NETWORK TOPOLOGY IN HUMAN PROTEIN INTERACTION DATA PREDICTS FUNCTIONAL ASSOCIATION

High-throughput assays, such as yeast two-hybrid system, have generated a huge amount of protein-protein interaction (PPI) data in the past decade. This tremendously increases the need for developing reliable methods to systematically and automatically suggest protein functions and relationships between them. With the available PPI data, it is now possible to study the functions and relationships in the context of a large-scale network. To data, several network-based schemes have been provided to effectively annotate protein functions on a large scale. However, due to those inherent noises in high-throughput data generation, new methods and algorithms should be developed to increase the reliability of functional annotations. Previous work in a yeast PPI network (Samanta and Liang, 2003) has shown that the local connection topology, particularly for two proteins sharing an unusually large number of neighbors, can predict functional associations between proteins, and hence suggest their functions. One advantage of the work is that their algorithm is not sensitive to noises (false positives) in high-throughput PPI data. In this study, we improved their prediction scheme by developing a new algorithm and new methods which we applied on a human PPI network to make a genome-wide functional inference. We used the new algorithm to measure and reduce the influence of hub proteins on detecting functionally associated proteins. We used the annotations of the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) as independent and unbiased benchmarks to evaluate our algorithms and methods within the human PPI network. We showed that, compared with the previous work from Samanta and Liang, our algorithm and methods developed in this study improved the overall quality of functional inferences for human proteins. By applying the algorithms to the human PPI network, we obtained 4,233 significant functional associations among 1,754 proteins. Further comparisons of their KEGG and GO annotations allowed us to assign 466 KEGG pathway annotations to 274 proteins and 123 GO annotations to 114 proteins with estimated false discovery rates of <21% for KEGG and <30% for GO. We clustered 1,729 proteins by their functional associations and made pathway analysis to identify several subclusters that are highly enriched in certain signaling pathways. Particularly, we performed a detailed analysis on a subcluster enriched in the transforming growth factor β signaling pathway (P<10-50) which is important in cell proliferation and tumorigenesis. Analysis of another four subclusters also suggested potential new players in six signaling pathways worthy of further experimental investigations. Our study gives clear insight into the common neighbor-based prediction scheme and provides a reliable method for large-scale functional annotations in this post-genomic era.

Doctor-patient communication in the medical interaction: Context, implications, and practice

Effective communication; whether from an interpersonal, mass media, or global perspective, is a critical component in public health. It is an essential conduit in increasing public awareness of available health resources, potential health hazards and related disease prevention strategies, and in delivering better health care. Within this context, available literature asserts doctor-patient communication as central to healthcare delivery. It has been shown to affect patient health outcomes, satisfaction with care, adherence to treatment recommendations, and even understanding of medical information. While research supports the essential imperative of interventions aimed at teaching doctors and patients the communication skills necessary for a successful and meaningful medical interaction, most interventions to date, focus on teaching these communication skills to doctors and seem to rely, largely, on mass media for providing patients with the information needed to increase communication efficacy. This study sought to fill a significant gap in the doctor-patient communication literature by reviewing the context of the doctor-patient exchange in the medical interaction, the implications of this exchange in resulting care of the patient, and the potential improvements to practice through interventions aimed at improving the communication exchange. Closing with an evaluation of a patient-centered communication intervention, the “How to Talk to Your Doctor” (HTTTYD) program that combines previously identified optimal strategies for improving communication between doctors and patients, this study examined the patients’ perspective of their potential as better communicators in the medical interaction. ^ Specific Aims, Hypotheses or Questions (Aim I) To examine the context of health communication within a public health framework and its relation to health care delivery. (Aim II) To review doctor-patient communication as a central focus within health care delivery and the resulting implications to patient care. (Aim III) To assess the utility of interventions to improve doctor-patient communication. Specifically, to evaluate the effectiveness of a patient-centered community education intervention, the “How to Talk to Your Doctor” (HTTTYD) program, aimed at improving patient communication efficacy.^

The roles of electrostatic charge pairing in the interaction between cytochrome P-450 and NADPH-cytochrome P-450 reductase

The cytochrome P450 enzyme catalysis requires two electrons transferred from NADPH-cytochrome P450 reductase (reductase) to P450. Electrostatic charge-pairing has been proposed to be one of the major forces in the interaction between P450 and reductase. In order to obtain further insight into the molecular basis for the protein interaction, I used two methods, chemical modification and specific anti-peptide antibodies, to study the involvement and importance of charged amino acid residues. Acetylation of lysine residues of P450c and P450b by acetic anhydride dramatically inhibited the reductase-supported P450c-dependent ethoxycoumarin hydroxylation activity, but P450 activity supported by cumene hydroperoxide is relatively unchanged. The modification of lysine residues of P450c and P450b did not grossly disturb the protein conformation as revealed by several spectral studies. This differential effect of lysine modification on the P450 activity in the system reconstituted with reductase versus the system supported by cumene hydroperoxide suggested an important role for P450 lysine residues in the interaction with reductase. Using $\rm\sp{14}C$-acetic anhydride, P450 lysine residues were labelled and further identified on P450c and P450b. Those lysine residues are at position 97, 271, 279, and 407 for P450c, and 251, 384, 422, 433, and 473 for P450b. Alignment of those identified lysine residues on P450c and P450b with amino acid residues identified in other studies indicated those residues reside in three major sequence areas. Modification of arginine residues of P450b by phenylglyoxal and 2, 3-butanedione have no significant effect on P450 activity either supported by NADPH and reductase or supported by cumene hydroperoxide. Further studies using $\rm\sp{14}C$-phenylglyoxal reveals that no incorporation of phenylglyoxal into P450b was found. These results demonstrated a predominant role of lysine residues of P450 in the electrostatic interaction with reductase. To understand the protein binding sites on each of P450 and reductase, I generated three anti-peptide antibodies against regions on reductase and five anti-peptide antibodies against five putative reductase binding sites on P450c. These anti-peptide antibodies were affinity purified and characterized on ELISA and by Western blot analysis. Inhibition experiments using these antibodies demonstrated that regions 109-120 and 204-220 of reductase are probably the two major binding sites for P450. The association of reductase with cytochromes P450 and cytochrome c may rely on different mechanisms. The data from experiments using anti-peptide (P450c) antibodies supports the important role of P450c lysine residues 271/279 and 458/460 in the interaction with reductase. ^

