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Biomedical subjects

J R Banavar

Publications and source records attributed to J R Banavar.

At least 19 recordsLinked to original sources

Protein threading by learning.

By using techniques borrowed from statistical physics and neural networks, we determine the parameters, associated with a scoring function, that are chosen optimally to ensure complete success in threading tests in a training set of proteins. These parameters provide a quantitative measure of the propensities of amino acids to be buried or exposed and to be in a given secondary structure and are a good starting point for solving both the threading and design problems.

Amino Acid Sequence↗

Conformations of proteins in equilibrium.

We introduce a simple theoretical approach for an equilibrium study of proteins with known native-state structures. We test our approach with results on well-studied globular proteins, chymotrypsin inhibitor (2ci2), barnase, and the alpha spectrin SH3 domain, and present evidence for a hierarchical onset of order on lowering the temperature with significant organization at the local level even at high temperatures. A further application to the folding process of HIV-1 protease shows that the model can be reliably used to identify key folding sites that are responsible for the development of drug resistance.

Animals↗

Learning effective amino acid interactions through iterative stochastic techniques.

The prediction of the three-dimensional structures of the native states of proteins from the sequences of their amino acids is one of the most important challenges in molecular biology. An essential task for solving this problem within coarse-grained models is the deduction of effective interaction potentials between the amino acids. Over the years, several techniques have been developed to extract potentials that are able to discriminate satisfactorily between the native and nonnative folds of a preassigned protein sequence. In general, when these potentials are used in actual dynamical folding simulations, they lead to a drift of the native structure outside the quasinative basin. In this article, we present and validate an approach to overcome this difficulty. By exploiting several numerical and analytical tools, we set up a rigorous iterative scheme to extract potentials satisfying a prerequisite of any viable potential: the stabilization of proteins within their native basin (less than 3-4 A RMSD). The scheme is flexible and is demonstrated to be applicable to a variety of parameterizations of the energy function, and it provides in each case the optimal potentials.

Amino Acids↗

Dynamic modeling of gene expression data.

We describe the time evolution of gene expression levels by using a time translational matrix to predict future expression levels of genes based on their expression levels at some initial time. We deduce the time translational matrix for previously published DNA microarray gene expression data sets by modeling them within a linear framework by using the characteristic modes obtained by singular value decomposition. The resulting time translation matrix provides a measure of the relationships among the modes and governs their time evolution. We show that a truncated matrix linking just a few modes is a good approximation of the full time translation matrix. This finding suggests that the number of essential connections among the genes is small.

Cell Cycle Proteins↗

Boundary conditions at a fluid-solid interface.

We study the boundary conditions at a fluid-solid interface using molecular dynamics simulations covering a broad range of fluid-solid interactions and fluid densities and both simple and chain-molecule fluids. The slip length is shown to be independent of the type of flow, but rather is related to the fluid organization near the solid, as governed by the fluid-solid molecular interactions.

Journal Article↗

Deciphering the folding kinetics of transmembrane helical proteins.

Nearly a quarter of genomic sequences and almost half of all receptors that are likely to be targets for drug design are integral membrane proteins. Understanding the detailed mechanisms of the folding of membrane proteins is a largely unsolved, key problem in structural biology. Here, we introduce a general model and use computer simulations to study the equilibrium properties and the folding kinetics of a C(alpha)-based two-helix bundle fragment (comprised of 66 aa) of bacteriorhodopsin. Various intermediates are identified and their free energy are calculated together with the free energy barrier between them. In 40% of folding trajectories, the folding rate is considerably increased by the presence of nonobligatory intermediates acting as traps. In all cases, a substantial portion of the helices is rapidly formed. This initial stage is followed by a long period of consolidation of the helices accompanied by their correct packing within the membrane. Our results provide the framework for understanding the variety of folding pathways of helical transmembrane proteins.

Bacteriorhodopsins↗

Optimal shapes of compact strings.

Optimal geometrical arrangements, such as the stacking of atoms, are of relevance in diverse disciplines. A classic problem is the determination of the optimal arrangement of spheres in three dimensions in order to achieve the highest packing fraction; only recently has it been proved that the answer for infinite systems is a face-centred-cubic lattice. This simply stated problem has had a profound impact in many areas, ranging from the crystallization and melting of atomic systems, to optimal packing of objects and the sub-division of space. Here we study an analogous problem--that of determining the optimal shapes of closely packed compact strings. This problem is a mathematical idealization of situations commonly encountered in biology, chemistry and physics, involving the optimal structure of folded polymeric chains. We find that, in cases where boundary effects are not dominant, helices with a particular pitch-radius ratio are selected. Interestingly, the same geometry is observed in helices in naturally occurring proteins.

Collagen↗

Fundamental patterns underlying gene expression profiles: simplicity from complexity.

Analysis of previously published sets of DNA microarray gene expression data by singular value decomposition has uncovered underlying patterns or "characteristic modes" in their temporal profiles. These patterns contribute unequally to the structure of the expression profiles. Moreover, the essential features of a given set of expression profiles are captured using just a small number of characteristic modes. This leads to the striking conclusion that the transcriptional response of a genome is orchestrated in a few fundamental patterns of gene expression change. These patterns are both simple and robust, dominating the alterations in expression of genes throughout the genome. Moreover, the characteristic modes of gene expression change in response to environmental perturbations are similar in such distant organisms as yeast and human cells. This analysis reveals simple regularities in the seemingly complex transcriptional transitions of diverse cells to new states, and these provide insights into the operation of the underlying genetic networks.

