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Molecular Biology - The Scripps Research Institute

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differed from the general folate template, and caused<br />

inhibition when used in micromolar concentrations.<br />

Currently, we are optimizing the lead candidates; our<br />

goal is to obtain novel nonfolate inhibitors.<br />

AutoDock is currently used in more than 3200<br />

academic and commercial laboratories worldwide. We<br />

continued development of AutoDock by testing a new<br />

empirical free-energy force field. <strong>The</strong> force field incorporates<br />

a charge-based model for evaluation of hydrophobicity<br />

and an improved method for evaluating the<br />

geometry of hydrogen bonding. <strong>The</strong> force field was<br />

calibrated by using a set of 138 protein complexes of<br />

known structure taken from the Ligand Protein Database<br />

from the laboratory of C.L. Brooks, Department<br />

of <strong>Molecular</strong> <strong>Biology</strong>. We anticipate that the revised<br />

AutoDock, which incorporates this new force field and<br />

methods for selective flexibility in the protein target, will<br />

be released in 2005.<br />

We also used AutoDock to predict intermolecular<br />

interactions in several biological systems. In collaboration<br />

with C.F. Barbas, Department of <strong>Molecular</strong> <strong>Biology</strong>,<br />

we investigated the binding of peptides to the catalytic<br />

aldolase antibody 93F3. To explore the large conformational<br />

space available to these peptides, we used a<br />

divide-and-conquer approach that separates the search<br />

space into searchable blocks. In studies with G. Legge,<br />

University of Texas, Austin, Texas, we explored the<br />

interaction between the cytoplasmic tail of tissue factor<br />

and the WW domain of proline isomerase PIN1,<br />

focusing on the interaction of several key phosphoserine<br />

residues.<br />

FIGHTING DRUG RESISTANCE IN HIV DISEASE<br />

We are continuing our work on inhibitors to fight<br />

drug resistance in the treatment of AIDS (Fig. 4). In<br />

collaboration with K.B. Sharpless and C.-H. Wong,<br />

Department of Chemistry, we have focused on the<br />

design of inhibitors that assemble within the active<br />

Fig. 4. <strong>The</strong> predicted bound conformation of sanguinarine, a potential<br />

lead compound for the development of novel HIV protease<br />

inhibitors.<br />

Published by TSRI Press ®. ©Copyright 2005,<br />

<strong>The</strong> <strong>Scripps</strong> <strong>Research</strong> <strong>Institute</strong>. All rights reserved.<br />

MOLECULAR BIOLOGY 2005 197<br />

site of HIV protease. We showed that the triazole<br />

formed in the click chemistry reaction is an effective<br />

mimic for the peptide group in traditional inhibitors,<br />

forming similar hydrogen-bonding interactions.<br />

Currently, we are moving the FightAIDS@Home<br />

system from an outside provider to a new server strategy<br />

that will be implemented in the <strong>Molecular</strong> Graphics<br />

Laboratory. FightAIDS@Home enlists the worldwide<br />

community in a large computational effort to design<br />

effective therapeutic agents to fight AIDS. Personal<br />

computers are used in the program when the computers<br />

are not in use by their owners, providing an enormous,<br />

and largely untapped, computational resource.<br />

<strong>The</strong> current goal is to identify inhibitors that are effective<br />

against the wild-type virus and against common<br />

mutant forms of the virus. <strong>The</strong> large computational<br />

resources provided by FightAIDS@Home enables the<br />

screening of large databases of compounds and use<br />

of multiple mutant targets, allowing estimation of the<br />

potential of a compound to remain effective when viral<br />

mutations occur that cause resistance to drugs currently<br />

used to treat HIV disease.<br />

PREDICTING PROTEIN-PROTEIN INTERACTIONS<br />

With the goal of creating a comprehensive tool for<br />

predicting protein-protein interactions, we incorporated<br />

both SurfDock and AutoDock into the Python programming<br />

environment. SurfDock uses a variable-resolution<br />

spherical harmonics representation to find candidate<br />

orientations, and AutoDock is then used to explore local<br />

atomic rearrangements at the interface. We tested the<br />

method on a set of 59 protein-protein complexes of<br />

known structure and optimized the level of smoothing<br />

used in the spherical harmonics approximation of the<br />

molecular surfaces. <strong>The</strong> results of the docking test<br />

depended on the force field used to score possible orientations.<br />

<strong>The</strong> best results were obtained with a residue-based<br />

pair-wise potential of mean force.<br />

VISUAL METHODS FROM ATOMS TO CELLS<br />

Understanding structural molecular biology is essential<br />

to foster progress and critical decision making among<br />

students, policy makers, and the general public. In the<br />

past year, we continued our longstanding commitment<br />

to science education and outreach with a combination<br />

of presentations, popular and professional illustrations<br />

and animation, 3-dimensional tangible models, and a<br />

presence on the Worldwide Web. In these projects, we<br />

use the diverse visualization tools developed in the<br />

<strong>Molecular</strong> Graphics Laboratory to disseminate results<br />

that range from atomic structure to cellular function.

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