Brendan Mumey

Antigen–antibody interface properties: Composition, residue interactions, and features of 53 non-redundant structures

The structures of protein antigen-antibody (Ag-Ab) interfaces contain information about how Ab recognize Ag as well as how Ag are folded to present surfaces for Ag recognition. As such, the Ab surface holds information about Ag folding that resides with the Ab-Ag interface residues and how they interact. In order to gain insight into the nature of such interactions, a data set comprised of 53 non-redundant 3D structures of Ag-Ab complexes was analyzed. We assessed the physical and biochemical features of the Ag-Ab interfaces and the degree to which favored interactions exist between amino acid residues on the corresponding interface surfaces. Amino acid compositional analysis of the interfaces confirmed the dominance of TYR in the Ab paratope-containing surface (PCS), with almost two fold greater abundance than any other residue. Additionally TYR had a much higher than expected presence in the PCS compared to the surface of the whole antibody (defined as the occurrence propensity), along with aromatics PHE, TRP, and to a lesser degree HIS and ILE. In the Ag epitope-containing surface (ECS), there were slightly increased occurrence propensities of TRP and TYR relative to the whole Ag surface, implying an increased significance over the compositionally most abundant LYS>ASN>GLU>ASP>ARG. This examination encompasses a large, diverse set of unique Ag-Ab crystal structures that help explain the biological range and specificity of Ag-Ab interactions. This analysis may also provide a measure of the significance of individual amino acid residues in phage display analysis of Ag binding.

Joint Stream Control and Scheduling in Multihop Wireless Networks with MIMO Links

MIMO links can significantly improve network throughput by supporting multiple concurrent data streams between a pair of nodes and suppressing wireless interference. In this paper, we formally define a new cross-layer optimization problem for MIMO-based multihop wireless networks, which is referred to as the joint stream control and scheduling problem (SCSP). We first present a constant factor approximation algorithm to solve the SCSP. In addition, we present a heuristic algorithm to improve the performance further, which is shown to be efficient in practice by our numerical results.

On Routing and Channel Selection in Cognitive Radio Mesh Networks

Secondary users in a cognitive radio mesh network may select from a set of available channels, provided that they do not disrupt communications among primary users. This ability can improve the overall network performance but introduces the question of how to best use the channels. This paper first considers the problem of selecting the channels to use given a routing path such that the end-to-end throughput along the path is maximized. We show that a dynamic programming-based approach can optimally solve the problem and, if the path satisfies a natural condition, in time, be linear in the length (hop count) of the path. In addition, the algorithm can easily be implemented in a distributed fashion. We also examine the harder joint problem of finding the best routing path and channel selection that maximizes the end-to-end throughput. We prove that obtaining a (2/3 + ε) approximation to the joint problem is NP-hard. We then present a heuristic algorithm for the joint problem and a second heuristic channel-aware routing-only algorithm. Numerical results are provided to demonstrate the effectiveness of the methods on several experimental scenarios.

Constraints on the conformation of the cytoplasmic face of dark-adapted and light-excited rhodopsin inferred from antirhodopsin antibody imprints.

Rhodopsin is the best‐understood member of the large G protein–coupled receptor (GPCR) superfamily. The G‐protein amplification cascade is triggered by poorly understood light‐induced conformational changes in rhodopsin that are homologous to changes caused by agonists in other GPCRs. We have applied the “antibody imprint” method to light‐activated rhodopsin in native membranes by using nine monoclonal antibodies (mAbs) against aqueous faces of rhodopsin. Epitopes recognized by these mAbs were found by selection from random peptide libraries displayed on phage. A new computer algorithm, FINDMAP, was used to map the epitopes to discontinuous segments of rhodopsin that are distant in the primary sequence but are in close spatial proximity in the structure. The proximity of a segment of the N‐terminal and the loop between helices VI and VIII found by FINDMAP is consistent with the X‐ray structure of the dark‐adapted rhodopsin. Epitopes to the cytoplasmic face segregated into two classes with different predicted spatial proximities of protein segments that correlate with different preferences of the antibodies for stabilizing the metarhodopsin I or metarhodopsin II conformations of light‐excited rhodopsin. Epitopes of antibodies that stabilize metarhodopsin II indicate conformational changes from dark‐adapted rhodopsin, including rearrangements of the C‐terminal tail and altered exposure of the cytoplasmic end of helix VI, a portion of the C‐3 loop, and helix VIII. As additional antibodies are subjected to antibody imprinting, this approach should provide increasingly detailed information on the conformation of light‐excited rhodopsin and be applicable to structural studies of other challenging protein targets.

A Markov-Based Reservation Algorithm for Wavelength Assignment in All-Optical Networks

Most routing and wavelength assignment algorithms for all-optical networks do not consider the potential problem of reservation connection, which occurs when two or more reservation requests compete for the same wavelength. Confliction can happen even if the network is only lightly loaded. In this paper, we propose a new reservation protocol Markov-based backward reservation (MBR) based on Markov modeling of the network traffic on optical links for resolving wavelength reservation confliction. Our simulations show that this new protocol can improve network performance as measured by decreased blocking probability. The MBR algorithm works best in small-hop-count networks with a comparatively small number of wavelengths per fiber compared to other frequently considered algorithms.

