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12 Consensus Drug Design Using IT Microcosm
there is a statistically highly significant dependence between the synergistic effect
of antidiabetic drug combinations and the metric of membership of these compounds in the hypoglycemic compound class calculated by IT Microcosm.
Thus, IT Microcosm permits pinpoint accuracy for predicting the presence and levels of various pharmacological activities of complex organic compound mixtures
with inclusion of the component synergism. This allows an optimisation of the qualitative and quantitative composition of the mixtures, which can lead to the design
of novel, powerful drugs based on several gently acting, nontoxic compounds and
several synergistic admixtures potentiating their effects.
Particular emphasis should be given to the fact that the successful prediction of
mixture activity, including prediction with the inclusion of the synergistic effects,
was performed on training sets comprising individual compounds only. For this purpose, a special toolkit for processing complex mixtures of up to 9999 components in
ratios of 1 to 9999 mol fraction of each substance was developed in IT Microcosm.
The results obtained indicate that IT Microcosm permits a prediction of the presence and level of the various pharmacological activity types of complex molecular
systems with consideration paid to the mutual effect of their components and optimisation of their quantitative and qualitative composition. This makes the technology helpful in designing novel, powerful drugs with minimal side effects.
12.6 Conclusions
The results of the computational and experimental studies described above indicate
that the complex methodology of IT Microcosm for predicting the pharmacological
activity of organic compounds, which includes consensus methods of constructing
integral prediction regularities, is a universal, highly effective tool that solves most
of the diverse problems associated with the search for novel drugs. The technology
makes it possible to predict the presence and level of various types of pharmacological activity of structurally diverse and structurally similar compounds in various
chemical classes (including chiral compounds) and to perform a directed search
for highly active substances with predetermined properties. The possibility to consider noncovalent interactions provides a successful prediction of the spectrum and
level of pharmacological activity. It also enables optimisation of the qualitative and
quantitative composition of complex molecular systems, such as organic salts, supramolecular complexes and mixtures of individual compounds, with account of
the mutual effect of the constituent components and of their synergism. This enables
the design of novel, multicomponent drugs showing powerful beneficial effects and
minimal side effects, on the basis of nontoxic, gently acting compounds and synergistic admixtures that potentiate their action.
The precision of search for highly active drug substances in IT Microcosm exceeds the precision of noncomputerized “intuitive” prediction performed by quali-
12 Consensus Drug Design Using IT Microcosm
there is a statistically highly significant dependence between the synergistic effect
of antidiabetic drug combinations and the metric of membership of these compounds in the hypoglycemic compound class calculated by IT Microcosm.
Thus, IT Microcosm permits pinpoint accuracy for predicting the presence and levels of various pharmacological activities of complex organic compound mixtures
with inclusion of the component synergism. This allows an optimisation of the qualitative and quantitative composition of the mixtures, which can lead to the design
of novel, powerful drugs based on several gently acting, nontoxic compounds and
several synergistic admixtures potentiating their effects.
Particular emphasis should be given to the fact that the successful prediction of
mixture activity, including prediction with the inclusion of the synergistic effects,
was performed on training sets comprising individual compounds only. For this purpose, a special toolkit for processing complex mixtures of up to 9999 components in
ratios of 1 to 9999 mol fraction of each substance was developed in IT Microcosm.
The results obtained indicate that IT Microcosm permits a prediction of the presence and level of the various pharmacological activity types of complex molecular
systems with consideration paid to the mutual effect of their components and optimisation of their quantitative and qualitative composition. This makes the technology helpful in designing novel, powerful drugs with minimal side effects.
12.6 Conclusions
The results of the computational and experimental studies described above indicate
that the complex methodology of IT Microcosm for predicting the pharmacological
activity of organic compounds, which includes consensus methods of constructing
integral prediction regularities, is a universal, highly effective tool that solves most
of the diverse problems associated with the search for novel drugs. The technology
makes it possible to predict the presence and level of various types of pharmacological activity of structurally diverse and structurally similar compounds in various
chemical classes (including chiral compounds) and to perform a directed search
for highly active substances with predetermined properties. The possibility to consider noncovalent interactions provides a successful prediction of the spectrum and
level of pharmacological activity. It also enables optimisation of the qualitative and
quantitative composition of complex molecular systems, such as organic salts, supramolecular complexes and mixtures of individual compounds, with account of
the mutual effect of the constituent components and of their synergism. This enables
the design of novel, multicomponent drugs showing powerful beneficial effects and
minimal side effects, on the basis of nontoxic, gently acting compounds and synergistic admixtures that potentiate their action.
The precision of search for highly active drug substances in IT Microcosm exceeds the precision of noncomputerized “intuitive” prediction performed by quali-