Molecular Libraries Small Molecule

MLSMR Molecular Libraries Small Molecule Repository... 

ADME-tox absorption, distribution, metabolism, and excretion/toxicologic properties ECS0 median effective concentration IC50 median inhibitory concentration MIC minimum inhibitory concentration MLSMR Molecular Libraries Small Molecule Repository TAACF-NIAID Tuberculosis Antimicrobial Acquisition and Coordinating Facility/ National Institute of Allergy and Infectious Diseases... 

Inspired by this work (24), we used Bayesian methods (24) with molecular function class fingerprints of maximum diameter 6 (53) to identify substructures that were shown to be important in recent TB screening datasets (21-23). Bayesian models were built with the previously described Molecular Libraries Small Molecule Repository (MLSMR) 220,463 library (4,096 active compounds) (15) and dose-response data using 2,273 molecules (475 active compounds). In addition, these models were tested (15) with the National Institute of Allergy and Infectious Diseases (NIAID) data and GVK Biosciences (Hyderabad, India) datasets used by Prathipati et al. (24). We have validated the models with compounds left out of the original models, in some cases showing up to tenfold enrichments in finding active compounds in the top-ranked 600 molecules (22). 

Sell, C. S. (2008). Rational odorant design Fantasy or feasibility Perfum. Flavor. 33,48-52. Singh, N., Guha, R., Giulianotti, M. A., Pinilla, C., Houghten, R. A., and Medina-Franco, J. L. (2009). Chemoinformatic analysis of combinatorial libraries, drugs, natural products, and molecular libraries small molecule repository. J. Chem. Inf. Model. 49,1010-1024. 

It is only in the past 5 years or so that chemical probe development has really taken off. This has largely been driven by the NIH roadmap initiative which engaged a network (Molecnlar Libraries Probe Production Centers Network http //mli.nih.gov/mli/ mlpcn/mlpcn/) of academic-based centers that provided state-of-the-art high-throughput screening (HTS) capabilities of a large diverse small-molecule library (the Molecular Libraries Small Molecule Repository (MLSMR) >350,000 compounds) as well as much expertise in the activities of assay development and downstream hit to probe (http //mli.nih.gov/mli/). Prior to this initiative, HTS was almost exclusively conducted within pharmacentical... 

Fig. 6 Example of useful visualizations of an HTS campaign on 365,000 compounds of the NIH molecular libraries small molecule repository in an example enzyme assay. The Z-factor for this HTS campaign over all the normalized controls was Z 0.82 and the robust Z-factor for the screened compounds was degraded only slightly to Z -0.8, and the signal-to-background of -24.2 and signal-to-noise of -143.3 indicated an excellent assay and HTS campaign. The (a) frequency distribution of the activities, the (b) 2-D scattergram of activities as a function of plate order, and (c) a 3-D view of the plates and wells against their activities, all indicate a robust close to normally distributed screen, with no serious plate-based artifacts...

For more about this, see Livingston, D., Lease, T. Behind the scenes at the NIH molecular libraries small molecule repository. Soc. Biomol. Sci. News, 19, December 2005. Available at http //mlsmr.glpg.com/ MLSMR HomePage/. 

Singh N, Guha R, Giulianotti MA, et al. Chemoinformatic analysis of combinatorial libraries, drugs, natural products, and molecular libraries small molecule repository. J Chem Inf Model 2009 49 1010-1024. 

Essential to this pilot phase was the creation of a chemical library the Molecular Libraries Small Molecule Repository, or MLSMR. This library, which is accessible by querying MLSMR in PubChem Substance, was subjected to MLSCN bioactivity screening between 2004 and 2008 for a total of 691 assays that were uploaded to PubChem. These included 242 primary, 402 confirmatory and 8 summary assays, which covered 171 targets and 29 phenotypic screens. These numbers continue to grow as pilot phase projects are completed. 

Levitan, B.S. and Kauffman, S.A, In Exploiting Molecular Diversity Small Molecule Libraries for Drug Discovery, Cambridge Healthtech Institute, January 1996. 

R. A. Hoaghten, Linear Arrays and Combinatorial Mixtures of Quinazolinones, conference Exploiting Molecular Diversity Small Molecule Libraries For Drug Discovery, San Diego, CA, 1996. 

Calculation of ADME predictions is now routine and often high throughput. However, unlike many published studies in which calculated properties are validated with experimental data for a diverse collection of molecules, for virtual small-molecule libraries, there are usually no physical data to validate the predictions. Often, the molecules that are the subject of calculation are dissimilar to those molecules used to develop prediction tools. As a result, one is usually looking for trends in the prediction as a function of the selection of specific diversity reagents around a common core or scaffold. Thus, it is important to consider predicted molecular properties with care and to interpret the results with the proper level of expectation. 

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