Summary: Topological indices



 Dear Netters,
 here is my summary for my recent question on software for topological
 indices.
 It took some time because two weeks ago the mainboard of my computer was stolen
 such that I didn't have access tothe data on my hard disk (meanwhile I got a
 new one).  Furthermore I have to admit that I hadn't remembered that the same
 question had been posted this spring (by "Richard Bone" <rgab -x-
 at -x- trpntech.com> on
 22 May 1995 14:45:43 - look for it in CCL archive). The inquiries I received
 show, however, that the need for information on this topic is not fulfilled yet.
 Thanks to all scientists who answered. My special thank are due to Dr. S. Basak
 of Resource Institute, Dulluth, MN, who even sent me a pile of (p)reprints of
 his works with a lot of valuable information and useful references.
 It turned out that there is excellent software available - but not public
 domain. Some simple connectivity or distance indices are certainly not hard to
 implement and can be looked up in a large number of publications. But some more
 efforts are needed to program more complex indices.
 Best regards,
 Th. Wieland
 Thomas Wieland               +---------------+
 Dipl. Math.                  |+----    +----+|
 Lehrstuhl II f. Mathematik   |\    \   |    ||
 Universitaet Bayreuth        | \    \  |    ||
                              |  \    \ |    ||
 95440 Bayreuth               |   \    \\    ||
 Germany                      |    \    \\   ||
 Tel. +49 (921) 553386        |     \     \\ ||
 Fax  +49 (921) 553385        |      \-------||
                              +---------------+
 ------------------------------------------------------------------------------
 Original question was:
 >Dear Colleagues,
 >
 >I am looking for some simple programs (preferably public-domain,
 >best with sources) that are able to compute topological indices
 >of molecular graphs, no matter which (Wiener-Index, Randic-Index
 >etc.)
 >
 >I would gratefully appreciate any hints to ftp-sites where such software
 >can be found. I tried some WWW-search machines but my key words
 "topological
 >index" didn't suffice.
 >
 ------------------------------------------------------------------------------
 From: Lipkowitz <lipkowitz -x- at -x- chem.iupui.edu>
 A great list of programs for computational chemistry is in each Appendix of
 Reviews in Computational Chemistry, VCH Publishers Inc. The list is prepared by
 Don Boyd and I'm sure has what you're looking for. Kenny
 ------------------------------------------------------------------------------
 From: "Dr. Subhash Basak" <sbasak -x- at -x- wyle.nrri.umn.edu>
 Thank you for your inquiry.  We have two programs, POLLY and APPROBE which
 are currently being used by companies like Upjohn, Glaxo, Government
 agencies like U S Environmental Protection Agency, National Institutes of
 Health, US Army for molecular design and QSAR analysis pertaining to health
 and environment.
 I am sending you info about POLLY AND APPROBE below.  I am also mailing you
 a collection of my papers in the area of development of topological indices
 and their applications in QSAR and quantifications of molecular similarity
 as well as applications of similarity in estimating properties of molecules.
 The POLLY software is copyright of the University of Minnesota.  Licensing/
 ordering information regarding POLLY can be obtained from Bob Hicks of the
 Office of Research and Technology Transfer Administration (ORTTA) of the U
 of Minnesota.  Bob can be reached at: bob -x- at -x- ortta.umn.edu.
 The price of the software is $2,000.00 (two thousand dollars only) per
 licensed site.  Mr. Hicks can give you more details about the licensing
 aspects.
 POLLY v. 2.3
 S.C. Basak
 Natural Resources Research Institute
 University of Minnesota
 Duluth, Minnesota 55811
 USA
 D.K. Harriss
 V.R. Magnuson
 Department of Chemistry
 University of Minnesota
 Duluth, Minnesota 55812
 USA
 !Copyright (C) 1986, 1988 Regents of the University of Minnesota.
 All Rights
 Reserved.
 I. Introduction
       POLLY is a tested and documented computer program which
 calculates the
 values of 98 topological (graph theoretic, connectivity and
 complexity type) indices for
 molecules containing up to 120 atoms composed of the following atom
 types:  carbon,
 nitrogen, oxygen, chlorine, bromine, sulfur, fluorine, phosphorous,
 iodine, boron and
 hydrogen.
       These indices include the Zagreg group indices1 , Wiener
 index2, Randic's
 connectivity index3, higher order connectivity indices and valence
 connectivity indices
 of different types4, bonding connectivity indices5, information
 theoretic indices based
 on distance matrix6, indices of neighborhood symmetry7,8,
 information theoretic indices
 of degree complexity, distance complexity and vertex complexity9,
 information theoretic
 indices on graph orbits10, and paths of different lengths.
