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Anirban Banerji

Publications and source records attributed to Anirban Banerji.

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Role of Resultant Dipole Moment in Mechanical Dissociation of Biological Complexes

Protein-peptide interactions play essential roles in many cellular processes and their structural characterization is the major focus of current experimental and theoretical research. Two decades ago, it was proposed to employ the steered molecular dynamics to assess the strength of protein-peptide interactions. The idea behind using steered molecular dynamics simulations is that the mechanical stability can be used as a promising and an efficient alternative to computationally highly demanding estimation of binding affinity. However, mechanical stability defined as a peak in force-extension profile depends on the choice of the pulling direction. Here we propose an uncommon choice of the pulling direction along resultant dipole moment vector, which has not been explored in simulations so far. Using explicit solvent all-atom MD simulations, we apply steered molecular dynamics technique to probe mechanical resistance of protein-peptide system pulled along two different vectors. A novel pulling direction, along the resultant dipole moment vector, results in stronger forces compared to commonly used peptide unbinding along center of masses vector. Our results demonstrate that resultant dipole moment is one of the factors influencing the mechanical stability of protein-peptide complex.

q-bio.BM

Deciphering general characteristics of residues constituting allosteric communication paths

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.

q-bio.BM

Attractors in residual interactions explain the differentially-conserved stability of Immunoglobulins

Proteins belonging to immunoglobulin superfamily(IgSF) show remarkably conserved nature both in their folded structure and in their folding process, but they neither originate from very similar sequences nor demonstrate functional conservation. Treating proteins as fractal objects, without studying spatial conservation in positioning of particular residues in IgSF, this work probed the roots structural invariance of immunoglobulins(Ig). Symmetry in distribution of mass, hydrophobicity, polarizability recorded very similar extents in Ig and in structurally-closest non-Ig structures. They registered similar symmetries in dipole-dipole, π-π, cation-π cloud interactions and also in distribution of active chiral centers, charged residues and hydrophobic residues. But in contrast to non-Ig proteins, extents of residual interaction symmetries in Ig.s of largely varying sizes are found to converge to exactly same magnitude of correlation dimension - these are named 'structural attractors', who's weightages depend on ensuring exact convergence of pairwise-interaction symmetries to attractor magnitude. Small basin of attraction for Ig attractors explained the strict and consistent quality control in ensuring stability and functionality of IgSF proteins. Low dependency of attractor weightage on attractor magnitude demonstrated that residual-interaction symmetry with less pervasive nature can also be crucial in ensuring Ig stability.

q-bio.BM

A probabilistic model to describe the dual phenomena of biochemical pathway damage and biochemical pathway repair

Biochemical pathways emerge from a series of Brownian collisions between various types of biological macromolecules within separate cellular compartments and in highly viscous cytosol. Functioning of biochemical networks suggests that such serendipitous collisions, as a whole, result into a perfect synchronous order. Nonetheless, owing to the very nature of Brownian collisions, a small yet non-trivial probability can always be associated with the events when such synchronizations fail to emerge consistently; which account for a damage of a biochemical pathway. The repair mechanism of the system then attempts to minimize the damage, in the pursuit to bring restore the appropriate level of synchronization between reactant concentrations. Present work presents a predictive probabilistic model that describes the various facets of this complicated and coupled process(damaging and repairing). By describing the cytosolic reality of Brownian collisions with Chapman-Kolmogorov equations, the model presents analytical answers to the questions, with what probability a fragment of any pathway may suffer damage within an arbitrary interval of time? and with what probability the damage to a pathway can be repaired within any arbitrary interval of time?

q-bio.OT

Structural and evolutionary tunnels of pairwise residue-interaction symmetries connect different structural classes of proteins

