Library metrics

Money and time are inseparable. Getting a billion-dollar drug into the market even just one month earlier can achieve an extra 100 million in revenue Library metrics are not confined to making the drug discovery process more effective they are as relevant in the downstream activities of drug development, process development, and clinical trials, where the big money is spent. 

Novelty is a library metric, and it can be measured. The only point to debate is Novel compared to what The next metric is much more difficult to pin down and remains highly subjective. It is called diversity. 

Resupply is an issue and certainly a library metric. One of the criteria applied in buying compounds from third-party vendors is whether more material can be delivered in a short time. In other words, can the risk of buying a small amount of a compound be reduced by the certainty of resupply The last years have seen a rapid growth in small synthetic chemistry laboratories that perform exactly this service to pharmaceutical companies, the resupply of interesting compounds regardless of the original source. The trend will continue. 

Library metrics lead us to believe that only certain classes of compounds can ever be seriously considered as potentially becoming drugs. Druglikeness, novelty, and diversity can become such awful mantras that we will miss the blue sky quantum leaps into new drug types. Even today, there is still room in the screening programs of some companies for compounds that are quite remote from the metric-designed library. 

Clearly, within the conceptual framework described above, there is extensive room for exploration in creating fingerprints and similarity measures to retrieve molecules based on varying conceptions of similarity [42—441. The simplest types of fingerprint consist simply of features indices that map the presence or absence of a small library of functional groups. The most well known and effective are the MACCS keys. These were initially chemical feature indices, that we later used successfully as a similarity metric. 

The goal of most HTS assays for enzyme targets is to identify library components that act as inhibitors of enzymatic activity. To identify and compare inhibitory compounds, we must first define a metric that reflects the ability of a fixed concentration of compound to reduce the activity of the target enzyme. The most commonly used metric for this purpose is the inhibition percentage, which can be defined as follows ... 

The aim of case-based reasoning is to provide advice based on a set of known examples that are judged to be relevant to the user s query. Files within the library contain data about past cases relevant to the area of expertise, how they were tackled, what the results of this approach were, and whether the action taken was appropriate and successful. Each case is tagged with a set of attributes that describe the case, so that when the library is searched for relevant material, it can quickly be identified through some form of similarity metric. 

One relevant concern has been to prioritize the order of screening, or to decide which compound libraries to purchase for screening. One approach that has been used relies on the complementary concepts of diversity and similarity. Given two compounds, how do you quantitate how divergent the two structures are. One major problem is the choice of a relevant metric, what parameters are considered, how are the parameters scaled, and so on. Similarity, like beauty, is clearly in the eye of the beholder. There is no generally relevant set of parameters to explain all observations and one should expect that a given subset of parameters will be more relevant to one problem than to another. 

Menard, P.R., Lewis, R.A., and Mason, J.S. Chemistry space metrics in diversity analysis, library design, and compound selection. J. Comput. Chem. Inf. Sci. 1998, 38, 1204-1213. 

Several other approaches with the goal of simultaneous optimization of several criteria have been reported. One such approach is the generation of a library that is both focused and diverse via the dual fingerprint metric described by Bajorath [94], In this method, individual compounds are randomly generated and their similarity to a known inhibitor is evaluated by comparison of their minifingerprints [95] using the Tanimoto coefficient. Those molecules that are above a similarity threshold are then... 

XuE, L, Godden, J.W., Stahura, F.L, and Bajorath, J. A dual fingerprint-based metric for the design of focused compound libraries and analogs. 

Technique 1 Clustering of the Metric Matrix. The first step In evaluating the library was to separate It Into classes by explicitly scanning the printed list of compounds. At this point It became... 

The further evaluation of the library and metric proceeds from the metric matrix. Its elements are the dot products of each spectriun with every other In Its class. 

One or more lead molecules may be used as a focusing target. Similarity metrics include Daylight fingerprint Tanimoto similarity. The penalty score for each compound in the library is defined as the distance between it and the most similar lead molecule. The penalty score for the library is the average of the individual compound penalty scores. QSAR predictions and docking scores can also be used in this term. 

W., Mills, J. E., Withka, J. M. (2010) Design of a multi-purpose fragment screening library using molecular complexity and orthogonal diversity metrics. / Comput-Aided Mol Des. Manuscript in preparation. 

The UTC-PAB is a library of cognitive tests that can be modified into smaller subsets or batteries for a specific purpose. The original UTC-PAB consisted of 25 tasks that were chosen due to their construct validity, reliability, and sensitivity to levels of cognitive functioning. Several of the commonly known subsets or variations include the Testor s Workbench/Automated Neuropsychological Assessment Metrics (TWB/ANAM or ANAM) battery, the Naval Medical Research Institute Performance Assessment Battery (NMRI-PAB), the UTC-PAB/NATO AGARD STRES Battery, and the Criterion Task Set (CTS).43... 

The first method used a similarity metric to select the top percentage of hits and the second method does the selection based only on number of common pharmacophores between the receptor active site fingerprint and the 3D fingerprint for compounds in the virtual library. Both analysis techniques are extremely fast. One of the major advantages of FLIP technology is its throughput. 

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