Chemistry Reference
In-Depth Information
nn(C, G)
=
110
+
150
=
260
=
7
×
037
+
1,
(10.49)
nn(U)
=
111
=
3
×
037;
(10.50)
many analogues combinations involve 0mod037 and 1mod037 as the binary 0&1
pairs (suitable for information computing) so controlling the forming of biomolecules
by blocks
chains analogue rules (Shcherbak
2003
). It appears therefore that cellular
structure and evolution, so accustomed with information terms such as self-similarity,
coding, copying, transcription, sequence, etc. (Hameroff and Penrose
2003
) are
indeed the major playground for any chemical bonding theory seeking verifiable
predictions. In this context, what is among the forefront interest for applicative
science in environmental, population protection and health safety (EC
2006
,EU
2008
) regards the green determination of the 50 %-effective concentration (
EC
50
)
dose of a given chemical compound targeting biological/toxicological activity
+
A
=
ln (1
/EC
50
)
(10.51)
for certain species, according with Organisation for Economic Co-operation and
Development (OECD
2005
).
While this aim is in general assigned to “classical” statistical computational task,
involving high throughput tedious screenings among large (under developing unified
international) databases, including those of European Joint Research Center (OECD
QSAR Toolbox
2012
), eventually involving the celebrated quantitative structure-
activity relationships (QSAR) analysis (OECD
2007
, Putz
2012d
).
The present project proposes the alternative determination of
EC
50
by using the
bondonic de-coding information for a molecule as it would pass a cellular hydropho-
bic wall targeting a specific organismal receptor. This can be done once realizing that
the molecules during the transduction of the cellular walls suffer selective bonding
breakages (Putz and Dudas
2013a
,
b
), according to their simplified molecular-input
line-entry system = SMILES form (Weininger
1988
; Drefahl
2011
), see Fig.
10.3
a;
worth noting that SMILES formalism avoids double and superior bonding breakage,
in accordance with the actual bonding prescriptions of Table
10.1
since associated
with smaller bondonic mass and life-time, i.e. bearing more photonic nature than the
bondon of the single carbon bonding.
Accordingly, the counting of breaking bonds in SMILES passages through cellu-
lar walls by detecting the maximum output of bondons (e.g. from LoSMoC to BraS
molecular forms in Fig.
10.3
a) would correspond with the ligand-receptor satura-
tion kinetics or maximum uptake (
β
max
): it eventually provides the direct reading of
the so formed q-
EC
50
by appropriately fitting with the hyperbolic kinetics, e.g. of
Michaelis-Menten type (Putz and Putz
2013
), as illustrated in Fig.
10.3
b for the ob-
served bondons “emitted” from the chemical systems on/from a surface mimicking
the cellular walls. This way, the main third objective of the actual project states as:
ENTA-QUA-CHEM-3:
DETERMINING QUANTUM CHEMICAL-BIOLOGICAL
GREEN MEASURE OF 50 % EFFECTIVE CONCENTRATION (q-EC
50
)OFA
CHEMICAL COMPOUND TRANSDUCTING SPECIFIC CELLULAR LIPIDIC
WALLS.
