Interpretation and Design of Chemically Based Experiments with

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Downloaded by NORTH CAROLINA STATE UNIV on December 29, 2017 | http://pubs.acs.org Publication Date: April 30, 1986 | doi: 10.1021/bk-1986-0306.ch006

Interpretation and Design of Chemically Based Experiments with Expert Systems 1

1

2

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David Garfinkel , Lillian Garfinkel , Von-Wun Soo , and Casimir A. Kulikowski 1

University of Pennsylvania, Philadelphia, PA 19104 Rutgers University, New Brunswick, NJ 08903

2

Expert system building programs, e.g., EXPERT, can now supervise numerical calculations in addition to performing qualitative reasoning and choosing among possible alternatives. This capability can be used to interpret experiments, calculate optimal designs for them, and automate model construction and mani pulation, as well as to resolve associated problems due to differing conceptual frameworks and defini tions. Three hierarchically arranged applications are suggested to (a) determine and manage free Mg levels; (b) construct an expert system to derive enzyme kinetic models (including Mg ) and f i t them to data; (c) design experiments (including enzyme kinetics) using minimal numbers of animals to prove drugs safe and effective. 2+

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E x p e r t systems, and a r t i f i c i a l i n t e l l i g e n c e i n g e n e r a l , a r e new f i e l d s whose b r e a d t h o f a p p l i c a t i o n , and i n d e e d , whose exact d e f i n i t i o n s , are not yet completely s e t t l e d . I t i s sometimes c l a i m e d t h a t no two e x p e r t s on a r t i f i c i a l i n t e l l i g e n c e agree e x a c t l y on what i t s d e f i n i t i o n i s . D e f i n i t i o n s o f e x p e r t systems a t l e a s t agree on t h e n e c e s s i t y f o r e x p e r t i s e , b u t even h e r e t h e r e a r e d i f f e r e n c e s i n emphasis and i n p r i o r i t y . E x p e r t systems, which e v o l v e d from many s o u r c e s , were r e c o g n i z e d as a d i s t i n c t system t y p e because o f a l a r g e body o f work on m e d i c a l c o n s u l t a t i o n problems. The r e s u l t i n g systems, such as MYCIN, CASNET, and INTERNIST/CADUCEUS, e s s e n t i a l l y s o l v e d what a r e c o n s i d e r e d c l a s s i f i c a t i o n problems, by c h o o s i n g among a s e t o f p o s s i b l e d i a g n o s t i c o r treatment a l t e r n a t i v e s . Such systems have u s u a l l y o b t a i n e d i n f o r m a t i o n by a s k i n g t h e u s e r q u e s t i o n s . They have u s u a l l y performed q u a l i t a t i v e r e a s o n i n g w i t h "knowledge" r u l e s o f t h e t y p e : i f c o n d i t i o n s A a r e t r u e then c o n c l u d e h y p o t h e s i s Β w i t h p r o b a b i l i t y X. There e x i s t o t h e r t y p e s o f e x p e r t systems, such as DENDRAL, w h i c h produces i n t e r p r e t a t i o n s o f q u a n t i t a t i v e e x p e r i m e n t a l e v i d e n c e , and MOLGEN, which f o r m u l a t e s p l a n s f o r t h e d e s i g n o f e x p e r i m e n t s . Most e x p e r t systems have been w r i t t e n i n some v a r i a n t o f LISP o r a r e -

0097-6156/86/0306-0075$06.00/0 © 1986 American Chemical Society Pierce and Hohne; Artificial Intelligence Applications in Chemistry ACS Symposium Series; American Chemical Society: Washington, DC, 1986.

