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Submitted by Ingrid Bernardes Santana Martins (ingridmartins@sjrp.unesp.br) on 2016-09-13T16:35:56Z No. of bitstreams: 1 martins_ibs_mestrado.pdf: 6028551 bytes, checksum: ec7b5156fa37647e00f034cc5488d54e (MD5) / Approved for entry into archive by Felipe Augusto Arakaki (arakaki@reitoria.unesp.br) on 2016-09-16T21:15:07Z (GMT) No. of bitstreams: 1 martins_ibs_me_sjrp.pdf: 6028551 bytes, checksum: ec7b5156fa37647e00f034cc5488d54e (MD5) / Made available in DSpace on 2016-09-16T21:15:07Z (GMT). No. of bitstreams: 1 martins_ibs_me_sjrp.pdf: 6028551 bytes, checksum: ec7b5156fa37647e00f034cc5488d54e (MD5) Previous issue date: 2016-08-17 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Diversos processos biológicos envolvendo proteínas são mediados por alterações de pH. Infecção de células por vírus, catálise enzimática, associação de ligantes e a solubilidade de compostos são exemplos de tais processos. Assim, investigar o comportamento das cargas dos grupos ionizáveis de proteínas em função de mudanças no pH é de grande interesse. Simulações de Dinâmica Molecular são amplamente utilizadas para estudo dos mais diversos sistemas biológicos devido à confiabilidade de seus resultados. No entanto, elas não se mostram eficientes para a descrição de sistemas sensíveis a variações de pH pois os graus de ionização precisariam variar ao longo da simulação. Esse estado é definido na modelagem do sistema com base no pKa desses grupos isolados e no pH da solução. Isso representa uma limitação severa, pois processos que são modulados pela mudança na protonação não podem ser observados, de modo que uma abordagem mais realista é executar simulações em que o estado de protonação dos componentes do sistema possam variar com o tempo. Neste trabalho é desenvolvido um sistema computacional que acopla Dinâmica Molecular comum, executada com o pacote GROMACS, a um algoritmo que modifica o estado de protonação dos resíduos ionizáveis do sistema em intervalos de tempo regulares utilizando o método Monte Carlo com o critério de Metrópolis. Objetivando-se testar o método desenvolvido, foram realizadas Simulações de Dinâmica Molecular a pH Constante de um pepídeo composto majoritariamente de alaninas e cujo único grupo ionizável é um ácido glutâmico em diferentes pHs, com a finalidade de obter a curva de titulação desse peptídeo e então compará-la com a curva de titulação do ácido glutâmico isolado. / Several biological processes involving proteins are mediated by pH changes. Virus infection of cells, enzymatic catalysis, association of ligands and compounds solubility are examples of such processes. Therefore, invetigation of the titration residues charges in proteins in function of pH changes is very concernment. Molecular Dynamics simulations are widely used to study the most diverse biological systems due to the reliability of its results. However, they are not efficient to describe systems that are sensitive to pH changes because the protonation state needs to vary throughout the simulation. This state is defined in the system modeling based on the pKa of these isolated groups and solution pH. This is a severe limitation as processes that are modulated by the change in the protonation can not be observed, so that a more realistic approach is to run simulations where the protonation state of the system components may vary with time. In this work a computer system that couples common Molecular Dynamics, performed with GROMACS, and an algorithm that changes the protonation state of titratable residues of the system at regular time intervals by using Monte Carlo - Metropolis is developed. In order to test the developed method, Molecular Dynamics Simulations by Constant pH of a peptide consisting of mostly alanines whose only titratable group is a glutamic acid was made in different pHs in order to obtain the titration curve of this peptide and then compare it with the titration curve of isolated glutamic acid.

Polymers that undergo dramatic changes in structural conformations in response to numerous stimuli such as temperature, pH, electric and magnetic fields, light inten- sity, biological molecules, and solvent polarity, are known as stimuli-responsive or ”smart” polymers. There is a broad range of very promising applications of these materials in catalysis, environmental remediation, sensors or actuator systems, and as delivery systems of therapeutic agents. Researchers have been trying to mimic smart polymers based on properties of polymers found in nature such as proteins, carbohydrates and nucleic acids. Novel bio-compatible polymers with a variety of chemical functional groups, diverse topologies, and cross-linking patterns with the ability to self-assemble in vivo are being engineered. Experimental and theoretical studies indicate that the thermodynamic properties relating to the hydrophobic effects play a pivotal role in determining the self-assembly process in smart polymers. At the same time, computational approaches based on simulation and modeling provide an understanding of this phenomenon on the micro- scopic level. Building empirical models based on statistical mechanics methods and simulation data helps to design polymeric materials with desirable traits. My research is mainly focused on investigating physicochemical characteristics of stimuli-responsive polymers under different conditions. I used atomistic molecular dynamics simulations to investigate these effects on polymer conformation. Given the size and complexity of our polymeric systems, we employed Graphical Process- ing Units (GPU) and enhanced sampling techniques such as REDS2 to increase the sampling time. These methods allow for the study of polymeric structural dynamics in solvents of varying polarity and in human skin epidermis. Our constant pH simulation of poly(methacrylic acid) revealed that the overall response is made up of local and global structural changes. The local structural re- sponse depends on the tacticity of the polymer, which leads to distinct cooperative effects for polymers with varying stereochemistry. Such simulations help to under- stand the principal driving forces behind the mechanism of self-assembly processes.

