ToMoCoMD Framework

SiliS-PREENZA, acronym of DRY-in Silico Screening and Prediction of Effects of Inhibitors on Enzyme Activity, was developed in Java 1.8, and thus it is fully cross-platform. For the development of this program, the CDK (v1.4.19), QuBiLS-MAS, and AMBIT (v0.0.4) libraries were used for the handling of chemical structures, computation of molecular descriptors, and computation of applicability domain (AD). All available models in this software were built with the WEKA (v3.8.0) software.

Currently, the available QSAR models are:

• Inhibitors of angiotensin converting enzyme (ACE): multiple linear regression models based on topological (2D) QuBiLS-MAS molecular descriptors
• Inhibitors of acetylcholinesterase (ACHE): multiple linear regression models based on topological (2D) QuBiLS-MAS molecular descriptors
• Inhibitors of the benzodiazepine receptor (BZR): multiple linear regression models based on topological (2D) QuBiLS-MAS molecular descriptors
• Inhibitors of cyclooxygenase-2 (COX2): multiple linear regression models based on topological (2D) QuBiLS-MAS molecular descriptors
• Inhibitors of dihydrofolate reductase (DHFR): multiple linear regression models based on topological (2D) QuBiLS-MAS molecular descriptors
• Inhibitors of dihydrofolate reductase (DHFR): multiple linear regression models based on topological (2D) QuBiLS-MAS molecular descriptors
• Inhibitors of glycogen phosphorylase b (GPB): multiple linear regression models based on topological (2D) QuBiLS-MAS molecular descriptors
• Inhibitors of thermolysin (THERM): multiple linear regression models based on topological (2D) QuBiLS-MAS molecular descriptors
• Inhibitors of thrombin (THR): multiple linear regression models based on topological (2D) QuBiLS-MAS molecular descriptors