Journal of Biosciences

Dynamical systems on graphs allow to describe multiple phenomena from different areas of Science. In particular, many complex systems in Ecology are studied by this approach. In this paper we analize the mathematical framework for the study of the structural stability of each stationary point, feasible or not, introducing a generalization for this concept, defined as Global Structural Stability. This approach would fit with the proper mathematical concept of structural stability, in which we find a full description of the complex dynamics on the phase space due to nonlinear dynamics. This fact can be analyzed as an informational field grounded in a global attractor whose structure can be completely characterized. These attractors are stable under perturbation and suppose the minimal structurally stable sets. We also study in detail, mathematically and computationally, the zones characterizing different levels of biodiversity in bipartite graphs describing mutualistic antagonistic systems of population dynamics. In particular, we investigate the dependence of the region of maximal biodiversity of a system on its connectivity matrix. On the other hand, as the network topology does not completely determine the robustness of the dynamics of a complex network, we study the correlation between structural stability and several graph measures. A systematic study on synthetic and biological graphs is presented, including 10 mutualistic networks of plants and seed-dispersal and 1000 random synthetic networks. We compare the role of centrality measures and modularity, concluding the importance of just cooperation strength among nodes when describing areas of maximal biodiversity. Indeed, we show that cooperation parameters are the central role for biodiversity while other measures act as secondary supporting functions. Author summaryWe introduce the concept of Global Structural Stability as a proper mathematical concept to fully understand biodiversity in some ecological systems. Our concept retakes the definitions in the classical works of R. Thom [1] and Andronov-Pontryagin [2]. Moreover, there exists a close relation between the structure of a complex network, described as a graph, and its associated dynamics. Mutualistic networks introduce cooperation links between two groups of species, as plant and pollinators or seed-dispersal. The understanding of organizational aspects leading to maximizing biodiversity is one of the more important research areas in Theoretical and Applied Ecology. In this work we introduce a systematic study on different graph measures in order to identify optimal organization for maximal biodiversity (defined as structural stability). Our results conclude that, for mutualistic systems, the strength in cooperation parameters are the core fact, i.e., cooperation is the real fact optimizing biodiversity among other possible structural configurations.

Biological systems, at all scales of organization from nucleic acids to ecosystems, are inherently complex and variable. Therefore mathematical models have become an essential tool in systems biology, linking the behavior of a system to the interaction between its components. Parameters in empirical mathematical models for biology must be determined using experimental data, a process called regression because the experimental data are noisy and incomplete. The term "regression" dates back to Galtons studies in the 1890s. Considering all this, biologists, therefore, use statistical analysis to detect signals from the system noise. Statistical analysis is at the core of most modern biology and many biological hypotheses, even deceptively. Regression analysis is used to demonstrate association among the variables believed to be biologically related and fit the model to give the best model. There are two types of regression, linear and nonlinear regression to determine the best fit of the model. In this manuscript, we perform a least squares error fit to different models and select the best fit model using the{chi} 2-test, and determine the p-value of the selected model to data that was collected when various doses of a drug were injected into three animals, and the change in blood pressure for each animal was recorded.

Glucocorticoids potently inhibit expression of many inflammatory mediators, and have been very widely used to treat both acute and chronic inflammatory diseases for more than seventy years. However, they can have several unwanted effects, amongst which immunosuppression is one of the most common. Here we investigated effects of the synthetic glucocorticoid dexamethasone on the responses of primary mouse bone marrow-derived macrophages to the pro-inflammatory agonist lipopolysaccharide (LPS). At the mRNA level, dexamethasone inhibited the LPS-induced expression of more than 100 genes that are involved in cell-intrinsic defence against viral pathogens. Expression of most of the corresponding proteins was also reduced by dexamethasone. This antiviral disarmament occurred at two distinct levels. First, dexamethasone strongly and dose-dependently inhibited the expression of the type I interferon IFN{beta} by LPS-activated macrophages. IFN{beta} mediates an autocrine positive feedback loop in LPS-treated macrophages, promoting the expression of antiviral genes and other interferon-stimulated genes. Hence reduction of IFN{beta} expression contributes to impaired expression of antiviral genes. Dexamethasone also acted downstream of IFN{beta} to inhibit expression of a subset of interferon-regulated genes. We tested a number of hypotheses based on previous publications, but found that no single mechanism could account for more than a small fraction of the broad suppressive impact of dexamethasone on macrophage type I interferon signaling, underlining the complexity of this pathway. Preliminary experiments indicated that dexamethasone exerted similar inhibitory effects on primary human monocyte-derived or alveolar macrophages.