Structural studies of cytochrome P4501A1: Identification of substrate and cumene hydroperoxide binding regions in the active site of P4501A1 and characterization of the P4501A1 interaction with cytochrome P450 reductase

Cytochromes P450 are a superfamily of heme-thiolate proteins that function in a concert with another protein, cytochrome P450 reductase, as terminal oxidases of an enzymatic system catalyzing the metabolism of a variety of foreign compounds and endogenous substrates. In order to better understand P450s catalytic mechanism and substrate specificity, information about the structure of the active site is necessary. Given the lack of a crystal structure of mammalian P450, other methods have been used to elucidate the substrate recognition and binding site structure in the active center. In this project I utilized the photoaffinity labeling technique and site-directed mutagenesis approach to gain further structural insight into the active site of mammalian cytochrome P4501AI and examine the role of surface residues in the interaction of P4501A1 with the reductase. ^ Four crosslinked peptides were identified by photoaffinity labeling using diazido benzphetamine as a substrate analog. Alignment of the primary structure of cytochrome P4501A1 with that of bacterial cytochrome P450102 (the crystal structure of which is known) revealed that two of the isolated crosslinked peptides can be placed in the vicinity of heme (in the L helix region and β10-β11 sheet region of cytochrome P450102) and could be involved in substrate binding. The other two peptides were located on the surface of the protein with the label bound specifically to Lys residues that were proposed to be involved in reductase-P450 interaction. ^ Alternatively, it has been shown that some of the organic hydroperoxides can support P450 catalyzed reactions in the absence of NADPH, O2 and reductase. By means of photoaffinity labeling the cumene hydroperoxide binding region was identified. Using azidocumene as the photoaffinity label, the tripeptide T501-L502-K503 was shown to be the site where azidocumene covalently binds to P4501A1. The sequence alignment of cytochrome P4501A1 with cytochrome P450102 predicts that this region might correspond to β-sheet structure localized on the distal side of the heme ring near the I helix and the oxygen binding pocket. The role of Thr501 in the cumene hydroperoxide binding was confirmed by mutations of this residue and kinetic analysis of the effects of the mutations. ^ In addition, the role of two lysine residues, Lys271 and Lys279, in the interaction with reductase was examined by means of site-directed mutagenesis. The lysine residues were substituted with isoleucine and enzymatic activity of the wild type and the mutants were compared in reductase- and cumene hydroperoxide-supported systems. The lysine 279 residue has been shown to play a critical role in the P4501A1-reductase interaction. ^

A novel method for evaluating an interaction effect of correlated continuous covariates in a linear model

Interaction effect is an important scientific interest for many areas of research. Common approach for investigating the interaction effect of two continuous covariates on a response variable is through a cross-product term in multiple linear regression. In epidemiological studies, the two-way analysis of variance (ANOVA) type of method has also been utilized to examine the interaction effect by replacing the continuous covariates with their discretized levels. However, the implications of model assumptions of either approach have not been examined and the statistical validation has only focused on the general method, not specifically for the interaction effect.^ In this dissertation, we investigated the validity of both approaches based on the mathematical assumptions for non-skewed data. We showed that linear regression may not be an appropriate model when the interaction effect exists because it implies a highly skewed distribution for the response variable. We also showed that the normality and constant variance assumptions required by ANOVA are not satisfied in the model where the continuous covariates are replaced with their discretized levels. Therefore, naïve application of ANOVA method may lead to an incorrect conclusion. ^ Given the problems identified above, we proposed a novel method modifying from the traditional ANOVA approach to rigorously evaluate the interaction effect. The analytical expression of the interaction effect was derived based on the conditional distribution of the response variable given the discretized continuous covariates. A testing procedure that combines the p-values from each level of the discretized covariates was developed to test the overall significance of the interaction effect. According to the simulation study, the proposed method is more powerful then the least squares regression and the ANOVA method in detecting the interaction effect when data comes from a trivariate normal distribution. The proposed method was applied to a dataset from the National Institute of Neurological Disorders and Stroke (NINDS) tissue plasminogen activator (t-PA) stroke trial, and baseline age-by-weight interaction effect was found significant in predicting the change from baseline in NIHSS at Month-3 among patients received t-PA therapy.^