Strengthening and Sustaining Inter-Institutional Research Collaborations and Partnerships.

Inter-institutional collaborations and partnerships play fundamental roles in developing and diversifying the basic biomedical, behavioral, and clinical research enterprise at resource-limited, minority-serving institutions. In conjunction with the Research Centers in Minority Institutions (RCMI) Program National Conference in Bethesda, Maryland, in December 2019, a special workshop was convened to summarize current practices and to explore future strategies to strengthen and sustain inter-institutional collaborations and partnerships with research-intensive majority-serving institutions. Representative examples of current inter-institutional collaborations at RCMI grantee institutions are presented. Practical approaches used to leverage institutional resources through collaborations and partnerships within regional and national network programs are summarized. Challenges and opportunities related to such collaborations are provided.

Aerobic Exercise Training-Induced Changes on DNA Methylation in Mild Cognitively Impaired Elderly African Americans: Gene, Exercise, and Memory Study - GEMS-I.

BACKGROUND: DNA methylation at CpG sites is a vital epigenetic modification of the human genome affecting gene expression, and potentially, health outcomes. However, evidence is just budding on the effects of aerobic exercise-induced adaptation on DNA methylation in older mild cognitively impaired (MCI) elderly African American (AAs). Therefore, we examined the effects of a 6-month aerobic exercise-intervention on genome-wide DNA methylation in elderly AA MCI volunteers. DESIGN: Elderly AA volunteers confirmed MCI assigned into a 6-month program of aerobic exercise (eleven participants) underwent a 40-min supervised-training 3-times/week and controls (eight participants) performed stretch training. Participants had maximal oxygen consumption (VO2max) test and Genome-wide methylation levels at CpG sites using the Infinium HumanMethylation450 BeadChip assay at baseline and after a 6-month exercise program. We computed false discovery rates (FDR) using Sidak to account for multiplicity of tests and performed quantitative real-time polymerase chain-reaction (qRT-PCR) to confirm the effects of DNA methylations on expression levels of the top 5 genes among the aerobic participants. CpG sites identified from aerobic-exercise participants were similarly analyzed by the stretch group to quantify the effects of exercise-induced methylation changes among the group of stretch participants. RESULTS: Eleven MCI participants (aerobic: 73% females; mean age 72.3 ± 6.6 years) and eight MCI participants (stretch: 75% female; mean age 70.6 ± 6.7 years) completed the training. Aerobic exercise-training was associated with increases in VO2max and with global hypo- and hypermethylation changes. The most notable finding was CpG hypomethylation within the body of the VPS52 gene (P = 5.4 × 10-26), a Golgi-associated protein, involved in intracellular protein trafficking including amyloid precursor protein. qRT-PCR confirmed a nearly twofold increased expression of VPS52. Other top findings with FDR q-value < 10-5, include hypomethylations of SCARB1 (8.8 × 10-25), ARTN (6.1 × 10-25), NR1H2 (2.1 × 10-18) and PPP2R5D (9.8 × 10-18). CONCLUSION: We conclude that genome-wide DNA methylation patterns is associated with exercise training-induced methylation changes. Identification of methylation changes around genes previously shown to interact with amyloid biology, intracellular protein trafficking, and lipoprotein regulations provide further support to the likely protective effect of exercise in MCI. Future studies in larger samples are needed to confirm our findings.

Association of Genetic Ancestry With DNA Methylation Changes in Prostate Cancer Disparity.

BACKGROUND: We hypothesized that ancestry-mediated methylated DNA changes may drive racial and ethnic disparity in prostate cancer (PCa). To test this hypothesis, we analyzed genetic ancestry and association with DNA methylation changes in PCa disparity. MATERIALS AND METHODS: Pyrosequencing and ancestry informative markers were used for DNA methylation and genetic ancestry testing, respectively. RESULTS: Using Spearman rho rank correlation test, the data demonstrated significant (p<0.05) and variable association between African-American ancestry and DNA methylation for all genes investigated in prostate tissues. CONCLUSION: Genetic ancestry influences DNA methylation and this modifying factor must be considered in epigenetic association studies in populations of admixed patients.

