ACD Labs Inc.

Vilnius, Lithuania

ACD Labs Inc.

Vilnius, Lithuania
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Lanevskij K.,VsI Aukstieji Algoritmai | Lanevskij K.,ACD Labs Inc. | Japertas P.,VsI Aukstieji Algoritmai | Japertas P.,ACD Labs Inc. | And 2 more authors.
Expert Opinion on Drug Metabolism and Toxicology | Year: 2013

Introduction: Ability to cross the blood-brain barrier is one of the key ADME characteristics of all drug candidates regardless of their target location in the body. While good brain penetration is essential for CNS drugs, it may lead to serious side effects in case of peripherally-targeted molecules. Despite a high demand of computational methods for estimating brain transport early in drug discovery, achieving good prediction accuracy still remains a challenging task. Areas covered: This article reviews various measures employed to quantify brain delivery and recent advances in QSAR approaches for predicting these properties from the compound's structure. Additionally, the authors discuss the classification models attempting to distinguish between permeable and impermeable chemicals. Expert opinion: Recent research in the field of brain penetration modeling showed an increasing understanding of the processes involved in drug disposition, although most models of brain/plasma partitioning still rely on purely statistical considerations. Preferably, new models should incorporate mechanistic knowledge since it is the prerequisite for guiding drug design efforts in the desired direction. To increase the efficiency of computational tools, a broader view is necessary, involving rate and extent of brain penetration, as well as plasma and brain tissue binding strength, instead of relying on any single property. © 2013 Informa UK, Ltd.

Lanevskij K.,ACD Labs Inc. | Lanevskij K.,Vilnius University | Dapkunas J.,ACD Labs Inc. | Dapkunas J.,Vilnius University | And 4 more authors.
Journal of Pharmaceutical Sciences | Year: 2011

The extent of brain delivery expressed as steady-state brain/blood distribution ratio (log BB) is the most frequently used parameter for characterizing central nervous system exposure of drugs and drug candidates. The aim of the current study was to propose a physicochemical QSAR model for log BB prediction. Model development involved the following steps: (i) A data set consisting of 470 experimental log BB values determined in rodents was compiled and verified to ensure that selected data represented drug disposition governed by passive diffusion across blood-brain barrier. (ii) Available log BB values were corrected for unbound fraction in plasma to separate the influence of drug binding to brain and plasma constituents. (iii) The resulting ratios of total brain to unbound plasma concentrations reflecting brain tissue binding were described by a nonlinear ionization-specific model in terms of octanol/water log P and pKa. The results of internal and external validation demonstrated good predictive power of the obtained model as both log BB and brain tissue binding strength were predicted with residual mean square error of 0.4 log units. The statistical parameters were similar among training and validation sets, indicating that the model is not likely to be overfitted. © 2011 Wiley-Liss, Inc.

Wright A.D.,Australian Institute of Marine Science | Wright A.D.,University of Hawaii at Hilo | Nielson J.L.,Australian Institute of Marine Science | Nielson J.L.,ACD Labs Inc. | And 4 more authors.
Marine Drugs | Year: 2012

The methanol extract of a Sinularia sp., collected from Bowden Reef, Queensland, Australia, yielded ten natural products. These included the new nitrogenous diterpene (4R*,5R*,9S*,10R*,11Z)-4-methoxy- 9-((dimethylamino)-methyl)-12,15-epoxy-11 (13)-en-decahydronaphthalen-16-ol (1), and the new lobane, (1R*,2R*,4S*,15E)-loba-8,10, 13(14),15(16)-tetraen-17,18-diol-17-acetate (2). Also isolated were two known cembranes, sarcophytol-B and (1E,3E,7E)-11,12-epoxycembratrien-15-ol, and six known lobanes, loba-8, 10,13(15)-triene-16,17,18-triol, 14,18-epoxyloba-8,10, 13(15)-trien-17-ol, lobatrientriol, lobatrienolide, 14,17-epoxyloba-8,10,13(15)- trien-18-ol-18-acetate and (17R)-loba-8,10,13 (15)-trien-17,18-diol. Structures of the new compounds were elucidated through interpretation of spectra obtained after extensive NMR and MS investigations and comparison with literature values. The tumour cell growth inhibition potential of 1 and 2 along with loba-8,10,13(15)-triene-16,17,18-triol, 14,17-epoxyloba-8,10,13 (15)-trien-18-ol-18-acetate, lobatrienolide, (1E,3E,7E)-11,12-epoxycembratrien- 15-ol and sarcophytol-B were assessed against three human tumour cell lines (SF-268, MCF-7 and H460). The lobanes and cembranes tested demonstrated 50% growth inhibition in the range 6.8-18.5 μM, with no selectivity, whilst 1 was less active (GI50 70-175 μM). © 2012 by the authors; licensee MDPI.

