Flexible protein folding by ant colony optimization

Protein structure prediction is one of the most challenging topics in bioinformatics. As the protein structure is found to be closely related to its functions, predicting the folding structure of a protein to judge its functions is meaningful to the humanity. This chapter proposes a flexible ant colony (FAC) algorithm for solving protein folding problems (PFPs) based on the hydrophobic-polar (HP) square lattice model. Different from the previous ant algorithms for PFPs, the pheromones in the proposed algorithm are placed on the arcs connecting adjacent squares in the lattice. Such pheromone placement model is similar to the one used in the traveling salesmen problems (TSPs), where pheromones are released on the arcs connecting the cities. Moreover, the collaboration of effective heuristic and pheromone strategies greatly enhances the performance of the algorithm so that the algorithm can achieve good results without local search methods. By testing some benchmark two-dimensional hydrophobic-polar (2D-HP) protein sequences, the performance shows that the proposed algorithm is quite competitive compared with some other well-known methods for solving the same protein folding problems

Protein multiple sequence alignment by hybrid bio-inspired algorithms

This article presents an immune inspired algorithm to tackle the Multiple Sequence Alignment (MSA) problem. MSA is one of the most important tasks in biological sequence analysis. Although this paper focuses on protein alignments, most of the discussion and methodology may also be applied to DNA alignments. The problem of finding the multiple alignment was investigated in the study by Bonizzoni and Vedova and Wang and Jiang, and proved to be a NP-hard (non-deterministic polynomial-time hard) problem. The presented algorithm, called Immunological Multiple Sequence Alignment Algorithm (IMSA), incorporates two new strategies to create the initial population and specific ad hoc mutation operators. It is based on the ‘weighted sum of pairs’ as objective function, to evaluate a given candidate alignment. IMSA was tested using both classical benchmarks of BAliBASE (versions 1.0, 2.0 and 3.0), and experimental results indicate that it is comparable with state-of-the-art multiple alignment algorithms, in terms of quality of alignments, weighted Sums-of-Pairs (SP) and Column Score (CS) values. The main novelty of IMSA is its ability to generate more than a single suboptimal alignment, for every MSA instance; this behaviour is due to the stochastic nature of the algorithm and of the populations evolved during the convergence process. This feature will help the decision maker to assess and select a biologically relevant multiple sequence alignment. Finally, the designed algorithm can be used as a local search procedure to properly explore promising alignments of the search space

The Role of MSA in the Global Regulation of Virulence in \u3ci\u3eStaphylococcus aureus\u3c/i\u3e

Staphylococcus aureus is an important pathogen causing life threatening diseases in humans. Previously we showed that msa modulates the activity of sarA (Staphylococcal accessory regulator), which is one of a major global regulator of virulence in S. aureus. The objective of this study is to characterize the role of msa (Modulator of SarA) in the global regulation of virulence in S. aureus. Structure and function predictions were done using several computational tools and approaches to understand the nature of msa. A novel S. aureus microarray meta-database (SAMMD) was designed and developed to compare and contrast other transcriptomes with msa transcriptome. msa and sarA transcriptomes were generated using the microarray technology. Phenotypic and molecular assays were performed to support microarray results. The results show that msa is a putative transmembrane protein, with three transmembrane segments, a distinct N-terminal cleavable signal peptide, four phophorylation sites (two outside and two inside the membrane) and a binding site in the cytoplasmic region. Microarray results and comparative transcriptome analysis using SAMMD showed that several genes regulated by msa are also regulated by sarA. Based on these results I hypothesize that msa is a novel signal transducer, which modulates the activity of genes involved in virulence in a sar/\-dependent manner, while modulating the activity of genes involved in metabolism in a sar-4-independent manner

DESARROLLO DE UN ALGORITMO EVOLUTIVO PARA LA PERFILACIÓN GEOGRÁFICA CRIMINAL

Tesis doctoralEsta tesis aplicó un algoritmo evolutivo desarrollado para la elaboración de perfiles geográficos delictivos. El algoritmo se basó en algoritmos genéticos, programación evolutiva y estrategias evolutivas. Las técnicas anteriores se aplicaron sobre un algoritmo para la elaboración de perfiles geográficos delictivos. El objetivo fue seleccionar individuos con características similares. El algoritmo evolutivo considera un cambio en las soluciones en caso de ingresar mínimos o máximos locales. Además, la selección de nuevos individuos de la población en caso de salir de los parámetros de evaluación. Las pruebas y la evaluación del algoritmo propuesto se obtuvieron heurísticamente. Los hechos considerados coincidieron con las características de la mayoría de la población inicial y con estos resultados. El algoritmo se puede utilizar como una herramienta adicional en la prevención del delito. Las pruebas y la evaluación del algoritmo propuesto se obtuvieron heurísticamente. Los hechos considerados coincidieron con las características de la mayoría de la población inicial y con estos resultados. El algoritmo se puede utilizar como una herramienta adicional en la prevención del delito

Impact of epigallocatechin-3-gallate (EGCG), a broad-spectrum anti-inflammatory, in controlling intestinal factors contributing to inflammatory bowel disease.

