O Mal de Alzheimer é a causa mais importante de demência em idosos. A progressão dos sintomas da doença está associada com modificações estruturais nas sinapses colinérgicas em determinadas regiões cerebrais e, consequentemente, à diminuição do potencial de neurotransmissão colinérgica. Desta forma, o aumento da capacidade de neurotransmissão colinérgica constitui o mecanismo fundamental dos fármacos utilizados para o tratamento do Mal de Alzheimer. Atualmente, o único tratamento clínico eficaz para o Mal de Alzheimer (MA) é a utilização de inibidores da acetilcolinesterase (AChE). Os anticolinesterásicos são os fármacos mais promissores desenvolvidos até hoje, pois é a única classe terapêutica que mostrou melhora nos sintomas cognitivos do MA. Para esse projeto, foram utilizadas diferentes técnicas de modelagem molecular como estratégia de planejamento racional de fármacos, tendo como base os inibidores de Acetilcolinesterase (AChE) descritos na literatura além dos que possuem estruturas depositadas no PDB, incluindo alguns que já vêm sendo utilizados no tratamento do Mal de Alzheimer. O objetivo foi planejar e testar novos potenciais inibidores desse alvo terapêutico, na tentativa de obter e futuramente otimizar novos protótipos como futuros candidatos a fármacos em Mal de Alzheimer. Os objetivos estendem-se a propostas de novos potenciais protótipos, selecionados de bases de dados de compostos comerciais contendo propriedades de fármacos. Os screenings virtuais foram tendenciados às estruturas dos inibidores já reportados da literatura bem como ao padrão farmacofórico comum a eles, a ser modelado. / Alzheimer\'s disease is the leading cause of dementia in the elderly. The progression of symptoms is associated with structural changes in cholinergic synapses in specific brain regions and consequentely to decrease the potential of cholinergic neurotransmission. Thus, the increased capacity of cholinergic neurotransmission is the fundamental mechanism of the drugs used to treat Alzheimer\'s disease. Currently, the only effective clinical treatment for Alzheimer\'s (MA) is the use of inhibitors of acetylcholinesterase (AChE). Cholinesterase inhibitors are the most promising drugs developed so far, it is the only therapeutic class that showed improvement in cognitive symptoms of MA. For this project, we used different techniques of molecular modeling as a strategy for rational design of drugs based on inhibitors of acetylcholinesterase (AChE) in the literature than those which have structures deposited in the PDB, including some that have already been used in the treatment Alzheimer\'s disease.The objective was to design and test new potential inhibitors of therapeutic target in attempts to obtain and optimize future new prototypes as future drug candidates in Alzheimer\'s disease. The goals extend to proposals from potential new prototypes, selected from databases of commercial compounds containing properties of drugs. The virtual screenings were trends to structures of the inhibitors already reported in the literature as well as the pharmacophoric pattern common to them, to be modeled.

