Sequence specific recognition and cleavage of DNA by synthetic molecules

DNA recognition is an essential biological process responsible for the regulation of cellular functions including protein synthesis and cell division and is implicated in the mechanism of action of some anticancer drugs. Studies directed towards defining the elements responsible for sequence specific DNA recognition through the study of the interactions of synthetic organic ligands with DNA are described.

DNA recognition by poly-N-methylpyrrolecarboxamides was studied by the synthesis and characterization of a series of molecules where the number of contiguous N-methylpyrrolecarboxamide units was increased from 2 to 9. The effect of this incremental change in structure on DNA recognition has been investigated at base pair resolution using affinity cleaving and MPE•Fe(II) footprinting techniques. These studies led to a quantitative relationship between the number of amides in the molecule and the DNA binding site size. This relationship is called the n + 1 rule and it states that a poly-N methylpyrrolecarboxamide molecule with n amides will bind n + 1 base pairs of DNA. This rule is consistent with a model where the carboxamides of these compounds form three center bridging hydrogen bonds between adjacent base pairs on opposite strands of the helix. The poly-N methylpyrrolecarboxamide recognition element was found to preferentially bind poly dA•poly dT stretches; however, both binding site selection and orientation were found to be affected by flanking sequences. Cleavage of large DNA is also described.

One approach towards the design of molecules that bind large sequences of double helical DNA sequence specifically is to couple DNA binding subunits of similar or diverse base pair specificity. Bis-EDTA-distamycin-fumaramide (BEDF) is an octaamide dimer of two tri-N methylpyrrolecarboxamide subunits linked by fumaramide. DNA recognition by BEDF was compared to P7E, an octaamide molecule containing seven consecutive pyrroles. These two compounds were found to recognize the same sites on pBR322 with approximately the same affinities demonstrating that fumaramide is an effective linking element for Nmethylpyrrolecarboxamide recognition subunits. Further studies involved the synthesis and characterization of a trimer of tetra-N-methylpyrrolecarboxamide subunits linked by β-alanine ((P4)_(3)E). This trimerization produced a molecule which is capable of recognizing 16 base pairs of A•T DNA, more than a turn and a half of the DNA helix.

DNA footprinting is a powerful direct method for determining the binding sites of proteins and small molecules on heterogeneous DNA. It was found that attachment of EDTA•Fe(II) to spermine creates a molecule, SE•Fe(II), which binds and cleaves DNA sequence neutrally. This lack of specificity provides evidence that at the nucleotide level polyamines recognize heterogeneous DNA independent of sequence and allows SE•Fe(II) to be used as a footprinting reagent. SE•Fe(II) was compared with two other small molecule footprinting reagents, EDTA•Fe(II) and MPE•Fe(II).

Proton magnetic resonance studies of ribonucleic acid complexes. I. Complexes of biological bases and oligonucleotides with RNA. II. Template recognition and the degeneracy of the genetic code

Part I. Complexes of Biological Bases and Oligonucleotides with RNA

The physical nature of complexes of several biological bases and oligonucleotides with single-stranded ribonucleic acids have been studied by high resolution proton magnetic resonance spectroscopy. The importance of various forces in the stabilization of these complexes is also discussed.

Previous work has shown that purine forms an intercalated complex with single-stranded nucleic acids. This complex formation led to severe and stereospecific broadening of the purine resonances. From the field dependence of the linewidths, T₁ measurements of the purine protons and nuclear Overhauser enhancement experiments, the mechanism for the line broadening was ascertained to be dipole-dipole interactions between the purine protons and the ribose protons of the nucleic acid.

The interactions of ethidium bromide (EB) with several RNA residues have been studied. EB forms vertically stacked aggregates with itself as well as with uridine, 3'-uridine monophosphate and 5'-uridine monophosphate and forms an intercalated complex with uridylyl (3' → 5') uridine and polyuridylic acid (poly U). The geometry of EB in the intercalated complex has also been determined.

The effect of chain length of oligo-A-nucleotides on their mode of interaction with poly U in D₂0 at neutral pD have also been studied. Below room temperatures, ApA and ApApA form a rigid triple-stranded complex involving a stoichiometry of one adenine to two uracil bases, presumably via specific adenine-uracil base pairing and cooperative base stacking of the adenine bases. While no evidence was obtained for the interaction of ApA with poly U above room temperature, ApApA exhibited complex formation of a 1:1 nature with poly U by forming Watson-Crick base pairs. The thermodynamics of these systems are discussed.