       Topological indices have been successfully used in the
 quantification of
 molecular similarity5, 11-15, structure-property
 correlations2-4,16-19, and prediction of
 biomedicinal and toxic properties of different classes of
 molecules4,7,8,20.
       The program is structured to accept molecular descriptions in
 the form of
 SMILES notation but is easily adapted to other, user oriented,
 forms of input such as
 MOLFILE.  The output consists of values of the 98 indices for each
 molecule.
       POLLY is programmed in ANSI C and has been tested on UNIX and
 MSDOS
 platforms.  POLLY is provided in source code form only on UNIX
 platforms, both
 source and executable for the MSDOS platform.
 II. Running POLLY
       POLLY may be run in either interactive (input from the
 keyboard) or
 batch (input from a file) modes.  To enter input from the keyboard,
 just type polly at
 the operating system prompt:
       Prompt> polly<ret>
       POLLY will then respond with a SMILES: prompt.  At this
 point, type in the
 SMILES string to specify the compound.  The indices, or an error
 message if an
 invalid SMILES string, will be output to the console.  A sequence
 number is output as
 well.  This number is just how many compounds POLLY has processed
 during the
 current session.
       The usage of POLLY in batch mode has the following format:
       Prompt> polly input_name <output_name> <error_name>
       Here input_name is the name of the file with molecule
 identifiers and SMILES
 strings (See Sec III for descriptions).  The default extension for
 this file is ".smi" and
 may be dropped from the command line.  If any other extension is
 used it must be
 explicitly stated.  By default, POLLY will write indices to a file
 with the same base
 name as the input file, appending the extension .mci and error
 messages to a file with
 the extension .err.  For example, if a user runs POLLY with the
 following command
 line:
    polly test.smi
 indices will be written to test.mci and error messages will be
 written to test.err.  You
 my override these defaults by specifying the output and error file
 names on the
 command line.
 III. Input
 A. Format
       For batch mode, POLLY requires an identifier followed by one
 or more spaces,
 and a SMILES21 string (described below).  The sequence number and
 SMILES string
 must occur on one line.  The identifier may be composed of any
 ASCII character,
 excluding white space characters and is limited to 80 characters in
 length.
 B. SMILES string
       POLLY uses the SMILES (Simplified Molecular Identification
 and Line Entry
 System) method for specifying topological structure of a compound.
       The structure represented by a SMILES string should, under
 most
 circumstances, be hydrogen suppressed.  The SMILES interpreter
 within POLLY will
 determine the location of hydrogens implicitly by the normal
 valence of the atoms to
 which they would be connected.
 1. Atom representation
       Each atom is represented by its atomic symbol.  For single
 letter symbols, use
 lower case letters to represent aromatic atoms, upper case letters
 to represent
 aliphatic atoms.  Double letter symbols are represented be an
 uppercase first letter,
 lowercase second letter.  If you must indicate aromaticity of an
 atom with a double
 letter symbol, the symbol should be followed by an "!".
       Double letter symbols can have ambiguous interpretation.  For
 example, the
 symbol for silicon, Si, could be interpreted as aliphatic sulfur
 bonded to aromatic
 iodine.  Any double letter symbol that could have ambiguous
 interpretation should be
 enclosed in square brackets "[]".  Silicon would then be
 represented by [Si].  If the
 double letter symbol would not have ambiguous interpretation, the
 brackets are not
 required (e.g. bromine is Br, not [Br]).
 Examples:  Chlorine              Cl or [Cl]
            Silicon               [Si]
            Aliphatic carbon      C
            Aromatic carbon       c
 2. Bonds
       By default, the bond between any two atoms is a single bond
 (see section
 III.B.4, aromatic rings for an exception).  To override this
 default, the bond must be
 explicitly represented.  The following bond types are available:
            Single     -
            Double     =
            Triple     #
 Examples:  Ethane     CC or C-C
            Ethene     C=C
            Ethyne     C#C
 3. Branches
       When an atom has more than two connecting atoms, the
 additional connecting
 chains should be enclosed in parentheses.  The chain within a set
 of parentheses is
 interpreted as being connected to the atom immediately preceding
 the left parenthesis.
 You may nest parentheses.
 Examples:  Carbon tetrachloride  ClC(Cl)(Cl)Cl
            Di-n-butylphosphate   O=P(OCCCC)OCCCC or
                                  CCCCOP(=O)OCCCC
       Note in the second SMILES string for Di-n-butylphosphate the
 double bond to
 the oxygen is also enclosed within the parentheses.  Any bonding
 information to an
 atom within parentheses must also be enclosed within the
 parentheses.
