Friday March 23, 10:01 am Eastern Time
Press Release
SOURCE: Variagenics, Inc.
Study Published in Journal of Molecular Biology
Describes Computational Method For Analyzing
Functional Consequences of SNPs
Variagenics uses scientific method for prioritizing genetic variations for
patient population studies
CAMBRIDGE, Mass., March 23 /PRNewswire/ -- Variagenics, Inc. (Nasdaq: VGNX -
news), a leader in pharmacogenomics, the science that correlates genetic variation with drug
response, today announced that it has developed a high-throughput computational method
for analyzing the functional consequences of certain single nucleotide polymorphisms (SNPs).
The method can predict which of the subset of SNPs that encode amino acid substitutions
are most likely to affect the function or stability of a target protein. Variagenics is using this
new computational approach to rapidly identify influential genetic variations in patient
populations.
``As we enter the post-genomic era, the ability to search through the millions of SNPs now
available in databases worldwide to find those few SNPs directly linked to important
biological effects becomes critically important,'' said Colin Dykes, Ph.D., Vice President,
Research. ``This new method reinforces our leadership position in selecting minimal,
informative subsets of SNPs for application in cost-effective pharmacogenomics programs
with our pharmaceutical and biotech partners.''
The study, published in the March 23, 2001 issue of Journal of Molecular Biology (Vol. 307,
No. 2: 683-702), describes a computational method for predicting functional consequences
of non-synonymous single nucleotide polymorphisms. Non-synonymous SNPs (nsSNPs)
cause amino acid substitutions in proteins and are less prevalent than synoymous SNPs, the
SNPs in protein encoding regions that do not affect protein sequence. Using this
methodology, the authors of the study, Daniel Chasman, Ph.D., and R. Mark Adams, Ph.D.,
estimate that approximately 30 percent of the natural nsSNPs in the human genome have
effects on function.
``This method puts the functional analysis of amino acid substitutions on a strong scientific footing,'' said Greg Verdine, Ph.D.,
Professor of Chemistry and Chemical Biology at Harvard University and Principal Scientific Advisor to Variagenics. ``It
significantly enhances available methods for characterizing SNPs and provides a means for zeroing in on those that are most
likely to affect the safety and efficacy of drugs.''
``We have devised a powerful methodology for predicting the effects of certain SNPs on protein function,'' said Daniel
Chasman, Ph.D., Variagenics Group Leader, Functional Annotation. ``By applying our structural modeling algorithms to
Variagenics' ProSNP(TM) database and the publicly available databases of genetic variations, we have the means to focus
effectively on the SNPs and haplotypes that are in those genes targeted by current drugs and are likely to affect the activity of
the encoded protein.''
R. Mark Adams, Ph.D, Senior Director of Bioinformatics added, ``The body of work around this robust computational
technique, which combines structural- modeling and sequence-based features, represents a major step towards putting the
prediction of SNP functional effects (previously predicted using heuristic methods) on a firm theoretical basis. This allows for
the development of high-throughput computational tools which increasingly are important in the post-genomic era.''
Study Details
To predict whether a nsSNP would affect protein function, Variagenics scientists formalized an approach that used features
from structural models and sequence information to anticipate which amino acid polymorphisms are likely to affect protein
function and stability. To develop and validate the approach, they analyzed how structure and sequence-based features
discriminate between mutations that do or do not affect protein function for exhaustive mutations in two well-studied proteins,
the lac repressor and lysoyzyme. They then determined the values of these features in structural models for amino acid
polymorphisms in recent surveys of nsSNPs from the Case Western Reserve University and Whitehead Institute genome
centers. These feature values provided an estimate of the prevalence of nsSNPs that affect protein function and stability.
Variagenics' scientists believe this study and a report by Sunyaev et al. (cited in the publication) mark the first attempt to
enumerate an extensive list of predictive features for nsSNPs, to develop a formalism for quantitatively evaluating their
performance in predictions, and to use the features for estimating a likelihood of their effect on function.
Variagenics, inc. applies its pharmacogenomic technologies to the discovery, development and commercialization of
individualized drugs and companion molecular diagnostic products. The Company identifies clinically important genetic
variations, including SNPs and haplotypes (groups of SNPs), and will use this information to enhance drugs in development, to
identify and validate new drug targets, and to create high-value diagnostics. By combining its expertise and proprietary
technologies, including the NuCleave(TM) genotyping and haplotyping analysis platform, Variagenics offers drug development
solutions to pharmaceutical companies seeking to optimize therapeutic outcomes. For more information visit the Company's
website at: variagenics.com
This press release may contain forward-looking statements, including statements regarding the effect of pharmacogenomics on
therapeutic outcomes and the delivery of healthcare and the role that the Company will play in the field of pharmacogenomics.
Such statements are based on management's current expectations and are subject to certain factors, risks and uncertainties that
may cause actual results, events and performance to differ materially from those referred to or implied in such statements. These
risks are identified in Variagenics' registration statement on Form S-1, Registration No. 333- 33558, filed with the Securities
and Exchange Commission and declared effective on July 20, 2000. The Company does not intend to update any of the
forward-looking statements after the date of this release to conform these statements to actual results or to changes in our
expectations, except as required by law.
SOURCE: Variagenics, Inc. |
