ACS Spring

March 27-31, 2011

Location:
Anaheim Convention Center
Anaheim, CA, USA
 
 
 
Website: ACS Spring

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Related presentations, posters, and scientific talks from this event have been posted here for your reference. Please click the associated link to download.

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In silico identification of metabolic soft spots: Case study using ACD/ADME Suite softwareJustas Dapkunas, Andrius Sazonovas, Remigijus Didziapetris, Pranas Japertas (ACD/Labs, Inc., Vilnius, Lithuania; Department of Biochemistry and Biophysics, Vilnius University, Vilnius, Lithuania)Download Poster
New approach for in silico genotoxicity testing of impurities and degradantsLiutauras Juska, Kiril Lanevskij, Remigijus Didziapetris, Pranas Japertas (ACD/Labs, Inc., Vilnius, Lithuania; Department of Biochemistry and Biophysics, Vilnius University, Vilnius, Lithuania) Download Poster
Novel QSAR models for predicting toxicity of chemicals to aquatic organisms and identifying the mode of actionMr. Kiril Lanevskij, Mr. Liutauras Juska, Dr. Remigijus Didziapetris, Dr. Pranas Japertas (ACD/Labs, Inc., Vilnius, Lithuania; Department of Biochemistry and Biophysics, Vilnius University, Vilnius, Lithuania) Download Poster
QSAR model of regioselectivity of metabolism in human liver microsomes: Development, validation, comparison and adaptation to novel compoundsJustas Dapkunas, Andrius Sazonovas, Pranas Japertas (ACD/Labs, Inc., Vilnius, Lithuania; Department of Biochemistry and Biophysics, Vilnius University, Vilnius, Lithuania) Download Poster
Conference Details

Booth # 850

Poster Schedule

Title: Novel QSAR models for predicting toxicity of chemicals to aquatic organisms and identifying the mode of action
Authors: Mr. Kiril Lanevskij, Mr. Liutauras Juska, Dr. Remigijus Didziapetris, Dr. Pranas Japertas (ACD/Labs, Inc., Vilnius, Lithuania; Department of Biochemistry and Biophysics, Vilnius University, Vilnius, Lithuania)
Date: Monday, March 28, 2011 & Wednesday March 30, 2011
Time: 8:00–10:00 PM
Location: Anaheim Convention Center – Hall B
Abstract #: 233
Abstract: View Abstract

This study presents the application of recently introduced GALAS modeling methodology for estimating toxicity of chemicals to several aquatic species. Experimental data were expressed as median lethal concentration of test compound in water (LC50) and the data set contained 904 LC50 values for fishes (Pimephales promelas) and 589 LC50 values for crustaceans (Daphnia magna). The utilized modeling approach was validated by applying the same principles to develop a predictive model for IGC50 (50% inhibitory growth concentration) to protozoan Tetrahymena pyriformis. This model was submitted as an entry for environmental toxicity prediction challenge hosted by CADASTER project. The model derived using known IGC50 values for 644 compounds was identified among the winners achieving RMSE under 0.8 log units for blind validation set of 120 chemicals. It is also demonstrated that the chemicals' Mode of Action (MOA) can be determined using a simple set of structural fragments associated with certain MOA classes.

Title: New approach for in silico genotoxicity testing of impurities and degradants
Authors: Mr. Liutauras Juska, Mr. Kiril Lanevskij, Dr. Remigijus Didziapetris, Dr. Pranas Japertas (ACD/Labs, Inc., Vilnius, Lithuania; Department of Biochemistry and Biophysics, Vilnius University, Vilnius, Lithuania)
Date: Monday, March 30, 2011
Time: 7:00–11:00 PM
Location: Anaheim Convention Center –Ballroom C/D/E
Abstract #: 276
Abstract: View Abstract

According to FDA Guidance for Industry, assessment of genotoxicity/carcinogenicity by computational methods is sufficient for impurities in drug products present at levels below the ICH qualification thresholds. This study presents a novel approach to aid this assessment based on a probabilistic predictor of Ames genotoxicity, and a knowledge-based system of structural alerts. The list of potentially hazardous structural fragments was compiled from various literature sources and refined by analyzing their performance on data from different assays detecting point mutational and/or clastogenic mechanisms of DNA damage (Ames test, in vitro chromosomal aberrations, micronucleus test, mouse lymphoma assay). Finally, the expert system was tested on the Carcinogenic Potency Database to ensure detection of common non-genotoxic carcinogens. Selected structural alerts achieved >90% sensitivity for recognizing positive compounds in Ames and Chromosomal Aberrations data sets showing that the absence of alerting groups is a reliable criterion for identifying impurities not posing significant genotoxic/carcinogenic risk.

Title: In silico identification of metabolic soft spots: Case study using ACD/ADME Suite software
Authors: Mr. Justas Dapkunas, Dr. Andrius Sazonovas, Dr. Remigijus Didziapetris, Dr. Pranas Japertas (ACD/Labs, Inc., Vilnius, Lithuania; Department of Biochemistry and Biophysics, Vilnius University, Vilnius, Lithuania)
Date: Monday, March 30, 2011
Time: 7:00–11:00 PM
Location: Anaheim Convention Center –Ballroom C/D/E
Abstract #: 277
Abstract: View Abstract

Metabolic stability, as determined in liver microsomes, is one of the primary assays used in early drug discovery. A key factor limiting compound half-life is the CYP mediated metabolism. High clearance by cytochrome P450 enzymes implies a higher and more frequent dosing as well as poses a risk for individual variations in exposure. Experimental identification of metabolic soft spots during lead optimization is a time and resource consuming task as it requires separation of individual metabolites and elucidation of their structure. Here we present a case study illustrating how this workflow can be facilitated by in silico regioselectivity prediction tools. Presented examples involve analysis of the detailed metabolite identification studies for recently published novel compounds and demonstrate the performance of the ACD/ADME Suite software in identification of their most likely metabolites, thus providing an insight on the structural modifications needed to achieve optimal metabolic stability.

Title: QSAR model of regioselectivity of metabolism in human liver microsomes: Development, validation, comparison and adaptation to novel compounds
Authors: Mr. Justas Dapkunas, Dr. Andrius Sazonovas, Dr. Pranas Japertas (ACD/Labs, Inc., Vilnius, Lithuania; Department of Biochemistry and Biophysics, Vilnius University, Vilnius, Lithuania)
Date: Monday, March 30, 2011
Time: 7:00–11:00 PM
Location: Anaheim Convention Center –Ballroom C/D/E
Abstract #: 278
Abstract: View Abstract

A probabilistic model predicting sites of human liver microsomal metabolism in a molecule has been developed using experimental data for 873 compounds and recently introduced GALAS modeling methodology. It involves calculation of the Reliability Index (RI) values which are shown to reflect the accuracy of predictions for the test set, thus serving as a basis for the Model Applicability Domain assessment. The main emphasis is made on the model evaluation using newly published data for >40 novel drug-like compounds. At least one metabolism site was found for more than 80% of compounds, and more than 60% of them had majority of metabolites identified correctly. High RI values again successfully identified correct predictions. After training procedure previously not recognized metabolism sites could be identified as well illustrating the straightforward expansion of the Applicability Domain for GALAS method based models. Analogously the developed model can be adapted for cytochrome P450 isoform profiling.