T cell receptor (TCR) and B cell receptor (BCR) stimulation of T and B lymphocytes, by antigen presented on an antigen-presenting cell (APC) induces the formation of the immunological synapse (IS). IS formation is associated with an initial increase in cortical filamentous actin (F-actin) at the IS, followed by a decrease in F-actin density at the central region of the IS, which contains the secretory domain. This is followed by the convergence of secretion vesicles towards the centrosome, and the polarization of the centrosome to the IS. These reversible, cortical actin cytoskeleton reorganization processes occur during lytic granule secretion in cytotoxic T lymphocytes (CTL) and natural killer (NK) cells, proteolytic granules secretion in B lymphocytes and during cytokine-containing vesicle secretion in T-helper (Th) lymphocytes. In addition, several findings obtained in T and B lymphocytes forming IS show that actin cytoskeleton reorganization also occurs at the centrosomal area. F-actin reduction at the centrosomal area appears to be associated with centrosome polarization. In this chapter we deal with the analysis of centrosomal area F-actin reorganization, as well as the centrosome polarization analysis towards the IS.

Persistence is a state of bacterial dormancy where cells with low metabolic activity and growth rates are phenotypically tolerant to antibiotics and other cytotoxic substances. Given its obvious advantage to bacteria, several researchers have been looking for the genetic mechanism behind persistence. However, other authors argue that there is no such mechanism and that persistence results from inadvertent cell errors. In this case, the persistent population should decay according to a power-law with a particular exponent of -2. Studying persisters decay is, therefore, a valuable way to understand persistence. Here we simulated the fate of susceptible cells in laboratory experiments in the context of indirect resistance. Eventually, under indirect resistance, detoxifying drug-resistant cells save the persister cells that leave the dormant state and resume growth. The simulations presented here show that, by assuming a power-law decline, the exponent is close to -2, which is the expected value if persistence results from unintentional errors. Whether persisters are cells in a moribund state or, on the contrary, result from a genetic program, should impact the research of anti-persistent drugs. Author SummaryPersistence, a form of bacterial dormancy, was discovered in the early days of the antibiotic era. Thanks to dormancy, these cells often evade antibiotic therapy and the immune system. However, despite its clinical importance, this phenotypes nature is still under debate. Arguably, the prevailing view is that persistence is an evolved (selected for) bet-hedging mechanism to survive in the presence of cytotoxic agents such as antibiotics. In that case, the persister population should decay exponentially, although at a much slower pace than the non-persister population. A few authors recently advanced an alternative hypothesis: bacterial persistence results from many malfunctions and cell division errors. In this case, persistent populations should decay according to a power-law with exponent of -2, that is, according to 1/t2. Here we simulated the fate of susceptible bacterial cells in the presence of bactericidal antibiotics in the context of indirect resistance based on laboratory experiments performed earlier. By showing that the dynamics of persister cells is consistent with 1/t2, our results corroborate the hypothesis that the phenomenon of bacterial persistence is an accidental consequence of inadvertent cell problems and errors. If confirmed, this conclusion should impact the research strategies of anti-persistent drugs. O_QD"The following day, no one died. This fact, being absolutely contrary to lifes rules, provoked enormous and, in the circumstances, perfectly justifiable anxiety in peoples minds, for we have only to consider that in the entire forty volumes of universal history there is no mention, not even one exemplary case, of such a phenomenon ever having occurred..." Death with interruptions Jose Saramago (2005) Nobel Prize for Literature 1998 C_QD

