SBIR-STTR Award

Learning Drug Specificity From Protein Families
Award last edited on: 9/30/04

Sponsored Program
SBIR
Awarding Agency
NIH : NIGMS
Total Award Amount
$1,062,975
Award Phase
2
Solicitation Topic Code
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Principal Investigator
Richard M Fine

Company Information

Biocomputing Group Inc (AKA: Structural Proteomics Inc)

4 Adele Avenue
Demarest, NJ 07627
   (201) 784-3621
   N/A
   N/A
Location: Single
Congr. District: 05
County: Bergen

Phase I

Contract Number: 1R43GM061465-01
Start Date: 00/00/00    Completed: 00/00/00
Phase I year
2000
Phase I Amount
$97,850
We propose to develop and apply methods for docking ligand fragments into families of proteins, for two specific purposes. The first of these is to develop methods to identify patterns which are unique to a specific family member, to avoid cross-reactivity in the design of highly specific drugs. The second is to develop methods to identify patterns of similarity, which can be used when multiple alleles of a target protein are known to help avoid the development of resistant strains of infectious disease organisms. The work is an extension of and suggested by our current efforts, funded by a separate Phase II SBIR, to develop methods for comparing surface features of proteins within and across families. The work proposed entails the development of (a) new docking methods which can directly use feature comparisons within families; (b) novel data segmentation tools based on unsupervised learning methods to assess similarity and differences obtained from docking results on individual family members; and (c) the development of new classification methods based on Vector Support Machines and other methods for optimizing separation functions to distinguish correctly docked from incorrectly docked structures within the families. While the work is exploratory, if successful it can provide a focussed set of powerful drug-discovery tools to take advantage of the increasingly rich amount of information on protein sequence and structure emerging from genomics and structural genomics efforts. Software developed will be offered for sale, and applied to available crystal structures to develop specialized databases which can be of immediate use in drug discovery. PROPOSED COMMERCIAL APPLICATIONS: The goals of the grant are to address key issues in current drug discovery, namely, specificity, cross-reactivity, and avoiding resistance in infectious disease organisms to new drugs. The methods are strongly enabled by the accumulation of knowledge from genomics and structural genomics efforts. We believe that these and similar methods will be necessary to reap the commercial and sociological benefit promised by this extraordinary accumulation of knowledge.

Thesaurus Terms:
binding protein, ligand, method development, protein binding, protein structure, structural biology conformation, protein sequence

Phase II

Contract Number: 2R44GM061465-02
Start Date: 00/00/00    Completed: 00/00/00
Phase II year
2003
(last award dollars: 2004)
Phase II Amount
$965,125

The goal is to provide a set of powerful docking-based rational drug discovery tools to take advantage of the increasingly rich amount of information on protein families sequence and structure emerging from genomics and structural genomics efforts. The tools will improve the reliability of current virtual screening methods by taking advantage of all available information on a protein target's family, including aligned sequences, available structures, co-crystalized ligands, and active compounds described in the literature. The tools will also specifically allow common regions of family active sites to be targeted in the design of family-focused combinatorial libraries with high activity rates against any member of the family. Lastly the tools will allow unique regions of the target active site to guide the design of compounds with high selectivity for a specific target. A key component of this suite of tools is a novel description of the interaction of a ligand with the surface of a protein called a footprint. Footprints are used as input to clustering, filtering, and learning methods to analyze the results of docking screens and to compare docking results across members of the target family. Virtual screening of large libraries of chemical compounds will be performed on four protein families, the data analyzed, and new promising scaffolds for future focused combinatorial libraries will be detected. In summary the successful development and application of the tools described in this grant request can: 1. Significantly increase the success rate of virtual screens; 2. Generate highly effective focused combinatorial libraries to protein families; 3. Generate target-specific leads in difficult target families such as kinases; 4. Guide the construction of highly focused in-vitro experimental screening.

Thesaurus Terms:
drug /agent, method development, protein structure, structural biology ligand, protein sequence