A doença de Alzheimer (DA) é uma desordem neurodegenerativa progressiva, caracterizada pela perda de neurônios corticais e subcorticais. Padrões patológicos da doença de Alzheimer incluem a presença de lesões neurofibrilares que consistem no acúmulo da proteína ?- amilóide e dos emaranhados neurofibrilares, decorrentes da hiperfosforilação da proteína Tau. Apenas dois grupos principais de fármacos são utilizados para o tratamento da DA, os inibidores colinesterásicos e antagonistas do receptor N-metil-D-aspartato. Entretanto, a fosforilação de proteínas pelas proteínas cinases constituem um dos principais mecanismos pelos quais as células se utilizam para regular seu metabolismo e demais funções e desequilíbrios nestas atividades estão relacionados a uma infinidade de doenças. O número elevado de isoformas de proteínas cinases 1 (CK1) encontradas na DA e sua associação em marcadores de lesões neurodegenerativas indicam sua participação nas etapas finais da degeneração, comum tanto à DA quanto a outras desordens neurodegenerativas. A abordagem da proteína CK1 como alvo terapêutico para a DA é promissora uma vez que os compostos usuais utilizados para diminuir a produção de ?-amilóide também bloqueiam a quebra de outras proteínas, causando graves efeitos colaterais. Cada vez mais as ferramentas de bioinformática vêm sendo utilizadas como auxílio na redução de custos e tempo para as pesquisas. Dentre estas técnicas destaca-se a triagem virtual, que reúne um conjunto de técnicas utilizadas de forma sequencial com o objetivo de selecionar compostos protótipos para os alvos desejados. Neste trabalho, foram utilizadas técnicas de triagem virtual baseada em ligantes e estrutura, a partir de uma base de 500 mil compostos, selecionando 35 compostos com perfil de atividade inibitória para a enzima CK1. Destes, os compostos 24, 25, 36, 39 41 e 42 apresentaram resultados significativos com relação ao potencial de inibição da enzima CK1?. Entre aqueles que já foram submetidos a ensaios de inibição enzimática, 25 apresentou seletividade para CK1?, com 40% de inibição. Para aqueles compostos com melhor potencial de inibição à concentração de 10 ?M será determinado o IC50 e uma extensa análise dos resultados será realizada futuramente. / Alzheimer\'s disease (AD) is a progressive neurodegenerative disorder characterized by loss of cortical and subcortical neurons. Pathological patterns of Alzheimer\'s disease include the presence of neurofibrillary lesions consisting of the accumulation of amyloid-? protein and the neurofibrillary tangles, resulting of hyperphosphorylated Tau protein. Only two major groups of drugs are used for treatment of AD, cholinesterase inhibitors and antagonists of Nmethyl- D-aspartate receptor. The phosphorylation of proteins by protein kinases constitute one of the major mechanisms which cells use to regulate their metabolism and imbalances in these activities are related to a series of diseases. The high number of isoforms of protein kinase 1 (CK1) found in AD and its association with neurodegenerative markers of indicate their participation in the final stages of degeneration, common to both AD and other neurodegenerative disorders. The approach of CK1 protein as a therapeutic target for AD is promising as the usual compounds used to reduce the production of amyloid-? also block the breakdown of other proteins, causing severe side effects. Increasingly, bioinformatics tools have been used as an aid in reducing costs and time to research. Among these techniques highlights the virtual screening, which includes a set of techniques used sequentially with the aim of select compounds prototypes for the desired target. Ligand and structure-based virtual screening techniches from a 500 thousand database resulted in 35 selected with inhibitory profile for CK1 enzyme were used in this study. The compounds 24, 25, 36, 39 41 and 42 had significan potential for CK1? enzyme inhibition. Among those submitted to enzyme inhibition assays, compound 25 showed selectivity for CK1? , with 40 % inhibition. For those compounds with the best inhibitory concentration at 10 mM and the IC50 will be given an extensive analysis of the results will be held in the future .

A drug discovery project typically starts with a pharmacological hypothesis: that the modulation of a specific molecular biological mechanism would be beneficial in the treatment of the targeted disease. In a small-molecule project, the next step is to identify hits, i.e. molecules that can effect this modulation. These hits are subsequently expanded into hit series, which are optimised with respect to pharmacodynamic and pharmacokinetic properties, through medicinal chemistry. Finally, a drug candidate is clinically developed into a new drug. This thesis concerns the use of structure-based virtual screening in the hit identification phase of drug discovery. Structure-based virtual screening involves using the known 3D structure of a target protein to predict binders, through the process of docking and scoring. Docking is the prediction of potential binding poses, and scoring is the prediction of the free energy of binding from those poses. Two new methodologies, based on post-processing of scoring results, were developed and evaluated using model systems. Both methods significantly increased the enrichment of true positives. Furthermore, correlation was observed between scores and simple molecular properties, and identified as a source of false positives in structure-based virtual screening. Two target proteins, Mycobacterium tuberculosis ribose-5-phosphate isomerase, a potential drug target in tuberculosis, and Plasmodium falciparum spermidine synthase, a potential drug target in malaria, were subjected to docking and virtual screening. Docking of substrates and products of ribose-5-phosphate isomerase led to hypotheses on the role of individual residues in the active site. Additionally, virtual screening was used to predict 48 potential inhibitors, but none was confirmed as an inhibitor or binder to the target enzyme. For spermidine synthase, structure-based virtual screening was used to predict 32 potential active-site binders. Seven of these were confirmed to bind in the active site.