Investigation of Chiral Recognition by Molecular Micelles with Molecular Dynamics Simulations.

Molecular dynamics simulations were used to characterize the binding of the chiral drugs chlorthalidone and lorazepam to the molecular micelle poly-(sodium undecyl-(L)-leucine-valine). The project's goal was to characterize the nature of chiral recognition in capillary electrophoresis separations that use molecular micelles as the chiral selector. The shapes and charge distributions of the chiral molecules investigated, their orientations within the molecular micelle chiral binding pockets, and the formation of stereoselective intermolecular hydrogen bonds with the molecular micelle were all found to play key roles in determining where and how lorazepam and chlorthalidone enantiomers interacted with the molecular micelle.

The diversity and disparity in biomedical informatics (DDBI) workshop.

The Diversity and Disparity in Biomedical Informatics (DDBI) workshop will be focused on complementary and critical issues concerned with enhancing diversity in the informatics workforce as well as diversity in patient cohorts. According to the National Institute of Minority Health and Health Disparities (NIMHD) at the NIH, diversity refers to the inclusion of the following traditionally underrepresented groups: African Americans/Blacks, Asians (>30 countries), American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, Latino or Hispanic (20 countries). Gender, culture, and socioeconomic status are also important dimensions of diversity, which may define some underrepresented groups. The under-representation of specific groups in both the biomedical informatics workforce as well as in the patient-derived data that is being used for research purposes has contributed to an ongoing disparity; these groups have not experienced equity in contributing to or benefiting from advancements in informatics research. This workshop will highlight innovative efforts to increase the pool of minority informaticians and discuss examples of informatics research that addresses the health concerns that impact minority populations. This workshop topics will provide insight into overcoming pipeline issues in the development of minority informaticians while emphasizing the importance of minority participation in health related research. The DDBI workshop will occur in two parts. Part I will discuss specific minority health & health disparities research topics and Part II will cover discussions related to overcoming pipeline issues in the training of minority informaticians.

Population differentiation in allele frequencies of obesity-associated SNPs.

BACKGROUND: Obesity is emerging as a global health problem, with more than one-third of the world's adult population being overweight or obese. In this study, we investigated worldwide population differentiation in allele frequencies of obesity-associated SNPs (single nucleotide polymorphisms). RESULTS: We collected a total of 225 obesity-associated SNPs from a public database. Their population-level allele frequencies were derived based on the genotype data from 1000 Genomes Project (phase 3). We used hypergeometric model to assess whether the effect allele at a given SNP is significantly enriched or depleted in each of the 26 populations surveyed in the 1000 Genomes Project with respect to the overall pooled population. Our results indicate that 195 out of 225 SNPs (86.7%) possess effect alleles significantly enriched or depleted in at least one of the 26 populations. Populations within the same continental group exhibit similar allele enrichment/depletion patterns whereas inter-continental populations show distinct patterns. Among the 225 SNPs, 15 SNPs cluster in the first intron region of the FTO gene, which is a major gene associated with body-mass index (BMI) and fat mass. African populations exhibit much smaller blocks of LD (linkage disequilibrium) among these15 SNPs while European and Asian populations have larger blocks. To estimate the cumulative effect of all variants associated with obesity, we developed the personal composite genetic risk score for obesity. Our results indicate that the East Asian populations have the lowest averages of the composite risk scores, whereas three European populations have the highest averages. In addition, the population-level average of composite genetic risk scores is significantly correlated (R2 = 0.35, P = 0.0060) with obesity prevalence. CONCLUSIONS: We have detected substantial population differentiation in allele frequencies of obesity-associated SNPs. The results will help elucidate the genetic basis which may contribute to population disparities in obesity prevalence.

Novel drug design for Chagas disease via targeting Trypanosoma cruzi tubulin: Homology modeling and binding pocket prediction on Trypanosoma cruzi tubulin polymerization inhibition by naphthoquinone derivatives.