PubMed | U.S. Food and Drug Administration, University of Maryland University College, U.S. Department of Agriculture, Zhejiang University of Technology and ACD Labs Inc.
Type: | Journal: Magnetic resonance in chemistry : MRC | Year: 2016

The structure of a novel compound from Adansonia digitata has been elucidated, and its

Didziapetris R.,VsI Aukstieji algoritmai | Didziapetris R.,ACD Labs Inc. | Lanevskij K.,VsI Aukstieji algoritmai | Lanevskij K.,ACD Labs Inc.
Journal of Computer-Aided Molecular Design | Year: 2016

A large and chemically diverse hERG inhibition data set comprised of 6690 compounds was constructed on the basis of ChEMBL bioactivity database and original publications dealing with experimental determination of hERG activities using patch-clamp and competitive displacement assays. The collected data were converted to binary format at 10 µM activity threshold and subjected to gradient boosting machine classification analysis using a minimal set of physicochemical and topological descriptors. The tested parameters involved lipophilicity (log P), ionization (pKa), polar surface area, aromaticity, molecular size and flexibility. The employed approach allowed classifying the compounds with an overall 75–80 % accuracy, even though it only accounted for non-specific interactions between hERG and ligand molecules. The observed descriptor-response profiles were consistent with common knowledge about hERG ligand binding site, but also revealed several important quantitative trends, as well as slight inter-assay variability in hERG inhibition data. The results suggest that even weakly basic groups (pKa < 6) might substantially contribute to hERG inhibition potential, whereas the role of lipophilicity depends on the compound’s ionization state, and the influence of log P decreases in the order of bases > zwitterions > neutrals > acids. Given its robust performance and clear physicochemical interpretation, the proposed model may provide valuable information to direct drug discovery efforts towards compounds with reduced risk of hERG-related cardiotoxicity. © 2016 Springer International Publishing Switzerland

Antler M.,ACD Labs Inc.
Reading for the R and D Community | Year: 2010

Mass spectrometry (MS) instrument vendors offer automated MS/MS data collection for analytes that are present above a certain intensity threshold, or for expected metabolites. ACD/Labs have developed ACD/Metabolite ID Suite™ that generates a report of retention times, peak areas, and spectra for each expected metabolite. Additional software modules can predict metabolite structures for a new drug, identifying the sites most likely to be susceptible to metabolism by human liver microsomes, which can help with both structure elucidation and drug design. The ACD/Metabolite ID Suite™ can help extract the likely metabolite peaks from a complex full-scan liquid chromatography-mass chromatography (LC/MS) data set. The software can compare the metabolized sample with a control sample and identify unique features in the metabolized sample. Software reduces the complex data set to a short list of peaks for further review, interprets the spectrum to determine the mass of the protonated molecule, and determines potential chemical formulae for the potential metabolite.

Sazonovas A.,ACD Labs Inc. | Sazonovas A.,Vilnius University | Japertas P.,ACD Labs Inc. | Didziapetris R.,ACD Labs Inc.
SAR and QSAR in Environmental Research | Year: 2010