 4. Rings
       To represent a ring as a linear structure, one bond in the
 ring must be broken.
 This structure can then be represented as a linear string.  To
 identify where the
 broken bond occurred, each atom that was involved is labeled with
 a digit(s).  These
 two atoms comprise a ring-closure pair.  The digit is placed
 following the two atoms
 that had the bond broken between them.  The interpreter may then
 re-establish the
 bond in the connection matrix.
       Two digits may be used to identify ring-closure pairs if they
 are preceded by the
 character "%".  Therefore, up to 99 (1-99) rings may be labeled.
 Examples:  Cyclohexane           C1CCCCC1
            1-Methylcyclopentene  CC%11=CCCC%11
       Aromatic ring: SMILES notation allows atoms in aromatic rings
 to be
 represented with lower case atomic symbols.  This avoids having to
 designate
 conjugated double bonds in aromatic rings, i.e. the default is not
 a single bond, but the
 conjugated double bond.
 Examples:  Benzene               c1ccccc1
            Naphthalene           c1cc2ccccc2cc1
 5. Atom Qualifiers
       Placing square brackets around an atom symbol allows you to
 specify additional
 information about an atom that can not be implicitly deduced from
 the connection
 table.  This would include formal charges or hydrogens about an
 aromatic nitrogen.
 Examples:  Pyrrole               c1cccc[nH]1
            Tetramethylammonium   C[N+](C)(C)C
 6. Restrictions
 a. POLLY utilizes only a subset of all possible atoms, those that
 allow the
 representation of most organic compounds.
 b. The maximum SMILES string length is 120.
 c. The maximum number of atoms for any compound is 120.
 d. Only compounds that can be represented by a connected graph are
 allowed.
 e. Hydrogens should not be included in the SMILES string except as
 qualifiers.
 IV. Output
       Appendix 1 describes the indices output by POLLY.  The order
 the indices are
 listed corresponds to the order in which they are output by POLLY.
 Appendix 2 lists
 the parameters output on a record by record basis.
 V.  References
 1.    I. Gutman, B. Ruscic, N. Trinajstic and C. F. Wilcox, Jr.,
 Graph theory and
       molecular orbitals, Part XII. Acyclic polyenes. J. Chem.
 Phys., 62, 3339-3405
       (1975).
 2.    H. Wiener, Structural determination of paraffin boiling
 points, J. Amer. Chem.
       Soc., 69, 17-20 (1947).
 3.    M. Randic', On characterization of molecular branching, J.
 Am. Chem. Soc. 97,
       6609-6615 (1975).
 4.    L.B. Kier and L.H. Hall, Molecular Connectivity in
 Structure-Activity Analysis
       (Research Studies Press, Letchworth, Hertfordshire, U.K.,
 1986).
 5.    S.C. Basak, V.R. Magnuson, G.J. Niemi and R.R. Regal,
 Determining structural
       similarity of chemicals using graph-theoretic indices,
 Discrete Applied
       Mathematics, 19, 17 (1988); Special Volume: Applications of
 Graph Theory in
       Chemistry and Physics, J.W. Kennedy and L.V. Quintas (eds.).
 6.    D. Bonchev and N. Trinajstic, Information theory, distance
 matrix and molecular
       branching, J. Chem. Phys., 67, 4517-4533 (1977).
 7.    A.B. Roy, S.C. Basak, D.K. Harriss and V.R. Magnuson,
 Neighborhood
       Complexities and Symmetry of Chemical graphs and their
 biological
       applications, in Mathematical Modelling in Science and
 Technology, X.J.R.
       Avula, R.E. Kalman, A.I. Lipais and E.Y. Rodin (Eds.), p.
 745, Pergamon Press,
       1984.
 8.    S.C. Basak, Use of molecular complexity indices in predictive
 pharmacology
       and toxicology: a QSAR approach, Med. Sci. Res., 15, 605
 (1987).
 9.    C. Raychaudhury, S.K. Ray, J.J. Ghosh, A.B. Roy and S.C.
 Basak,
       Discrimination of isomeric structures using
 information-theoretic topological
       indices, J. Comput. Chem., 5, 581 (1984).
 10.   N. Rashevsky, Life, information theory and topology, Bull.
 Math. Biophys., 17,
       229-235 (1955).
 11.   M. Randic', in: Computer Based Methods of Molecular
 Similarity, ed. G.M.
       Maggiora (John Wiley, in press, 1989).