What is the nature of the ageing process? What is the spore survival, that one would expect upon analysing a self-cross, in a wild fission yeast strain? Could this two research questions be, somehow, related? In this manuscript, I am describing some interesting observations obtained while studying fission yeast spore survival values upon genetic crosses. Early findings brought my attention into mainly studying self-crosses (intra-strain crosses in which any cell can be involved in by mating with a sibling cell). This study, yield some interesting findings. As a summary: 1) most fission yeast self-crosses do show low spore survival values; 2) clonally related strains show a high phenotypic variability in self-cross spore survival values; 3) differences in self-cross spore survival values can be detected when comparing zygotic and azygotic matings; 4) self-cross spore survival values are highly affected by environmental factors, mainly producing a reduction in the spore survival values; 5) self-cross spore survival values are "recovered" when cells are subjected to several rounds of meiotic divisions; 6) signs of correlation between spore survival and vegetative cell survival (prior to the entry into meiosis) have been observed in this study. All those observations, among others, are discussed as part of an epigenetic variability that exist in fission yeast populations. A cyclical behaviour, of this epigenetic variability it is proposed, defining an underlying ratchet-like epigenetic mechanisms acting in all cells. In this manuscript, I propose that this mechanism, is, indeed, the main cause of the ageing process.

Although honey bee responses to pathogens have been systematically described in the past decades, antiviral signalling pathways mechanisms are not thoroughly characterized. To decipher direct antiviral roles of an immune pathway, we firstly used the infectious clone of Israeli acute paralysis virus (IAPV) to screen 42 immune genes involved in mTOR, MAPK, Toll, Endocytosis, Jak-STAT pathway and homeobox protein, heat shock protein, as well as antimicrobial peptides (AMPs), and found that Toll pathway was a potential predominant immune pathway in Apis mellifera. Consistent with this, only dsRNA-PGRP-S2 treated A. mellifera significantly exhibited impaired activation of Toll pathway, promoting susceptibility to the IAPV infection. Finally, immunofluorescence results confirmed that the Toll pathway was initiated by peptidoglycan recognition protein S2 (PGRP-S2) interacting with Toll protein. Co-immunoprecipitation findings also further preliminarily confirmed PGRP-S2 directly interacting with viral capsid protein IAPV-VP3 to induce the activation of the Toll pathway in A. mellifera. These findings highlight that the Toll pathway is demanded efficient inhibitions of IAPV replication as a specific antiviral pathway in A. mellifera, and PGRP-S2, acting as a pattern recognition receptor, could be a new approach for control of the viral disease. Author summaryHoney bee viruses, particularly IAPV, had been implicated in the colony decline with a global distribution resulting in insufficient pollination services. However, little is known about the antiviral mechanism of honey bee. In this study, we found that the Toll pathway was required for A. mellifera against IAPV infection and initiated by PGRP-S2. We also confirmed that dsRNA-PGRP-S2 treated A. mellifera exhibited impaired Toll pathway activation and promoted susceptibility to the IAPV infection. As a result, we employed co-immunoprecipitation technique to identify the interaction between the PGRP-S2 with Toll. Moreover, it was found the PGRP-S2 directly recognized IAPV-VP3 to activate the immune pathway against IAPV infection. Our work provides novel evidence that honey bees own a specific antiviral immune pathway and suggests that targeting PGRP-S2 could be a new approach for controlling the viral disease.