This study presents a new type of acute toxicity (LD50) prediction that enables automated assessment of the reliability of predictions (which is synonymous with the assessment of the Model Applicability Domain as defined by the Organization for Economic Cooperation and Development). Analysis involved nearly 75,000 compounds from six animal systems (acute rat toxicity after oral and intraperitoneal administration; acute mouse toxicity after oral, intraperitoneal, intravenous, and subcutaneous administration). Fragmental Partial Least Squares (PLS) with 100 bootstraps yielded baseline predictions that were automatically corrected for non-linear effects in local chemical spaces-a combination called Global, Adjusted Locally According to Similarity (GALAS) modelling methodology. Each prediction obtained in this manner is provided with a reliability index value that depends on both compound's similarity to the training set (that accounts for similar trends in LD50 variations within multiple bootstraps) and consistency of experimental results with regard to the baseline model in the local chemical environment. The actual performance of the Reliability Index (RI) was proven by its good (and uniform) correlations with Root Mean Square Error (RMSE) in all validation sets, thus providing quantitative assessment of the Model Applicability Domain. The obtained models can be used for compound screening in the early stages of drug development and prioritization for experimental in vitro testing or later in vivo animal acute toxicity studies. © 2010 Taylor & Francis.

Didziapetris R.,ACD Labs Inc. | Dapkunas J.,ACD Labs Inc. | Sazonovas A.,ACD Labs Inc. | Japertas P.,ACD Labs Inc.
Journal of Computer-Aided Molecular Design | Year: 2010

A new structure-activity relationship model predicting the probability for a compound to inhibit human cytochrome P450 3A4 has been developed using data for >800 compounds from various literature sources and tested on PubChem screening data. Novel GALAS (Global, Adjusted Locally According to Similarity) modeling methodology has been used, which is a combination of baseline global QSAR model and local similarity based corrections. GALAS modeling method allows forecasting the reliability of prediction thus defining the model applicability domain. For compounds within this domain the statistical results of the final model approach the data consistency between experimental data from literature and PubChem datasets with the overall accuracy of 89%. However, the original model is applicable only for less than a half of PubChem database. Since the similarity correction procedure of GALAS modeling method allows straightforward model training, the possibility to expand the applicability domain has been investigated. Experimental data from PubChem dataset served as an example of in-house high-throughput screening data. The model successfully adapted itself to both data classified using the same and different IC50 threshold compared with the training set. In addition, adjustment of the CYP3A4 inhibition model to compounds with a novel chemical scaffold has been demonstrated. The reported GALAS model is proposed as a useful tool for virtual screening of compounds for possible drug-drug interactions even prior to the actual synthesis. © 2010 Springer Science+Business Media B.V.

Samokhin A.,Moscow State University | Sotnezova K.,Moscow State University | Lashin V.,ACD Labs Inc. | Revelsky I.,Moscow State University
Journal of Mass Spectrometry | Year: 2015

Performance of several library search algorithms (against EI mass spectral databases) implemented in commercial software products (acd/specdb, chemstation, gc/ms solution and ms search) was estimated. Test set contained 1000 mass spectra, which were randomly selected from NIST'08 (RepLib) mass spectral database. It was shown that composite (also known as identity) algorithm implemented in ms search (NIST) software gives statistically the best results: the correct compound occupied the first position in the list of possible candidates in 81% of cases; the correct compound was within the list of top ten candidates in 98% of cases. It was found that use of presearch option can lead to rejection of the correct answer from the list of possible candidates (therefore presearch option should not be used, if possible). Overall performance of library search algorithms was estimated using receiver operating characteristic curves. © 2015 John Wiley & Sons, Ltd.

Pletnev I.,FIZ CHEMIE Berlin | Erin A.,ACD Labs Inc. | McNaught A.,U.S. National Institute of Standards and Technology | Blinov K.,ACD Labs Inc. | And 2 more authors.
Journal of Cheminformatics | Year: 2012

InChIKey is a 27-character compacted (hashed) version of InChI which is intended for Internet and database searching/indexing and is based on an SHA-256 hash of the InChI character string. The first block of InChIKey encodes molecular skeleton while the second block represents various kinds of isomerism (stereo, tautomeric, etc.). InChIKey is designed to be a nearly unique substitute for the parent InChI. However, a single InChIKey may occasionally map to two or more InChI strings (collision). The appearance of collision itself does not compromise the signature as collision-free hashing is impossible; the only viable approach is to set and keep a reasonable level of collision resistance which is sufficient for typical applications. © 2012 Bachrach; licensee Chemistry Central Ltd.

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