ARTIFICIAL INTELLIGENCE APPLICATIONS IN CHEMISTRY


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l a t e d l a n g u a g e , w h i c h were o r i g i n a l l y not as w e l l s u i t e d f o r c a l c u l a t i o n as f o r l o g i c a l m a n i p u l a t i o n . More r e c e n t l y i t has been p o s s i b l e t o g e t an e x p e r t system t o s u p e r v i s e c a l c u l a t i o n s , d i g e s t c o n s i d e r a b l e masses of o b s e r v a t i o n a l d a t a , and draw c o n c l u s i o n s which a r e not s t r i c t l y c o m p u t a t i o n a l , as i n t h e c a s e of ELAS and t h e o i l w e l l d r i l l i n g programs. These i n v o l v e t h e EXPERT system b u i l d e r ( 1 ) , w h i c h has t h e f o l l o w i n g advantages: i t i s w r i t t e n i n FORTRAN and can t h e r e f o r e e a s i l y communicate w i t h FORTRAN programs; a PROLOG v e r s i o n has a l s o r e c e n t l y been p r e p a r e d ; i t has d a t a b a s e c a p a b i l i t i e s ; and i t i s good a t e x p l a i n i n g what i t i s d o i n g and why. Intera c t i o n between a r t i f i c i a l i n t e l l i g e n c e and m o d e l i n g has e v o l v e d t o where m o d e l i n g s o c i e t i e s r o u t i n e l y program a r t i f i c i a l i n t e l l i g e n c e s e s s i o n s a t m e e t i n g s , and a r e f o r m i n g t e c h n i c a l committees on t h i s subj e c t . T h i s paper r e f l e c t s t h e p a s t a c t i v i t i e s of some of i t s a u t h o r s i n computer m o d e l i n g of t h e c h e m i c a l a s p e c t s of b i o l o g i c a l systems. T h i s a c t i v i t y r e q u i r e s e x p e r t i s e i n b o t h m o d e l - b u i l d i n g and i n t h e relevant biology. I t a l s o i n v o l v e s e x a m i n a t i o n of the a c t i o n s of and r e s u l t s o b t a i n e d by e x p e r t s , l i k e t h a t r o u t i n e l y done i n b u i l d i n g exp e r t systems. I t a l s o i n v o l v e s k e e p i n g t r a c k o f and coherently e x p l a i n i n g sequences o f d e c i s i o n s , w h i c h e x p e r t systems a r e equipped t o do. In t h i s paper we a r e c o n c e r n e d w i t h a s e t of r e l a t i v e l y s i m i l a r p o s s i b l e a p p l i c a t i o n s i n v o l v i n g management of c a l c u l a t i o n s and of modeling. These i n v o l v e a c t i o n s ( c a l c u l a t i o n , i n f o r m a t i o n r e t r i e v a l , and " i n t e l l i g e n t " r e a s o n i n g ) a t more t h a n one h i e r a r c h i c a l l e v e l . P a r t i c u l a r a t t e n t i o n w i l l be g i v e n t o t h e d e s i g n and i n t e r p r e t a t i o n of e x p e r i m e n t s i n enzyme k i n e t i c s . D e s i g n i n g an experiment may i n v o l v e c o m p u t a t i o n o f o p t i m a l c o n d i t i o n s , and i t s i n t e r p r e t a t i o n may i n v o l v e f i t t i n g of o p t i m a l parameters of a model, but n o n - n u m e r i c a l reasoning procedures are a l s o involved. Attention i s therefore req u i r e d t o t h e k i n d s of r e a s o n i n g employed i n d e s i g n i n g e x p e r i m e n t s and t o t h e c r i t i q u i n g o f t h e r e a s o n i n g and t e c h n i q u e s i n v o l v e d i n such experiments. A h i g h - l e v e l d e s c r i p t i o n o f an e x p e r i m e n t a l d e s i g n c y c l e can be g i v e n i n s u c h s t e p s a s : d e f i n i t i o n of the problem (what q u e s t i o n s a r e t o be a d d r e s s e d ? what h y p o t h e s e s a r e t o be t e s t e d ? ) ; q u a n t i t a t i v e m o d e l i n g ; d e s i g n and t h e n p e r f o r m a n c e of t h e n e c e s s a r y e x p e r i m e n t s ; a n a l y s i s of t h e r e s u l t s ; and t h e n model r e i n t e r p r e t a t i o n and p o s s i b l e problem r e d e f i n i t i o n (2). A Problem of D e f i n i t i o n The p r o c e s s of b u i l d i n g e x p e r t systems u s u a l l y i n v o l v e s d e t e r m i n i n g the c o n c e p t u a l framework and p a t t e r n o f d e c i s i o n making of e x p e r t s ( o f t e n one o u t s t a n d i n g e x p e r t ) . These a r e o f t e n not w r i t t e n down and may not be c l e a r l y e x p l a i n a b l e b e c a u s e t h e r e i s heavy r e l i a n c e on h e u r i s t i c s and even hunches. However, we would l i k e t o s u g g e s t t h a t t h i s may not be t h e o n l y way t o a p p l y e x p e r t i s e . We have e n c o u n t e r e d workers i n d i f f e r e n t f i e l d s h a n d l i n g t h e same s u b j e c t m a t t e r d i f f e r e n t l y b e c a u s e t h e y have d i f f e r e n t c o n c e p t u a l frameworks and d i f f e r e n t j a r g o n as w e l l as d i f f e r e n t h e u r i s t i c s and p r i o r i t i e s . We o f f e r t h e f o l l o w i n g example i n v o l v i n g a r e l a t i v e l y s i m p l e m u l t i p l e e q u i l i b r i u m calculation.