The immune system is one of the most complex biological systems in the body. During infection, the immune system is under attack by a large number of viruses, bacteria, fungi and parasites. Immune response firstly involves, recognition of the pathogen or foreign object and secondly, a reaction to eliminate it. Aqueous extract of Antiaris africana is used to study their immune modulator activity. This plant has its various parts used in folk medicines. The mechanism of action has not been fully elucidated. Therefore, this research work studies the effect of aqueous extract of Antiaris Africana stem bark on phagocytic activities of neutrophil isolated from apparently healthy individual using a non-subjective commercial colourimetric assay kit obtained from Cell-Biolab Inc., USA. The purity and viability of isolated neutrophils were >90% and >95% respectively. The extract enhances neutrophil phagocytosis at 1.0, 5.0, 10.0, 15.0, 20.0 and 25 g/ml by 2.5%, 11.6%, 18.4%, 24.4%, 31.2% and 38.2% respectively, compared to the control (100%). Hence, it was observed that neutrophil phagocytosis increases with increased extract concentrations. It can be concluded from the study that enhancement of phagocytosis may be the possible mechanism of action of the plant as an immune modulator.

Th1 and Th2 cytokines determine the outcome of Leishmania major infection and immune protection depends mainly on memory T cells induced during vaccination. This largely hinges on the nature and type of memory T cells produced. In this study, transgenic Leishmania major expressing membrane associated ovalbumin (mOVA) and soluble ovalbumin (sOVA) are used as a model to study whether fully differentiated Th1/ Th2 &Th17 cells can recall immune memory and tolerate pathogen manipulation. Naive OT-II T cells were in vitro polarised into Th1/Th2, and these cells were transferred adoptively into recipient mice. Following transferring the memory cells, recipient mice were challenged with OVA transgenic Leishmania major and wild type parasite was used a control. The in vitro polarised T helper cells continued to produce the same cytokine signatures after challenged by both forms of OVA-expressing Leishmania major parasites in vivo. This suggests antigen-experienced cells cells remain the same or unaltered in the face of OVA transgenic Leishmania major. Such ability of the antigen-experienced cells to remain resilient to manipulation by the parasite signifies that vaccines might be able to produce immune memory responses and withstand against the parasite immune manipulation and protect the host from infection.

Life history theory suggests that aging is one of the costs of reproduction. Accordingly, a higher reproductive allocation is expected to increase the deterioration of both the somatic and the germinal lines through enhanced telomere attrition. In most species, males reproductive allocation mainly regards traits that increase mating and fertilization success, i.e. sexually selected traits. In the current study, we tested the hypothesis that a higher investment in sexually selected traits is associated with a reduced telomere length in the guppy (Poecilia reticulata), an ectotherm species characterized by strong pre- and postcopulatory sexual selection. We first measured telomere length in both the soma and the sperm over the course of guppys lifespan to see if there was any variation in telomere length associated with age. Secondly, we investigated whether a greater expression of pre- and postcopulatory sexually selected traits is linked to shorter telomere length in both the somatic and the sperm germinal lines, and in young and old males. We found that telomeres lengthened with age in the somatic tissue, but there was no age-dependent variation in telomere length in the sperm cells. Telomere length in guppies was significantly and negatively correlated with sperm production in both tissues and life stages considered in this study. Our findings indicate that telomere erosion in male guppies is more strongly associated with their reproductive investment (sperm production) rather than their age, suggesting a trade-off between reproduction and maintenance is occurring at each stage of males life in this species.

