TOMOCOMD-CARDD, a novel approach for computer-aided 'rational' drug design: I. Theoretical and experimental assessment of a promising method for computational screening and in silico design of new anthelmintic compounds.
In this work, the TOMOCOMD-CARDD approach has been applied to estimate the anthelmintic activity. Total and local (both atom and atom-type) quadratic indices and linear discriminant analysis were used to obtain a quantitative model that discriminates between anthelmintic and non-anthelmintic drug-like compounds. The obtained model correctly classified 90.37% of compounds in the training set. External validation processes to assess the robustness and predictive power of the obtained model were carried out. The QSAR model correctly classified 88.18% of compounds in this external prediction set. A second model was performed to outline some conclusions about the possible modes of action of anthelmintic drugs. This model permits the correct classification of 94.52% of compounds in the training set, and 80.00% of good global classification in the external prediction set. After that, the developed model was used in virtual in silico screening and several compounds from the Merck Index, Negwer's handbook and Goodman and Gilman were identified by models as anthelmintic. Finally, the experimental assay of one organic chemical (G-1) by an in vivo test coincides fairly well (100%) with model predictions. These results suggest that the proposed method will be a good tool for studying the biological properties of drug candidates during the early state of the drug-development process.
Marrero-Ponce
Yovani
Y
Department of Pharmacy, Faculty of Chemical-Pharmacy, Central University of Las Villas, Santa Clara 54830, Villa Clara, Cuba. yovanimp@qf.uclv.edu.cu
Castillo-Garit
Juan A
JA
Olazabal
Ervelio
E
Serrano
Hector S
HS
Morales
Alcidez
A
Castañedo
Nilo
N
Ibarra-Velarde
Froylán
F
Huesca-Guillen
Alma
A
Jorge
Elisa
E
del Valle
Arletys
A
Torrens
Francisco
F
Castro
Eduardo A
EA
D000818:Animals; D000977:Antiparasitic Agents; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D015195:Drug Design; D006801:Humans; D021281:Quantitative Structure-Activity Relationship; D012984:Software
D000977:Antiparasitic Agents