Submitted by Vinicius de Godoi Contessoto null (vinicius@sjrp.unesp.br) on 2016-09-09T18:11:23Z No. of bitstreams: 1 Tese-Vinícius_Contessoto-Final.pdf: 17297320 bytes, checksum: f601c338b5bf6436dc595bad581418f5 (MD5) / Approved for entry into archive by Juliano Benedito Ferreira (julianoferreira@reitoria.unesp.br) on 2016-09-13T13:26:05Z (GMT) No. of bitstreams: 1 contessoto_vg_dr_sjrp.pdf: 17297320 bytes, checksum: f601c338b5bf6436dc595bad581418f5 (MD5) / Made available in DSpace on 2016-09-13T13:26:05Z (GMT). No. of bitstreams: 1 contessoto_vg_dr_sjrp.pdf: 17297320 bytes, checksum: f601c338b5bf6436dc595bad581418f5 (MD5) Previous issue date: 2016-08-16 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Entender a contribuição das interações eletrostáticas no processo de enovelamento e na estabilidade do estado nativo de proteínas é de grande relevância em biofísica molecular. Este trabalho possui duas frentes de estudos. Na primeira etapa é apresentado o estudo das interações eletrostáticas no processo de enovelamento utilizando modelos baseados em estruturas com cargas em dinâmica molecular com pH constante. O estudo foi realizado na parte N-terminal da proteína ribossomal L9 (NTL9), uma proteína com o mecanismo de enovelamento de 2 estados, reversível e realizado desde pH 1.0 até 12.0. Foi possível comparar os resultados das simulações com os resultados experimentais presentes na literatura e os dados obtidos indicam que o modelo proposto é capaz de capturar informações fundamentais sobre o processo de enovelamento referentes à estabilidade e dependência com pH. Na segunda etapa é apresentado o estudo sobre as interações eletrostáticas na estabilidade de enzimas com interesse na produção de bioetanol de segunda geração. O objetivo final deste trabalho é adequar as enzimas às condições do reator para a produção de bioetanol. Neste trabalho foi utilizada uma metodologia capaz de indicar possíveis mutações, pela otimização da interação carga–carga na superfície da proteína, que levam ao aumento de termostabilidade. Este trabalho conta com a colaboração do grupo experimental do Laboratório Nacional de Ciência e Tecnologia do Bioetanol (CTBE) que realizam os testes experimentais e as validações das mutações propostas. / The understanding of electrostatic interactions in protein folding process and in native state stability is important to molecular biophysics area. This work has two areas of interest. At first step it is presented the study about electrostatic interactions in the protein folding process using structure-based models in a constant pH molecular dynamics. It was used the N-terminal domain of ribosomal protein L9 (NTL9), which folding mechanism is a two-state pathway, fully reversible and foldable in a pH range from 1.0 to 12.0. The simulation results were compared with experimental results from literature and the obtained data indicates that the proposed model is capable of capturing essential features of folding mechanism about stability and pH dependence. At second step, it is presented the study about electrostatic interactions in stability of enzymes related with second generation bioethanol production. The final goal of this work is to adjust the enzymes to reactor conditions of bioethanol production. It was employed a method that can suggest rational mutation, based on optimization of charge-charge interactions, that leads to thermostability increase. This work can count on the collaboration of an experimental group of Brazilian Bioethanol Science and Technology Laboratory (CTBE) that performs the wet lab tests and validates the suggested mutations.

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Ligand-gated ion channels play an important role in electrochemical signal transduction across diverse organisms, yet their structural and functional intricacies are not fully understood. Particularly lacking is the knowledge of their response to variations in pH, an aspect necessary for understanding their physiological relevance and potential therapeutic targeting in neurological diseases. In this thesis project, I have investigated the mechanistic response of sTeLIC, a recently reported prokaryotic member of the pentameric ligand-gated ion channel family, to different environmental conditions. Using molecular dynamics simulations, a total of 16 different environmental conditions have been explored including variations in pH (neutral and alkaline), the presence and absence of calcium, and the inclusion of an electric field acting as an external driving force on charged atoms. The results reveal a comprehensive pH-sensing and gating mechanism involving key residues, notably E106 (on the β6 strand) and E160 (on loop F), and their local microenvironments. Additionally, an inhibitory mechanism for calcium is proposed, with E160 playing an important role. The simulations including an electric field has provided support for a non-conventional ion pathway through the pore. Collectively, these results offer insights into a mechanistic framework that may extend to other physiologically relevant systems, providing a foundation for further investigations and potential future therapeutic intervention. / pLGICs har en viktig roll i det elektrokemiska signalsystemet i många organismer, men detaljerna i deras struktur och framför allt funktion är fortfarande inte helt klargjorda. Särskilt är detaljerna kring deras reaktion på ändringar i pH-värde relativt okända, vilket är en viktig del i att förstå kanalernas fysiologiska roll och för att potentiellt hitta läkemedel mot neurologiska sjukdomar där dessa är inblandade. I det här arbetet har jag undersökt hur sTeLIC, som är ett nyligen publicerat bakteriellt protein i familjen pLGICs, reagerar på olika ändringar i miljön. Jag har använt molekyldynamiksimuleringar för att unders öka 16 olika miljöer med två olika pH-värden (neutralt och alkaliskt), med eller utan kalcium samt med eller utan en extern drivkraft över membranet i form av ett elektrisk fält. Arbetet har resulterat i en föreslagen mekanism förhur sTeLIC känner av pH och hur öppningen av kanalen går till. Denna mekanism involverar aminosyrorna E106, som finns på β6-strängen, och E160, som finns på F-loopen, samt deras omgivning. Dessutom har en modulatorisk mekanism föreslagits för en kalciuminhiberande effekt på sTeLIC som också involverar E160. Simuleringarna med en drivkraft över membranet har gett stöd för en ny väg för joner genom kanalen. Tillsammans ger dessa resultat insikt i en mekanism som eventuellt kan appliceras p ̊a andra system. Detta har lagt grunden för fortsatt undersökning som potentiellt kan leda till framtida läkemedelsutveckling inom området.