Project description:Circulating protein biomarkers provide information regarding pathways in heart failure (HF) and can add important value to clinicians. Advancements in proteomics allow researchers to measure a multitude of proteins simultaneously with excellent sensitivity and selectivity to detect low abundance proteins. This helps identify previously unrecognized pathways in HF and discover biomarkers and potential targets for HF therapies. Although several proteomic methods exist, including mass spectrometry, protein microarray, aptamer, and proximity extension assay-based techniques, each have their unique advantages. This paper provides an overview of the various proteomic methods, with examples of how each has contributed to understanding the pathways in HF.
Project description:Ticks and tick-borne diseases are significant public health concerns. Bioactive molecules in tick saliva facilitate prolonged blood-feeding and transmission of tick-borne pathogens to the vertebrate host. Alpha-gal syndrome (AGS), a newly reported food allergy, is believed to be induced by saliva proteins decorated with a sugar molecule, the oligosaccharide galactose-⍺-1,3-galactose (α-gal). This syndrome is characterized by an IgE antibody-directed hypersensitivity against α-gal. The α-gal antigen was discovered in the salivary glands and saliva of various tick species including, the Lone Star tick (Amblyomma americanum). The underlying immune mechanisms linking tick bites with α-gal-specific IgE production are poorly understood and are crucial to identify and establish novel treatments for this disease. This article reviews the current understanding of AGS and its involvement with tick species.
Project description:Prediction of protein tertiary structures from amino acid sequence and understanding the mechanisms of how proteins fold, collectively known as "the protein folding problem," has been a grand challenge in molecular biology for over half a century. Theories have been developed that provide us with an unprecedented understanding of protein folding mechanisms. However, computational simulation of protein folding is still difficult, and prediction of protein tertiary structure from amino acid sequence is an unsolved problem. Progress toward a satisfying solution has been slow due to challenges in sampling the vast conformational space and deriving sufficiently accurate energy functions. Nevertheless, several techniques and algorithms have been adopted to overcome these challenges, and the last two decades have seen exciting advances in enhanced sampling algorithms, computational power and tertiary structure prediction methodologies. This review aims at summarizing these computational techniques, specifically conformational sampling algorithms and energy approximations that have been frequently used to study protein-folding mechanisms or to de novo predict protein tertiary structures. We hope that this review can serve as an overview on how the protein-folding problem can be studied computationally and, in cases where experimental approaches are prohibitive, help the researcher choose the most relevant computational approach for the problem at hand. We conclude with a summary of current challenges faced and an outlook on potential future directions.
Project description:Collectively, viruses have the greatest genetic diversity on Earth, occupy extremely varied niches and are likely able to infect all living organisms. Viral infections are an important issue for human health and cause considerable economic losses when agriculturally important crops or husbandry animals are infected. The advent of metagenomics has provided a precious tool to study viruses by sampling them in natural environments and identifying the genomic composition of a sample. However, reaching a clear recognition and taxonomic assignment of the identified viruses has been hampered by the computational difficulty of these problems. In this perspective paper we examine the trends in current research for the identification of viral sequences in a metagenomic sample, pinpoint the intrinsic computational difficulties for the identification of novel viral sequences within metagenomic samples, and suggest possible avenues to overcome them.
Project description:High-throughput screening is an essential component of the toolbox of modern technologies that improve speed and efficiency in contemporary cancer drug development. This is particularly important as we seek to exploit, for maximum therapeutic benefit, the large number of new molecular targets emerging from the Human Genome Project and cancer genomics. Screening of diverse collections of low molecular weight compounds plays a key role in providing chemical starting points for iterative optimisation by medicinal chemistry. Examples of successful drug discovery programmes based on high-throughput screening are described, and these offer potential in the treatment of breast cancer and other malignancies.
Project description:In Mexico's territory, the center of origin and domestication of maize (Zea mays), there is a large phenotypic diversity of this crop. This diversity has been classified into "landraces." Previous studies have reported that genomic variation in Mexican maize is better explained by environmental factors, particularly those related with altitude, than by landrace. Still, landraces are extensively used by agronomists, who recognize them as stable and discriminatory categories for the classification of samples. In order to investigate the genomic foundation of maize landraces, we analyzed genomic data (35,909 SNPs from Illumina MaizeSNP50 BeadChip) obtained from 50 samples representing five maize landraces (Comiteco, Conejo, Tehua, Zapalote Grande, and Zapalote Chico), and searched for markers suitable for landrace assignment. Landrace clusters could not be identified taking all the genomic information, but they become manifest taking only a subset of SNPs with high FST among landraces. Discriminant analysis of principal components was conducted to classify samples using SNP data. Two classification analyses were done, first classifying samples by landrace and then by altitude category. Through this classification method, we identified 20 landrace-informative SNPs and 14 altitude-informative SNPs, with only 6 SNPs in common for both analyses. These results show that Mexican maize phenotypic diversity can be classified in landraces using a small number of genomic markers, given the fact that landrace genomic diversity is influenced by environmental factors as well as artificial selection due to bio-cultural practices.