Studying all non-redundant proteins in 76 most-commonly found structural domains, the present work attempts to decipher latent patterns that characterize acceptable and unacceptable symmetries in residue-residue interactions in functional proteins. We report that cutting across the structural classes, a select set of pairwise interactions are universally favored by geometrical and evolutionary constraints, termed 'acceptable' structural and evolutionary tunnels, respectively. An equally small subset of residue-residue interactions, the 'unacceptable' structural and evolutionary tunnels, is found to be universally disliked by structural and evolutionary constraints. Non-trivial overlapping is detected among acceptable structural and evolutionary tunnels, as also among unacceptable structural and evolutionary tunnels. A subset of tunnels is found to have equal relative importance, structurally and evolutionarily, in different structural classes. The MET-MET tunnel is detected to be universally most unacceptable by both structural and evolutionary constraints, whereas the ASP-LEU tunnel was found to be the closest approximation to be universally most acceptable. Residual populations in structural and evolutionary tunnels are found to be independent of stereochemical properties of individual residues. It is argued with examples that tunnels are emergent features that connect extent of symmetry in residue-residue interactions to the level of quaternary structural organization.

q-bio.BM

Residue mobility has decreased during protein evolution

Upon studying the B-Factors of all the atoms of all non-redundant proteins belonging to 76 most commonly found structural domains of all four major structural classes, it was found that the residue mobility has decreased during the course of evolution. Though increased residue-flexibility was preferred in the early stages of protein structure evolution, less flexibility is preferred in the medieval and recent stages. GLU is found to be the most flexible residue while VAL recorded to have the least flexibility. General trends in decrement of B-Factors conformed to the general trend in the order of emergence of protein structural domains. Decrement of B-Factor is observed to be most decisive (monotonic and uniform) for VAL, while evolution of CYS and LYS flexibility is found to be most skewed. Barring CYS, flexibility of all the residues is found to have increased during evolution of alpha by beta folds, however flexibility of all the residues (barring CYS) is found to have decreased during evolution of all beta folds. Only in alpha by beta folds the tendency of preferring higher residue mobility could be observed, neither alpha plus beta, nor all alpha nor all beta folds were found to support higher residue-mobility. In all the structural classes, the effect of evolutionary constraint on polar residues is found to follow an exactly identical trend as that on hydrophobic residues, only the extent of these effects are found to be different. Though protein size is found to be decreasing during evolution, residue mobility of proteins belonging to ancient and old structural domains showed strong positive dependency upon protein size, however for medieval and recent domains such dependency vanished. It is found that to optimize residue fluctuations, alpha by beta class of proteins are subjected to more stringent evolutionary constraints.

q-bio.BM

ProtFract: A server to calculate interior and exterior fractal properties of proteins: Case study with Ras superfamily proteins

Motivation: Protein surface roughness is fractal in nature. Mass, hydrophobicity, polarizability distributions of protein interior are fractal too, as are the distributions of dipole moments, aromatic residues, and many other structural determinants. The open-access server ProtFract, presents a reliable way to obtain numerous fractal-dimension and correlation-dimension based results to quantify the symmetry of self-similarity in distributions of various properties of protein interior and exterior. Results: Fractal dimension based comparative analyses of various biophysical properties of Ras superfamily proteins were conducted. Though the extent of sequence and functional overlapping across Ras superfamily structures is extremely high, results obtained from ProtFract investigation are found to be sensitive to detect differences in the distribution of each of the properties. For example, it was found that the RAN proteins are structurally most stable amongst all Ras superfamily proteins, the ARFs possess maximum extent of unused hydrophobicity in their structures, RAB protein interiors have electrostatically least conducive environment, GEM/REM/RAD proteins possess exceptionally high symmetry in the structural organization of their active chiral centres, neither hydrophobicity nor columbic interactions play significant part in stabilizing the RAS proteins but aromatic interactions do, though cation-pi interactions are found to be more dominant in RAN than in RAS proteins. Ras superfamily proteins can best be classified with respect to their class-specific pi-pi and cation-pi interaction symmetries. Availability: ProtFract is freely available online at the URL: http://bioinfo.net.in/protfract/index.html

