The 3rd diagonal element of inertia tensor matrix with respect to axes which go through the center of gravity of mass in a molecule (I_C)
Inertial shape factor
3D asphericity
molecular eccentricity
Shadow area in the XY plane
Shadow area in the YZ plane
Rodent Carcingogenicity
Carcinogenicity is a toxicity that causes cancer in body. Generally carcinogenicity test requires long time (usually 2 years), currently only in vivo test methods are established. Usually the test uses mice or rats, exposing them to a compound. And the variable to be observed is existence of cancer. PreADMET predicts the result from its model, which is built from the data of NTP (National Toxicology Program) and US FDA, which are the results of the in vivo carcinogenicity tests of mice and rats for 2 years.
| Type | NTP Definition | Description |
| negative | Clear evidence of carcinogenic activity | negative prediction |
| positive | No evidence of carcinogenic activity | positive prediction |
Ames test
Ames test is a simple method to test mutagenicity of a compound, which is suggested by Dr. Ames. It uses several strains of the bacterium Salmonella typhimurium that carry mutations in genes involved in histidine synthesis, so that they require histidine for growth. The variable being tested is the mutagen’s ability to cause a reversion to growth on a histidine-free medium. [Bruce N. Ames, E. G. Gurney, James A. Miller, and H. Bartsch (1973). “Carcinogens as Frameshift Mutagens: Metabolites and Derivatives of 2-acetylaminofluorene and other Aromatic Amine Carcinogens”. PNAS 69: 3128-213] [ Ames,B.N. et al. PNAS. 1972, 69, 3128. ]
PreADMET predicts toxicity to TA98, TA100 and TA1535 which are often used in Ames test. And the result can be calculated both with consideration of metabolite (Metabolic activation by rat liver 10% homogenate, +S9) and without consideration of metabolite. (No metabolic activation, -S9) The actual value of the prediction result is “positive” or “negative”.
|
Type |
NTP Definition | Description |
|
negative |
no change of population (vs. blank plate) |
negative prediction |
| positive | change of population, more than double of blank plate’s change |
positive prediction |
WDI-like rule
This measurement is based on compounds that have molecular properties within the 90 % upper bound found in the WDI (World Drug Index).
[ Brown,R.D. et al. ”Tools for designing diverse, drug-like, cost-effective combinatorial libraries”; in Combinatorial Library Design and Evaluation”, Marcel Dekker, Inc. New York, 2001, 328. ]
| Descriptors | 90% cutoff | Descriptors | 90% cutoff |
| MW | 550 | Kappa-2A | 12 |
| Rotbond | 13 | Kappa-3A | 8 |
| Hbond acceptor | 9 | CHI-V-0 | 20 |
| Hbond donor | 5 | CHI-V-1 | 12 |
| AlogP | 5 | CHI-V-2 | 10 |
| MolRef | 120 | CHI-V-3P | 8 |
| Balaban Jx | 2.8 | CHI-V-3C | 2.2 |
| PHI | 8 | Wiener | 4000 |
| Kappa-1A | 25 | Zabreb | 175 |
Reactive functional group
Reactive functional group
Filtering by reactive functional group is the one of the important steps for the drug discovery. A compound with a reactive functional group is reactive in human body, and it has possibility to cause toxicity. Additionally, a compound with a reactive functional group leads to reaction during a process of an in vitro experiment, such as a case of HTS. This may results some serious error of activity for drug.
These compounds can be filtered off or removed, at the beginning of drug discovery. This filtering reduces probability of causing toxicity or error. PreADMET can find compounds with electrophilic functional group which tends to make a covalent bond with protein, causing false positive. And PreADMET also finds compounds with 3 prohibited functional groups that are extremely unusual in drug discovery. The number of both kinds of functional groups are 23 in total.
[ (1) Rishton,G.M. DDT. 1997, 2, 382. (2) Walters,W.P. et al. Adv. Drug Deliv. Rev. 2002, 54, 255. ]