This dissertation explores the role of epigallocatechin-3-gallate (EGCG), as a potential treatment for patients with inflammatory bowel disease (IBD). IBD is a common disorder that causes a great deal of suffering. Our understanding of the etiologies, pathogenic mechanisms, and treatment targets continues to evolve. Many new therapeutic targets are making their way through the pharmaceutical pipelines. However, not all patients benefit from these therapies. EGCG has long been studied as an anti-cancer agent. Most of our understanding of this compound comes from the oncologic literature. As the pathways of oncology and inflammation converge, new lessons can be taken from the cross discipline. EGCG’s effects on intracellular signaling bridges cancer to inflammation. Many of the same cytokines, chemokines, and molecular signals influencing cancer cells to grow also stimulate immune cells. Chapter 3 first explores the role of EGCG as both a preventative as well as a therapeutic agent and its effect on the dextran sulfate sodium (DSS) mouse model of colitis. The influence of EGCG on immune cell function is then explored in chapter 4. One novel approach in chapter 4 has to do with a focus on intestinal epithelial cells as agents of an immune response, and how EGCG impacts their function in that role. Chapter 5 explores the impact of EGCG on bolstering barrier function, as this is an important aspect of inflammatory bowel disease that is often neglected when considering new approaches to treating IBD. Finally, chapter 6 ends this dissertation with the first clinical trial in the world’s literature to evaluate EGCG as a therapeutic for IBD

Exploring the relationship between statistical and physics-based free energies within the protein sequence-structure paradigm

In the field of protein stability prediction, computational resources remain a major limitation. Modeling approaches using all-atom force fields provide a wealth of information about the energetic determinants of sequence-structure compatibility, but require significant amounts of processing power, memory, and data storage. Here we utilize the COREX algorithm to develop a thermodynamic framework to evaluate the stability of a protein through the lens of compatibility of any sequence for any fold. The heuristics in this approach are based on the naturally occurring frequencies of different amino acids in defined thermodynamic environments that encompass all possible energetic profiles. Our hypothesis is that these frequencies are directly related to the energetic impact of a residue on the stability of the protein, given the residue’s environment. If true, the frequency-based scores could provide information that is comparable to validated physics-based approaches that directly evaluate the energy of a mutation and therefore the effects on the compatibility between the sequence and structure. To test this hypothesis, we compared the sequence compatibility scores obtained from COREX analysis with the computed energy determined using the well-known physics- based software embodied in the Rosetta platform. Importantly, we find a substantial correlation between the energetic scores obtained from each approach, when applied to a large database of proteins, ranging in size from 50 to 250 amino acids. To further investigate this correlation and control for the well-known size dependence of protein stability, we investigated the ability of each algorithm to identify which of two potential structures would be adopted by an engineered set of high identity sequences of identical length. The demonstrated agreement between COREX and Rosetta suggests that the thermodynamic heuristics provide a fast and efficient means of evaluating the compatibility of a sequence for a particular fold while maintaining important information often not captured in structure-based heuristic methods. Because the COREX-based scores are derived from efficiently additive position specific frequencies, they represent a 104 -fold decrease in computational resources necessary to exhaustively evaluate the effects of sequence variation in a 200 amino acid protein. The intentional combination of these methods provides a unique opportunity to investigate previously elusive research questions with an accessible, computationally reasonable approach

Evolución dirigida de penicilina V acilasa de "Streptomyces lavendulae" y aculeacina A acilasa de "Actinoplanes utahensis"