Chagas disease, also called American trypanosomiasis, is a parasitic disease caused by Trypanosoma cruzi (T. cruzi). Recent findings have underscored the abundance of the causative organism, (T. cruzi), especially in the southern tier states of the US and the risk burden for the rural farming communities there. Due to a lack of safe and effective drugs, there is an urgent need for novel therapeutic options for treating Chagas disease. We report here our first scientific effort to pursue a novel drug design for treating Chagas disease via the targeting of T. cruzi tubulin. First, the anti T. cruzi tubulin activities of five naphthoquinone derivatives were determined and correlated to their anti-trypanosomal activities. The correlation between the ligand activities against the T. cruzi organism and their tubulin inhibitory activities was very strong with a Pearson's r value of 0.88 (P value <0.05), indicating that this class of compounds could inhibit the activity of the trypanosome organism via T. cruzi tubulin polymerization inhibition. Subsequent molecular modeling studies were carried out to understand the mechanisms of the anti-tubulin activities, wherein, the homology model of T. cruzi tubulin dimer was generated and the putative binding site of naphthoquinone derivatives was predicted. The correlation coefficient for ligand anti-tubulin activities and their binding energies at the putative pocket was found to be r=0.79, a high correlation efficiency that was not replicated in contiguous candidate pockets. The homology model of T. cruzi tubulin and the identification of its putative binding site lay a solid ground for further structure based drug design, including molecular docking and pharmacophore analysis. This study presents a new opportunity for designing potent and selective drugs for Chagas disease.

Molecular Dynamics Simulation and NMR Investigation of the Association of the ß-Blockers Atenolol and Propranolol with a Chiral Molecular Micelle.

Molecular dynamics simulations and NMR spectroscopy were used to compare the binding of two ß-blocker drugs to the chiral molecular micelle poly-(sodium undecyl-(L)-leucine-valine). The molecular micelle is used as a chiral selector in capillary electrophoresis. This study is part of a larger effort to understand the mechanism of chiral recognition in capillary electrophoresis by characterizing the molecular micelle binding of chiral compounds with different geometries and charges. Propranolol and atenolol were chosen because their structures are similar, but their chiral interactions with the molecular micelle are different. Molecular dynamics simulations showed both propranolol enantiomers inserted their aromatic rings into the molecular micelle core and that (S)-propranolol associated more strongly with the molecular micelle than (R)-propranolol. This difference was attributed to stronger molecular micelle hydrogen bonding interactions experienced by (S)-propranolol. Atenolol enantiomers were found to bind near the molecular micelle surface and to have similar molecular micelle binding free energies.

A Molecular Dynamics Simulation Study of the Association of 1,1'-Binaphthyl-2,2'-diyl hydrogenphosphate Enantiomers with a Chiral Molecular Micelle.

Molecular dynamics (MD) simulations were used to investigate the binding of 1,1'-binaphthyl-2,2'-diyl hydrogenphosphate (BNP) enantiomers to the molecular micelle poly-(sodium undecyl-(L,L)-leucine-valine) (poly(SULV)). Poly(SULV) is used as a chiral selector in capillary electrophoresis separations. Four poly(SULV) binding pockets were identified and either (R)-BNP or (S)-BNP were docked into each pocket. MD simulations were then used to identify the preferred BNP binding site. Within the preferred site, both enantiomers formed hydrogen bonds with poly(SULV) and penetrated into the poly(SULV) core. Comparisons of BNP enantiomer binding to the preferred poly(SULV) pocket showed that (S)-BNP formed stronger hydrogen bonds, moved deeper into the binding site, and had a lower poly(SULV) binding free energy than the (R) enantiomer. Finally, MD simulation results were in agreement with capillary electrophoresis and NMR experiments. Each technique showed (S)-BNP interacted more strongly with poly(SULV) than (R)-BNP and that the site of chiral recognition was near the poly(SULV) leucine chiral center.

A Molecular Dynamics Simulation Study of Two Dipeptide Based Molecular Micelles: Effect of Amino Acid Order.

