Function first: a powerful approach to post-genomic drug discovery

Stephen F. Betz, Susan M. Baxter and Jacquelyn S. FetrowGeneFormatics

Presented by Jamie DukeApril 7th, 2004

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Goal:

To answer this question:– How can we effectively use the new information

from the genome sequencing projects to accelerate the development of new therapeutics that target gene products or their functions?

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A “deluge of targets”

There is an overwhelming amount of nucleotide sequences generate from high-throughput sequencing and differential expression methods

Targets are not necessarily even expressed in vivo

The actual targets are waiting to be discovered

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Post-genomic drug discovery

Methods must be able to deal with a large number of targets

General strategy relies on high-throughput sequencing of large compound libraries against target proteins

– Requires a knowledge of enzymatic activity, or binding against a known ligand

Methods are costly, number of targets analyzed are limited, and a second assay is generally required

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Screening Strategies

Use of nuclear magnetic resonance (NMR) and x-ray crystallography

Structure based drug design has also come into play with therapeutics

Both strategies still require analyzing single proteins serially– Best method for the future involves automation

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Screening Strategies

Experimental efforts are resource intensive, and limited to proteins that can be cloned

X-ray Crystallography is only possible if the protein can form diffraction-quality crystals

NMR is only possible if the protein is well behaved in solution

Structural biology is only possible with high quality structures

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Structure

Structural prediction is neither easy nor cheap Knowing tertiary structure does not guarantee the

transfer of function or small molecule binding sites Inference of function from similar sequences with

known function is correct less than 50% of the time– A “similar sequence” is a sequence that is 30% or more

identical, most proteins do not meet this requirement– Additionally, different structures have been known to

support the same activity

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Selectivity

The aim is to develop truly selective compounds from the beginning of the discovery process

Decrease the failure rate of compounds in development and ultimately lower cost and time

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Function in Drug Discovery

Drug discovery starts by determining the function of the drug leads from mining the genomic data

– Pathway involvement, catalytic activity, protein class or active-site chemistry

Functional features can be used to develop assays for a more straightforward path

“Parallel large-scale processes and analyses to identify function first will be key for this lead discovery approach to be successful in the post-genomic era.”

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Function Assignment

Function of the sequences is often inferred through sequence “similarity”

– Function is automatically transferred, and can lead to misannotation and misinterpretation

SAGE and parallel protein analysis are generally used

– These experimental procedures allow for the gene product function to be identified in a complex environment yielding data which is used to validate the target

– Unfortunately, low copy genes and a high false positive rate limit the use of these methods

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Function first approach to structural and chemo-proteomics

Process starts with the identifying a set of protein sequences in the human proteome

– Looking for sequence that have particular binding sites, carries out catalysis, or has been previously identified

Proteins are classified by their functional sites– Analysis of the families is key to specific drug design

Structures of family members are determined using protein folding algorithms

Small molecule binding sites are identified This approach saves crucial time and money in the

drug discovery process

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Approximate Structure Analysis

For each protein, an approximate model is generated

Algorithms developed by Jeffrey Skolnick for the CASP competitions are used to predict the structure

Models are not perfect due to imperfect scoring functions and energy potentials

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Fuzzy Functional Forms™

A technique to identify biochemical function An FFF is a motif that describes the

chemistry and geometry of the functional site within the protein

Information is based upon known structures in the PDB

– Functional residues are identified in related protein structures

– Residues are selected based on the nature of the function, chemistry or structure of the site

– Geometric constraints are defined for key residues in the structure

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Functional Family Approach

Functional sites are (generally) well conserved in families

FFF’s are used to determine all proteins in the genome with the given functional site

Functional families are identified by:– Sites identified by FFF, and– Computational information on the functional site

that yields valuable biologically relevant data necessary for drug discovery

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Functional Family Approach

The ultimate goal is to identify small molecules that will selectively inhibit a single member of a family, thus reducing interaction with other proteins

This approach allows for the account and classification of functionally related proteins

Provides a better assurance of the “druggability” for a putative target

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Complementary to Cell Based Information

This method allows for efficient target validation due to parallel identification

Allows for large-scale identification of function and structure without large-scale investments

Provides information that is relevant to assays being run to determine functionality and interpretation of microarray data

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Rapid Analysis of the Structure

Because the structure of the protein does not need to be determined to the atomic level, it is much less computationally intense

Far fewer protein folding is done in silico because only models identified through FFF or high scoring models are folded

The process is automated– Scientists can compute more than 25,000 protein sequences and

make structure-function assignments in weeks, not months or years as would take to serially test each sequence through the experimental techniques

The combination of structure and function information that allows for more reliable assignments than sequence based methods

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Alternative Drug Binding Sites

One key feature of FFF is it’s ability to identify multiple active sites for one protein

A protein may be annotated as a phosphatase, but it may also have a catalytic site, a metal binding site, and a regulatory site, as does serine-threonine phosphatase

Alternative sites are also potentially druggable The information from multifunctional

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Binding Sites

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Key Information

It is key to know the structure of the functional site– Recognition of the similarities and differences

among a set of potential targets allows for designing specific small molecules that are specific for each member of the family

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Conclusion

The function first approach provides an effective way to mine the genomic data to lead to compounds that can be developed into drugs

Using this method, in association with biological, structural, and chemical methods will lead to drug discovery that is more efficient, and cost effective