Enoch S. Huang, PhD Adjunct Assistant Professor, Bioinformatics Head of Computational Sciences, Pfizer PharmaTherapeutics R&D

I have been Adjunct Assistant Professor of Bioinformatics at Boston University since June 2001.

I also lead a global Computational Sciences group while based at Pfizer's research lab in Cambridge, MA.

We are proud to have released Pfaat, a Java-based tool for multiple sequence alignment visualization, editing, annotation and interaction with phylograms and 3-D structure. We invite all to download the application and source code, which is an open-source project under the GNU General Public License. A manuscript describing Pfaat was published in the March 2003 issue of Bioinformatics. In October 2004 we completed a significant update to Pfaat. The current version (and all future updates) are now made available using Java Web Start technology. The updated functionality in PFAAT was covered in BMC Bioinformatics in 2007. We use Pfaat extensively in our research to analyze functional regions of proteins, such as protein-protein interfaces and residues involved in ligand recognition.

In January 2007, the group published a paper on a physical model to predict the druggability of protein targets by small molecules in Nature Biotechnology.

We have recently been developing methods to interpret data generated from large-scale 'omics platforms such as microarrays. One such technique, which we call "Causal Reasoning" was published in 2012 in Bioinformatics.

Selected publications:

• Causal reasoning on biological networks (Bioinformatics 2012).
• Biophysical model to score protein target druggability (Nature Biotechnology 2007)
• Sequence conservation at protein-protein interfaces (Prot Sci 2004)
• Sequence motif for aminergic GPCRs (Prot Sci 2003)
• Pfaat (Bioinformatics 2003)
• Followup on side-chain placement on approximate folds (Prot Eng 00) with Ram Samudrala
• Hierarchical approach to protein structure prediction (J Mol Biol 00) with the Michael Levitt laboratory
• Blind prediction results from the CASP3 experiment (Proteins 99)
• Ab initio folding with distance geometry (J Mol Biol 99)
• Predicting function from structure (Structure 99) with the Russ Altman laboratory
• Combined approach to protein structure prediction (PSB 99) with Ram Samudrala
• Consensus distance geometry (Prot Sci 98)
• Side-chain prediction on ab initio folds (Proteins 98)
• Ab initio fold prediction (J Mol Biol 97) with the David Baker laboratory
• Levitt group review on the 'End Game' of protein folding (Ann Rev Biochem 97)
• Systematic assessment of scoring functions (J Mol Biol 97)
• Molecular dynamics decoy set (J Mol Biol 96)
• Hydrophobic scoring function (J Mol Biol 95)
• Role of turns in folding and stability (Nature 93)

Thoughts on drug discovery

A panel discussion at Harvard in which my unscripted remarks were captured by BioIT World (unbeknownst to me at the time). My fifteen minutes of fame hit its zenith when this was picked up by Derek Lowe, a well-known industry blogger.

We later wrote a perspectives piece in Drug Discovery Today which reflected many of the challenges I spoke about, and suggested how we might address them with a knowledge engineering implementation.

Full citations and CV.