An application of the theoretical group methods to modeling of complex systems

The applicability of theoretical group methods to studying complex physical and biological systems with the potential of self-organization was demonstrated. The problem of calculating climate sensitivity parameters taking into account the cyclone-anticyclone structure of the atmosphere optically dense in the infrared region is considered as an example.     

Application of balancing methods in modeling the penicillin fermentation

This paper shows the application of elementary balancing methods in combination with simple kinetic equations in the formulation of an unstructured model for the fed-batch process for the production of penicillin. The rate of substrate uptake is modeled with a Monod-type relationship. The specific penicillin production rate is assumed to be a function of growth rate. Hydrolysis of penicillin to penicilloic acid is assumed to be first order in penicillin. In simulations with the present model it is shown that the model, although assuming a strict relationship between specific growth rate and penicillin productivity, allows for the commonly observed lag phase in the penicillin concentration curve and the apparent separation between growth and production phase (idiophase-trophophase concept). Furthermore it is shown that the feed rate profile during fermentation is of vital importance in the realization of a high production rate throughout the duration of the fermentation. It is emphasized that the method of modeling presented may also prove rewarding for an analysis of fermentation processes other than the penicillin fermentation.     

The semiotics of control and modeling relations in complex systems

We provide a conceptual analysis of ideas and principles from the systems theory discourse which underlie Pattee's semantic or semiotic closure, which is itself foundational for a school of theoretical biology derived from systems theory and cybernetics, and is now being related to biological semiotics and explicated in the relational biological school of Rashevsky and Rosen. Atomic control systems and models are described as the canonical forms of semiotic organization, sharing measurement relations, but differing topologically in that control systems are circularly and models linearly related to their environments. Computation in control systems is introduced, motivating hierarchical decomposition, hybrid modeling and control systems, and anticipatory or model-based control. The semiotic relations in complex control systems are described in terms of relational constraints, and rules and laws are distinguished as contingent and necessary functional entailments, respectively. Finally, selection as a meta-level of constraint is introduced as the necessary condition for semantic relations in control systems and models.     

On the theoretical and experimental modeling of initial stages of metabolism formation in prebiotic systems

A concept of the initial stages of chemical prebiotic evolution, which eliminates a number of difficulties in the problem of the origin of life and permits experimental verification, is proposed. According to this concept, a predecessor of living beings has to be sufficiently simple to allow its self-assembly during a geologically short time period. In addition, the predecessor has to possess autocatalytic properties, and an ability for further complication (evolution). A possible scenario of the initial steps of the origin of life in nature and inside an experimental facility is considered. In the scope of the scenario the model of a multivariant oligomeric autocatalyst coupled with phase-separated particles is described. Results of computational simulations of possible initial steps in chemical evolution are presented. The estimates obtained show that the emergence of autocatalytic oligomeric phase-separated systems is possible at reasonable values of kinetics parameters of involved chemical reactions in a small-scale flow reactor.     

Validation of semiempirical methods for modeling of corrinoid systems

Several semiempirical methods (MNDO-d, PM3tm, PM3-d, PM5, PM6, and AM1-d) have been tested against experimental data and density functional theory (DFT) results in search for the best methods that can be used for quantum-mechanical-molecular mechanics (QM/MM) modeling of corrinoid systems of vitamin B(12) co-factor. It has been found that the PM6 parametrization in its present form gives results closest to hybrid DFT calculations that are most widely used thus far. In comparison with pure DFT and experimental data the best agreement is obtained for PM3tm parametrization, while PM6 yields slightly worse results. AM1-d yields bad geometry of the corrin moiety. The worst performance was observed for MNDO-d, which has severe problem with position and orientation of the alpha-ligands.     

