Docking is a computational procedure in which a potential drug molecule or ligand is placed in the active site of the target molecule. Using models of the binding energy of various parts of the molecules, the interaction between the two can be evaluated to find if there is likely to be a good 'fit'.
The procedure can also be used to find the best location for a ligand in the active site, and this can guide the addition of side chains that can improve the fit, a process known as structure-based drug design. Almost all research teams working in drug discovery will make use of this type of software, according to Quantum.
The Quantum 2.0 programme completed proof of principle testing in February, and is being launched into a market dominated by in-house software packages and commercial products such as Tripos' Sibyl, Cambridge Crystallographic Data Centre's GOLD or DOCK, developed at the University of California San Francisco.
Quantum maintains that its software improves on rival products by offering higher accuracy, better selectivity (i.e. the ability to differentiate between the binding affinities of similar compounds), which makes it a more powerful tool for structure-based drug design.
And this should lead to improved virtual screening success rates, producing fewer, more accurate ligand groups. In turn, this reduces the need for expensive and time-consuming high-throughput screening (HTS) and ultimately could reduce the time it takes to bring a new drug to market, one of the primary obstacles to R&D productivity identified by the Tufts Centre for the Study of Drug Development in a report published earlier this year.
The improvements in Quantum 2.0 overcome the limitations of rival software, such as fairly limited accuracy (around 50 per cent variation in terms of ligand position, and anything up to 100 per cent in binding energy determination), and limitations in their ability to cope with the inherent flexibility of both ligand and protein molecules.
The key is a new series of calculation methods that accounts for molecular flexibility (taking into account electrostatic and Van der Waals energy contributions) and thermodynamic variables such as entropy (loss of energy). The result is binding accuracy with an error margin of around 15 per cent on average and a maximum of 30 per cent, even for complicated interactions.
"Calculations with such accuracy enable us to apply our technology for lead optimisation in silico, which is revolutionary in drug discovery," said a spokesperson for Quantum.
In contrast, other packages use empirical 'scoring' systems that estimate binding in a very rough manner, he said, and this is the main difference with Quantum 2,0 and makes it unique in the marketplace.
Other advantages of Quantum 2.0 include: the use of linear scaling rather than the cubic scaling used with rival products, which makes it impossible to apply them for calculations on molecules with thousands of atoms; and a modular system that allow modifications to the programme to improve its accuracy still further for particular applications.
The company has added a new page to its website that will allow researchers to upload any protein and ligand. Quantum will run the calculations and send the results - the optimal coordinates of the ligand with minimum pKd and free binding energy - to the researchers via email.
The spokesperson said that the closest competitor to Quantum in this sector is Locus Pharmaceuticals, a US company which has developed its own computational drug design and discovery platform.