Visual Molecular Dynamics Investigations of the Impact of Hydrophobic Nanoparticles on Prognosis of Alzheimer’s Disease and Cancers

The possible impact of hydrophobic lectin nanoparticles on the prognosis and progression of Alzheimer's disease (AD) and cancers was investigated by Visual Molecular Dynamics (VMD) computer modeling programs available from the Beckmann Advanced Research Institute at the University of Illinois at Urbana. Our results indicate the possibility of impeding pathological aggregation of certain proteins such as modified tau- or beta-amyloid that are currently being considered as possible causes of Alzheimer's disease. VMD programs serve as useful tools for investigation hydrophobic protein aggregation that may play a role in aging of human populations

Novel Techniques and Their Applications to Health Foods, Agricultural and Medical Biotechnology: Functional Genomics and Basic Epigenetic Controls in Plant and Animal Cells

Selected applications of novel techniques for analyzing Health Food formulations, as well as for advanced investigations in Agricultural and Medical Biotechnology aimed at defining the multiple connections between functional genomics and epigenomic, fundamental control mechanisms in both animal and plant cells are being reviewed with the aim of unraveling future developments and policy changes that are likely to open new niches for Biotechnology and prevent the shrinking or closing of existing markets. Amongst the selected novel techniques with applications in both Agricultural and Medical Biotechnology are: immobilized bacterial cells and enzymes, microencapsulation and liposome production, genetic manipulation of microorganisms, development of novel vaccines from plants, epigenomics of mammalian cells and organisms, and biocomputational tools for molecular modeling related to disease and Bioinformatics. Both fundamental and applied aspects of the emerging new techniques are being discussed in relation to their anticipated, marked impact on future markets and present policy changes that are needed for success in either Agricultural or Medical Biotechnology. The novel techniques are illustrated with figures presenting the most important features of representative and powerful tools which are currently being developed for both immediate and long term applications in Agriculture, Health Food formulation and production, pharmaceuticals and Medicine. The research aspects are naturally emphasized in our review as they are key to further developments in Biotechnology; however, the course adopted for the implementation of biotechnological applications, and the policies associated with biotechnological applications are clearly the determining factors for future Biotechnology successes, be they pharmaceutical, medical or agricultural

Complex Biological Systems Analysis of Cell Cycling Models in Carcinogenesis: I. The essential roles of modifications in the c-Myc, TP53/p53, p27 and hTERT modules in Cancer Initiation and Progression

A new approach to the integration of results from a modular, complex biological systems analysis of nonlinear dynamics in cell cycling network transformations that are leading to carcinogenesis is proposed. Carcinogenesis is a complex process that involves dynamically inter-connected biomolecules in the intercellular, membrane, cytosolic, nuclear and nucleolar compartments that form numerous inter-related pathways referred to as networks. One such network module contains the cell cyclins whose functions are essential to cell cycling and division. Cyclins are proteins that also link to several critical pro-apoptotic and other cell cycling/division components, such as: c-Myc, p27, the tumor suppressor gene TP53 and its product-- the p53 protein with key roles in controlling DNA repair, inducing apoptosis and activating p21 (which can depress cell cyclins if activated), mdm2(with its biosynthesis activated by p53 and also, in its turn, inhibiting p53), p21, the Thomsen-Friedenreich antigen(T- antigen),Rb,Bax, Bad and Bcl-2. These key network components were reported to play major roles in the carcinogenesis of many types of cancer. Our novel theoretical analysis is based on recently published studies of intra-cellular cyclin signaling, with special emphasis being placed on the roles of cyclins D1 and E. This novel analysis suggests strategies for successful clinical trials and rational therapies of cancer through re-establishment of the cell cycling inhibition in metastatic cancer cells. Cyclins are proteins that are often found to be over-expressed in cancerous cells (Dobashi et al., 2004). Cyclin-dependent kinases (CDK), their respective cyclins, and inhibitors of CDKs (CKIs) were identified as central, highly-connected components of the cell cycle-regulating machinery. In mammalian cells the complexes of cyclins D1, D2, D3, A and E with CDKs are considered to be the 'motors that drive' cells to enter and pass through the G2 to the S and M phases of the cell cycle. Specific cell cycle regulation mechanisms determine both the cell division and tissue proliferation; thus the cell cycle was reported to be finely regulated by the interactions of cyclins with CDKs and CKIs, among other molecules (Morgan et al., 1995), such as p27 and p21 that when activated are capable of deppressing or completely inhibiting the cell cycling. The Genetic database I (DSI, Paris, France) sequence for Cyclin-D1 can be found and downloaded at the PDB website:=http://www.dsi.univ-paris5.fr/genatlas/fiche.php?symbol=CCND1. The signaling pathways in cells that are thought to be involved in Carcinogenesis in humans and mice are extensively, but not completely, documented at the CGAP website supported by the National Cancer Institute(NCI)of the NIH in the USA. Extensive tumor genomics data sets are also available at this CGAP web site and also at several other web sites supported in the USA by NCI, such as those of the existing National Integrative Complex Systems Cancer Biology Program and the Fred Hutchinson Cancer Center. Urgent progress with Proteomics and Cell Interactomics high-quality, high throughput/ high-speed data acquisition for separated, human tumor cell lines is needed in order to design and implement rational, individualized cancer therapy strategies and successful clinical trials at Cancer Centers