Antiviral therapies are among the most effective pharmaceutical interventions in treatment of a variety of viral pathogens. To optimize the antiviral effectiveness it is crucial to characterize the relationship between multiple cellular modes of antiviral action and the complex response of the hosts innate immune system relative to the within host dynamics of a proliferating virus. Since their introduction in 1968 and 2019, Influenza A virus (IAV) H3N2 and Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), respectively, have caused unprecedented damage on the public health infrastructure globally. In addition to the substantial burden of morbidity and mortality around the world, both viruses have the potential of undergoing evolution leading to antigenic escape from the prevailing interventions. These biological characteristics advocate for urgent development of effective antivirals for the treatment of IAV and SARS-CoV-2. In this multi-stage study, we develop a suite of within-host models encompassing a number of hypotheses regarding virus-specific innate host functional responses and their impacts on the proliferation of IAV H3N2 and SARS-CoV-2 viruses. We use likelihood-based statistical inference to confront these hypotheses with infection data on IAV H3N2 and SARS-CoV-2 from infection experiments in ferrets. Upon identifying the best-fitting model of within-host dynamics, we can quantify the potential impact of antiviral drug therapy as a function of effectiveness and timing of initiation. We find significant mechanistic differences between the infection dynamics of H3N2 IAV and SARS-CoV-2 and associated model parameters. The treatment consequences of these differences are that SARS-CoV-2 is harder to control with antivirals, requiring earlier initiation and a more effective drug. Author summaryAntiviral drugs are prophylactic chemical agents that are used to contain several viral infections. Influenza A H3N2 virus (H3N2) and Severe Acute Respiratory Syndrome Corona Virus-2 (SARS-CoV-2) are very important viral pathogens that have caused unprecedented, global public health damage in the recent times. This makes development of antiviral drugs crucial along with other pharmaceutical prophylactics like vaccination. To optimize the pathogen specific effectiveness, however, it is necessary to simultaneously explore the relationship among the intra-host viral kinetics, immune dynamics and modes of antiviral action. In this article we theoretically analyze antiviral action of a drug in union with effect of the hosts innate immune system in containing infections of SARS-CoV-2 and H3N2 in infection experiments with ferrets. We find fundamental differences in the requisite antiviral effectiveness which, we posit, is due to substantially different inter-cellular proliferation potential between the two viruses.

Fishers reproductive compensation (fRC) occurs when a species demography means the death of an individual allows increased survival of his/her relatives, usually assumed to be full sibs. This likely occurs in many species, including humans. Several important recessive human genetic diseases cause early foetal/infant death allowing fRC to act on these mutations. The impact of fRC on these genetic conditions has been calculated and shown to be substantial as quantified by {omega}, the fold increase in equilibrium frequencies of the mutation under fRC compared to its absence i.e. {omega}=1.22 and {omega}=1.33 for autosomal and sex-linked loci, respectively. However, the impact of fRC on the frequency of the much large class of semi-dominant, non-lethal mutations is unknown. This is calculated here by a mixture of simulation and algebra and shown that {omega}=2-h*s and {omega}{approx}2-0.19s-0.85h*s for autosomal and sex-linked loci respectively where h is dominance (varied between 0.05 and 0.95) and s is selection coefficient (varied between 0.05 and 0.9). These results show that the actions of fRC can almost double equilibrium frequency of mutations with low values of h and/or s. The dynamics of fRC acting on this type of mutation are also identified and discussed.

Human-Brain Artificial-Intelligence Matrix is a new technology aims to connect the human brain with the machine for the purpose of enabling the human brain to perform defined functions even if it becomes unable to perform them such as performing the function of vision in case of blindness, the function of hearing in case of deafness, Performing the function of motion in case of paralysis and many other functions. This technology will be based on the Cognition Theory which I argue about that the whole process of cognition can be treated quantum-mechanically. The cognition starts when a neuron sends data to be processed in the brain and ends in an effector to respond. The data "action potential" is a current of particles which can be described quantum-mechanically as a wave-impulse based on the dual nature of the particles. The neurons are a net of entangled cells classically and quantum-mechanically. When the action potential changes the potential of the neurons, it creates quantum mechanical potential wells and barriers. The action potential perfectly transmits in and out the neurons through quantum mechanical tunnels. The form of energy before processing is not the same after, but the amount of energy is always conserved. Since the neurons are entangled during the action potential transmission, the brain and effector will be entangled during the action potential processing. The effectors cognition of data must be a discrete cognition of single-valued data from its self-adjoint matrix which entangled with brain matrix.

