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| Title |
Author |
Link |
| Classification of drugs by CNS access: An insight from quantitative blood-brain transport characteristics | K. Lanevskij, P. Japertas, R. Didziapetris | Download Poster |
| In silico test battery for rapid evaluation of genotoxic and carcinogenic potential of chemicals | K. Lanevskij, L. Juska, J. Dapkunas, A. Sazonovas, P. Japertas, R. Didziapetris | Download Poster |
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property prediction. Learn more about these products, and try our predictors in ACD/I-Lab (our online prediction engine). Play a quiz and enter to win an
iPad at our booth!
Conference Details
Presentation Schedule
Rendering the stages of structure elucidation: ACD/Labs Markush representation
Program Area: CINF: Division of Chemical Information
Symposium Title: (CINF001) Joint CINF-CSA Trust Symposium
Date: March 26, 2012
Time: 10:20–10:45 AM
Location: San Diego Convention Centre, Room 25C
Authors: Andrey Yerin, Ian Peirson
Abstract: View Abstract
The Markush structure is a favourite tool of patents, allowing a large number of discreet structures by definition of a single object.
While recent cheminformatics tools provide a possibility to operate with Markush structure, it remains almost totally the object for patents, being beyond everyday chemical
applications. The workflow of metabolite identification or impurity and degradant profiling now demands the rendering of stages corresponding to the specific degree of knowledge
about the chemical structure.
ACD/Labs have developed several tools that allow encoding and visualization by Markush tools multiple variable substitution points, mass and formula modifications. The ability to create
and search a database of such structures extends possibilities to retain, extract and leverage knowledge in the organization. The implemented structure representation can be encoded by
traditional structure formats and may become a standard tool for the exchange of partially defined structures between various chemical applications.
InChIKey collision safety: Experimental estimation for algorithmically generated structure libraries
Program Area: CINF: Division of Chemical Information
Symposium Title: (CINF007) InChI Symposium
Date: March 28, 2012
Time: 10:55–11:25 AM
Location: San Diego Convention Centre, Room 27A
Authors: Andrey Yerin, Kirill Blinov
Abstract: View Abstract
The InChIKey is a hash-based fixed length representation of the IUPAC International Chemical Identifier (InChI) and has growing importance
in chemical informatics as a basis for searching and indexing chemical structures. Since it is composed of 22 variable letters the InChIKey theoretically has an extremely low
collision rate but certainly cannot uniquely encode the whole of chemical space. While InChIKey collisions have already been reported experimental tests of collision rates for
extremely large databases have not yet been performed.
A protocol allowing for the generation of InChIKeys for algorithmically created virtual structure databases has been launched at ACD/Labs. We will report on our work analyzing
large generated data sets and provide reliable statistical estimations of InChIKey collisions.
Poster Schedule
In silico test battery for rapid evaluation of genotoxic and carcinogenic potential of chemicals
Division: Division of Medicinal Chemistry
Session: General Poster Session
Paper ID: 19034
Authors: K. Lanevskij, L. Juska, J. Dapkunas, A. Sazonovas, P. Japertas, R. Didziapetris
Abstract: View Abstract
This work is an extension of our previous study focusing on computational assessment of genotoxic impurities in drug products.
Our new approach relies on a battery of probabilistic QSAR models supplemented by a knowledge-based expert system that identifies structural fragments potentially
responsible for hazardous activity. The analysis was based on experimental data obtained from FDA, and involved 21 endpoints corresponding to different mechanisms
of toxic action: mutagenicity, clastogenicity, carcinogenicity, etc. Probabilistic models were derived using GALAS (Global, Adjusted Locally According to Similarity)
modeling methodology developed in our group. The updated list of alerting groups contained 70 distinct substructures. The expert system was highly sensitive, recognizing
>90% of potent carcinogens, as classified by FDA. Sensitivity of probabilistic GALAS models ranged from 60% to 93%, whilst maintaining high (>80%) specificity of predictions.
These results show that the described computational platform ensures sufficient prediction accuracy for rapid genotoxicity/carcinogenicity profiling of various chemicals.
Classification of drugs by CNS access: An insight from quantitative blood-brain transport characteristics
Division: Division of Medicinal Chemistry
Session: General Poster Session
Paper ID: 19034
Authors: K. Lanevskij, P. Japertas, R. Didziapetris
Abstract: View Abstract
The ultimate goal of QSAR analysis focusing on blood-brain barrier penetration is the ability to discriminate between CNS active
and inactive molecules. The objective of the current study was to establish the relationship between quantitative blood-brain transport parameters and qualitative data
indicating whether the compound penetrates into the brain efficiently enough to exhibit central action. Two quantitative characteristics were considered: brain/plasma
equilibration rate, and the extent of brain/plasma partitioning at equilibrium (logBB). Analysis of a diverse data set consisting of >1500 compounds from World Drug Index
database with experimentally assigned brain penetration categories revealed that a linear combination of the above mentioned parameters allowed classifying drugs by CNS access
with 94% overall accuracy. Furthermore, the devised classification score well correlated with unbound brain/plasma partitioning coefficient (logKp,uu), which is recognized as
an unambiguous determinant of brain exposure. The obtained results confirm the validity of the proposed classification approach.
