Antibiotic resistance is increasing at a rate that far exceeds the pace of new development of drugs. Antimicrobial peptides, both synthetic and from natural sources, have raised interest as pathogens become resistant against conventional antibiotics. Indeed, one of the major strengths of this class of molecules is their ability to kill multidrug-resistant bacteria. Antimicrobial peptides are relatively small (6 to 100 aminoacids), amphipathic molecules of variable length, sequence and structure with activity against a wide range of microorganisms including bacteria, protozoa, yeast, fungi, viruses and even tumor cells. They usually act through relatively non-specific mechanisms resulting in membranolytic activity but they can also stimulate the innate immune response. Several peptides have already entered pre-clinical and clinical trials for the treatment of catheter site infections, cystic fibrosis, acne, wound healing and patients undergoing stem cell transplantation. We review the advantages of these molecules in clinical applications, their disadvantages including their low in vivo stability, high costs of production and the strategies for their discovery and optimization.

https://www.degruyter.com/downloadpdf/j/biol.2007.2.issue-1/s11535-007-0010-5/s11535-007-0010-5.xml

Antimicrobial peptides: an overview of a promising class of therapeutics

Genomics is a highly cross-disciplinary field that creates paradigm shifts in such diverse areas as medicine and agriculture. It is believed that many significant scientific and technological endeavors in the 21st century will be related to the processing and interpretation of the vast information that is currently revealed from sequencing the genomes of many living organisms, including humans. Genomic information is digital in a very real sense; it is represented in the form of sequences of which each element can be one out of a finite number of entities. Such sequences, like DNA and proteins, have been mathematically represented by character strings, in which each character is a letter of an alphabet. In the case of DNA, the alphabet is size 4 and consists of the letters A, T, C and G; in the case of proteins, the size of the corresponding alphabet is 20. As the list of references shows, biomolecular sequence analysis has already been a major research topic among computer scientists, physicists, and mathematicians. The main reason that the field of signal processing does not yet have significant impact in the field is because it deals with numerical sequences rather than character strings. However, if we properly map a character string into, one or more numerical sequences, then digital signal processing (DSP) provides a set of novel and useful tools for solving highly relevant problems. For example, in the form of local texture, color spectrograms visually provide significant information about biomolecular sequences which facilitates understanding of local nature, structure, and function. Furthermore, both the magnitude and the phase of properly defined Fourier transforms can be used to predict important features like the location and certain properties of protein coding regions in DNA. Even the process of mapping DNA into proteins and the interdependence of the two kinds of sequences can be analyzed using simulations based on digital filtering. These and other DSP-based approaches result in alternative mathematical formulations and may provide improved computational techniques for the solution of useful problems in genomic information science and technology.

Genomic signal processing

http://llama.mshri.on.ca/courses/BCMP370/papers/bork.pdf

Predicting function: from genes to genomes and back.

Background: Most eukaryotic genomes include a substantial repeat-rich fraction termed heterochromatin, which is concentrated in centric and telomeric regions. The repetitive nature of heterochromatic sequence makes it difficult to assemble and analyze. To better understand the heterochromatic component of the Drosophila melanogaster genome, we characterized and annotated portions of a whole-genome shotgun sequence assembly. Results: WGS3, an improved whole-genome shotgun assembly, includes 20.7 Mb of draft-quality sequence not represented in the Release 3 sequence spanning the euchromatin. We annotated this sequence using the methods employed in the re-annotation of the Release 3 euchromatic sequence. This analysis predicted 297 protein-coding genes and six non-protein-coding genes, including known heterochromatic genes, and regions of similarity to known transposable elements. Bacterial artificial chromosome (BAC)-based fluorescence in situ hybridization analysis was used to correlate the genomic sequence with the cytogenetic map in order to refine the genomic definition of the centric heterochromatin; on the basis of our cytological definition, the annotated Release 3 euchromatic sequence extends into the centric heterochromatin on each chromosome arm. Conclusions: Whole-genome shotgun assembly produced a reliable draft-quality sequence of a significant part of the Drosophila heterochromatin. Annotation of this sequence defined the intron-exon structures of 30 known protein-coding genes and 267 protein-coding gene models. The cytogenetic mapping suggests that an additional 150 predicted genes are located in heterochromatin at the base of the Release 3 euchromatic sequence. Our analysis suggests strategies for improving the sequence and annotation of the heterochromatic portions of the Drosophila and other complex genomes.

