Rational drug design is a powerful method in which new and innovative therapeutics can be designed based on knowledge of the biological target aiming to provide more efficacious and responsible therapeutics. Understanding aspects of the targeted biological agent is important to optimize drug design and preemptively design to slow or avoid drug resistance. Chagas disease, an endemic disease for South and Central America and Mexico is caused by Trypanosoma cruzi, a protozoan parasite known to consist of six separate genetic clusters or DTUs (discrete typing units). Chagas disease therapeutics are problematic and a call for new therapeutics is widespread. Many researchers are working to use rational drug design for developing Chagas drugs and one potential target that receives a lot of attention is the T. cruzi trans-sialidase protein. Trans-sialidase is a nuclear gene that has been shown to be associated with virulence. In T. cruzi, trans-sialidase (TcTS) codes for a protein that catalyzes the transfer of sialic acid from a mammalian host coating the parasitic surface membrane to avoid immuno-detection. Variance in disease pathology depends somewhat on T. cruzi DTU, as well, there is considerable genetic variation within DTUs. However, the role of TcTS in pathology variance among and within DTU’s is not well understood despite numerous studies of TcTS. These previous studies include determining the crystalline structure of TcTS as well as the TS protein structure in other trypanosomes where the enzyme is often inactive. However, no study has examined the role of natural selection in genetic variation in TcTS. In order to understand the role of natural selection in TcTS DNA sequence and protein variation, we sequenced 540 bp of the TcTS gene from 48 insect vectors. Because all 48 sequences had multiple polymorphic bases, we examined cloned sequences from two of the insect vectors. The data are analyzed to understand the role of natural selection in shaping genetic variation in TcTS and interpreted in light of the possible role of TcTS as a drug target.

Magister Pharmaceuticae - MPharm / Leonotis leonorus and Mentha longifolia are two herbs commonly used in South Africa, mostly in oral liquid dosage forms. Several disadvantages are associated with these traditional dosage forms which can perhaps be remedied by using an appropriate oral solid dosage form, provided the actual plant material in the latter still resemble, as closely as possible, the traditionally used material and provide products of suitable pharmaceutical quality. The objectives of this study were to prepare and evaluate the pharmaceutical suitability of the freeze-dried aqueous extracts of Leonotis Leonorus and Mentha Longifolia as plant raw material for the capsule dosage of these two therapies and to formulate and manufacture capsules of Leonotis Leonorus and Mentha Longifolia aqueous extract that would contain amounts of the plant materials equivalent to that found in their traditional liquid dosage forms, and have immediate release characteristics and suitability stability. / South Africa

Virtual screening is a fast, low cost method to identify potential small molecule therapeutics from large chemical databases for the vast amount of target proteins emerging from the life sciences and bioinformatics. In this work, we applied several conventional and newly developed virtual screening approaches to identify novel non-steroidal ligands for the human and zebrafish sex hormone binding globulin (SHBG). The ‘benchmark set of steroids’ is a set of steroids with known affinities for human SHBG that has been widely used for validation in the development of different virtual screening methods. We have updated this data set by including additional steroidal SHBG ligands and by modifying the predicted binding orientations of several benchmark steroids in the SHBG binding site based on the use of an improved docking protocol and information from recent crystallographic data. The new steroid binding orientations and the expanded version of the benchmark set was then used to create new in silico models which were applied in virtual screening to identify high-affinity non-steroidal human SHBG ligands from a large chemical database. Anthropogenic compounds with the capacity to interact with the steroid-binding site of SHBG pose health risks to humans and other vertebrates including fish. We constructed a homology model of SHBG from zebrafish and applied virtual screening to identify ligands for zebrafish SHBG from a set of 80 000 existing commercial substances, many of which can be exposed to the aquatic environment. Six hits from this in silico screen were tested experimentally for zebrafish SHBG binding and three of them, hexestrol, 4-tert-octylcatechol, dihydrobenzo(a)pyren-7(8H)-one demonstrated micromolar binding affinity for the zebrafish SHBG. These findings demonstrate the feasibility of using virtual screening to identify anthropogenic compounds that may disrupt or highjack functionally important protein:ligand interactions. Studies applying this new computational toxicology method could increase the awareness of hazards posed by existing commercial chemicals at relatively low cost. / Science, Faculty of / Graduate

No description available.

