genomes2drugs identifies target proteins and lead drugs from proteome datagenomes2drugs标识目标蛋白质和药物从蛋白质组数据.pdfVIP

Genomes2Drugs: Identifies Target Proteins and Lead Drugs from Proteome Data 1 2 1 3 1 David Toomey , Heinrich C. Hoppe , Marian P. Brennan , Kevin B. Nolan , Anthony J. Chubb * 1 Molecular Modelling Group, Royal College of Surgeons in Ireland, Dublin, Ireland, 2 CSIR Biosciences, Pretoria, South Africa, 3 Pharmaceutical and Medicinal Chemistry, Royal College of Surgeons in Ireland (RCSI), Dublin, Ireland Abstract Background: Genome sequencing and bioinformatics have provided the full hypothetical proteome of many pathogenic organisms. Advances in microarray and mass spectrometry have also yielded large output datasets of possible target proteins/genes. However, the challenge remains to identify new targets for drug discovery from this wealth of information. Further analysis includes bioinformatics and/or molecular biology tools to validate the findings. This is time consuming and expensive, and could fail to yield novel drugs if protein purification and crystallography is impossible. To pre-empt this, a researcher may want to rapidly filter the output datasets for proteins that show good homology to proteins that have already been structurally characterised or proteins that are already targets for known drugs. Critically, those researchers developing novel antibiotics need to select out the proteins that show close homology to any human proteins, as future inhibitors are likely to cross-react with the host protein, causing off-target toxicity effects later in clinical trials. Methodology/Principal Findings: To solve many of these issues, we have developed a free online resource called Genomes2Drugs which ranks sequences to identify proteins that are (i) homologo