Daniel R Caffrey
Daniel R Caffrey has a total of 11 co-authors. Here are the top co-authors by number of shared publications:
- Brian E Caffrey
School of Theoretical Physics, Dublin Institute for Advanced Studies, 10 Burlington Road, Dublin 4, Ireland
1 shared publication - Deborah J Moshinsky
Pfizer Research Technology Center, 620 Memorial Drive, Cambridge, MA 02139, USA
1 shared publication - Elizabeth A. Lunney
Computational Biology Group, Oncology Research Unit, Pfizer Global Research and Development, San Diego, CA, 92121, USA
1 shared publication - Enoch S Huang
Bioinformatics Program and Biomedical Engineering Department, Boston University, MA 02215, USA
1 shared publication - Eun-Jong Hong
Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, MA 02139, USA
1 shared publication - Marco Ocano
Pfizer Global Research and Development, 620 Memorial Drive, Cambridge, MA 02139, USA
1 shared publication
Latest Publications
- Open Access
- 25 November 2008
- Published by Springer Nature in BMC Bioinformatics
- Vol. 9 (1) , 491
Prediction of specificity-determining residues for small-molecule kinase inhibitors
Designing small-molecule kinase inhibitors with desirable selectivity profiles is a major challenge in drug discovery. A high-throughput screen for inhibitors of a given kinase will typically yield many compounds that inhibit more than one kinase. A series of chemical modifications are usually required before a compound exhibits an acceptable selectivity profile. Rationalizing the selectivity profile for a small-molecule inhibitor in terms of the specificity-determining kinase residues for that molecule can be an important step toward the goal of developing selective kinase inhibitors.
- 25 November 2008
- Published by Springer Nature in BMC Bioinformatics
- Vol. 9 (1) , 491
Open AccessPrediction of specificity-determining residues for small-molecule kinase inhibitors
Designing small-molecule kinase inhibitors with desirable selectivity profiles is a major challenge in drug discovery. A high-throughput screen for inhibitors of a given kinase will typically yield many compounds that inhibit more than one kinase. A series of chemical modifications are usually required before a compound exhibits an acceptable selectivity profile. Rationalizing the selectivity profile for a small-molecule inhibitor in terms of the specificity-determining kinase residues for that molecule can be an important step toward the goal of developing selective kinase inhibitors.
- Open Access
- 11 October 2007
- Published by Springer Nature in BMC Bioinformatics
- Vol. 8 (1) , 381
PFAAT version 2.0: A tool for editing, annotating, and analyzing multiple sequence alignments
By virtue of their shared ancestry, homologous sequences are similar in their structure and function. Consequently, multiple sequence alignments are routinely used to identify trends that relate to function. This type of analysis is particularly productive when it is combined with structural and phylogenetic analysis.
- 11 October 2007
- Published by Springer Nature in BMC Bioinformatics
- Vol. 8 (1) , 381
Open AccessPFAAT version 2.0: A tool for editing, annotating, and analyzing multiple sequence alignments
By virtue of their shared ancestry, homologous sequences are similar in their structure and function. Consequently, multiple sequence alignments are routinely used to identify trends that relate to function. This type of analysis is particularly productive when it is combined with structural and phylogenetic analysis.