Cell Cycle Proteins↗

Topology of the fittest transportation network.

The presence or absence of loops in the emergent transportation networks, that are characterized by a minimum overall cost, is shown to depend on the convexity of the cost function for the local transportation of material. Our results are directly applicable to a variety of situations across disciplines.

Models, Cardiovascular↗

Role of secondary motifs in fast folding polymers: a dynamical variational principle.

A fascinating and open question challenging biochemistry, physics, and even geometry is the presence of highly regular motifs such as alpha helices in the folded state of biopolymers and proteins. Stimulating explanations ranging from chemical propensity to simple geometrical reasoning have been invoked to rationalize the existence of such secondary structures. We formulate a dynamical variational principle for selection in conformation space based on the requirement that the backbone of the native state of biologically viable polymers be rapidly accessible from the denatured state. The variational principle is shown to result in the emergence of helical order in compact structures.

Kinetics↗

Scoring functions in protein folding and design.

We present an analysis of the assumptions behind some of the most commonly used methods for evaluating the goodness of the fit between a sequence and a structure. Our studies on a lattice model show that methods based on statistical considerations are easy to use and can capture some of the features of protein-like sequences and their corresponding native states, but unfortunately are incapable of recognizing, with certainty, the native-like conformation of a sequence among a set of decoys. Meanwhile, an optimization method, entailing the determination of the parameters of an effective free energy of interaction, is much more reliable in recognizing the native state of a sequence. However, the statistical method is shown to perform quite well in tests of protein design.

Monte Carlo Method↗

Size and form in efficient transportation networks.

Many biological processes, from cellular metabolism to population dynamics, are characterized by allometric scaling (power-law) relationships between size and rate. An outstanding question is whether typical allometric scaling relationships--the power-law dependence of a biological rate on body mass--can be understood by considering the general features of branching networks serving a particular volume. Distributed networks in nature stem from the need for effective connectivity, and occur both in biological systems such as cardiovascular and respiratory networks and plant vascular and root systems, and in inanimate systems such as the drainage network of river basins. Here we derive a general relationship between size and flow rates in arbitrary networks with local connectivity. Our theory accounts in a general way for the quarter-power allometric scaling of living organisms, recently derived under specific assumptions for particular network geometries. It also predicts scaling relations applicable to all efficient transportation networks, which we verify from observational data on the river drainage basins. Allometric scaling is therefore shown to originate from the general features of networks irrespective of dynamical or geometric assumptions.

Biological Transport↗

Statistical mechanics of protein-like heteropolymers.

A strategy is outlined for obtaining the free energy of a typical designed heteropolymer. The design procedure considers the probability that the target conformation is occupied in comparison with all the other conformations that could house the given sequence. Numerical calculations on lattice heteropolymer models are presented to illustrate the key physical principles.

Animals↗

Design of proteins with hydrophobic and polar amino acids.

A two amino acid (hydrophobic and polar) scheme is used to perform the design on target conformations corresponding to the native states of 20 single chain proteins. Strikingly, the percentage of successful identification of the nature of the residues benchmarked against naturally occurring proteins and their homologues is around 75%, independent of the complexity of the design procedure. Typically, the lowest success rate occurs for residues such as alanine that have a high secondary structure functionality. Using a simple lattice model, we argue that one possible shortcoming of the model studied may involve the coarse-graining of the 20 kinds of amino acids into just two effective types.

Algorithms↗

Structure-based design of model proteins.

A structure-based, sequence-design procedure is proposed in which one considers a set of decoy structures that compete significantly with the target structure in being low energy conformations. The decoy structures are chosen to have strong overlaps in contacts with the putative native state. The procedure allows the design of sequences with large and small stability gaps in a random-bond heteropolymer model in both two and three dimensions by an appropriate assignment of the contact energies to both the native and nonnative contacts. The design procedure is also successfully applied to the two-dimensional HP model.

Amino Acid Sequence↗

Interaction potentials for protein folding.

We outline a general strategy for determining the effective coarse-grained interactions between the amino acids of a protein from the experimentally derived native-state structures. The method is, in principle, free from any adjustable or empirically determined parameters, and it is tested on simple models and compared with other existing approaches.

Amino Acids↗

Cell dynamics of folding in two-dimensional model proteins.

BACKGROUND: Functionally useful proteins are sequences of amino acids that fold rapidly under appropriate conditions into their native states. It is believed that rapid folders are sequences for which the folding dynamics entail the exploration of restricted conformations-the phase space can be thought of as a folding funnel. While there are many experimentally accessible predictions pertaining to the existence of such funnels and a coherent picture of the kinetics of folding has begun to emerge, there have been relatively few simple studies in the controlled setting of well-characterized lattice models. RESULTS: We design rapidly folding sequences by assigning the strongest couplings to the contacts present in a target native state in a two-dimensional model of heteropolymers. Such sequences have large folding transition temperatures and low glass transition temperatures. The dependence of median folding times on temperature is investigated. The pathways to folding and their dependence on the temperature are illustrated via a study of the cell dynamics-a mapping of the dynamics into motion within the space of the maximally compact cells. CONCLUSIONS: Folding funnels can be defined operationally in a coarse-grained sense by mapping the states of the system into maximally compact conformations and then by identifying significant connectivities between them.

Models, Chemical↗