/pdf/heterochromatic-sequences-in-a-drosophila-whole-genome-5bk34mer4b.pdf

Heterochromatic sequences in a Drosophila whole-genome shotgun assembly

The identification of genes with selective expression in specific organs or cell types provides an entry point for understanding biological processes that occur uniquely within a particular tissue Using a subtraction approach designed to identify genes preferentially expressed in specific tissues, we have identified prostase, a human serine protease with prostate-restricted expression The prostase cDNA encodes a putative 254-aa polypeptide with a conserved serine protease catalytic triad and an amino-terminal pre-propeptide sequence, indicating a potential secretory function The genomic sequence comprises five exons and four introns and contains multiple copies of a chromosome 19q-specific minisatellite repeat Northern analysis indicates that prostase mRNA is expressed in hormonally responsive normal and neoplastic prostate epithelial tissues, but not in prostate stromal constituents Prostase shares 35% amino acid identity with prostate-specific antigen (PSA) and 78% identity with the porcine enamel matrix serine proteinase 1, an enzyme involved in enamel matrix degradation and with a putative role in the disruption of intercellular junctions Radiation-hybrid-panel mapping localized prostase to chromosome 19q13, a region containing several other serine proteases, including protease M, pancreatic/renal kallikrein hK1, and the prostate-specific kallikreins hK2 and hK3 (PSA) The sequence homology between prostase and other well-characterized serine proteases suggests several potential functional roles for the prostase protein that include the degradation of extracellular matrix and the activation of PSA and other proteases

https://www.pnas.org/content/pnas/96/6/3114.full.pdf

Molecular cloning and characterization of prostase, an androgen-regulated serine protease with prostate-restricted expression.

Motivation: The major signal in coding regions of genomic sequences is a three-base periodicity. Our aim is to use Fourier techniques to analyse this periodicity, and thereby to develop a tool to recognize coding regions in genomic DNA. Result: The three-base periodicity in the nucleotide arrangement is evidenced as a sharp peak at frequency f — 1/3 in the Fourier (or power) spectrum. From extensive spectral analysis of DNA sequences of total length over 5.5 million base pairs from a wide variety or organisms (including the human genome), and by separately examining coding and non-coding sequences, we find that the relative height of the peak at f = 1/3 in the Fourier spectrum is a good discriminator of coding potential. This feature is utilized by us to detect probable coding regions in DNA sequences, by examining the local signal-to-noise ratio of the peak within a sliding window. While the overall accuracy is comparable to that of other techniques currently in use, the measure that is presently proposed is independent of training sets or existing database information, and can thus find general application. Availability: A computer program GeneScan which locates coding open reading frames and exonic regions in genomic sequences has been developed, and is available on request. Contact: E-mail: rama@jnuniv.emet.in.

/pdf/prediction-of-probable-genes-by-fourier-analysis-of-genomic-4zzq3jq387.pdf

Prediction of probable genes by Fourier analysis of genomic sequences

Adaptive control in a resource management model

The ultimate goal of molecular cell biology is to understand the physiology of living cells in terms of the information that is encoded in the genome of the cell – and we would like to address the question how computational biology can help in achieving this goal. Genes coding for proteins is a very important pattern recognition problem in bioinformatics and this lecture focuses on some computational issues in gene identification.

Gene identification in silico

We study the dynamics of a hamiltonian system with two degrees of freedom coupled to a Nose-Hoover thermostat. In the absence of the thermostat, the system is quasi-integrable: at low energies, most of the motion is on two-dimensional tori, while at higher energies, the motion is mainly chaotic. Upon coupling to the thermostat the system becomes more chaotic, as evidenced by the magnitude of the largest Lyapunov exponent. In contrast to the case of isotropic oscillator systems coupled to thermostats, there is no evidence for a regime of integrable behaviour, even for large values of Q.

Shrish Tiwari

Papers

Prediction of probable genes by Fourier analysis of genomic sequences

Adaptive control in a resource management model

Gene identification in silico

Nose-Hoover dynamics of a nonintegrable hamiltonian system