In this thesis several important proteins are investigated from a structural perspective. Some of the proteins are disease related while other have important but not completely characterised functions. The techniques used are general as demonstrated by applications on metabolic proteins (CYP21, CYP11B1, IAPP, ADH3), regulatory proteins (p53, GDNF) and a transporter protein (ANTR1). When the protein CYP21 (steroid 21-hydroxylase) is deficient it causes CAH (congenital adrenal hyperplasia). For this protein, there are about 60 known mutations with characterised clinical phenotypes. Using manual structural analysis we managed to explain the severity of all but one of the mutations. By observing the properties of these mutations we could perform good predictions on, at the time, not classified mutations. For the cancer suppressor protein p53, there are over thousand mutations with known activity. To be able to analyse such a large number of mutations we developed an automated method for evaluation of the mutation effect called PREDMUT. In this method we include twelve different prediction parameters including two energy parameters calculated using an energy minimization procedure. The method manages to differentiate severe mutations from non-severe mutations with 77% accuracy on all possible single base substitutions and with 88% on mutations found in breast cancer patients. The automated prediction was further applied to CYP11B1 (steroid 11-beta-hydroxylase), which in a similar way as CYP21 causes CAH when deficient. A generalized method applicable to any kind of globular protein was developed. The method was subsequently evaluated on nine additional proteins for which mutants were known with annotated disease phenotypes. This prediction achieved 84% accuracy on CYP11B1 and 81% accuracy in total on the evaluation proteins while leaving 8% as unclassified. By increasing the number of unclassified mutations the accuracy of the remaining mutations could be increased on the evaluation proteins and substantially increase the classification quality as measured by the Matthews correlation coefficient. Servers with predictions for all possible single based substitutions are provided for p53, CYP21 and CYP11B1. The amyloid formation of IAPP (islet amyloid polypeptide) is strongly connected to diabetes and has been studied using both molecular dynamics and Monte Carlo energy minimization. The effects of mutations on the amount and speed of amyloid formation were investigated using three approaches. Applying a consensus of the three methods on a number of interesting mutations, 94% of the mutations could be correctly classified as amyloid forming or not, evaluated with in vitro measurements. In the brain there are many proteins whose functions and interactions are largely unknown. GDNF (glial cell line-derived neurotrophic factor) and NCAM (neural cell adhesion molecule) are two such neuron connected proteins that are known to interact. The form of interaction was studied using protein--protein docking where a docking interface was found mediated by four oppositely charged residues in respective protein. This interface was subsequently confirmed by mutagenesis experiments. The NCAM dimer interface upon binding to the GDNF dimer was also mapped as well as an additional interacting protein, GFRα1, which was successfully added to the protein complex without any clashes. A large and well studied protein family is the alcohol dehydrogenase family, ADH. A class of this family is ADH3 (alcohol dehydrogenase class III) that has several known substrates and inhibitors. By using virtual screening we tried to characterize new ligands. As some ligands were already known we could incorporate this knowledge when the compound docking simulations were scored and thereby find two new substrates and two new inhibitors which were subsequently successfully tested in vitro. ANTR1 (anion transporter 1) is a membrane bound transporter important in the photosynthesis in plants. To be able to study the amino acid residues involved in inorganic phosphate transportation a homology model of the protein was created. Important residues were then mapped onto the structure using conservation analysis and we were in this way able to propose roles of amino acid residues involved in the transportation of inorganic phosphate. Key residues were subsequently mutated in vitro and a transportation process could be postulated. To conclude, we have used several molecular modelling techniques to find functional clues, interaction sites and new ligands. Furthermore, we have investigated the effect of muations on the function and structure of a multitude of disease related proteins.

Anthraquinone (AQ) derivatives with relatively high reduction potentials have been synthesized to afford good candidates for electron transfer studies in DNA. Electron withdrawing groups on the anthraquinone ring gave derivatives with less negative reduction potentials. The anthraquinone imide (AQI) derivatives had reduction potentials less negative than AQ derivatives. The AQI ring system was subject to base-induced hydrolysis. Water-soluble sulfonated tetraarylporphyrins have been studied in a wide variety of contexts. Herein, we report the first synthesis of a pentasulfonated porphyrin bearing an internal cyclic sulfone ring. Treatment of 5,10,15,20-tetrakis(4-sulfonatophenyl)porphyrin (TPPS4) with fuming H2SO4 gave a structure consistent with initial sulfonation followed by dehydration to give a sulfone bridge between an ortho-position of one of the phenyl groups and a β-pyrrole position on the porphine ring (TPPS4Sc). The structure was established by ESI-MS and 1HNMR. The Soret absorption is red shifted by about 32 nm compared to that of TPPS4. Streptococcus pyogenes obtains iron by taking up heme from the environment during infection. One of the heme uptake pathways is the Sia or Hts pathway. The initial protein in this pathway is Shr, which has two heme-binding NEAT domains, NEAT1 nearer the N-terminus, and NEAT2 nearer the C-terminus. We report biophysical characteristics of these two NEAT domains. To assess stability of this domain towards heme release, denaturation studies of the Fe(II) and Fe(III) forms were performed. For each domain, both the Fe(II) and the Fe(III) forms behave similarly in thermal denaturation and guanidinium denaturation. Overall, NEAT2 is more stable than NEAT1. Spectral signatures, sequence alignment and homology modeling for both domains suggest that one of the axial ligands is methionine. NEAT2 autoreduces as the pH increases and autooxidizes as the pH decreases. Heme uptake from the host environment is the only iron acquisition pathway in S. pyogenes; inhibition of this pathway might be an approach to infection control. Compounds that might inhibit the heme uptake pathway were selected via virtual screening.

