells to obtain cancer-perturbed protein network can shed light on how a normal cell transforms into a cancer cell. Results Rough protein-protein interaction networks of apoptosis in cancer and normal cells are constructed according to human yeast-two-hybrid datasets an

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28

Cossar, Peter. "Inhibiting the NusB-NusE protein-protein interaction - a novel target for antibiotic drug development." Thesis, 2018. http://hdl.handle.net/1959.13/1383709.

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Research Doctorate - Doctor of Philosophy (PhD)<br>The strain of antibiotic resistances on global health has led to a movement away from traditional approaches to iterative antibiotic development. Over the past decade, there has been a growing body of evidence indicating that targeting protein-protein interactions (PPIs) is an efficacious approach to drug development. The bacterial interactome is central to all microbial processes and modulation of PPI by small molecule compounds leads to disruption of homeostasis, resulting in arrestment of bacterial proliferation. One microbial PPI of partic

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KOUTOU, Wend-Nougui Odilon, and 江歐狄. "Similarity-Boosted Hybrid Conditional Restricted Boltzmann Machine (SB H-CRBM) for Drug-Target Interaction Prediction." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/3v2pxs.

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碩士<br>國立清華大學<br>資訊系統與應用研究所<br>106<br>Uncovering drug-target interactions plays a key role in the drug development process. Recently, in silico (docking simulation and machine learningbased) techniques have emerged as an alternative to costly and time consuming biochemical experiments. In machine learning-based techniques, many network-based approaches have been proposed such as Restricted Boltzmann Machine (RBM), Bipartite Local Models (BLM), Network Based Inference (NII), Weighted profile method and Advanced Local Drug-Target Interaction Prediction Technique (ALADIN). In this research, we ext

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Xu, David. "Computational Methods to Identify and Target Druggable Binding Sites at Protein-Protein Interactions in the Human Proteome." Diss., 2019. http://hdl.handle.net/1805/21086.

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Indiana University-Purdue University Indianapolis (IUPUI)<br>Protein-protein interactions are fundamental in cell signaling and cancer progression. An increasing prevalent idea in cancer therapy is the development of small molecules to disrupt protein-protein interactions. Small molecules impart their action by binding to pockets on the protein surface of their physiological target. At protein-protein interactions, these pockets are often too large and tight to be disrupted by conventional design techniques. Residues that contribute a disproportionate amount of energy at these interfaces are k

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31

Behnke, Felix [Verfasser]. "Target-Fishing entzündungsrelevanter Arzneistoffe sowie biochemisch- molekularpharmakologische Charakterisierung der Arzneistoff-Target Interaktion = Target-fishing of drugs relevant to inflammation and biochemical molecular pharmacological characterisation of the drug-target interaction / vorgelegt von Felix Behnke." 2011. http://d-nb.info/1013219929/34.

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Oliveira, Ana Filipa Martins de. "Study of Tau and Synaptogyrin-3 interaction - A drug discovery approach." Master's thesis, 2019. http://hdl.handle.net/10316/87940.

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Dissertação de Mestrado em Bioquímica apresentada à Faculdade de Ciências e Tecnologia<br>Tau protein has been identified as an important player in the development and progression of several neurodegenerative disorders, commonly addressed to as Tauopathies. Tauopathies comprise more than 20 neurodegenerative disorders, being the most common Alzheimer’s disease. These disorders are characterized by the aggregation and accumulation of insoluble hyperphosphorylated Tau protein in the brain. Despite the increasing number of cases, the pathologic mechanism of Tauopathies is not yet clear and theref

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33

Das, Basudeb. "Identification of potential Therapeutic Targets and Investigating Piwi-interacting RNA (piRNA)Mediated Target Regulations Implicated in Oncogenesis and Drug Resistance of Sarcoma." Thesis, 2022. http://ethesis.nitrkl.ac.in/10300/1/2022_PhD_BDas_516LS1002_Identification.pdf.

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Sarcomas are rare, and aggressive cancers of mesenchymal origin, with a survival rate ＜15% if metastasized. The molecular heterogeneity of this cancer complicates its diagnosis, prognosis, and treatment. Further, acquired chemoresistance remains a major clinical challenge, accounting for its treatment failure and tumor relapse. Therefore, it is critical to decrypt key regulators and the underlying molecular mechanisms of sarcomagenesis and drug resistance. The current study sought to identify key regulators of tumorigenesis and chemoresistance that could be modulated by PIWI-interacting RNA (p

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Adasme, Melissa F. "Structure based drug repositioning by exploiting structural properties of drug's binding mode." 2021. https://tud.qucosa.de/id/qucosa%3A75443.

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The rapid pace of scientific advances is enabling a greater understanding of diseases at the molecular level. In turn, the process for researching and developing new medicines is growing in difficulty, costs, and length as a result of the scientific, technical, and regulatory challenges related to the development process. In light of these challenges, drug repositioning, the utilization of known drugs for a new medical indication, has emerged as an increasingly important strategy for the new drug discovery. Availability of prior knowledge regarding safety, efficacy and the appropriate administ

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