 12.   S.C. Basak, V.R. Magnuson, G.J. Niemi, R.R. Regal and G.D.
 Veith,
       Topological indices: their nature, mutual relatedness, and
 applications,
       Mathematical Modelling, 8, 300 (1987).
 13.   M. Johnson, S.C. Basak and G. Maggiora, A characterization of
 molecular
       similarity methods for property prediction, Mathematical and
 Computer
       Modelling, II, 630 (1988).
 14.   M. Lajiness, Molecular Similarity Based Methods for Selecting
 compounds for
       Screening, in: Computational Chemical Graph Theory, Ed. D. H.
 Rouvray,
       Nova, New York. pp. 299-316 (199).
 15.   S.C. Basak, S. Bertelsen and G.D. Grunwald, Application of
 graph theoretic
       parameters in quantifying molecular similarity and
 structure-activity
       relationships, presented at the Fifth International
 Conference on Mathematical
       Chemistry (1993).
 16.   S.C. Basak and G.D. Grunwald, Use of graph invariants, volume
 and total
       surface area in predicting boiling point of alkanes,
 Mathematical Modelling and
       Scientific Computing, 2, 735-740 (1993).
 17.   S.C. Basak, G.J. Niemi and G.D. Veith, Optimal
 characterization of structure for
       prediction of properties, J. Math. Chem., 4, 185 (1990).
 18.   Basak, S.C.  A Nonempirical Approach to Predicting Molecular
 Properties using
       Graph-Theoretic Invariants, in PRACTICAL APPLICATIONS OF
       QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIPS (QSAR) IN
       ENVIRONMENTAL CHEMISTRY AND TOXICOLOGY, eds. W. Karcher and
 J.
       Devillers, Kluwer Academic Publishers, (1990).
 19.   G.J. Niemi, S.C. Basak, G.D. Veith and G. Grunwald,
 Prediction of octanol-
       water partition coefficient (Kow) using
 algorithmically-derived variables,
       Environmental Toxicology and Chemistry, 11, 893-900 (1992).
 20.   G.J. Niemi, S.C. Basak and G.D. Veith, A theoretical and
 computational
       approach to chemical evaluation based on structure-activity
 relationships,
       Procedeedings of the First Conference of the International
 Society of
       Environmental Protection, pp 57-68 (1990).
 21.   E.B. Anderson, G.D. Veith, and D. Weininger, SMILES: A Line
 notation and
       computerized interpreter for chemical structures,
 Environmental Research Brief,
       U.S. EPA, (1987).
 !
 Appendix 1:  The 98 topological indices calculated by POLLY.
 IWD        Information index for the magnitudes of distances
 between all possible
            pairs of vertices of a graph
 IWD        Mean information index for the magnitude of distance
 W          Wiener index = half-sum of the off-diagonal elements of
 the distance
            matrix of a graph
 ID         Degree complexity
 HV         Graph vertex complexity
 HD         Graph distance complexity
 IC         Information content of the distance matrix partitioned
 by frequency of
            occurrences of distance h
 O          Order of neighborhood when ICr reaches its maximum value
 for the
            hydrogen-filled graph
 IORB       Information content or complexity of the
 hydrogen-suppressed graph at
            its maximum neighborhood of vertices
 OORB       Maximum order of neighborhood of vertices for IORB
 within the hydrogen-
            suppressed graph
 M1         A Zagreb group parameter = sum of square of degree over
 all vertices
 M2         A Zagreb group parameter = sum of cross-product of
 degrees over all
            neighboring (connected) vertices
 ICr        Mean information content or complexity of a graph based
 on the rth (r =
            0..6) order neighborhood of vertices in a
 hydrogen-filled graph
 SICr       Structural information content for rth (r = 0..6) order
 neighborhood of
            vertices in a hydrogen-filled graph
 CICr       Complementary information content for rth (r = 0..6)
 order neighborhood
            of vertices in a hydrogen-filled graph
 h!         Path connectivity index of order h = 0..6
 h!C        Cluster connectivity index of order h = 3..6
 h!Ch       Chain connectivity index of order h = 3..6
 h!PC       Path-cluster connectivity index of order h = 4..6
 h!b        Bonding path connectivity index of order h = 0..6
 h!bC       Bonding cluster connectivity index of order h = 3..6
 h!bCh      Bonding chain connectivity index of order h = 3..6
 h!bPC      Bonding path-cluster connectivity index of order h =
 4..6
 h!v        Valence path connectivity index of order h = 0..6
 h!vC       Valence cluster connectivity index of order h = 3..6
 h!vCh      Valence chain connectivity index of order h = 3..6
 h!vPC      Valence path-cluster connectivity index of order h =
 4..6
 Ph         Number of paths of length h = 0..10
 !
