RT Book,_Section
T1 Unify Markov model for Rational Design and Synthesis of More Safe Drugs. Predicting Multiple Drugs Side Effects
A1 Cruz Monteagudo, Maykel
A1 González Díaz, Humberto
A1 Cabrera Pérez, Miguel A.
A1 Molina Ruiz, Reinaldo
A1 Pérez Castillo, Yunierkis
AB Most of present mathematical models for rational design and synthesis of new drugs consider just the molecular structure. In the present article we pretend extending the use of Markov Chain models to define novel molecular descriptors, which consider in addition other parameters like target site or biological effect. Specifically, this model takes into consideration not only the molecular structure but the specific biological system the drug affects too. Herein, it is developed a general Markov model that describes 19 different drugs side effects grouped in 8 affected biological systems for 178 drugs, being 270 cases finally. The data was processed by Linear Discriminant Analysis (LDA) classifying drugs according to their specific side effects, forward stepwise was fixed as strategy for variables selection. The average percentage of good classification and number of compounds used in the training/predicting sets were 100/95.8% for endocrine manifestations(18 out of 18)/(13 out of 14); 90.5/92.3% for gastrointestinal manifestations (38 out of 42)/(30 out of 32); 88.5/86.5% for systemic phenomena (23 out of 26)/(17 out of 20); 81.8/77.3% for neurological manifestations (27 out of 33)/(19 out of 25); 81.6/86.2% for dermal manifestations (31 out of 38)/(25 out of 29); 78.4/85.1% for cardiovascular manifestation (29 out of 37)/(24 out of 28); 77.1/75.7% for breathing manifestations (27 out of 35)/(20 out of 26) and 75.6/75% for psychiatric manifestations (31 out of 41)/(23 out of 31). Additionally a Back-Projection Analysis (BPA) was carried out for two ulcerogenic drugs to prove in structural terms the physic interpretation of the models obtained. This article develops a model that encompasses a large number of drugs side effects grouped in specifics biological systems using stochastic absolute probabilities of interaction (Apk (j)) by the first time.
PB MDPI
SN 3-906980-16-2
YR 2005
FD 2005
LK http://hdl.handle.net/10347/26893
UL http://hdl.handle.net/10347/26893
LA eng
NO Proceedings of the 9th International Electronic Conference on Synthetic Organic Chemistry, 1–30 November 2005, MDPI: Basel, Switzerland, doi:10.3390/ecsoc-9-01658
NO The 9th International Electronic Conference on Synthetic Organic Chemistry session Computational Chemistry
DS Minerva
RD 22 abr 2026