Related Resources for ACD/PhysChem Suite

Showing 1-13 of 13

Sirius Analytical and ACD/Labs Announce PhysChem Partnership
Dec 01, 2011
ACD/Labs
Press Release
Sirius Analytical and ACD/Labs Announce PhysChem Partnership - Dec 2011

ACD/Labs Focuses all Japanese Distribution with Fujitsu
May 01, 2011
ACD/Labs
Press Release
ACD/Labs Focuses all Japanese Distribution with Fujitsu - July 2011

Introducing ACD/Percepta: A New Generation Platform for Physicochemical, ADME, and Tox Prediction
Apr 19, 2011
Daria Thorp (ACD/Labs)
Presentation
Apr 19, 2011, North American Users' Meeting
Download Presentation

Powerful Analytical Chemistry Software Solutions for CROs Through ACD/Labs Subscription Service
Feb 23, 2011
ACD/Labs
Press Release
Powerful Analytical Chemistry Software Solutions for CROs Through ACD/Labs Subscription Service - Feb 2011

FDA to Collaborate with ACD/Labs to Develop Predictive QSAR Models
Nov 04, 2010
ACD/Labs
Press Release
FDA to Collaborate with ACD/Labs to Develop Predictive QSAR Models - Nov 2010

Calculation of Boiling Point and Vapor Pressure
May 25, 2010
ACD/Labs
Movie
Read Abstract
  • Calculate the boiling point as a function of pressure, vapor pressure as a function of temperature, enthalpy of vaporization, and flash point
    		•
    View Movie

    Comparison of Nine Programs Predicting pKa Values of Pharmaceutical Substances
    Dec 04, 2009
    Chenzhong Liao and Marc C. Nicklaus
    Article
    Journal of Chemical Information and Modelling
    49(12): 2801–2812, 2009

    Knowledge of the possible ionization states of a pharmaceutical substance, embodied in the pKa values (logarithm of the acid dissociation constant), is vital for understanding many properties essential to drug development. We compare nine commercially available or free programs for predicting ionization constants. Eight of these programs are based on empirical methods: ACD/pKa DB 12.0, ADME Boxes 4.9, ADMET Predictor 3.0, Epik 1.6, Marvin 5.1.4, Pallas pKalc Net 2.0, Pipeline Pilot 5.0, and SPARC 4.2; one program is based on a quantum chemical method: Jaguar 7.5. We compared their performances by applying them to 197 pharmaceutical substances with 261 carefully determined and highly reliable experimental pKa values from a literature source. The programs ADME Boxes 4.9, ACD/pKa DB 12.0, and SPARC 4.2 ranked as the top three with mean absolute deviations of 0.389, 0.478, and 0.651 and r2 values of 0.944, 0.908, and 0.894, respectively. ACD/pKa DB 12.0 predicted all sites, whereas ADME Boxes 4.9 and SPARC 4.2 failed to predict 5 and 18 sites, respectively. The performance of the quantum chemical-based program Jaguar 7.5 was not as expected, with a mean absolute deviation of 1.283 and an r2 value of 0.579, indicating the potential for further development of this type of approach to pKa prediction.
    View online at the ACS Publications web site

    Integrated ADME Risk Assessment in Lead Optimization
    Oct 22, 2009
    Dr. Bernard Faller (Novartis Pharma AG)
    Presentation
    Oct 22, 2009, ADMET & PhysChem Symposium
    Download the presentation (751 Kb PDF file)

    Obtaining Solvation Descriptors For Ions and Ionic Species
    Oct 22, 2009
    Prof. Mike Abraham (University College London)
    Presentation
    Oct 22, 2009, ADMET & PhysChem Symposium
    Download the presentation (110 Kb PDF file)

    Novel Uses of pKa and ADME/Tox Calculation in Medicinal Chemistry Planning
    Oct 22, 2009
    Dr. Chris Lipinski (Melior Discovery, USA)
    Presentation
    Oct 22, 2009, ADMET & PhysChem Symposium
    Download the presentation (666 Kb PDF file)

    pKa Expert Training and Automation
    Oct 22, 2009
    Eduard Kolovanov
    Presentation
    Oct 22, 2009, ADMET & PhysChem Symposium
    Download the presentation (546 Kb PDF file)

    ACD/Labs and Pharma Algorithms Join Forces to Strengthen In Silico Screening and Prediction
    Feb 09, 2009
    ACD/Labs
    Press Release
    ACD/Labs and Pharma Algorithms Join Forces to Strengthen In Silico Screening and Prediction - February 2009

    ACD/LogP Method Description
    Sep 01, 2000
    Alanas A. Petrauskas and Eduard A. Kolovanov
    Article
    Perspect. Drug Discovery Des.
    19(1):99-116(18), 2000

    This study describes the development of the ACD/Log P calculation method. Analysis of 14 calculation methods revealed that the most accurate calculations are obtained when correction factors are used. We evaluated the correction factors used by Hansch and Leo in CLOGP in order to simplify their method. Most of the CLOGP structural factors are included in our fragmental increments. Aliphatic and aromatic factors are replaced with additive interfragmental increments. Missing increments are estimated by two empirical equations with simple physical interpretation. The final method uses three simple equations with several types of parameters. The training set included 3601 compounds and the correlation between experimental and calculated Log P values gave R = 0.992, S = 0.21. The method was validated by comparing it with 17 other methods on various data sets of independently selected drugs and other compounds. In all cases, our method produced the best results. The weakness of this method is that it uses a large number of individual increments for aromatic interactions. Each increment represents a combination of several effects which presently cannot be separated.
    View online at Perspectives in Drug Discovery and Design