Mala L. Radhakrishnan

Manipulation of magnetic microbeads in suspension using micromagnetic systems fabricated with soft lithography

Current-carrying microcircuits can generate strong magnetic-field gradients; these gradients, in turn, can control the position of magnetic microbeads in aqueous suspension. Micromagnetic systems were prepared using two representative soft lithography techniques—micromolding in capillaries and microtransfer molding—combined with electrodeposition. They can capture microbeads from solution, hold them in a fixed position, and move them along complex paths. Simply changing the current flowing in the systems can dynamically reconfigure the paths. The manipulation of magnetic microbeads using microfabricated circuits should expand current sample handling capabilities for biotechnology and combinational technology with or without the presence of net fluid flow and microfluidic channels.

A dual receptor crosstalk model of G-protein-coupled signal transduction.

Macrophage cells that are stimulated by two different ligands that bind to G-protein-coupled receptors (GPCRs) usually respond as if the stimulus effects are additive, but for a minority of ligand combinations the response is synergistic. The G-protein-coupled receptor system integrates signaling cues from the environment to actuate cell morphology, gene expression, ion homeostasis, and other physiological states. We analyze the effects of the two signaling molecules complement factors 5a (C5a) and uridine diphosphate (UDP) on the intracellular second messenger calcium to elucidate the principles that govern the processing of multiple signals by GPCRs. We have developed a formal hypothesis, in the form of a kinetic model, for the mechanism of action of this GPCR signal transduction system using data obtained from RAW264.7 macrophage cells. Bayesian statistical methods are employed to represent uncertainty in both data and model parameters and formally tie the model to experimental data. When the model is also used as a tool in the design of experiments, it predicts a synergistic region in the calcium peak height dose response that results when cells are simultaneously stimulated by C5a and UDP. An analysis of the model reveals a potential mechanism for crosstalk between the Gαi-coupled C5a receptor and the Gαq-coupled UDP receptor signaling systems that results in synergistic calcium release.

Symmetric Signaling by an Asymmetric 1 Erythropoietin: 2 Erythropoietin Receptor Complex

Via sites 1 and 2, erythropoietin binds asymmetrically to two identical receptor monomers, although it is unclear how asymmetry affects receptor activation and signaling. Here we report the design and validation of two mutant erythropoietin receptors that probe the role of individual members of the receptor dimer by selectively binding either site 1 or site 2 on erythropoietin. Ba/F3 cells expressing either mutant receptor do not respond to erythropoietin, but cells co-expressing both receptors respond to erythropoietin by proliferation and activation of the JAK2-Stat5 pathway. A truncated receptor with only one cytosolic tyrosine (Y343) is sufficient for signaling in response to erythropoietin, regardless of the monomer on which it is located. Similarly, only one receptor in the dimer needs a juxtamembrane hydrophobic L253 or W258 residue, essential for JAK2 activation. We conclude that despite asymmetry in the ligand-receptor interaction, both sides are competent for signaling, and appear to signal equally.

Designing electrostatic interactions in biological systems via charge optimization or combinatorial approaches: insights and challenges with a continuum electrostatic framework

Electrostatic interactions between biological molecules are crucially influenced by their aqueous environment, with efficient and accurate models of solvent effects required for robust molecular design strategies. Continuum electrostatic models provide a reasonable balance between computational efficiency and accurate system representation. In this article, I review two specific molecular design strategies, charge optimization and combinatorial design, paying particular attention to how the continuum framework (also briefly described herein) successfully enables both theoretical insights and molecular designs and presents a challenge in design applications due to what I call “the isostericity constraint.” Efforts to work around the isostericity constraint and other challenges are discussed. Additionally, particular emphasis is placed on using such models in the rational design of particularly tight, specific, or promiscuous interactions, in keeping with the increased sophistication of current molecular design applications.

Investigating the nucleic acid interactions of histone‐derived antimicrobial peptides

While many antimicrobial peptides (AMPs) disrupt bacterial membranes, some translocate into bacteria and interfere with intracellular processes. Buforin II and DesHDAP1 are thought to kill bacteria by interacting with nucleic acids. Here, molecular modeling and experimental measurements are used to show that neither nucleic acid binding peptide selectively binds DNA sequences. Simulations and experiments also show that changing lysines to arginines enhances DNA binding, suggesting that including additional guanidinium groups is a potential strategy to engineer more potent AMPs. Moreover, the lack of binding specificity may make it more difficult for bacteria to evolve resistance to these and other similar AMPs.

The Effect of Macromolecular Crowding on the Electrostatic Component of Barnase–Barstar Binding: A Computational, Implicit Solvent-Based Study

Macromolecular crowding within the cell can impact both protein folding and binding. Earlier models of cellular crowding focused on the excluded volume, entropic effect of crowding agents, which generally favors compact protein states. Recently, other effects of crowding have been explored, including enthalpically-related crowder–protein interactions and changes in solvation properties. In this work, we explore the effects of macromolecular crowding on the electrostatic desolvation and solvent-screened interaction components of protein–protein binding. Our simple model enables us to focus exclusively on the electrostatic effects of water depletion on protein binding due to crowding, providing us with the ability to systematically analyze and quantify these potentially intuitive effects. We use the barnase–barstar complex as a model system and randomly placed, uncharged spheres within implicit solvent to model crowding in an aqueous environment. On average, we find that the desolvation free energy penalties incurred by partners upon binding are lowered in a crowded environment and solvent-screened interactions are amplified. At a constant crowder density (fraction of total available volume occupied by crowders), this effect generally increases as the radius of model crowders decreases, but the strength and nature of this trend can depend on the water probe radius used to generate the molecular surface in the continuum model. In general, there is huge variation in desolvation penalties as a function of the random crowder positions. Results with explicit model crowders can be qualitatively similar to those using a lowered “effective” solvent dielectric to account for crowding, although the “best” effective dielectric constant will likely depend on multiple system properties. Taken together, this work systematically demonstrates, quantifies, and analyzes qualitative intuition-based insights into the effects of water depletion due to crowding on the electrostatic component of protein binding, and it provides an initial framework for future analyses.

