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Reviews in Computational Chemistry Volume 18

Reviews in Computational Chemistry Volume 18

Reviews in Computational Chemistry Volume 18

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44 The Use of Scor<strong>in</strong>g Functions <strong>in</strong> Drug Discovery Applications<br />

Once a reasonable b<strong>in</strong>d<strong>in</strong>g hypothesis has been generated, the next step<br />

is the actual virtual screen<strong>in</strong>g. Whether one uses databases of commercially<br />

available compounds or ‘‘virtual’’ libraries of hypothetical chemical structures,<br />

it makes sense to dock not just any compound, but only those that pass a number<br />

of simple property filters. Such filters remove<br />

1. Compounds with reactive functional groups. Reactive groups such as<br />

SO2Cl and CHO cause problems <strong>in</strong> some biological assays due to<br />

nonspecific covalent b<strong>in</strong>d<strong>in</strong>g to the prote<strong>in</strong>.<br />

2. Compounds with a molecular weight below 150 or above 500. Very small<br />

molecules like benzene are known to b<strong>in</strong>d to prote<strong>in</strong>s <strong>in</strong> a rather<br />

nonspecific manner and at several sites. Very large molecules (like<br />

polypeptides) are difficult to optimize subsequently because bioavailability<br />

is usually low for compounds with a molecular weight above 500.<br />

3. Compounds that are not ‘‘drug-like’’ accord<strong>in</strong>g to criteria that have been<br />

derived from sets of known drugs. 22,23<br />

Each rema<strong>in</strong><strong>in</strong>g compound is then docked <strong>in</strong>to the b<strong>in</strong>d<strong>in</strong>g site and<br />

scored. The dock<strong>in</strong>g process is the most demand<strong>in</strong>g step computationally<br />

and is usually carried out on multiprocessor computers. Depend<strong>in</strong>g on the<br />

dock<strong>in</strong>g algorithm and the scor<strong>in</strong>g function, this step may easily take several<br />

days of CPU time. The result is a list of several hundred to a few thousand<br />

docked small molecule structures each with a computed score, which is further<br />

analyzed to weed out undesirable structures. Selection criteria could be<br />

1. Lipophilicity, if not addressed before. Highly lipophilic molecules are<br />

difficult to test because of their low solubility <strong>in</strong> water.<br />

2. Structural class. If 50% of the docked structures belong to a s<strong>in</strong>gle chemical<br />

class, it is probably unnecessary to test all of them.<br />

3. Improbability of docked b<strong>in</strong>d<strong>in</strong>g mode. Fast dock<strong>in</strong>g tools cannot produce<br />

reasonable solutions for all compounds. Often even some high-scor<strong>in</strong>g<br />

compounds are found to be docked to the outer surface of the prote<strong>in</strong>.<br />

<strong>Computational</strong> filters help to detect such situations.<br />

F<strong>in</strong>ally, the selected compounds are purchased or synthesized and then<br />

tested. If the goal is to identify weakly b<strong>in</strong>d<strong>in</strong>g small molecules, it is important to<br />

ensure that the biological assay is sensitive and robust enough to pick up these<br />

molecules. Measurements us<strong>in</strong>g 100–1000 mM concentration of the ligand frequently<br />

cause problems due to the limited solubility of the ligands <strong>in</strong> water. To<br />

compensate for this, the assay is often carried out <strong>in</strong> the presence of 1–5%<br />

dimethyl sulfoxide (DMSO) (see, e.g., Ref. 14).<br />

Note that the process of virtual screen<strong>in</strong>g still <strong>in</strong>volves manual <strong>in</strong>terventions<br />

at various stages. In pr<strong>in</strong>ciple, the whole process can be carried out <strong>in</strong> a<br />

fully automated manner, but <strong>in</strong> practice visual <strong>in</strong>spection and manual selection<br />

are still very useful.

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