Pierce and Hohne; Artificial Intelligence Applications in Chemistry ACS Symposium Series; American Chemical Society: Washington, DC, 1986.

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Chemically Based Experiments with Expert Systems 77

GARFINKEL ET AL.

A l t h o u g h t h e r e i s no c o n t r o v e r s y about t h e b a s i c d e f i n i t i o n o f s t a b i l i t y c o n s t a n t s , p h y s i c a l c h e m i s t s and b i o c h e m i s t s h a n d l e t h e c o n c e p t s i n v o l v e d and t h e r e s u l t i n g c a l c u l a t i o n s d i f f e r e n t l y . Physi c a l c h e m i s t s t h i n k i n terms o f r e a c t i v e s p e c i e s and b i o c h e m i s t s i n terms o f t o t a l c o n c e n t r a t i o n s o f components. A f u r t h e r source of c o n f u s i o n i s t h e d i f f e r i n g d e f i n i t i o n s o f "apparent c o n s t a n t . To a p h y s i c a l chemist t h e s t a b i l i t y c o n s t a n t f o r MgATP formation 1 1


Mg

2+

+ ATP

4-

= MgATP

2-

i s d e f i n e d as 2

CMgATP "*]

=

^

CMg

2 +

][ATP -] 4

For a g i v e n temperature the standard s t a t e i s a t zero i o n i c strength. The c o n s t a n t o b s e r v e d e x p e r i m e n t a l l y a t f i n i t e i o n i c s t r e n g t h s would be c o n s i d e r e d " a p p a r e n t " . A b i o c h e m i s t would c a l l s u c h a c o n s t a n t "intrinsic". The p r e s e n c e o f i n t e r f e r i n g i o n s ^ ( H and Κ ) w h i c h f o r m Η and Κ c h e l a t e s o f ATP by b i n d i n g t o ATP " would be h a n d l e d by c a l c u l a t i o n s i n v o l v i n g the corresponding e q u i l i b r i a . +

+

B i o c h e m i s t s h a n d l e t h e s e c a l c u l a t i o n s d i f f e r e n t l y , and d e f i n e apparent c o n s t a n t S 2 i n terms o f t o t a l components. Tljius an apparent c o n s t a n t f o r MgATP a t low pH i n t h e p r e s e n c e o f Κ would be d e f i n e d as

*SlgATP Κ = *

Interpretation and Design of Chemically Based Experiments with

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