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Drug Target Research Center Planned for UMass Amherst

A center that will identify new drug targets based on protein research at University of Massachusetts (UMass) Amherst is among western Massachusetts projects winning a total $100.5 million in funding from the quasi-public agency that oversees the commonwealth’

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A center that will identify new drug targets based on protein research at University of Massachusetts (UMass) Amherst is among western Massachusetts projects winning a total $100.5 million in funding from the quasi-public agency that oversees the commonwealth’s $1 billion, 10-year Life Sciences Initiative.

The Massachusetts Life Sciences Center (MLSC) yesterday approved most of the money—$95 million—toward construction and equipment for Phase II of the new $157-million Life Sciences Laboratories (LSL) at UMass Amherst.

The lab building will house three new research centers created to develop innovative products and services by partnering with regional life sciences and precision manufacturing companies. One center, Models to Medicine, will focus on translating basic protein research by UMass Amherst research into new therapeutic targets by studying protein dysfunctions believed to play a role in Alzheimer’s, Parkinson’s, cancer, and infectious diseases.

Nearly 50 researchers will be associated with Models to Medicine. One of them, Lila Gierasch, runs a lab focused on how protein homeostasis networks facilitate proper folding in the cell, and how the networks inhibit disease-producing processes. Over the past five years, Dr. Gierasch and nine other faculty members have formed a core team that has won more than $14 million in NIH research funding.

The other two centers will focus on patient monitoring through biosensors, nanotechnology, and big data management; and on application of new drug, agricultural, and “nutraceutical” compounds. Space not filled by the centers will be devoted to bioinformatics, conference space, and a testing center.

The life-sci lab fits with UMass Amherst’s emphasis on translating industry-sponsored research. The campus is home to the UMass Innovation Institute at Amherst, which now attracts $14 million annually in industry research awards, a figure it expects to balloon in five years to $30 million annually.

Construction on the LSL began in February 2010, funded by $100 million from the commonwealth for Phase I and $56.5 million from UMass Amherst for Phase II’s unfurnished “shell” space, providing a total of 310,000 square feet of research space.

MLSC also approved $5.5 million for the Pioneer Valley Life Sciences Institute (PVLSI) to establish a Health Informatics and Technology Innovation Center in Springfield, MA. PVLSI is a joint venture of Baystate Medical Center in Springfield and UMass Amherst. The center will focus on advancing public/private-sector partnerships and incubating new technologies from startups and established companies in big data analytics, health care quality, mobile health, and population health management.

The PVLSI funding comes more than three months after the MLSC-approved $4.5 million grant for another regional bioinformatics project, the Massachusetts Green High Performance Computing Center in Holyoke, MA. The MLSC-funded Commonwealth Computational Cloud for Data Driven Biology will expand the center’s capacity for life sciences-related research and data analysis through large-scale computation and big data analytics.

“These investments support the kind of innovation that propels our economy forward and prepares our citizens for the 21st century global marketplace,” Gov. Deval Patrick, who enacted the life-sci initiative in 2008, said in a statement.

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Related questions

01How stable is the antibody?

A crucial question often addressed during preclinical development focuses on the in vivo stability of therapeutic antibodies. Increasing the half-life of a therapeutic antibody has several benefits ranging from higher treatment efficacy to increased advantages for the patients who will have a fewer number of therapy sessions and a reduced cost. Given these compelling benefits, following the identification of therapeutic antibodies with the desired specificity, developers usually subject them to a refinement step to increase their stability. This process is often hindered by the lack of reliable experimental tools to predict the half-life of antibodies in patients. The major hurdle of using mouse models to predict antibody stability in the serum lies in the way immunoglobulin proteins are processed by the organism. In mammals, most proteins circulating in the serum undergo constant uptake by endothelial cells and are routed through the endosomes to the lysosomal compartment for degradation. In the endosomes, immunoglobulin G (IgG) proteins are recognized and bound by a transmembrane protein, called the neonatal Fc receptor (FcRn), which mediates their recycling to the plasma membrane and subsequent release back into the serum. As a result, the half-life of IgGs are significantly extended by this mechanism. Since most therapeutic antibodies belong to the IgG class, this recycling system is very relevant for their relative stability in the body. Remarkably, the relative affinity between IgGs and FcRn is extremely disparate between different species, with the mouse receptor showing a much higher affinity than its human counterpart.

Source: www.genengnews.com ↗
02Undruggable or unscreenable?

Another obstacle to discovering new PPI inhibitors is the lack of libraries designed to hunt for them, points out Philippe Roche, PhD, senior scientist at the Integrative Structural and Chemical Biology team at the Cancer Research Center of Marseilles, France. “If you screen PPIs using libraries that were designed for kinases or GPCRs, that’s why you don’t get a lot of good results,” he says. To that end, his group began assembling a library focused on orthosteric inhibitors of PPIs. The result was 2P2Idb, a hand-curated, structural database cataloguing orthosteric inhibitors of PPIs for which the interface had been 3D characterized. From analyzing these known PPI inhibitors, and what structures they had in common, Roche and his colleagues developed a model to predict whether compounds would likely inhibit PPIs. Using this method, 2P2Idb creates an enriched screening library that dramatically increases the hit rate compared to standard libraries. Having proven their success with a small library of 1600 compounds, they are in the process of expanding the library to 10,000 compounds. Once that’s published, “the idea is to make this library available to labs around the world,” Roche says. “We will provide the library free of charge for people to be able to screen PPI targets.”

Source: www.genengnews.com ↗
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Peptide Therapy Guide Editorial Team

Editorial team for Peptide Therapy Guide.

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