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Farmacia, Departamento de Microbiología II, leída el 14-07-2016Actualmente la secuenciación y el consecuente depósito en bases de datos públicas de genomas bacterianos han incrementado de manera exponencial y constituye una herramienta inevitable en la investigación básica y aplicada. Sin embargo, la elucidación de la información encriptada en sus secuencias codificantes aunado a las particularidades de cada microorganismo, constituyen las barreras a ser superadas por parte de los investigadores, para lo cual estudios bioinformáticos integrados con evidencias experimentales son ineludibles de abordar en el laboratorio. En particular, es menester reconocer la versatilidad que ostentan las bacterias Gram-positivas y sus implicaciones que trascienden los entornos naturales y se inmiscuyen cada vez más en procesos biotecnológicos. Por tal motivo, en el presente estudio se secuenciaron los genomas de las cepas bacterianas Streptomyces lavendulae ATCC 13664 y Actinoplanes utahensis NRRL 12052, gracias a lo cual se logró determinar múltiples características de dichos microorganismos. En este sentido, el presente estudio logró determinar con base en la secuencia del 16S rRNA, al igual que con fundamento en una comparación de todo el genoma frente a una base de datos local de genomas, que la cepa de S. lavendulae se encuentra mal asignada y por lo tanto debería ser reasignada como una nueva especie, dado que fue detectada filogenéticamente cerca a otras especies de S. lavendulae, y en contraste dicha cepa se localiza aún más cerca de otras especies de S. griseus. Igualmente, dentro del genoma de A. utahensis resalta la detección de una acil-homoserin lactona acilasa (AuAHLA) putativa, la cual es documentada por primera vez en este estudio. Los análisis bioinformáticos desarrollados destacaron que dicha enzima presenta características similares a la aculeacin A acilasa (AuAAC) de A. utahensis y a la penicilina V acilasa (SlPVA) de S. lavendulae. Igualmente, cabe mencionar que no fue detectada la equinocandina B (ECB) deacilasa transmembrana dentro del genoma de A. utahensis, la cual se había descrito previamente por otros autores y que solo difiere ligeramente en su secuencia con respecto a AuAAC (aunque no se ha depositado la secuencia completa de la ECB deacilasa, si se ha informado sobre fragmentos del amino-terminal de cada subunidad), lo cual permite proponer que la ECB deacilasa debe ser reasignada. Asimismo, es de resaltar que en los dos microorganismos secuenciados fueron detectados clúster relacionados con la biosíntesis de NRPS (de su sigla en inglés non-ribosomal peptide-synthase) y PKS (de su sigla en inglés polyketide synthase). Específicamente, tanto AuAAC como AuAHLA fueron localizadas dentro de clústeres relacionados con la biosíntesis de sideróforos (i.e. gobichelina y laspartomicina, respectivamente según la predicción realizada), moléculas que son empleadas por las bacterias como compuestos quelantes del hierro, y que los seres humanos aprovechan gracias a su actividad biológica. En contraste, a pesar de que la plataforma empleada no predijo ningún clúster que contenga SlPVA, estudios adicionales permitieron que el presente estudio no descarte que SlPVA esté implicada en la biosíntesis de algún sideróforo, tal y como fue el caso de las acilasas de A. utahensis...Nowadays sequencing and consequent deposit in public data bases of bacterial genomes have been increased exponentially and constitutes an inevitable tool in basic and applied research. However, the elucidation of the encrypted information along their coding sequences and the particularities of each microorganism are barriers to be overcome by the researcher. Thus, bioinformatic studies integrated with experimental evidences are inescapably addressed in the laboratory. In particular, it is important to mention the versatility that holds the Gram-positive bacteria and its implications that transcends natural environments and interferes time after time in biotechnological processes. For this reason, in this study the genomes of the bacterial strains Streptomyces lavendulae ATCC 13664 and Actinoplanes utahensis NRRL 12052 were sequenced, and thanks to this information, it was possible to determine several features from those microorganisms. In this sense, the analysis of the 16S rRNA sequence as well as the comparison of the whole genome against a local database of genomes suggests that the strain of S. lavendulae is misassigned and should be assigned as a new specie, because despite the fact that it was detected phylogenetically close to other strains of S. lavendulae, it was located closer to other S. griseus species. Likewise, within the genome of A. utahensis highlights the presence of acyl-homoserine lactone acylase (AuAHLA), which is reported here for the first time. The bioinformatic analyses developed emphasizes that this enzyme had similar characteristics with respect to aculeacin A acylase (AuAAC) from A. utahensis and penicillin V acylase (SlPVA) from S. lavendulae. Surprisingly, it is noteworthy to mention that the transmembrane echinocandin B (ECB) deacylase was not detected within the genome of A. utahensis. Information about ECB deacylase reported by other authors and its sequence differs slightly with respect to AuAAC. Although the sequence of ECB deacylase has not been deposited, the authors reported the amino-terminus of each subunit. Thus, the present study suggests that this ECB deacylase should be reassigned. Likewise, it is important to mention that in both genomes clusters related with the biosynthesis of NRPS (non-ribosomal peptide-synthase) and PKS (polyketide synthase) were detected. Specifically, both AuAAC as AuAHLA were located within a cluster associated with the biosynthesis of siderophores (i.e. predicted gobichelin and laspartomycin, respectively). These molecules are employed by the bacteria as iron chelating compounds, and humans use their biological activity. In contrast, although the platform employed did not predict any cluster containing SlPVA, further studies might indicate that SlPVA could be implicated in the biosynthesis of some siderophore, similarly to that exposed with the acylases from A. utahensis...Depto. de Microbiología y ParasitologíaFac. de FarmaciaTRUEunpu

Analysis of Spectral Data in Clinical Proteomics by use of Learning Vector Quantizers

Schleif F-M, Hammer B, Villmann T. Analysis of Spectral Data in Clinical Proteomics by use of Learning Vector Quantizers. In: Van de Werff M, Delder A, Tollenaar R, eds. Computational Intelligence in Biomedicine and Bioinformatics: Current Trends and Applications. Berlin: Springer; 2008: 141-167