Classification and prediction of carcinogenic and cytostatic properties of Metal(-oid) Ions from network patterns which apply to autocatalysis in biochemistry (Stoichiometric network analysis)

S. Fränzle, B. Markert,

International Graduate School Zittau; D 02763 Zittau, Germany

The aim is to understand control of cell replication by a thorough and provably reliable method of complexity reduction using stoichiometric network analysis (SNA; Clarke 1974). From this a prediction of novel cytostatic approaches (based on other central ions than Pt, Ga, Ti and the like) and systematic identification of suitable agents in the realm of bioinorganic chemistry is pursued. Methods: Fundamental patterns of autocatalytic cycles in both metalloproteins and replication/budding of entire cells are identified considering dynamic effects of carcinogenic and cytostatic agents on cell division and bioinorganic chemistry, respectively. As autocatalysis is essential for life with loss of replication control bringing about malignant tumours SNA method can be applied in a qualitative but reliable way making use of theorems which directly refer to behaviours of chemicals in biology. Investigation of chemical properties of appropriate (active) inorganic and organometal compounds and their capability to perturb or modify autocatalytic cycles then yields results pertinent to cell and cancer biology. Results: Most biochemical cycles both concerning metalloproteins and nucleic-acid-based processes including cell division belong to the 1B pattern. Both cytostatic and carcinogenic properties of metal species can be attributed to certain modes of interaction/biological autocatalysis which in turn can be inferred from trace element biochemistries straightforwardly. Conditions are given which cause a certain element or speciation form to behave either way (causing and fighting cancer, respectively), be it (putatively) essential elements (As, V, Cr, Ni) or e.g. cis-platinum. Phase shift rules for interference with some perturbent derived from the SNA classification allow to describe possible features of novel chemotherapeutics. Conclusions: It is feasible to use network dynamics theories and general criteria which by definition apply to all living systems together with chemical properties to estimate carcinogenic potentials and cytostatic activities for at least inorganic compounds. This predictive capacity is not limited to species which directly interact with DNA or RNA, respectively, because competition effects Ga(III) instead of Fe(III) in tumor enzymes) bring about grave consequences for autocatalytic systems too even if the replacing ion would work, too.

KEY WORDS: carcinogenic properties, cytostatic properties, same chemical species, stoichiometric network analysis, metal-based cytostatic agents, bioinorganic chemistry.

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Paper presented at the International Symposium on Predictive Oncology and Intervention Strategies; Paris, France; February 9 - 12, 2002; in the section on Metastasis.