It has been an exciting year here in Quantum Pharmaceuticals, another great year for our highly effective small molecule drug discovery and ADMET platform development. Our work is firmly based in basic science: QUANTUM science team developed a vector field theory of water capable of describing numerous anomalous thermodynamic and dielectric of water, as well as interactions of biomolecules in aqueous environments (arXiv:0808.0991).

The progress in our understanding of biomolecules interactions led to further accuracy improvements in our major calculation routines (IC50, solvation energy, etc.). Speed increase and sophistication of the models employed in our simulations provided better ways for false positive elimination. Direct application of our software brought up novel inhibitors of HIV integrase and gp120 proteins, human neutrophyle elastase (HNE) (see collaborations). Massive computations made using Amazon EC2 computing platform let us develop new and refind existing ADMET models (see drug absorbtion prediction (arXiv:0810.2617) as an example).

All the scientific advances are plugged in and available through the following releases of Quantum sofware (sold separately and in packages at discount prices):

q-TOX - enables researches to compute toxic effects of chemicals solely from their molecular structure (LD50, MRDD, side effects) . The robust model is based on completely new approaches. While there are numerous commercially available toxicity prediction software, none offers the depth, scope and precision comparing to q-TOX. The paradigm in the q-TOX approach is based on the premise that biological activity results from the capacity of small molecules to modulate the activity of the proteome.

q-Mol - calculates such physicochemical parameters as Solubility in H2O (g/l); Solubility in DMSO (g/l); LogP, water/octanol; Mol weight; H-bond donors; H-bond acceptors; The number of rotatable bonds;Lipinski-rule-of-5.

q-ADME - For the first time we identified proteins, binding to which correlates well with FA and T1/2. This enabled us to simulate the active component of the ADME properties that has been the heel of Achilles for existing computational approaches still. The software predicts the following properties: Drug half-life (T1/2); Fraction of oral dose absorbed (FA); Caco-2 permeability; Volume of distribution (VD); Octanol/water distribution coefficient (LogP)

q-hERG - a unique and innovative software, which allows you to predict from a molecule structures of compounds their inhibition constants (IC50) for hERG channels.

q-Albumin software takes a molecular structure and calculates HSA binding constant by docking the molecule to both of the HSA active sites (Sudlow site I and Sudlow site II).

Quantum Pharmaceuticals is pleased to release Quantum Science Overview. The document conveys an overview Quantum's drug discovery solutions and scientific results. The content of the report are summarized below:
I. A Novel Integrated Approach in Drug Discovery 1
II. QUANTUM free energy vs. statistical scoring functions
III. Inside Quantum Drug Discovery Studio: Molecular Modeling Concepts and Tools
IV. QDDS and Molecular Interactions in Aqueous Environments (Solvation Model).
V. Collective (non-additive) contributions to a protein-ligand complex binding free energy.
VI. Discovery of new classes of HIV integrase inhibitors.
VII. Biological Spectra Analysis: Linking Biological Activity Profiles to Molecular Toxicity.

Appendices
A. Structure of a Basic PBPK Model applied in q-ADME
B. Binding affinity calculation of known drugs tohuman serum albumin
C. Rediscovery of Blockbuster drugs with QUANTUM

Below we provide an example of Molecular Dynamics of HIV-integrase monomer with 1- (5- CHLOROINDOL-3- YL)-3 -HYDROXY-3 -(2H- TETRAZOL- 5- YL)-PROPENONE (pdb code 1qs4).

The protein structure is taken from the original 1qs4 pdb data and combined with the missing loop data from 2itg structure. The complete calculation yuilds -27kJ/mol binding energy, close to the experimentally observed value.

The inhibitor molecule is shown in red licorice. The Mg++ ion is shown as a megenta sphere.

Human neutrophil elastase complexed with an inhibitor (gw475151) studied with QUANTUM normal modes analysis tools. The video shows the inhibitor (red licorice) remains in a strongly interacting position regardless of the protein most probable motion:

Most of available docking software performs free energy scoring for different ligands positions on the same rigid protein structure. The validity of such procedure can not be easily asserted. Not only different PDB Data Bank structures of the same protein are different, NMR studies show often impressive protein flexibility and thus uncertainty in the protein atoms positions. The necessity to compensate for the lack of the structure information makes scoring functions developers utilize smooth energy scores corresponding to some kind of coarse grain approximation for the protein-ligand interactions. Such an averaging leads to inability to recover fine details of interactions and hence to lack of selectivity and false postives, i.e. hits with binding constants actually lower than predicted.

The movie above helps explain this situation. While a scoring function could suggest an accurate value for the particular ligand docked in the experimentally observed position, the scores for "hits" overlapping with the protein motion could be the same good or better, but false, since the protein position extracted from the PDB data represents only a single member of the statistical ensemble. Mathematically speaking the ligand gw475151 does not only have a good interaction energy (enthalpy), but also remains complementary to the protein pocket in spite of sufficiently large protein displacements (has a low entropy loss associated with the protein degrees of freedom).

Materials and methods:The initial information about the protein-ligand structure is taken from 1h1b PDB entry. The ligand was taken out and protein was let to relax in QUANTUM continuum water (see cond-mat/0601129). After a sufficiently long molecular dynamics simulation the protein motion has been analyzed and the lowest normal mode (highest amplitude protein motion) was separated. The ligand is then placed back at a fixed position to highlight dynamic overlap between the ligand steric interactions and the protein motion.