Metamorphic insects apparently rely on a finite number of cells after emergence to counterbalance either commensal and pathogen presence. For hematophagous insects, blood-feeding is a crucial step for offspring development, therefore enteric cells repairing molecular mechanisms consists in fine regulated pathways to counterattack biotic and abiotic insults. Nevertheless, recent research suggests that midgut cells are capable to adapt their immune responses to pathogen challenges. Recently, Anopheles and Aedes mosquitoes have been observed to increase their DNA cell content upon encounter with parasites, bacteria and virus respectively. Genomic endoreplication is one of the most important processes in larval development for fast transcriptional activity and protein secretion. So, in this paper we explore the ability of Aedes aegypti Aag-2 culture cells to develop a likely endoreplication process to face pathogen presence. Aag-2 cells at 6 and 12 hours post-biotic insult enter a proliferation arrest and increases DNA content, these two phenomena recovers control levels at 24 h post-treatment. It requires more research data about the type of genomic regions that has been replicated in the process, and the concentration that antimicrobial molecules are released into culture media.

The reactions of functional molecules like proteins and RNAs to mutation affect both host cell viability and biomolecular evolution. These molecules are considered robust if function is maintained despite mutations. Proteins and RNAs have different structural and functional characteristics that affect their robustness, and to date, comparisons between them have been theoretical. In this work, we test the relative mutational robustness of RNA and protein pairs using three approaches: evolutionary, structural, and functional. We compare the nucleotide diversities of functional RNAs with those of matched proteins. Across different levels of conservation, we found the nucleotide-level variations between the biomolecules largely overlapped, with proteins generally supporting more variation than matched RNAs. We then directly tested the robustness of the protein and RNA pairs with in vitro and in silico mutagenesis of their respective genes. The in silico experiments showed that proteins and RNAs reacted similarly to point mutations and insertions or deletions, yet proteins are slightly more robust on average than RNAs. In vitro, mutated fluorescent RNAs retained greater levels of function than the proteins. Overall this suggests that proteins and RNAs have remarkably similar degrees of robustness, with the average protein having moderately higher robustness than RNA as a group.\n\nSignificance StatementThe ability of proteins and non-coding RNAs to maintain function despite mutations in their respective genes is known as mutational robustness. Robustness impacts how molecules maintain and change phenotypes, which has a bearing on the evolution and the origin of life as well as influencing modern biotechnology. Both protein and RNA have mechanisms that allow them to absorb DNA-level changes. Proteins have a redundant genetic code and non-coding RNAs can maintain structure and function through flexible base-pairing possibilities. The few theoretical treatments comparing protein and RNA robustness differ in their conclusions. In this experimental comparison of protein and RNA, we find that they have remarkably similar degrees of overall genetic robustness.

In molecular dynamics simulations we can often increase the time step by imposing constraints on internal degrees of freedom, such as bond lengths and bond angles. This allows us to extend the length of the time interval and therefore the range of physical phenomena that we can afford to simulate. In this article we analyse the impact of the accuracy of the constraint solver. We present ILVES-PC, an algorithm for imposing constraints on proteins accurately and efficiently. ILVES-PC solves the same system of differential algebraic equations as the celebrated SHAKE algorithm, but uses Newtons method for solving the nonlinear constraint equations. It solves the necessary linear systems of equations using a specialised linear solver that utilises the molecular structure. ILVES-PC can rapidly solve the nonlinear constraint equations to nearly the limit of machine precision. This eliminates the spurious forces introduced to simulations through the very common use of inaccurate approximations. The run-time of ILVES-PC is proportional to the number of constraints. We have integrated ILVES-PC into GROMACS and simulated proteins of different sizes. Compared with SHAKE, we have achieved speedups of up to 4.9x in single-threaded executions and up to 76x in shared-memory multi-threaded executions. Moreover, we find that ILVES-PC is more accurate than the P-LINCS algorithm. Our work is a proof-of-concept of the utility of software designed specifically for the simulation of polymers. Author summaryMolecular dynamics simulates the time evolution of molecular systems. It has become a tool of extraordinary importance for e.g. understanding biological processes and designing drugs and catalysts. This article presents an algorithm for computing the forces needed to impose constraints in molecular dynamics, i.e., the constraint forces; moreover, it analyses the effect of the accuracy of the constraint solver. Presently, it is customary to calculate the constraint forces with a relative error that that is not tiny. This is due to the high computational cost associated with the available software. Accurate calculations are possible, but they are very time-consuming. The algorithm that we present solves this problem: it computes the constraint forces accurately and efficiently. Our work will improve the accuracy and reliability of molecular dynamics simulations beyond the present state-of-the-art. The results that we present are also a proof-of-concept that special-purpose code can increase the performance of software for the simulation of polymers. The algorithm is implemented into a popular molecular simulation package, and is now available for the research community.

