An attempt to construct a (general) mathematical framework to model biological “context-dependence”

Banerji, Anirban

doi:10.1007/s11693-013-9122-6

Cited by 5 publications

(3 citation statements)

References 32 publications

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“…Further, the aforementioned studies have been largely limited to understand the metabolism of glioblastoma in parts, and have not been focused to identify or predict feasible drug targets on a network scale. Moreover, these studies have also overlooked the context-dependent understanding of glioblastoma metabolism and its role in achieving specific biological goals (Banerji 2013).…”

Section: Introductionmentioning

confidence: 99%

Exploring the differences in metabolic behavior of astrocyte and glioblastoma: a flux balance analysis approach

2015

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Brain cancers demonstrate a complex metabolic behavior so as to adapt the external hypoxic environment and internal stress generated by reactive oxygen species. To survive in these stringent conditions, glioblastoma cells develop an antagonistic metabolic phenotype as compared to their predecessors, the astrocytes, thereby quenching the resources expected for nourishing the neurons. The complexity and cumulative effect of the large scale metabolic functioning of glioblastoma is mostly unexplored. In this study, we reconstruct a metabolic network comprising of pathways that are known to be deregulated in glioblastoma cells as compared to the astrocytes. The network, consisted of 147 genes encoding for enzymes performing 247 reactions distributed across five distinct model compartments, was then studied using constrained-based modeling approach by recreating the scenarios for astrocytes and glioblastoma, and validated with available experimental evidences. From our analysis, we predict that glycine requirement of the astrocytes are mostly fulfilled by the internal glycine-serine metabolism, whereas glioblastoma cells demand an external uptake of glycine to utilize it for glutathione production. Also, cystine and glucose were identified to be the major contributors to glioblastoma growth. We also proposed an extensive set of single and double lethal reaction knockouts, which were further perturbed to ascertain their role as probable chemotherapeutic targets. These simulation results suggested that, apart from targeting the reactions of central carbon metabolism, knockout of reactions belonging to the glycine-serine metabolism effectively reduce glioblastoma growth. The combinatorial targeting of glycine transporter with any other reaction belonging to glycine-serine metabolism proved lethal to glioblastoma growth.

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Section: Introductionmentioning

confidence: 99%

Exploring the differences in metabolic behavior of astrocyte and glioblastoma: a flux balance analysis approach

2015

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“…Allosteric signalling achieved at the structural level show certain differences for various proteins (69)(70)(71). Thus, we expect to observe differences in composition of ACSS residues for four different classes of proteins.…”

Section: Composition Of the Acss Populationmentioning

confidence: 99%

Deciphering General Characteristics of Residues Constituting Allosteric Communication Paths

Malik

Banerji

Kloczkowski

2017

Biophysical Journal

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Considering all the PDB annotated allosteric proteins (from ASD -AlloSteric Database) belonging to four different classes (kinases, nuclear receptors, peptidases and transcription factors), this work has attempted to decipher certain consistent patterns present in the residues constituting the allosteric communication sub-system (ACSS). The thermal fluctuations of hydrophobic residues in ACSSs were found to be significantly higher than those present in the non-ACSS part of the same proteins, while polar residues showed the opposite trend.The basic residues and hydroxyl residues were found to be slightly more predominant than the acidic residues and amide residues in ACSSs, hydrophobic residues were found extremely frequently in kinase ACSSs. Despite having different sequences and different lengths of ACSS, they were found to be structurally quite similar to each other -suggesting a preferred structural template for communication. ACSS structures recorded low RMSD and high Akaike Information Criterion(AIC) scores among themselves. While the ACSS networks for all the groups of allosteric proteins showed low degree centrality and closeness centrality, the betweenness centrality magnitudes revealed nonuniform behavior. Though cliques and communities could be identified within the ACSS, maximal-common-subgraph considering all the ACSS could not be generated, primarily due to the diversity in the dataset. Barring one particular case, the entire ACSS for any class of allosteric proteins did not demonstrate "small world" behavior, though the sub-graphs of the ACSSs, in certain cases, were found to form small-world networks.

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“…A complete framework for the construction of computational models of bio-systems is yet to be formulated (Blakes et al 2011). Modeling biological systems from the molecular to organismal scales are to be extensively studied (Banerji 2013). The emergence of biochemical pathways occurred due to the impact of the series of reactions between different bio-molecules which comprised to form a pathway (Banerji 2014).…”

Section: Introductionmentioning

confidence: 99%

Computational model for monitoring cholesterol metabolism

2014

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A non-deterministic finite automaton is designed to observe the cholesterol metabolism with the states of acceptance and rejection. The acceptance state of the automaton depicts the normal level of metabolism and production of good cholesterol as an end product. The rejection state of this machine shows the inhibition of enzymatic activity in cholesterol synthesis and removal of free fatty acids. The deficiency in human cholesterol metabolism pathway results in abnormal accumulation of cholesterol in plasma, arterial tissues leading to diseases such as hypercholesterolemia, atherosclerosis respectively and formation of gallstones. The designed machine can be used to monitor the cholesterol metabolism at molecular level through regulation of enzymes involved in the biosynthesis and metabolism of cholesterol for the treatment of diseases incident due to the respective metabolic disorder. In addition, an algorithm for this machine has been developed to compare the programmed string with the given string. This study demonstrates the construction of a machine that is used for the development of molecular targeted therapy for the disorders in cholesterol metabolism.

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An attempt to construct a (general) mathematical framework to model biological “context-dependence”

Cited by 5 publications

References 32 publications

Exploring the differences in metabolic behavior of astrocyte and glioblastoma: a flux balance analysis approach

Exploring the differences in metabolic behavior of astrocyte and glioblastoma: a flux balance analysis approach

Deciphering General Characteristics of Residues Constituting Allosteric Communication Paths

Computational model for monitoring cholesterol metabolism

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