Molecular dynamics (MD) simulations were used to compare the structures of the chiral molecular micelles (MM) poly-(sodium undecyl-(L,L)-leucine-valine) (poly(SULV)) and poly-(sodium undecyl-(L,L)-valine-leucine) (poly (SUVL)). Both MM contained polymerized surfactant monomers tenninated by chiral dipeptide headgroups. The study was undertaken to investigate why poly(SULV) is generally a better chiral selector compared to poly(SUVL) in electrokinetic chromatography separations. When comparing poly(SULV) to poly(SUVL), poly(SULV) had the more conformational flexible dipeptide headgroup and hydrogen bond analyses revealed that the poly(SULV) headgroup conformation allowed a larger number of intramolecular hydrogen bonds to form between monomer chains. In addition, a larger number of water molecules surrounded the chiral centers of the poly(SULV) molecular micelle. Poly(SULV) was also found to have a larger solvent accessible surface area (SASA) than poly(SUVL) and fluctuations in the poly(SULV) SASA during the MD simulation allowed dynamic monomer chain motions expected to be important in chiral recognition to be identified. Finally, approximately 50% of the Na+ counterions were found in the first three solvation shells surrounding both MM, with the remainder located in the bulk. Overall the MD simulations point to both greater headgroup flexibility and solvent and analyte access to the chiral centers of the dipeptide headgroup as factors contributing to the enhanced chiral selectivity observed with poly(SULV).

Identification of two post-translational modifications via tandem mass spectrometry.

Post-Translational Modifications (PTMs) play most important roles in the accomplishment of biological processes and molecular functions. It is challenging to identify two PTMs for a tandem mass spectrum. In this paper, we proposed a new algorithm to detect two PTMs with unknown types. First, we constructed a Pair of Peak Set (PPS) which is composed of pairs of peaks that have the highest sum of intensities. Second, we revealed the relationship between PPS and the whole experimental spectrum. Third, a series of logic conditions was proposed to detect PTMs from a MS/MS spectrum. Finally, we used a scoring function to rank the candidate hits. We applied the method to a large MS/MS data set and the experimental results demonstrated that the proposed method achieved better performance of identifying any types of PTMs in a blind mode than current existing methods.

Investigation of Chiral Molecular Micelles by NMR Spectroscopy and Molecular Dynamics Simulation.

NMR spectroscopy and molecular dynamics (MD) simulation analyses of the chiral molecular micelles poly-(sodium undecyl-(L,L)-leucine-valine) (poly-SULV) and poly-(sodium undecyl-(L,L)- valine-leucine) (poly-(SUVL)) are reported. Both molecular micelles are used as chiral selectors in electrokinetic chromatography and each consists of covalently linked surfactant chains with chiral dipeptide headgroups. To provide experimental support for the structures from MD simulations, NOESY spectra were used to identify protons in close spatial proximity. Results from the NOESY analyses were then compared to radial distribution functions from MD simulations. In addition, the hydrodynamic radii of both molecular micelles were calculated from NMR-derived diffusion coefficients. Corresponding radii from the MD simulations were found to be in agreement with these experimental results. NMR diffusion experiments were also used to measure association constants for polar and non-polar binaphthyl analytes binding to both molecular micelles. Poly(SUVL) was found to bind the non-polar analyte enantiomers more strongly, while the more polar analyte enantiomers interacted more strongly with poly(SULV). MD simulations in tum showed that poly(SUL V) had a more open structure that gave greater access for water molecules to the dipeptide headgroup region.

Computational investigation of the anti-HIV activity of Chinese medicinal formula Three-Huang Powder.