This dissertation presents a collection of biological simulations and predictions in collaboration with experiment to support and elucidate the trends observed in various protein–ligand systems. Within the model systems, there is a strong focus on the support for the development of peptidomimetic inhibitors for post-translational reader proteins (CBX proteins). The systems studied throughout this document each present their own unique challenges but fall under the general theme of protein flexibility and the difficulties of sampling such systems. As part of this work, methodological advances were made to address the challenges of structural prediction on flexible proteins and ultimately form the method Selective Ligand-Induced Conformational Ensemble (SLICE). The development, validation, and future directions of the SLICE method are also discussed. Ultimately, the collaborative efforts presented in this dissertation bring forward a greater understanding of the drug design challenges on the CBX proteins as well a new methodology in the field of structure-based drug design. / Graduate

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第19738号 / 工博第4193号 / 新制||工||1647(附属図書館) / 32774 / 京都大学大学院工学研究科物質エネルギー化学専攻 / (主査)教授 近藤 輝幸, 教授 辻 康之, 教授 大江 浩一 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DGAM

This work explores a binary reagent approach to increase the specificity of covalent inhibitors. In this approach, two ligand analogs equipped with inert pre-reactive groups specifically bind a target biopolymer. The binding event brings the pre-reactive groups in proximity with each other. The two groups react, generating active chemical intermediates that covalently modify and inactivate the target. In the present study we compare the new approach with the traditional single-component reagent strategy using DNA polymerase from bacteriophage T4 as a model target biopolymer. We report the design and synthesis of two analogs of deoxythymidine triphosphate, a natural DNA polymerase substrate. Together, the analogs function as a binary nucleotide reagent which is activated by light with wavelengths 365 nm and longer. However, the active analog functions as a traditional single component reagent when activated by light with wavelengths at 300 nm and longer. The traditional single-component reagent efficiently inactivated DNA polymerase. However, in the presence of non-target protein the inactivation efficiency is greatly diminished. Under the same conditions, the binary nucleotide reagent also inactivated DNA polymerase, and the inactivation efficiency is not affected by the presence of the non-target protein. Our results validate that a binary approach can be employed to design highly specific covalent inhibitors. The binary reagent strategy might be useful as a research tool for investigation of ligand-protein interactions in complex biological systems and for drug design

In 2020, cancer impacted an estimated 1.8 million people and result in over 600,000 deaths in the United States. Some cancer treatments options are limited due to drug resistance, requiring additional drug development to improve patient survival rates. It is necessary to continuously develop new therapeutic approaches and identify novel targets, as cancer is ever-growing and adapting. Experimental research strategies have limitations when exploring how to target certain protein classes, including membrane-embedded or protein-protein bound, due to the complexity of their environments. These two domains of research are experimentally challenging to explore, and in silico research practices provide insight that would otherwise take years to study. Computer-aided drug design (CADD) routes can support the areas of drug discovery that are considered difficult to explore with experimental techniques. In this work, we provide research practices that are easily adaptable and translatable to other difficult protein targets and interfaces. First, we identified the morphological impact of a single-site mutation in the G-protein coupled receptor (GPCR), OR2T7, which had been identified as a novel prognostic marker for glioblastoma. Next, we explored the blockbuster target, Programmed Cell Death Protein 1 – (PD-1) and the agonistic vs antagonistic response that can be exploited for Non-Small Cell Lung Cancer (NSCLC) therapeutic development. Last, we explored the sphingolipid transport protein, Spns2, which has been demonstrated to be important in regulating the metastatic cancer enabling microenvironment. This work utilized molecular dynamics simulations (MDS) to explore the protein structure-function relationship for each protein of interest, allowing for the exploration of biophysical properties and protein dynamics. We identified that the D125V mutation in OR2T7 likely influences activation of the MAPK pathway by impacting G-protein binding via reducing the helical plasticity in the TM6 and TM7 regions. PD-1 was identified to have a domain near the PD-L1 binding interface that increases β-sheet stability and increases residue-residue distances with the membrane-proximal region within PD-1, thus leading to an active conformation. Lastly, Spns2 was identified to follow a rocker-switch transport model and provided preliminary insight into sphingolipid-Spns2 channel binding, interacting with residues Thr216, Arg227, and Met230, as well as highlighting the role of Arg119 in a salt-bridge network of interactions essential in substrate translocation. Collectively, this work illustrates the advantages of computational workflows in the drug discovery process and provides a framework that can be applied for additional GCPRs, transport proteins, or protein-protein interfaces to enhance and accelerate the CADD research. / Doctor of Philosophy / Cancer is an ever-evolving disease that requires continuous development of new treatment options. Experimental research strategies can be timely, expensive, or lack atomistic insight into drug development processes. Computer-aided drug design (CADD) routes provide research strategies to support areas of drug discovery that can be difficult to explore with experimental techniques. Membrane-bound proteins and protein-protein interfaces are two domains of research that are typically difficult to explore, and computational research practices provide insight that would otherwise take years to study. In this work, we provide research practices that are easily adaptable and translatable to other difficult protein targets and interfaces. First, we identified the impact of a single-site mutation in the G-protein coupled receptor (GPCR), OR2T7, which had been identified as a novel prognostic marker for glioblastoma. Next, we explored the blockbuster target, Programmed Cell Death Protein 1 – (PD-1) and active vs inactive states that can be exploited for Non-Small Cell Lung Cancer (NSCLC) therapeutic development. Last, we explored the sphingolipid transport protein, Spns2, which has been demonstrated to be important in metastatic cancer growth. This work utilized molecular dynamics simulations (MDS) to explore the protein structure-function relationship for each protein of interest, allowing for the exploration of biophysical properties and protein movement. We identified that the D125V mutation in OR2T7 likely influences activation of the MAPK pathway, which supports multiple cancer-regulation pathways, by impacting G-protein binding via reducing the structural flexibility. PD-1 was identified to have a domain near the PD-L1 binding interface that increases structural stability, thus leading to an upregulation of cancer survival pathways. Lastly, Spns2 analysis provided insight into movement involved in sphingolipid transport, provided preliminary insight into sphingolipid-Spns2 binding, as well as highlighting the role of Arg119 in a network of interactions essential in substrate translocation. Collectively, this work highlights the usefulness of computational workflows in the drug discovery process and provides a framework that can be utilized for additional GPCRs, transport proteins, or protein-protein interfaces to enhance and accelerate the CADD research.