Application of theoretical methods to increase succinate production in engineered strains

Computational methods have enabled the discovery of non-intuitive strategies to enhance the production of a variety of target molecules. In the case of succinate production, reviews covering the topic have not yet analyzed the impact and future potential that such methods may have. In this work, we review the application of computational methods to the production of succinic acid. We found that while a total of 26 theoretical studies were published between 2002 and 2016, only 10 studies reported the successful experimental implementation of any kind of theoretical knowledge. None of the experimental studies reported an exact application of the computational predictions. However, the combination of computational analysis with complementary strategies, such as directed evolution and comparative genome analysis, serves as a proof of concept and demonstrates that successful metabolic engineering can be guided by rational computational methods.

     

Wave-separation in complex systems. Application to brain-signals

A departure from single-system dynamics, that may arise in characterizing self-organized dynamics of complex systems, is dealt with by using the Karhunen-Loève expansion of the trajectory matrix to decompose an experimental signal in a sum of spectral features. For an electroencephalographic -signal, a separation of waves and extraction of additive sub-signals are achieved, each sub-signal covering a well-bounded and physiologically meaningful frequency range. From the subsignals, an attractor that vanishes on phase-randomizing the data is characterized, under conditions where none was found for the recorded signal.     

Some nonstandard modeling techniques in theoretical biology

Three topics are surveyed. (1) The quasisteady-state assumption is a fundamental example of frequent instances in theoretical biology where advantage can be taken of the simultaneous existence of widely separated time scales. It is shown that appropriate scaling can provide a markedly sharper estimate of the range of validity of this approximation. (2) A new methodology for modelling dynamically changing networks is applied to simple morphogenesis in fungal colonies. A brief discussion is given of possible application to the complex polymerization and cross-linking that characterize cytoplasmic fibers. (3) It is shown that problems in ecology and immunology can be illuminated by considering nonlocal interactions (and hence integrodifferential equations) that generate patterns in “aspect space” or “shape space.”     

Graph theoretical analysis of complex networks in the brain

Since the discovery of small-world and scale-free networks the study of complex systems from a network perspective has taken an enormous flight. In recent years many important properties of complex networks have been delineated. In particular, significant progress has been made in understanding the relationship between the structural properties of networks and the nature of dynamics taking place on these networks. For instance, the 'synchronizability' of complex networks of coupled oscillators can be determined by graph spectral analysis. These developments in the theory of complex networks have inspired new applications in the field of neuroscience. Graph analysis has been used in the study of models of neural networks, anatomical connectivity, and functional connectivity based upon fMRI, EEG and MEG. These studies suggest that the human brain can be modelled as a complex network, and may have a small-world structure both at the level of anatomical as well as functional connectivity. This small-world structure is hypothesized to reflect an optimal situation associated with rapid synchronization and information transfer, minimal wiring costs, as well as a balance between local processing and global integration. The topological structure of functional networks is probably restrained by genetic and anatomical factors, but can be modified during tasks. There is also increasing evidence that various types of brain disease such as Alzheimer's disease, schizophrenia, brain tumours and epilepsy may be associated with deviations of the functional network topology from the optimal small-world pattern.     

Analysis and modeling of mycolyl-transferases in the CMN group

Mycolyl-transferases are a family of proteins that are specifically present in the CMN (Corynebacterium, Mycobacterium and Nocardia) genera and are responsible for the synthesis of cell wall components. We modeled the three-dimensional structures of mycolyl-transfersases from Corynebacterium and Nocardia using homology modeling methods based on the crystal structures of mycolyl-transferases from M. tuberculosis. Comparison of the models revealed significant differences in their substrate binding site. Some mycolyl-transferases identified by the following Gene Ids: Nfa25110, Nfa45560, Nfa7210, Nfa38260, Nfa32420, Nfa23770, Nfa43800, Nfa30260, Dip0365, Ncgl0987, Ce1488, Ncgl0885, Ce0984, Ncgl2101, Ncgl0336, Ce0356 are associated with a relatively larger substrate binding site and amino acid residue mutations (D40N, R43D/G, S236N/A) are likely to affect binding to trehalose.     