 Appendix 2: Format of the POLLY output file
 Record  1: Chemical id
                  (a80)
 Record  2: IWD, IWD, W, ID, HV, HD, IC
                  (f11.3, f8.3, i6, 4f8.3)
 Record  3: O, IORB, OORB, M1, M2
                  (i6, f8.3, 3i6)
 Record  4: IC0, IC1, ..., IC6
                  (7f8.3)
 Record  5: SIC0, SIC1, ..., SIC6
                  (7f8.3)
 Record  6: CIC0, CIC2, ..., CIC6
                  (7f8.3)
 Record  7: 0!, 1!, ..., 6!
                  (7f8.3)
 Record  8: 3!C, 4!C, 5!C, 6!C
                  (24x, 4f8.3)
 Record  9: 3!Ch, 4!Ch, 5!Ch, 6!Ch
                  (24x, 4f8.3)
 Record 10: 4!PC, 5!PC, 6!PC
                  (32x, 3f8.3)
 Record 11: 0!b, 1!b, ..., 6!b
                  (7f8.3)
 Record 12: 3!bC, 4!bC, 5!bC, 6!bC
                  (24x, 4f8.3)
 Record 13: 3!bCh, 4!bCh, 5!bCh, 6!bCh
                  (24x, 4f8.3)
 Record 14: 4!bPC, 5!bPC, 6!bPC
                  (32x, 3f8.3)
 Record 15: 0!v, 1!v, ..., 6!v
                  (7f8.3)
 Record 16: 3!vC, 4!vC, 5!vC, 6!vC
                  (24x, 4f8.3)
 Record 17: 3!vCh, 4!vCh, 5!vCh, 6!vCh
                  (24x, 4f8.3)
 Record 18: 4!vPC, 5!vPC, 6!vPC
                  (32x, 3f8.3)
 Record 19: P0, P1, ..., P10
                  (11i6)
 ------------------------------------------------------------------------
 From: lnl -x- at -x- novo.dk (Leif Norskov)
 Molconn-X is *THE* program for calculating topological indices.
 ( - sometimes referred to as Kier and Hall indices).
 It is available for $ 295 for academic users from
 	Lowell H. Hall
 	Hall Associates Consulting
 	2 Davis Street
 	Quincy, MA 02170, U.S.A.
 	Tel. (617) 773-4833
 Lowell does not seem to have an email address, but he certainly
 does put some nice stamps on his ordinary mail :-)
 ------------------------------------------------------------------------
 From: "Igor Baskin" <baskin -x- at -x- qsar.chem.msu.su>
 In connection with your inquiry about topological indexes, I
 enclose a small extraction from the description of the
 EMMA package.
 "EMMA" ("EFFECTIVE MODELLING OF MOLECULAR ACTIVITY") - THE
 SOFTWARE
      FOR THE PREDICTION OF PROPERTIES/BIOLOGICAL ACTIVITIES OF
        ORGANIC COMPOUNDS ON THE BASIS OF REGRESSION ANALYSIS
 ...
      For each  structure  in  a  training set EMMA allows to
 compute from hundreds to thousands of descriptors.  The  set
 of descriptors   includes   topological   indices   (various
 connectivity indices,  Balaban index J,  Wiener and extended
 Wiener, Hosoya,  Merrifield-Simmons,  Gutman  and some other
 indices), informational indices,  the indices which are  the
 functions of  charge distribution in molecules,  the indices
 based on  atomic  electronegativities  and  those  based  on
 inductive parameters,  steric indices, various local indices
 and, what is important,  the substructural descriptors which
 are equal  to  the  number of chaines (1- to 9-atomic),  the
 number of cycles  (3-  to  6-membered)  and  the  number  of
 branched fragments  (4-,  5-,  and  6-atomic),  the atoms in
 substructures being  classified  taking  into  account   the
 number of  hydrogens at them,  bond types and formal charge.
 EMMA can manage 2000 descriptors computed and construct  the
 regression equations    including    only   a   few   "best"
 descriptors. A  user  can  easily  add  his  own  descriptor
 programs or  can  input  the  additional  descriptor  values
 manually.
 ...
      Developers:
      Professor N.S.Zefirov,  Department of Chemistry, Moscow State
      University, Moscow, 119899, Russia. Fax: (095) 939-0290,
      phone (095) 939-1620
      Dr. D.V.Sukhachev, Dr. I.I.Baskin, Dr. V.A.Palyulin