Bawden, David (1978) Substructural analysis techniques for structure - property correlation within computerised chemical information systems. PhD thesis, University of Sheffield.
Abstract
The  work  described  in  this  thesis  involves  a  novel  method 
of  substructural  analysis,  with  potential  application 
for  structure- 
property  correlation  and 
information 
retrieval  within  computerised 
chemical 
information 
systems. 
A 
review 
is 
given  of 
the  development  of 
the  concept  of  chemical 
structure  and 
its 
representation, 
its  application 
in 
computerised 
chemical 
information 
systems,  and  methods 
for  correlating  structure 
with  molecular  properties. 
A  method 
is  presented 
for  derivation  of  structural 
features, 
representing 
the  whole  structure, 
from  Wiswesser  Line  Notation 
(WLN) 
by  computer  program. 
These  features  are 
then  used  as  variables 
in 
statistical  analysis  procedures: 
in  this  work  multiple  regression 
analysis  and  cluster  analysis  are  used.  This  procedure  allows 
for  a 
rapid,  convenient  and 
thorough  analysis  of 
large  data-sets.  The  type 
of  structural 
features  used  may  be  easily  varied,  allowing 
for  investi- 
gation  of 
factors  such  as  ring  substitution  patterns,  group 
interactions, 
and 
three-dimensional  structure. 
The  method 
is  applicable 
to  sets  of 
diverse  or  structurally  related  compounds.  Statistical  tests  of 
the 
results  enable  quantitative 
testing  of  hypotheses. 
Multiple 
regression  analysis  allows  a  direct,  quantitative 
correlation  between 
structure  and  molecular  property,  and  subsequent 
property  prediction. 
It  is  applied 
to  sets  of  aliphatic,  alicyclic aromatic,  and  heterocyclic  compounds, 
including  sets  of  highly  diverse 
structures.  Properties  examined 
include  biological  effects, 
toxicty, 
pK, 
thermochemical  properties,  boiling  point,  solubility,  and 
partition  coefficient.  Some  of 
these  properties  are  highly  dependent 
upon  electronic  and  steric  effects,  and  hence  upon  relative  position 
of  substituents,  and  on 
three-dimensional  structure.  Highly 
significant 
correlations  are  obtained 
in  all  cases,  and 
the  potential 
for  property 
prediction 
is  demonstrated. 
Cluster  analysis 
is  applied 
to  several  sets  of  structures. 
Intuitively  sensible  classifications  are  obtained,  and 
the  potential 
for  both  property  prediction  and 
information 
retrieval 
discussed. 
Since  these  techniques  involve  the  widely  used  WLN, 
relatively  simple  COBOL  programs,  and  standard  statistical  packages, 
they  should 
be  applicable  within  operational  environments.
Metadata
| Awarding institution: | University of Sheffield | 
|---|---|
| Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield) | 
| Identification Number/EthosID: | uk.bl.ethos.449232 | 
| Depositing User: | EThOS Import Sheffield | 
| Date Deposited: | 03 Dec 2012 09:51 | 
| Last Modified: | 08 Aug 2013 08:50 | 
| Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:3038 | 
        
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