An essential step in the life cycle of human immunodeficiency virus type 1 (HIV-1) is integration of the double-stranded retroviral DNA into the genome of the host cell. HIV-1 integrase, the enzyme that inserts the vital DNA into the host chromosome, is an attractive and rational target for anti-AIDS drug design because it is essential for HIV replication and there are no known counterparts in the host cell. Inhibitors of this enzyme have the great potential to complement the therapeutic use of HIV protease and reverse transcriptase inhibitors. Natural products have provided a source of new drug candidates for anti-AIDS therapy. Baicalein and baicalin, identified components of a Chinese herbal medicine Scutellaria baicalensis Georgi, have been shown to inhibit infectivity and replication of HIV. They are therefore promising lead compounds for developing new anti-AIDS drugs. To understand how the inhibitors work and therefore design more potent and specific inhibitors, we have used molecular modeling techniques to investigate the binding modes of these inhibitors. The three-dimensional structures of these inhibitors were first built. Then, computational binding studies of these inhibitors, based on the crystal structure of the HIV-1 integrase catalytic domain, were performed to study the complex structure. The preliminary results of our computational modeling study demonstrated that Baicalein binds to the active site region of the HIV-1 integrase. Our study will be of help to identify the pharmacophores of inhibitors binding to HIV-1 integrase and design new pharmaceuticals for the treatment of AIDS.

Combination effects of salvianolic acid B with low-dose celecoxib on inhibition of head and neck squamous cell carcinoma growth in vitro and in vivo.

Head and neck squamous cell carcinoma (HNSCC) development is closely associated with inflammation. Cyclooxygenase-2 (COX-2) is an important mediator of inflammation. Therefore, celecoxib, a selective inhibitor of COX-2, was hailed as a promising chemopreventive agent for HNSCC. Dose-dependent cardiac toxicity limits long-term use of celecoxib, but it seems likely that this may be diminished by lowering its dose. We found that salvianolic acid B (Sal-B), isolated from Salvia miltiorrhiza Bge, can effectively suppress COX-2 expression and induce apoptosis in a variety of cancer cell lines. In this study, we report that combination of Sal-B with low-dose celecoxib results in a more pronounced anticancer effect in HNSCC than either agent alone. The combination effects were assessed in four HNSCC cell lines (JHU-06, JHU-011, JHU-013, and JHU-022) by evaluating cell viability, proliferation, and tumor xenograft growth. Cell viability and proliferation were significantly inhibited by both the combined and single-agent treatments. However, the combination treatment significantly enhanced anticancer efficacy in JHU-013 and JHU-022 cell lines compared with the single treatment regimens. A half-dose of daily Sal-B (40 mg/kg/d) and celecoxib (2.5 mg/kg/d) significantly inhibited JHU-013 xenograft growth relative to mice treated with a full dose of Sal-B or celecoxib alone. The combination was associated with profound inhibition of COX-2 and enhanced induction of apoptosis. Taken together, these results strongly suggest that combination of Sal-B, a multifunctional anticancer agent, with low-dose celecoxib holds potential as a new preventive strategy in targeting inflammatory-associated tumor development.

DomSVR: domain boundary prediction with support vector regression from sequence information alone.

Protein domains are structural and fundamental functional units of proteins. The information of protein domain boundaries is helpful in understanding the evolution, structures and functions of proteins, and also plays an important role in protein classification. In this paper, we propose a support vector regression-based method to address the problem of protein domain boundary identification based on novel input profiles extracted from AAindex database. As a result, our method achieves an average sensitivity of approximately 36.5% and an average specificity of approximately 81% for multi-domain protein chains, which is overall better than the performance of published approaches to identify domain boundary. As our method used sequence information alone, our method is simpler and faster.

Genome-Targeted Drug Design: Understanding the Netropsin-DNA Interaction.

Knowledge of the sequence of the human genome has provided significant opportunities to exploit DNA as a target in the rational design of therapeutic agents. Among agents that target DNA, netropsin exhibits a strong preference for binding A/T rich regions. In order to investigate the key factors responsible for DNA recognition and binding by netropsin, molecular dynamics simulations were carried out on a DNA-netropsin complex in which two netropsin molecules are bound to each AATT site of the 16-mer d(CTTAATTCGAATTAAG)(2). In this complex, the two netropsins are bound to the DNA minor groove in a head-to-head orientation with the guanidinium-termini of both netropsins pointed toward the center of the DNA. Despite their identical environments, molecular dynamics simulations showed that the two netropsins exhibited differences in their respective RMS behaviors, binding energies, minor groove width fluctuations, and rotations of their structural planes. These observations suggest that DNA recognition and binding by small molecules may be governed by mechanism(s) that are much more complex than initially anticipated and may represent unexpected challenges in genome-targeted drug design.