Quantum Interactomics and Cancer Molecular Mechanisms: I. Report Outline

Single cell interactomics in simpler organisms, as well as somatic cell interactomics in multicellular organisms, involve biomolecular interactions in complex signalling pathways that were recently represented in modular terms by quantum automata with ‘reversible behavior’ representing normal cell cycling and division. Other implications of such quantum automata, modular modeling of signaling pathways and cell differentiation during development are in the fields of neural plasticity and brain development leading to quantum-weave dynamic patterns and specific molecular processes underlying extensive memory, learning, anticipation mechanisms and the emergence of human consciousness during the early brain development in children. Cell interactomics is here represented for the first time as a mixture of ‘classical’ states that determine molecular dynamics subject to Boltzmann statistics and ‘steady-state’, metabolic (multi-stable) manifolds, together with ‘configuration’ spaces of metastable quantum states emerging from complex quantum dynamics of interacting networks of biomolecules, such as proteins and nucleic acids that are now collectively defined as quantum interactomics. On the other hand, the time dependent evolution over several generations of cancer cells --that are generally known to undergo frequent and extensive genetic mutations and, indeed, suffer genomic transformations at the chromosome level (such as extensive chromosomal aberrations found in many colon cancers)-- cannot be correctly represented in the ‘standard’ terms of quantum automaton modules, as the normal somatic cells can. This significant difference at the cancer cell genomic level is therefore reflected in major changes in cancer cell interactomics often from one cancer cell ‘cycle’ to the next, and thus it requires substantial changes in the modeling strategies, mathematical tools and experimental designs aimed at understanding cancer mechanisms. Novel solutions to this important problem in carcinogenesis are proposed and experimental validation procedures are suggested. From a medical research and clinical standpoint, this approach has important consequences for addressing and preventing the development of cancer resistance to medical therapy in ongoing clinical trials involving stage III cancer patients, as well as improving the designs of future clinical trials for cancer treatments. *Communicated to: The Institute of Genomic Biology (currently under construction at UIUC, at 905 S. Goodwin Avenue, Urbana,IL.61801,USA). KEYWORDS: Cancer cell interactomics; Somatic cell genomics and Proteomics; current limitations of modular models of carcinogenesis; Complex quantum dynamics; Quantum Automata models and Quantum Interactomics; quantum-weave dynamic patterns underlying human consciousness; specific molecular processes underlying extensive memory, learning, anticipation mechanisms and human consciousness; emergence of human consciousness during the early brain development in children; Cancer cell ‘cycling’; interacting networks of proteins and nucleic acids; genetic mutations and chromosomal aberrations in cancers, such as colon cancer; development of cancer resistance to therapy; ongoing clinical trials involving stage III cancer patients’ possible improvements of the designs for future clinical trials and cancer treatments

Cell Interactomics and Carcinogenetic Mechanisms

Single cell interactomics in simpler organisms, as well as somatic cell interactomics in multicellular organisms, involve biomolecular interactions in complex signalling pathways that were recently represented in modular terms by quantum automata with ‘reversible behavior’ representing normal cell cycling and division. Other implications of such quantum automata, modular modeling of signaling pathways and cell differentiation during development are in the fields of neural plasticity and brain development leading to quantum-weave dynamic patterns and specific molecular processes underlying extensive memory, learning, anticipation mechanisms and the emergence of human consciousness during the early brain development in children. Cell interactomics is here represented for the first time as a mixture of ‘classical’ states that determine molecular dynamics subject to Boltzmann statistics and ‘steady-state’, metabolic (multi-stable) manifolds, together with ‘configuration’ spaces of metastable quantum states emerging from complex quantum dynamics of interacting networks of biomolecules, such as proteins and nucleic acids that are now collectively defined as quantum interactomics. On the other hand, the time dependent evolution over several generations of cancer cells --that are generally known to undergo frequent and extensive genetic mutations and, indeed, suffer genomic transformations at the chromosome level (such as extensive chromosomal aberrations found in many colon cancers)-- cannot be correctly represented in the ‘standard’ terms of quantum automaton modules, as the normal somatic cells can. This significant difference at the cancer cell genomic level is therefore reflected in major changes in cancer cell interactomics often from one cancer cell ‘cycle’ to the next, and thus it requires substantial changes in the modeling strategies, mathematical tools and experimental designs aimed at understanding cancer mechanisms. Novel solutions to this important problem in carcinogenesis are proposed and experimental validation procedures are suggested. From a medical research and clinical standpoint, this approach has important consequences for addressing and preventing the development of cancer resistance to medical therapy in ongoing clinical trials involving stage III cancer patients, as well as improving the designs of future clinical trials for cancer treatments