Histone acetyltransferases (HATs) are important enzymes in transcriptional control and potential targets for chemotherapeutic intervention in malignant diseases. Among different HAT members, the yeast Esa1 and human Tip60 (the HIV-1 Tat interactive protein, 60KDa) play multiple roles in normal cellular processes including transcription, cell cycle and checkpoint machinery, double strand DNA break repair, apoptosis, and cell cycle progression. Tip60 is also implicated in several human diseases such as prostate cancer, and gastric cancer. These studies suggest that Tip60 is a potential therapeutic target for new cancer treatment. So, we designed experimental work to synthesize and investigate organic inhibitors of Tip60 using different strategies, including substrate analogs, small molecule screening, and modification of the natural product anacardic acid. These studies provide important chemical agents for basic biology research of HAT function, and produce potential lead compounds for future pharmacologic intervention of HAT deregulation in cancer. Currently, of the methods used for the measurement of acetyltransferase activities, many comprise tedious separation procedures and involve enzyme-coupled steps or radioactive materials. These shortcomings have limited their applications in high-throughput screening (HTS) of HAT inhibitors. To circumvent these problems, a homogenous fluorescent HAT assay based on engineered H4 peptide was designed, synthesized, and evaluated. The data showed that these fluorescent reporters can be used to detect the acetyltransferase activities.

The main aim of the study in this thesis was to use structure-based protocols to design new drugs for enzymes, DXS and DXR in the non mevalonate pathway. Another aim of this study was to identify the dimer interface in E.coli FabH as an allosteric binding site for designing new class of anti-infective drugs. We have attempted to identify potential inhibitors for DXS by docking the NCI Diversity set compounds, compound libraries available from GSK-MMV and St. Jude's Children's research center. FabH dimer interface has been identified as a potential target using SiteMap, Alanine mutagenesis and docking studies. The first chapter gives an overview of the computational methods. The next two chapters briefly introduce the biological targets in the author's study. Chapter two explains the importance of non-mevalonate pathway in microbes. Different enzymes in the non-mevalonate pathway are discussed and the importance of terpenoids in biological processes and also the use of terpenoids as drugs have been extensively discussed in this chapter. The crystal structures available for DXS and DXR are also discussed. Chapter three brings out the importance of FabH as an anti-infective target. Crystal structure of FabH E.coli is discussed and the importance of FabH as a dimer has been discussed in this chapter. Chapter 3 describes the methods, homology models generated, and analysis from docking studies. The homology models for PvDXS and PvDXR have been used in this study to identify potential inhibitors. Domain swapping and the structural organization of PvDXS before and after domain swaping are discussed. Identification of domain swaping in PvDXS using entropy changes has been extensively discussed. Chapter 4 focuses on FabH (Fatty Acid Biosynthesis, enzyme H also referred to as β-ketoacyl-ACP-synthase III) dimer interface as an allosteric target. SiteMap analysis and MD simulations on the FabH monomer and dimer structures revealed the dimer interface as a binding region. Further analyses were done by mutagenesis studies on the Phe87 residue, a key residue at the dimer interface region and validating the results using docking studies. NCI Diversity Set compounds were docked at the dimer interface of FabH, which revealed that compounds NSC91529 and NSC19803 docked best at the dimer interface region with the phenyl ring of both the compounds