Prediction of inter-residue contact clusters from hydrophobic cores.

A contact map is a key factor representing a specific protein structure. To simplify the protein contact map prediction, we predict the inter-residue contact clusters centred at the groups of their surrounding inter-residue contacts. In this paper, we adopt a Support Vector Machine (SVM)-based approach to predict the inter-residue contact cluster centres. The input of the SVM predictor includes sequence profile, evolutionary rate and predicted secondary structure. The SVM predictor is based on hydrophobic cores that may be considered as locations of the inter-residue contact clusters. About 35% of clustering centres of inter-residue contacts can be predicted accurately.

Protein fold classification with genetic algorithms and feature selection.

Protein fold classification is a key step to predicting protein tertiary structures. This paper proposes a novel approach based on genetic algorithms and feature selection to classifying protein folds. Our dataset is divided into a training dataset and a test dataset. Each individual for the genetic algorithms represents a selection function of the feature vectors of the training dataset. A support vector machine is applied to each individual to evaluate the fitness value (fold classification rate) of each individual. The aim of the genetic algorithms is to search for the best individual that produces the highest fold classification rate. The best individual is then applied to the feature vectors of the test dataset and a support vector machine is built to classify protein folds based on selected features. Our experimental results on Ding and Dubchak's benchmark dataset of 27-class folds show that our approach achieves an accuracy of 71.28%, which outperforms current state-of-the-art protein fold predictors.

Enaminones 8: CoMFA and CoMSIA studies on some anticonvulsant enaminones.

3D-QSAR studies comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were carried out on 26 structurally diverse subcutaneous pentylenetetrazol (scPTZ) active enaminone analogues, previously synthesized in our laboratory. CoMFA and CoMSIA were employed to generate models to define the specific structural and electrostatic features essential for enhanced binding to the putative GABA receptor. The 3D-QSAR models demonstrated a reliable ability to predict the CLogP of the active anticonvulsant enaminones, resulting in a q(2) of 0.558 for CoMFA, and a q(2) of 0.698 for CoMSIA. The outcomes of the contour maps for both models provide detailed insight for the structural design of novel enaminone derivatives as potential anticonvulsant agents.

Computational modeling study of human nicotinic acetylcholine receptor for developing new drugs in the treatment of alcoholism.

Alcohol abuse and alcoholism are serious and costly problem in USA. Thus, the development of anti-alcoholism agents could be very significant. The understanding of the neurochemical basis underlying the addictive properties of drugs of abuse is imperative for the development of new pharmacological means to reverse the addictive state, prevent relapse or to reduce the intake of addictive compounds. The nicotinic acetylcholine receptors (nAChRs) are important therapeutic targets for various diseases. Recent studies have revealed that the alpha3beta2, alpha3beta3, and alpha6 subunits of nAChR protein family might be pharmacological targets for developing new drugs in the treatment of alcoholism. We have performed computational homology modeling of the alpha3beta2, alpha3beta3, and alpha6 subunits of human nACHRs based upon the recently determined crystal structure of the extracellular domain (ECD) of the mouse nAChR alpha1 subunit complexed with alpha-bungarotoxin at 1.94 A resolution. For comparison, we also built the ECD models of alpha4beta2, and alpha7 subunits of human nACHRs which are neurochemical targets for cessation of smoking. The three-dimensional (3D) models of the ECD of the monomer, and pentamer of these human nAChR were constructed. The docking of the agonist in the ligand-binding pocket of the human nAChR dimers was also performed. Since the nAChR ligand-binding site is a useful target for mutagenesis studies and the rational design of drugs against various diseases, these models provide useful information for future investigation.