q-bio.BM

Quantification of Biological Robustness at the Systemic Level

Biological systems possess negative entropy. In them, one form of order produces another, more organized form of order. We propose a formal scheme to calculate robustness of an entire biological system by quantifying the negative entropy present in it. Our Methodology is based upon a computational implementation of two-person non-cooperative finite zero-sum game between positive (physico-chemical) and negative (biological) entropy, present in the system(TCA cycle, for this work). Biochemical analogue of Nash equilibrium, proposed here, could measure the robustness in TCA cycle in exact numeric terms, whereas the mixed strategy game between these entropies could quantitate the progression of stages of biological adaptation. Synchronization profile amongst macromolecular concentrations (even under environmental perturbations) is found to account for negative entropy and biological robustness. Emergence of synchronization profile was investigated with dynamically varying metabolite concentrations. Obtained results were verified with that from the deterministic simulation methods. Categorical plans to apply this algorithm in Cancer studies and anti-viral therapies are proposed alongside. From theoretical perspective, this work proposes a general, rigorous and alternative view of immunology.

q-bio.SC

3-10 and Pi-Helices: Stochastic Events on Sequence Space; Reasons and Implications of their Accidental Occurrences across Protein Universe

Considering all available non-redundant protein structures across different structural classes, present study identified the probabilistic characteristics that describe several facets of the occurrence of 3(10) and Pi-helices in proteins. Occurrence profile of 3(10) and Pi-helices revealed that, their presence follows Poisson flow on the primary structure; implying that, their occurrence profile is rare, random and accidental. Structural class-specific statistical analyses of sequence intervals between consecutive occurrences of 3(10) and Pi-helices revealed that these could be best described by gamma and exponential distributions, across structural classes. Comparative study of normalized percentage of non-glycine and non-proline residues in 3(10), Pi and alpha-helices revealed a considerably higher proportion of 3(10) and Pi-helix residues in disallowed, generous and allowed regions of Ramachandran map. Probe into these findings in the light of evolution suggested clearly that 3(10) and Pi-helices should appropriately be viewed as evolutionary intermediates on long time scale, for not only the α-helical conformation but also for the 'turns', equiprobably. Hence, accidental and random nature of occurrences of 3(10) and Pi-helices, and their evolutionary non-conservation, could be described and explained from an invariant quantitative framework. Extent of correctness of two previously proposed hypotheses on 3(10) and Pi-helices, have been investigated too. Alongside these, a new algorithm to differentiate between related sequences is proposed, which reliably studies evolutionary distance with respect to protein secondary structures.

q-bio.BM

How happy is your web browsing? A model to quantify satisfaction of an Internet user, searching for desired information

We feel happy when web-browsing operations provide us with necessary information; otherwise, we feel bitter. How to measure this happiness (or bitterness)? How does the profile of happiness grow and decay during the course of web-browsing? We propose a probabilistic framework that models evolution of user satisfaction, on top of his/her continuous frustration at not finding the required information. It is found that the cumulative satisfaction profile of a web-searching individual can be modeled effectively as the sum of random number of random terms, where each term is mutually independent random variable, originating from 'memoryless' Poisson flow. Evolution of satisfaction over the entire time interval of user's browsing was modeled with auto-correlation analysis. A utilitarian marker, magnitude of greater than unity of which describe happy web-searching operations; and an empirical limit that connects user's satisfaction with his frustration level - are proposed too. Presence of pertinent information in the very first page of a web-site and magnitude of the decay parameter of user satisfaction (frustration, irritation etc.), are found to be two key aspects that dominate web-browser's psychology. The proposed model employed different combination of decay parameter, searching time and number of helpful web-sites. Obtained results are found to match the results from three real-life case-studies.

cs.HC

An algorithm to relate protein surface roughness with local geometry of protein exterior shape

Changes in the extent of local concavity along with changes in surface roughness of binding sites of proteins have long been considered as useful markers to identify functional sites of proteins. However, an algorithm that describes the connection between the simultaneous changes of these important parameters - eludes the students of structural biology. Here a simple yet general mathematical scheme is proposed that attempts to achieve the same. Instead of n-dimensional random vector description, protein surface roughness is described here as a system of algebraic equations. Such description resulted in the construction of a generalized index that not only describes the shape-change-vs-surface-roughness-change process but also reduces the estimation error in local shape characterization. Suitable algorithmic implementation of it in context-specific macromolecular recognition can be attempted easily. Contemporary drug discovery studies will be enormously benefited from this work because it is the first algorithm that can estimate the change in protein surface roughness as the local shape of the protein is changing (and vice-versa).