Cause-effect modeling as a general method of description and study of phenomena in complex hierarchical systems

The definition of the cause-effect model of a phenomenon and the rules of presenting these models in the form of cause-effect diagrams have been formulated. The relationship between cause-effect modeling and traditional methods of mathematical modeling has been analyzed. Examples of cause-effect models (diagrams) of phenomena of different physical nature are given, and the application of these models in studies of some problems is demonstrated. In particular, the mechanism of renormalizing the rate constans of chemical reactions in terms of dissipative resonance is considered. In addition, the renormalization of the climate sensitivity parameters and the relaxation time of the Earth climate system in terms of the two-component (CO2 + H2O) greenhouse effect is considered.     

Experimental and theoretical study of energetics of complex formation between nucleic acid bases and the bases with amide group.

A number of nucleic acid base pairs and complexes between the bases and the amide group of acrylamide have been studied experimentally by using mass spectrometry and theoretically by the method of atom-atom potential function calculations. It has been found from temperature dependencies of peak intensities in mass spectra of m2.2.9(3) Gua.m1Ura, m9 Ade.m1Cyt, m2.2.9(3) Gua.m1Gua.m1Cyt pairs that enthalpy values, delta H, of the complex formation are equal to 14.2 +/- 1.1, 13.5 +/- 1.3 and 16.4 +/- 1.4 kcal/M, respectively, and those of acrylamide with m1.3(2) Ura and m1Thy corresponds to 9.7 +/- 1.0 and 6.8 +/- 0.6 kcal/M. There is a good agreement of the experimental data with calculations when taking into account both the amino-oxo and the amino-hydroxy tautomeric forms of guanine. A combined use of the data allows us to determine the energy, the modes of interaction and the structure of the complexes. The results are discussed in connection with the modelling of molecular structure of biopolymers by the method of classical potential functions, protein-nucleic acids recognition and fidelity of nucleic acids biosynthesis.     

Cause-effect modeling as a general method for describing and studying phenomena in complex hierarchical systems

A strict definition of a cause-effect model of a complex phenomenon is given, and the rules for presenting such models in the form of cause-effect diagrams are formulated. The relationship between the cause-effect modeling and conventional methods of mathematical modeling is analyzed. Examples of the cause-effect models (diagrams) of phenomena of various physical nature are presented, and the application of these models to some specific problems is shown. In particular, the mechanism of renormalizing the rate constants of chemical reactions is considered in terms of dissipative resonance. An example of renormalizing the parameters of climate sensitivity and the relaxation time of the Earth’s climatic system in terms of a two-component (CO₂ + H₂O) greenhouse effect is considered.     

Dynamic modeling of complex biological systems: a link between metabolic and macroscopic description

In this study, a class of dynamic models based on metabolic reaction pathways is analyzed, showing that systems with complex intracellular reaction networks can be represented by macroscopic reactions relating extracellular components only. Based on rigorous assumptions, the model reduction procedure is systematic and allows an equivalent 'input-output' representation of the system to be derived. The procedure is illustrated with a few examples.     

Molecular modeling study of the norfloxacin-DNA complex

Molecular modeling and molecular dynamics were performed to investigate the interaction of norfloxacin with the DNA oligonucleotide 5'-d(ATACGTAT)(2). Eight quinolone-DNA binding structures were built by molecular modeling on the basis of experimental results. A 100ps molecular dynamics calculation was carried out on two groove binding models and six partially intercalating models. The resulting average structures were compared with each other and to free DNA structure as a reference. The favorable binding mode of norfloxacin to a DNA substrate was pursued by structural assess including steric hindrance, presence of hydrogen-bonding, non-bonding energies of the complex and presence of abnormal structural distortion. Although two of the intercalative models showed the highest binding energy and the lowest non-bonding interaction energy, they presented structural features which contrast with experimental results. On the other hand, one groove binding model demonstrated the most acceptable structure when the experimental observation was accounted. In this model, hydrogen bonding of the carbonyl and carboxyl group of the norfloxacin rings with the DNA bases was present, and norfloxacin binds to the amine group of the guanine base which protrudes toward the minor groove of B-DNA.