No description available.

O Projeto Genoma Humano do Câncer (PGHC), financiado pela FAPESP e pelo Instituto Ludwig de Pesquisa sobre o câncer, buscou identificar os genes expressos nos tipos mais comuns de câncer no Brasil. Tal projeto conseguiu identificar aproximadamente um milhão de sequências de genes de tumores frequentes no Brasil. A contribuição brasileira foi maior para tumores de cabeça e pescoço, mama e cólon. Uma das iniciativas mais recentes e estimuladas pelo PGHC é o projeto Genoma Clínico, o qual visa desenvolver novas formas de diagnóstico e tratamento do câncer através do estudo de genes expressos. A partir da análise molecular de tecidos saudáveis e neoplásicos em diferentes estágios, é possível identificar marcadores de prognóstico, permitindo escolhas de terapias mais adequadas e eficientes. A proteína MARK3 foi identificada como um desses marcadores, em neoplasias de tecidos de cabeça e pescoço, sendo o objetivo deste estudo a aplicação de técnicas de bioinformática e modelagem molecular no planejamento baseado em estrutura de candidatos a fármacos antineoplásicos que bloqueiem a atividade da proteína MARK3. Após screening virtual em bases de dados de compostos (1.000.000 aproximadamente) com propriedades drug-like, 20 compostos com potencial de inibidor da MARK3 foram selecionados. Os modos de ligação para cada um dos mesmos no sítio ligante da proteína MARK3 foram sugeridos por simulações de docking e apresentaram um bom encaixe espacial com os sítios receptores virtuais calculados pelos campos de interação molecular (MIF). Simulações de dinâmica molecular foram realizadas com o intuito de avaliar a estabilidade dos compostos selecionados, que também foram avaliados quanto à presença de grupamentos toxicofóricos em sua estrutura. / The Brazilian Project Genoma Câncer (PGHC) supported by FAPESP and the Ludwig Institute for Cancer Research, intended to identify the genes involved in the most common cases of cancer in Brazil. In this project about a million of gene sequences were identified. The major contribution was made in breast, colorectal and head and neck cancers. The results obtained stimulated the creation of another project, called Genoma Clínico, which intend to develop new trends in treatments and diagnosis of cancer based on the study of expressed genes. Analyzing healthy and neoplasic tissues in different stages, it is possible to identify molecular markers related to the prognosis of cancer, allowing the use of more efficient therapies. The MARK3 protein was identified as a molecular marker in head and neck cancer, where the objective of this work lies in the application of bioinformatics and molecular modeling strategies by structure-based drug design to identify potential antineoplasic drug candicates that could act against MARK3 protein. After the virtual screening simulations performed with drug-like compound databases, containing approximately 1.000.000 compounds, 20 were selected as potential ligands of MARK3 protein. The binding modes suggested for these compounds, by docking simulations, presented a good spatial fit when compared with the virtual receptor sites calculated by molecular interaction fields (MIF). Molecular dynamics simulations were performed in order to evaluate de stability of the binding modes suggested. The potential ligands were also evaluated to identify toxicophoric features in its chemical structures.