Theoretical Aspects of Designing New Vaccines for Breast Cancer: Docking Studies of Peptide/HLA-A2.1 Complexes

HER2/neu is a transmembrane glycoprotein that is overexpressed in many tumors, including ovarian and breast cancers. The HER2/neu peptide IISAVVGIL (GP2) is recognized by tumor-specific cytotoxic T lymphocytes in the context of human class I major histocompatibility complex (MHC) HLA-A2.1. One limiting-factor for using GP2 as a tumor vaccine is its poor affinity for HLA-A2.1, even though it has the correct peptide-binding motif. The research aims are to develop an accurate docking method for the binding of GP2 to HLA-A2.1, to understand the molecular forces that give rise to strong binding, and to predict mutations that lead to new tumor vaccines. AutoDock and GOLD have been used for docking calculations. The binding free energies from AutoDock correlate qualitatively with experiment. The docked structures for 14 ligands from Autodock3 are in good agreement with experiment. However, the ligands are not fully flexible. GOLD allowed full flexibility to reproduce experimental GP2 structure

Integrating protein structural information

Dissertação apresentada para obtenção de Grau de Doutor em Bioquímica,Bioquímica Estrutural, pela Universidade Nova de Lisboa, Faculdade de Ciências e TecnologiaThe central theme of this work is the application of constraint programming and other artificial intelligence techniques to protein structure problems, with the goal of better combining experimental data with structure prediction methods. Part one of the dissertation introduces the main subjects of protein structure and constraint programming, summarises the state of the art in the modelling of protein structures and complexes, sets the context for the techniques described later on, and outlines the main points of the thesis: the integration of experimental data in modelling. The first chapter, Protein Structure, introduces the reader to the basic notions of amino acid structure, protein chains, and protein folding and interaction. These are important concepts to understand the work described in parts two and three. Chapter two, Protein Modelling, gives a brief overview of experimental and theoretical techniques to model protein structures. The information in this chapter provides the context of the investigations described in parts two and three, but is not essential to understanding the methods developed. Chapter three, Constraint Programming, outlines the main concepts of this programming technique. Understanding variable modelling, the notions of consistency and propagation, and search methods should greatly help the reader interested in the details of the algorithms, as described in part two of this book. The fourth chapter, Integrating Structural Information, is a summary of the thesis proposed here. This chapter is an overview of the objectives of this work, and gives an idea of how the algorithms developed here could help in modelling protein structures. The main goal is to provide a flexible and continuously evolving framework for the integration of structural information from a diversity of experimental techniques and theoretical predictions. Part two describes the algorithms developed, which make up the main original contribution of this work. This part is aimed especially at developers interested in the details of the algorithms, in replicating the results, in improving the method or in integrating them in other applications. Biochemical aspects are dealt with briefly and as necessary, and the emphasis is on the algorithms and the code

Bioinformatics

This book is divided into different research areas relevant in Bioinformatics such as biological networks, next generation sequencing, high performance computing, molecular modeling, structural bioinformatics, molecular modeling and intelligent data analysis. Each book section introduces the basic concepts and then explains its application to problems of great relevance, so both novice and expert readers can benefit from the information and research works presented here

Developing microfluidics and microscopy approaches to investigate bacterial populations with single-cell resolution

Failures in antibiotic treatments for bacterial infections are typically attributed to antibiotic resistance. However, it has long been realised that bacteria can also employ other mechanisms to aid survival in the presence of antibiotics. Indeed, some bacterial cells react to the presence of antimicrobial drugs by blocking or retarding growth. These cells are named persister cells and can survive bactericidal antibiotics that require active growth for killing. This property is known as “persistence”. Increasing evidence suggests a link between specific environmental conditions and the development of persistence. In this study, the temporal windows during the growth cycle when the fraction of persisters to β-lactams, quinolones or aminoglycoside increases have been investigated. Our results confirmed that the environment plays a significant role in persister cell formation. Indeed, cells treated with antibiotics but without fresh media, regrow at a higher density than the cells in the nutrient-rich environment. Nowadays classic microbiological approaches are not sufficient for the study of persister cells, since the persister frequency is often low and dynamic changes in phenotype cause cells to switch between the persister and normal phenotype. Over the past decade, microfluidic techniques have gained increasing interest in the research community. Integrated micro- and nanofluidic lab-on-a-chip systems able to handle samples in a picoliter range are now available, and are certain to become an everyday item in biotechnology and biomedicine within a few years. Here we present a novel microfluidic-microscopy assay for the study of persister cell formation under controlled delivery of antibiotics. Our device is fabricated from polydimethylsiloxane, PDMS, and is able to trap single cells. The microfluidic setup has been integrated with a microscope in order to obtain high-resolution imaging and quantitatively measure growth and shape changes of large numbers of individual cells. Our device allowed us to challenge a culture of E. coli with three different antibiotics, and record the individual response of thousands of bacteria. When fresh media was given we distinguished not only dividing cells, as per classic microbiological techniques, but also two further phenotypes: elongating and non-growing. Furthermore, a preliminary study has been conducted regarding the possibility of combining DNA-PAINT with microfluidics for the future investigation of persister cells, with sub-cellular resolution. Together, the results from this thesis enable future investigations, with the goal of advancing our understanding of persistence in response to antibiotics