Project description:Interactions between protein domains and lipid molecules play key roles in controlling cell membrane signalling and trafficking. The pleckstrin homology (PH) domain is one of the most widespread, binding specifically to phosphatidylinositol phosphates (PIPs) in cell membranes. PH domains must locate specific PIPs in the presence of a background of approximately 20% anionic lipids within the cytoplasmic leaflet of the plasma membrane. We investigate the mechanism of such recognition via a multiscale procedure combining Brownian dynamics (BD) and molecular dynamics (MD) simulations of the GRP1 PH domain interacting with phosphatidylinositol (3,4,5)-trisphosphate (PI(3,4,5)P?). The interaction of GRP1-PH with PI(3,4,5)P? in a zwitterionic bilayer is compared with the interaction in bilayers containing different levels of anionic 'decoy' lipids. BD simulations reveal both translational and orientational electrostatic steering of the PH domain towards the PI(3,4,5)P?-containing anionic bilayer surface. There is a payoff between non-PIP anionic lipids attracting the PH domain to the bilayer surface in a favourable orientation and their role as 'decoys', disrupting the interaction of GRP1-PH with the PI(3,4,5)P? molecule. Significantly, approximately 20% anionic lipid in the cytoplasmic leaflet of the bilayer is nearly optimal to both enhance orientational steering and to localise GRP1-PH proximal to the surface of the membrane without sacrificing its ability to locate PI(3,4,5)P? within the bilayer plane. Subsequent MD simulations reveal binding to PI(3,4,5)P?, forming protein-phosphate contacts comparable to those in X-ray structures. These studies demonstrate a computational framework which addresses lipid recognition within a cell membrane environment, offering a link between structural and cell biological characterisation.
Project description:Studies aimed at elucidating the unknown Mg2+ binding site in protein farnesyltransferase (FTase) are reported. FTase catalyzes the transfer of a farnesyl group to a conserved cysteine residue (Cys1p) on a target protein, an important step for proteins in the signal transduction pathways (e.g., Ras). Mg2+ ions accelerate the protein farnesylation reaction by up to 700-fold. The exact function of Mg2+ in catalysis and the structural characteristics of its binding remain unresolved to date. Molecular dynamics (MD) simulations addressing the role of magnesium ions in FTase are presented, and relevant octahedral binding motifs for Mg2+ in wild-type (WT) FTase and the D?352A mutant are explored. Our simulations suggest that the addition of Mg2+ ions causes a conformational change to occur in the FTase active site, breaking interactions known to keep FPP in its inactive conformation. Two relevant Mg2+ ion binding motifs were determined in WT FTase. In the first binding motif, WT1, the Mg2+ ion is coordinated to D352?, zinc-bound D297?, two water molecules, and one oxygen atom from the ?- and ?-phosphates of farnesyl diphosphate (FPP). The second binding motif, WT2, is identical with the exception of the zinc-bound D297? being replaced by a water molecule in the Mg2+ coordination complex. In the D?352A mutant Mg2+ binding motif, D297?, three water molecules, and one oxygen atom from the ?- and ?-phosphates of FPP complete the octahedral coordination sphere of Mg2+. Simulations of WT FTase, in which Mg2+ was replaced by water in the active site, recreated the salt bridges and hydrogen-bonding patterns around FPP, validating these simulations. In all Mg2+ binding motifs, a key hydrogen bond was identified between a magnesium-bound water and Cys1p, bridging the two metallic binding sites and, thereby, reducing the equilibrium distance between the reacting atoms of FPP Cys1p. The free energy profiles calculated for these systems provide a qualitative understanding of experimental results. They demonstrate that the two reactive atoms approach each other more readily in the presence of Mg2+ in WT FTase and mutant. The flexible WT2 model was found to possess the lowest barrier toward the conformational change, suggesting it is the preferred Mg2+ binding motif in WT FTase. In the mutant, the absence of D352? makes the transition toward a conformational change harder. Our calculations find support for the proposal that D352? performs a critical role in Mg2+ binding and Mg2+ plays an important role in the conformational transition step.