The IMD and Toll signaling pathways in Drosophila melanogaster mediate the innate immune responses to Gram-negative and Gram-positive bacteria and fungi, respectively. Here we studied the involvement of the NF-{kappa}B transcription factor Relish, which is a mediator of the IMD pathway, in the humoral immune response to the Gram-positive bacteria Micrococcus luteus and Bacillus subtilis and the entomopathogenic fungus Metarhizium anisopliae, using D. melanogaster S2 cells as a model. Activation of Relish proteolysis was observed after S2 cell treatment with the control Gram-negative bacterium Escherichia coli. We found that M. luteus had also a noticeable effect on Relish activation, while B. subtilis and M. anisopliae effects were modest. Activation patterns of the genes encoding predominantly the IMD-pathway-dependent antimicrobial peptides (AMPs) and peptidoglycan recognition proteins (PGRPs), as well as the levels of Relish recruitment to the promoters of the genes, were found to be very similar in S2 cells treated with E. coli or M. luteus but were lower and differed in the case of B. subtilis and M. anisopliae. A Relish knockdown (KD) decreased the induction levels observed for all AMP and some PGRP genes in response to M. luteus treatment and the induction levels observed for several AMP genes after M. anisopliae and B. subtilis exposures. Therefore, our findings suggest that Relish plays a critical role in inducing the humoral immune response in Drosophila S2 cells, contributing primarily to the response against M. luteus and, to a lesser extent, to the responses against B. subtilis and M. anisopliae.

Base substitution mutations such as transition (ti) and transversion (tv) in organisms are major driving force in molecular evolution. In this study, different possible types of base pairing that can cause ti and tv were investigated using the density functional theory (DFT) method. The chemical structures of bases as well as base pairs were optimized using B3LYP hybrid functional along with 6-31G(d,p) basis set. We performed single point energy calculation of all optimized species using the same functional but combined with higher diffuse and polarized basis set i.e. 6-311++G(d,p) to get more refined energy of all species. The binding energy of various base pairs was calculated considering basis set superposition error (BSSE) as well as without BSSE. The binding energy of the base pairs leading to ti was found to be more stable than that of the base pairs leading to tv. This was interesting considering the observations in organisms that tis are more frequent than tvs. Among the base pairs leading to the same ti, G(keto): T (enol) base pair was found to be more stable than A(imino):C(amino) base pair. This theoretical study of binding energy of different base pairs using the DFT method has provided additional evidences in support to the biological observations of a higher transition rate than transversion in genomes.

The study of natural and the design of artificial multivalent proteins is a promising field of molecular biology. Working with such proteins is much more difficult than with their monovalent analogues. In this paper, we show how using a ring of heptameric Sm-like protein as a scaffold, it is possible to create a multivalent protein with a different number of binding sites. This is an urgent task for the study of multivalent and multicenter protein-protein interactions. The method of analysis used in the work allows us to evaluate the stoichiometry and the dissociation constant of complexes of artificial chaperone with a non-native protein. It is shown that for reliable binding of non-native LA, its interaction with several apical domains of GroEL is necessary. At the same time, the dissociation constant of such a complex does not significantly change with an increase in the number of binding domains in the oligomer. Up to 4 LA molecules can be attached to the complete heptameric ring of apical domains. The proposed methods have a good cost-to-result ratio and can be applied to the study and design of other new proteins.

The consequences of assortative model in the additive polygenic model have been extensively explored by several authors. In this note we extend their results by introducing a correlation between parental and offspring environments.