Part II. Template Recognition and the Degeneracy of the Genetic Code

The interaction of ApApG and poly U was studied as a model system for the codon-anticodon interaction of tRNA and mRNA in vivo. ApApG was shown to interact with poly U below ~20°C. The interaction was of a 1:1 nature which exhibited the Hoogsteen bonding scheme. The three bases of ApApG are in an anti conformation and the guanosine base appears to be in the lactim tautomeric form in the complex.

Due to the inadequacies of previous models for the degeneracy of the genetic code in explaining the observed interactions of ApApG with poly U, the "tautomeric doublet" model is proposed as a possible explanation of the degenerate interactions of tRNA with mRNA during protein synthesis in vivo.

Live 3D shape reconstruction, recognition and registration

We present a video-based system which interactively captures the geometry of a 3D object in the form of a point cloud, then recognizes and registers known objects in this point cloud in a matter of seconds (fig. 1). In order to achieve interactive speed, we exploit both efficient inference algorithms and parallel computation, often on a GPU. The system can be broken down into two distinct phases: geometry capture, and object inference. We now discuss these in further detail. © 2011 IEEE.

A new distance for scale-invariant 3D shape recognition and registration

This paper presents a method for vote-based 3D shape recognition and registration, in particular using mean shift on 3D pose votes in the space of direct similarity transforms for the first time. We introduce a new distance between poses in this spacethe SRT distance. It is left-invariant, unlike Euclidean distance, and has a unique, closed-form mean, in contrast to Riemannian distance, so is fast to compute. We demonstrate improved performance over the state of the art in both recognition and registration on a real and challenging dataset, by comparing our distance with others in a mean shift framework, as well as with the commonly used Hough voting approach. © 2011 IEEE.

Scale-invariant vote-based 3D recognition and registration from point clouds

This chapter presents a method for vote-based 3D shape recognition and registration, in particular using mean shift on 3D pose votes in the space of direct similarity transformations for the first time. We introduce a new distance between poses in this spacethe SRT distance. It is left-invariant, unlike Euclidean distance, and has a unique, closed-form mean, in contrast to Riemannian distance, so is fast to compute. We demonstrate improved performance over the state of the art in both recognition and registration on a (real and) challenging dataset, by comparing our distance with others in a mean shift framework, as well as with the commonly used Hough voting approach. © 2013 Springer-Verlag Berlin Heidelberg.

Cancer subtypes recognition and its gene expression profiles analysis based on geometrical learning

The accurate recognition of cancer subtypes is very significant in clinic. Especially, the DNA microarray gene expression technology is applied to diagnosing and recognizing cancer types. This paper proposed a method of that recognized cancer subtypes based on geometrical learning. Firstly, the cancer genes expression profiles data was pretreated and selected feature genes by conventional method; then the expression data of feature genes in the training samples was construed each convex hull in the high-dimensional space using training algorithm of geometrical learning, while the independent test set was tested by the recognition algorithm of geometrical learning. The method was applied to the human acute leukemia gene expression data. The accuracy rate reached to 100%. The experiments have proved its efficiency and feasibility.

A new development on ANN in China - Biomimetic pattern recognition and multi weight vector neurons

A new model of pattern recognition principles-Biomimetic Pattern Recognition, which is based on "matter cognition" instead of "matter classification", has been proposed. As a important means realizing Biomimetic Pattern Recognition, the mathematical model and analyzing method of ANN get breakthrough: a novel all-purpose mathematical model has been advanced, which can simulate all kinds of neuron architecture, including RBF and BP models. As the same time this model has been realized using hardware; the high-dimension space geometry method, a new means to analyzing ANN, has been researched.

A new development on ANN in China - Biomimetic pattern recognition and multi weight vector neurons

A new model of pattern recognition principles-Biomimetic Pattern Recognition, which is based on "matter cognition" instead of "matter classification", has been proposed. As a important means realizing Biomimetic Pattern Recognition, the mathematical model and analyzing method of ANN get breakthrough: a novel all-purpose mathematical model has been advanced, which can simulate all kinds of neuron architecture, including RBF and BP models. As the same time this model has been realized using hardware; the high-dimension space geometry method, a new means to analyzing ANN, has been researched.