←Within this dissertation the topic of virtual screening is discussed with regard to three different cancer targets and also a brief introduction of the tools used in virtual screening. In Chapter 1, the reader will be introduced to virtual screening and the programs that are used in virtual screening. In Chapter 2, the first of three projects are discussed. This project consists of the work that was done to find inhibitors of the P53 binding domain of MDMX. In this project the mobility of residues within the binding site of MDMX are discussed and the ways in which we attempted to model how drugs would bind two adjacent pockets within MDMX. In Chapter 3, the virtual screening and modeling work done for RING domain of MDM2 and MDMX is discussed. This work was done in conjunction with Moffitt Cancer Center in order to solve the 60 year old mystery of the mechanism of how thalidomide and possibly its analog lenalidomide caused children to be born limbless. Current thinking is that Cereblon through an unknown teratogenic mechanism activates an increase in FGF8. We suggest a mechanism that may happen in parallel that involves stabilization of MDM2 and the reduction of P63 levels. Chapter 4, the work that was done against the BH3 binding domain of MCL-1 is discussed in conjunction with collaboration with the Manetsch lab. In order to complete this screening the validation of IC50 values and then attempt to modify those products based upon the structure of MCL-1. Chapter 5 discusses the work done to find inhibitors of deoxycytidine kinase. All of these chapters taken together provide a brief overview of the computational work done produce inhibitors of Protein-Protein Interaction against three major cancer targets.

Ricin and Shiga toxin type 1 are potent cytotoxins known as ribosome inhibition proteins, abbreviated RIPs. Proteins of this family shut down protein synthesis by removing a critical adenine in the conserved stem-loop structure of 28S rRNA. Due to its exquisite cytotoxicity, the plant toxin ricin has been used as a biological warfare agent. Although great achievement has been made on ricin research, including catalytic mechanism and structure analysis, there is still no specific treatment available for ricin exposure. In addition, ricin A chain inhibitors may also be useful against the homologous bacterial proteins shiga toxins, which are responsible for dysentery, and diseases related to food poisoning, including hemolytic uremic syndrome. Previous study on RTA inhibitor search has provided a number of substrate analog inhibitors, all of which, however, are weaker inhibitors. Therefore, the goal of this work is to improve the binding affinity of known inhibitors and to discovery new scaffolds for inhibitor discovery and development. In this work, multiple approaches were employed for this purpose, including optimizing known inhibitors and searching new inhibitors by Virtual Drug Screening (VDS) and High Throughput Screening (HTS). A number of new RTA inhibitors were discovered by these strategies, which provide a variety of pharmacophores for RTA inhibitor design, and also added a new line of evidence for VDS as an advanced technology for drug discovery and development. / text

Στα πλαίσια της συγκεκριμένης μεταπτυχιακής εργασίας μελετήθηκαν αλγόριθμοι και εργαλεία σχεδίασης φαρμάκων με τη βοήθεια Η/Υ που υπάρχουν στη διεθνή βιβλιογραφία. Η μελέτη εστιάστηκε σε αλγορίθμους ανάκτησης πιθανών φαρμακοφόρων μορίων από Βάσεις Βιολογικών Δεδομένων (search algorithms for virtual ligand screening), με χρήση της μεθόδου μοριακής αναγνώρισης (docking method). Η μέθοδος αυτή προσπαθεί να εντοπίσει μικρά μόρια-προσδέτες τα οποία ταιριάζουν, όσο το δυνατόν καλύτερα, στην κοιλότητα πρόσδεσης των μακρομορίων-στόχων που μας ενδιαφέρουν. Το ταίριασμα στηρίζεται στην ικανοποίηση: - γεωμετρικών κριτηρίων, τα οποία ελέγχουν την συμπληρωματικότητα στις δομές (σχήματα) των μορίων που επιδιώκουμε να ταιριάσουμε, και - ενεργειακών κριτηρίων τα οποία εξασφαλίζουν ότι αναπτύσσονται οι βέλτιστες αλληλεπιδράσεις μεταξύ των εμπλεκόμενων μορίων. Στόχος της διπλωματικής εργασίας ήταν η σχεδίαση ενιαίου πλαισίου αξιολόγησης των σχετικών εργαλείων και αλγορίθμων σχεδιασμού Φαρμάκων, ώστε να αποτελέσει βάση για περαιτέρω έρευνα, εντοπίζοντας ανοικτά προβλήματα ή/και προτείνοντας πιθανές βελτιώσεις. / In this dissertation algorithms and tools for computer-aided drug design that are available in the international bibliography were studied. The study focussed on virtual screening search algorithms and tools using the docking methodology, which locates small molecules (ligands) with optimal fit in the binding cavity of the target macromolecules of interest. Fit is based in the fulfilment of: - geometric criteria, which check for structural complementarity of the molecules involved and - energetic criteria, which check for optimal interactions between the molecules. The goal of this study was to develop an evaluation context for tools and algorithms used for computer-aided drug design in order to be used as the basis for further research and help us proposing possible improvements or addressing open problems.