q-bio.BM

A (possible) mathematical model to describe biological "context-dependence" : case study with protein structure

Context-dependent nature of biological phenomena are well documented in every branch of biology. While there have been few previous attempts to (implicitly) model various facets of biological context-dependence, a formal and general mathematical construct to model the wide spectrum of context-dependence, eludes the students of biology. An objective and rigorous model, from both 'bottom-up' as well as 'top-down' perspective, is proposed here to serve as the template to describe the various kinds of context-dependence that we encounter in different branches of biology. Interactions between biological contexts was found to be transitive but non-commutative. It is found that a hierarchical nature of dependence amongst the biological contexts models the emergent biological properties efficiently. Reasons for these findings are provided with a general model to describe biological reality. Scheme to algorithmically implement the hierarchic structure of organization of biological contexts was achieved with a construct named 'Context tree'. A 'Context tree' based analysis of context interactions among biophysical factors influencing protein structure was performed.

q-bio.OT

Criteria to observe mesoscopic emergence of protein biophysical properties

Proteins are regularly described with some general indices (mass fractal dimension, surface fractal dimension, entropy, enthalpy, free energies, hydrophobicity, denaturation temperature etc..), which are inherently statistical in nature. These general indices emerge from innumerable (innately context-dependent and time-dependent) interactions between various atoms of a protein. Many a studies have been performed on the nature of these inter-atomic interactions and the change of profile of atomic fluctuations that they cause. However, we still do not know, under a given context, for a given duration of time, how does a macroscopic biophysical property emerge from the cumulative inter-atomic interactions. An exact answer to that question will involve bridging the gap between nano-scale distinguishable atomic description and macroscopic indistinguishable (statistical) measures, along the mesoscopic scale of observation. In this work we propose a computationally implementable mathematical model that derives expressions for observability of emergence of a macroscopic biophysical property from a set of interacting (fluctuating) atoms. Since most of the aforementioned interactions are non-linear in nature; observability criteria are derived for both linear and the non-linear descriptions of protein interior. The study assumes paramount importance in 21st-century biology, from both the theoretical and practical utilitarian point of view.

q-bio.BM

How often does theory match experiment?

In every sphere of science, theories make predictions and experiments validate them. However, common experience suggests that theoretically predicted exact magnitude for a parameter, constitute a small subset of all the experimentally obtained magnitudes for that particular parameter. Typically, irrespective of the branch of science and the particular problem under consideration, the set of obtained experimental results form an interval [x_min,x_max], within which the theoretically predicted magnitude, say 'x', occurs with time, apparently randomly. We attempt here to find the characteristics of the statistical distribution of events of experimental observation of the occurrence of theoretically predicted 'x'; in other words, characterization of the time interval when theoretical predictions match the experimental readings, exactly.

physics.data-an

Existence of biological uncertainty principle implies that we can never find 'THE' measure for biological complexity

There are innumerable 'biological complexity measure's. While some patterns emerge from these attempts to represent biological complexity, a single measure to encompass the seemingly countless features of biological systems, still eludes the students of Biology. It is the pursuit of this paper to discuss the feasibility of finding one complete and objective measure for biological complexity. A theoretical construct (the 'Thread-Mesh model') is proposed here to describe biological reality. It segments the entire biological space-time in a series of different biological organizations before modeling the property space of each of these organizations with computational and topological constructs. Acknowledging emergence as a key biological property, it has been proved here that the quest for an objective and all-encompassing biological complexity measure would necessarily end up in failure. Since any study of biological complexity is rooted in the knowledge of biological reality, an expression for possible limit of human knowledge about ontological biological reality, in the form of an uncertainty principle, is proposed here. Two theorems are proposed to model the fundamental limitation, owing to observer dependent nature of description of biological reality. They explain the reasons behind failures to construct a single and complete biological complexity measure. This model finds support in various experimental results and therefore provides a reliable and general way to study biological complexity and biological reality.

q-bio.OT