For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
161
views
38
references
 Top references
cited by
742
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
0 collections
    0
    shares
      168
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: not found

      pkCSM: Predicting Small-Molecule Pharmacokinetic and Toxicity Properties Using Graph-Based Signatures

      rapid-communication

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Drug development has a high attrition rate, with poor pharmacokinetic and safety properties a significant hurdle. Computational approaches may help minimize these risks. We have developed a novel approach (pkCSM) which uses graph-based signatures to develop predictive models of central ADMET properties for drug development. pkCSM performs as well or better than current methods. A freely accessible web server ( http://structure.bioc.cam.ac.uk/pkcsm), which retains no information submitted to it, provides an integrated platform to rapidly evaluate pharmacokinetic and toxicity properties.

          Related collections

          Most cited references38

          • Record: found
          • Abstract: found
          • Article: not found

          The meaning and use of the area under a receiver operating characteristic (ROC) curve.

          J A Hanley, B J McNeil, Marnix van Holsbeeck (1982)
          A representation and interpretation of the area under a receiver operating characteristic (ROC) curve obtained by the "rating" method, or by mathematical predictions based on patient characteristics, is presented. It is shown that in such a setting the area represents the probability that a randomly chosen diseased subject is (correctly) rated or ranked with greater suspicion than a randomly chosen non-diseased subject. Moreover, this probability of a correct ranking is the same quantity that is estimated by the already well-studied nonparametric Wilcoxon statistic. These two relationships are exploited to (a) provide rapid closed-form expressions for the approximate magnitude of the sampling variability, i.e., standard error that one uses to accompany the area under a smoothed ROC curve, (b) guide in determining the size of the sample required to provide a sufficiently reliable estimate of this area, and (c) determine how large sample sizes should be to ensure that one can statistically detect differences in the accuracy of diagnostic techniques.
          Article 0 comments Cited 3873 times – based on 0 reviews     Review now
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            DUET: a server for predicting effects of mutations on protein stability using an integrated computational approach

            Douglas Pires, David B. Ascher, Tom Blundell (2014)
            Cancer genome and other sequencing initiatives are generating extensive data on non-synonymous single nucleotide polymorphisms (nsSNPs) in human and other genomes. In order to understand the impacts of nsSNPs on the structure and function of the proteome, as well as to guide protein engineering, accurate in silicomethodologies are required to study and predict their effects on protein stability. Despite the diversity of available computational methods in the literature, none has proven accurate and dependable on its own under all scenarios where mutation analysis is required. Here we present DUET, a web server for an integrated computational approach to study missense mutations in proteins. DUET consolidates two complementary approaches (mCSM and SDM) in a consensus prediction, obtained by combining the results of the separate methods in an optimized predictor using Support Vector Machines (SVM). We demonstrate that the proposed method improves overall accuracy of the predictions in comparison with either method individually and performs as well as or better than similar methods. The DUET web server is freely and openly available at http://structure.bioc.cam.ac.uk/duet.
            Article 0 comments Cited 316 times – based on 0 reviews     Review now
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Physiochemical drug properties associated with in vivo toxicological outcomes.

              Jason Hughes, Julian Blagg, David A. Price … (2008)
              Relationships between physicochemical drug properties and toxicity were inferred from a data set consisting of animal in vivo toleration (IVT) studies on 245 preclinical Pfizer compounds; an increased likelihood of toxic events was found for less polar, more lipophilic compounds. This trend held across a wide range of types of toxicity and across a broad swath of chemical space.
              Article 0 comments Cited 167 times – based on 0 reviews     Review now
                Bookmark
                All references

                Author and article information

                Journal
                Journal ID (nlm-ta): J Med Chem
                Journal ID (iso-abbrev): J. Med. Chem
                Journal ID (publisher-id): jm
                Journal ID (coden): jmcmar
                Title: Journal of Medicinal Chemistry
                Publisher: American Chemical Society
                ISSN (Print): 0022-2623
                ISSN (Electronic): 1520-4804
                Publication date (Electronic): 10 April 2015
                Publication date (Print): 14 May 2015
                Volume: 58
                Issue: 9
                Pages: 4066-4072
                Affiliations
                [† ]Department of Biochemistry, University of Cambridge , 80 Tennis Court Road, Sanger Building, Cambridge, Cambridgshire CB2 1GA, U.K.
                [‡ ]Centro de Pesquisas René Rachou, Fundação Oswaldo Cruz , Belo Horizonte 30190-002, Brazil
                Author notes
                [* ]For D.E.V.P.: phone, +44 1223766033; fax, +44 1223766002; E-mail, douglas.pires@ 123456cpqrr.fiocruz.br .
                [* ]For D.B.A.: phone, +44 1223766033; fax, +44 1223766002; E-mail, dascher@ 123456svi.edu.au .
                Article
                DOI: 10.1021/acs.jmedchem.5b00104
                PMC ID: 4434528
                PubMed ID: 25860834
                SO-VID: 7eed35fd-a794-4b07-abea-46bbd00fb34f
                Copyright © Copyright © 2015 American Chemical Society
                License:

                This is an open access article published under a Creative Commons Attribution (CC-BY) License, which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited.

                History
                Date received : 20 January 2015
                Categories
                Subject: Brief Article
                Custom metadata
                document-id-old-9 jm5b00104
                document-id-new-14 jm-2015-00104e
                ccc-price

                ScienceOpen disciplines: Pharmaceutical chemistry
                Data availability:
                ScienceOpen disciplines: Pharmaceutical chemistry

                Comments

                Comment on this article

                scite_

                Similar content168

                See all similar

                Cited by817

                See all cited by

                Most referenced authors621

                See all reference authors