swMATH ID: 25864
Software Authors: García-Mera, Xerardo; Tapia, Ricardo A.; Ubeira, Florencio M.
Description: NL MIND-BEST: A web server for ligands and proteins discovery—Theoretic-experimental study of proteins of Giardia lamblia and new compounds active against Plasmodium falciparum. There are many protein ligands and/or drugs described with very different affinity to a large number of target proteins or receptors. In this work, we selected Ligands or Drug-target pairs (DTPs/nDTPs) of drugs with high affinity/non-affinity for different targets. Quantitative Structure–Activity Relationships (QSAR) models become a very useful tool in this context to substantially reduce time and resources consuming experiments. Unfortunately most QSAR models predict activity against only one protein target and/or have not been implemented in the form of public web server freely accessible online to the scientific community. To solve this problem, we developed here a multi-target QSAR (mt-QSAR) classifier using the MARCH-INSIDE technique to calculate structural parameters of drug and target plus one Artificial Neuronal Network (ANN) to seek the model. The best ANN model found is a Multi-Layer Perceptron (MLP) with profile MLP 20:20-15-1:1. This MLP classifies correctly 611 out of 678 DTPs (sensitivity=90.12
Homepage: https://www.sciencedirect.com/science/article/pii/S0022519311000221
Keywords: Ligands-protein interaction; drugs-targets prediction; protein structure networks; multi-target QSAR; Markov model
Related Software: Cell-PLoc; NR-2L; OligoPred; SecretP; iLoc-Virus; PseAAC; GPCR-CA; MARCH-INSIDE; Bio-AIMS; PHP; Quat-2L; GPCR-GIA; HyperChem; 2D-MH; BLAST; PSI-BLAST; Memtype-2L; Nuc-ploc; GAUSSIAN; COSMOS
Cited in: 2 Documents

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