Mass & secondary structure propensity of amino acids explain their mutability and evolutionary replacements

Why is an amino acid replacement in a protein accepted during evolution? The answer given by bioinformatics relies on the frequency of change of each amino acid by another one and the propensity of each to remain unchanged. We propose that these replacement rules are recoverable from the secondary structural trends of amino acids. A distance measure between high-resolution Ramachandran distributions reveals that structurally similar residues coincide with those found in substitution matrices such as BLOSUM: Asn Asp, Phe Tyr, Lys Arg, Gln Glu, Ile Val, Met → Leu; with Ala, Cys, His, Gly, Ser, Pro, and Thr, as structurally idiosyncratic residues. We also found a high average correlation (\overline{R} R = 0.85) between thirty amino acid mutability scales and the mutational inertia (I X ), which measures the energetic cost weighted by the number of observations at the most probable amino acid conformation. These results indicate that amino acid substitutions follow two optimally-efficient principles: (a) amino acids interchangeability privileges their secondary structural similarity, and (b) the amino acid mutability depends directly on its biosynthetic energy cost, and inversely with its frequency. These two principles are the underlying rules governing the observed amino acid substitutions. © 2017 The Author(s)

Dynamics of DNA Breathing and Folding for Molecular Recognition and Computation

This thesis is centered on the development of the molecular beacon, as a new DNA probe for DNA genotyping, D N A computation and biophysical studies of DNA conformations. Molecular beacons are single-stranded DNA molecules that form a stem-and-loop structure. A fluorophore and a quencher are grafted at their two ends to report their conformations: when the molecular beacon is closed, fluorophore and quencher are held in close proximity and the fluorescence is quenched; when the molecular beacon is open, fluorophore and quencher are far apart, and the fluorescence is restored. Molecular beacons are ideal DNA probes coupling conformational switch with fluorescence signal turning-ON. We use molecular beacons to study the molecular recognition of single-stranded DNA (ssDNA) oligonucleotide. We present a thermodynamic diagram to show that structural constraints make the molecular beacon highly sensitive to the presence of mismatches in its target. We introduce a sequence sensitivity parameter to quantitatively compare different DNA probes, and propose an algorithm to optimally tune the probe\u27s structure for enhanced sequence discrimination. Logic gates (OR and AND gates) using molecular beacons are designed to carry most elementary molecular computations. The conformational changes associated with such computations can be used to concatenate many chemical reactions, and carry out complex molecular computations. Molecular beacons are also ideal probes to study DNA secondary structures and their fluctuations. We develop the fluorescence correlation spectroscopy (FCS) technique to monitor the dynamics of relaxation of DNA conformational fluctuations. We first measure the opening and closing timescales of DNA hairpin-loops. Activation barriers for opening and closing for different loop lengths and sequences are analyzed to better account for the stability of DNA secondary structures. A sequence dependent rigidity of ssDNA has been discovered, and analyzed in terms of base stacking. We then use F C S to study the dynamics of double-stranded DNA (dsDNA) breathing modes with synthetic DNA constructs. The analysis of the base pairing fluctuation dynamics, monitored by fluorescence, unravels lifetimes of breathing modes ranging from 1/us to 1ms. Long-range distortions of the d s DNA have been unraveled for purine-rich sequences, of relevance to the specificity of transcription initiation in prokaryotes