C-Terminal Tail Phosphorylation of N-Formyl Peptide Receptor: Differential Recognition of Two Neutrophil Chemoattractant Receptors by Monoclonal Antibodies NFPR1 and NFPR2

The N-formyl peptide receptor (FPR), a G protein-coupled receptor that binds proinflammatory chemoattractant peptides, serves as a model receptor for leukocyte chemotaxis. Recombinant histidine-tagged FPR (rHis-FPR) was purified in lysophosphatidyl glycerol (LPG) by Ni2+-NTA agarose chromatography to >95% purity with high yield. MALDI-TOF mass analysis (>36% sequence coverage) and immunoblotting confirmed the identity as FPR. The rHis-FPR served as an immunogen for the production of 2 mAbs, NFPR1 and NFPR2, that epitope map to the FPR C-terminal tail sequences, 305-GQDFRERLI-313 and 337-NSTLPSAEVE-346, respectively. Both mAbs specifically immunoblotted rHis-FPR and recombinant FPR (rFPR) expressed in Chinese hamster ovary cells. NFPR1 also recognized recombinant FPRL1, specifically expressed in mouse L fibroblasts. In human neutrophil membranes, both Abs labeled a 45–75 kDa species (peak Mr ∼60 kDa) localized primarily in the plasma membrane with a minor component in the lactoferrin-enriched intracellular fractions, consistent with FPR size and localization. NFPR1 also recognized a band of Mr ∼40 kDa localized, in equal proportions to the plasma membrane and lactoferrin-enriched fractions, consistent with FPRL1 size and localization. Only NFPR2 was capable of immunoprecipitation of rFPR in detergent extracts. The recognition of rFPR by NFPR2 is lost after exposure of cellular rFPR to f-Met-Leu-Phe (fMLF) and regained after alkaline phosphatase treatment of rFPR-bearing membranes. In neutrophils, NFPR2 immunofluorescence was lost upon fMLF stimulation. Immunoblotting ∼60 kDa species, after phosphatase treatment of fMLF-stimulated neutrophil membranes, was also enhanced. We conclude that the region 337–346 of FPR becomes phosphorylated after fMLF activation of rFPR-expressing Chinese hamster ovary cells and neutrophils.

Algorithmic Aspects of Communications in Multihop Wireless Networks with MIMO Links

MIMO links enable concurrent transmissions of multiple independent data streams between a pair of nodes, which can significantly improve network throughput. In this paper, we study the stream control and scheduling problems in multihop wireless networks with MIMO links. We present a constant factor approximation algorithm as well as an efficient heuristic algorithm for stream control. Moreover, we extend the results to incorporate TDMA-based scheduling and present effective heuristic algorithms to solve the joint Stream Control and Scheduling Problem (SCSP), whose efficiency is justified by simulation results.

Probe location in the presence of errors: a problem from DNA mapping

Abstract We consider the problem of mapping probes to locations along the genome given noisy pairwise distance data as input. The model used is quite general: The input consists of a collection of probe pairs and a distance interval for the genomic distance separating each pair. We call this the probe-location problem. Because the distance intervals are only known with some confidence level, some may be erroneous and must be identified and removed in order to find a consistent map. This is cast as the gang-filtering problem. To the authors knowledge, this is a previously unstudied combinatorial problem that can be viewed as a generalization of classical group testing. A randomized algorithm for this problem is proposed. All the algorithms were implemented and experimental results were collected for synthetic data sets (with and without errors) and real data from a region of human chromosome 4.

Enabling green networking with a power down approach

The most straightforward way to reduce network power consumption is to turn off idle links and nodes (switches/routers), which we call the power down approach. In a wired network, especially in a backbone network, many links are actually “bundles” of multiple physical cables and line cards that can be shut down independently. In this paper, we study the following routing problem for green networking in wired networks: Given a set of end-to-end communication sessions, determine how to route data traffic through the network such that total power consumption is minimized by turning off unused cables in bundled links and nodes, subject to the constraint that the traffic demand of each session is satisfied. We present an integer linear programming to provide optimal solutions. We also present two fast and effective heuristic algorithms to solve the problem in polynomial time. It has been shown by simulation results based on the Abilene network and the NSF network that the proposed heuristic algorithms consistently provide close-to-optimal solutions.

Leveraging Cooperative, Channel and Multiuser Diversities for Efficient Resource Allocation in Wireless Relay Networks

Relay stations can be deployed between mobile stations and base stations in a single-hop wireless network to extend its coverage and improve its capacity. In this paper, we exploit cooperative diversity, channel diversity and multiuser diversity gains in an OFDMA-based wireless relay network. We study a joint channel and relay assignment problem with the objective of maximizing a well-adopted utility function that can lead to a stable system. This problem turns out to be NP-hard. First, a mixed integer linear programming formulation is presented to provide optimal solutions. We then present three simple greedy algorithms to solve the problem in polynomial time, namely, Greedy-ChannelFirst, Greedy-RelayFirst and Greedy-Joint. We also perform a comprehensive theoretical analysis for the performance of the proposed algorithms. Our analytical results show the Greedy-ChannelFirst algorithm is a constant factor approximation algorithm which always provides a solution whose objective value is guaranteed to be no smaller than the optimal value multiplied by a constant less than 1; however, the other two algorithms do not provide a similar performance guarantee. Extensive simulation results have been presented to show that all three proposed algorithms perform very well on average cases.