Multiple drugs and multiple targets: an analysis of the electrostatic determinants of binding between non-nucleoside HIV-1 reverse transcriptase inhibitors and variants of HIV-1 RT.

We present a systematic, computational analysis of the electrostatic component of binding of three HIV‐1 RT inhibitors—nevirapine (NVP), efavirenz (EFV), and the recently approved rilpivirine (RPV)—to wild‐type (WT) and mutant variants of RT. Electrostatic charge optimization was applied to determine how suited each molecules charge distribution is for binding WT and individual mutants of HIV‐1 RT. Although the charge distributions of NVP and EFV are rather far from being optimal for tight binding, RPVs charge distribution is close to the theoretical, optimal charge distribution for binding WT HIV‐1 RT, although slight changes in charge can dramatically impact binding energetics. Moreover, toward the L100I/K103N double mutant, RPVs charge distribution is quite far from optimal. We also determine the contributions of chemical moieties on each molecule toward the electrostatic component of binding and show that different regions of a drug molecule may be used for recognition by different RT variants. The electrostatic contributions of certain RT residues toward drug binding are also computed to highlight critical residues for each interaction. Finally, the charge distribution of RPV is optimized to promiscuously bind to three RT variants rather than to each one in turn, with the resulting charge distribution being a compromise between the optimal charge distributions to each individual variant. Taken together, this work demonstrates that even in a binding site considered quite hydrophobic, electrostatics play a subtle yet varying role that must be considered in designing next‐generation molecules that recognize rapidly mutating targets. Proteins 2012.

Effect of the Spiroiminodihydantoin Lesion on Nucleosome Stability and Positioning.

DNA is constantly under attack by oxidants, generating a variety of potentially mutagenic covalently modified species, including oxidized guanine base products. One such product is spiroiminodihydantoin (Sp), a chiral, propeller-shaped lesion that strongly destabilizes the DNA helix in its vicinity. Despite its unusual shape and thermodynamic effect on double-stranded DNA structure, DNA duplexes containing the Sp lesion form stable nucleosomes upon being incubated with histone octamers. Indeed, among six different combinations of lesion location and stereochemistry, only two duplexes display a diminished ability to form nucleosomes, and these only by ∼25%; the other four are statistically indistinguishable from the control. Nonetheless, kinetic factors also play a role: when the histone proteins have less time during assembly of the core particle to sample both lesion-containing and normal DNA strands, they are more likely to bind the Sp lesion DNA than during slower assembly processes that better approximate thermodynamic equilibrium. Using DNase I footprinting and molecular modeling, we discovered that the Sp lesion causes only a small perturbation (±1-2 bp) on the translational position of the DNA within the nucleosome. Each diastereomeric pair of lesions has the same effect on nucleosome positioning, but lesions placed at different locations behave differently, illustrating that the location of the lesion and not its shape serves as the primary determinant of the most stable DNA orientation.

Dead-End Elimination as a Heuristic for Min-Cut Image Segmentation

We apply the dead-end elimination (DEE) strategy from protein design as a heuristic for the max-flow/min-cut formulation of the image segmentation problem. DEE combines aspects of constraint propagation and branch-and-bound to eliminate solutions incompatible with global optimization of the objective function. Though DEE can be used for segmentation into an arbitrary number of regions, in this paper we evaluate only the case of binary segmentation. We provide a runtime analysis and evaluation of DEE applied to two min-cut algorithms. Preliminary results show that DEE consistently reduces the search space for the Edmonds-Karp algorithm; tuning DEE as a heuristic for Boykov-Kolmogorov and other algorithms is future work.

Molecular mechanisms and design principles for promiscuous inhibitors to avoid drug resistance: Lessons learned from HIV‐1 protease inhibition

Molecular recognition is central to biology and ranges from highly selective to broadly promiscuous. The ability to modulate specificity at will is particularly important for drug development, and discovery of mechanisms contributing to binding specificity is crucial for our basic understanding of biology and for applications in health care. In this study, we used computational molecular design to create a large dataset of diverse small molecules with a range of binding specificities. We then performed structural, energetic, and statistical analysis on the dataset to study molecular mechanisms of achieving specificity goals. The work was done in the context of HIV‐1 protease inhibition and the molecular designs targeted a panel of wild‐type and drug‐resistant mutant HIV‐1 protease structures. The analysis focused on mechanisms for promiscuous binding to bind robustly even to resistance mutants. Broadly binding inhibitors tended to be smaller in size, more flexible in chemical structure, and more hydrophobic in nature compared to highly selective ones. Furthermore, structural and energetic analyses illustrated mechanisms by which flexible inhibitors achieved binding; we found ligand conformational adaptation near mutation sites and structural plasticity in targets through torsional flips of asymmetric functional groups to form alternative, compensatory packing interactions or hydrogen bonds. As no inhibitor bound to all variants, we designed small cocktails of inhibitors to do so and discovered that they often jointly covered the target set through mechanistic complementarity. Furthermore, using structural plasticity observed in experiments, and potentially in simulations, is suggested to be a viable means of designing adaptive inhibitors that are promiscuous binders. Proteins 2015; 83:351–372.