Table 6.
Selected Approaches to Generate (Ultra-)large Virtual Chemical Space
| Feature | Approach Described in This Work | Previous Feasibility-Based approachesa | Recent AI-Based approachesb |
|---|---|---|---|
| Virtual chemical space | Multibillion (over 3 × 1010) | Large (~109) | Varied but typically less than 109 |
| Synthetic methods | Experimentally validated three-component two- or three-step reaction sequences | Experimentally validated two-component one-step reactions (mostly) | Various; typically based on the literature data (not always validated experimentally) |
| Algorithm | Very straightforward | Sophisticated | |
| Synthetic feasibility | Average value for each method or synthon, described as average synthesis success rate | Varied; from unknown to predicted for each particular member | |
| Building block reactivity assessment | Semi-qualitative; by a chemical expert aided by a computer | Typically quantitative; by AI | |
a
Previous version of our REAL methodology is referred here; much larger datasets were also generated internally within big pharma companies (Hoffmann and Gastreich, 2019).
b
The subject was reviewed and critically accessed in a number of recent publications (Schneider, 2018; Schwaller and Laino, 2019; Brown et al., 2020; Lemonick, 2020).