Virtual fragment screening: exploration of MM-PBSA re-scoring

In silico fragment-based drug design with SEED

We report on two fragment-based drug design protocols, SEED2XR and ALTA, which start by high-throughput docking. SEED2XR is a two-stage protocol for fragment-based drug design. The first stage is in silico and consists of the automatic docking of 10³-10⁴ fragments using SEED, which requires about 1 s per fragment. SEED is a docking software developed specifically for fragment docking and binding energy evaluation by a force field with implicit solvent. In the second stage of SEED2XR, the 10-10² fragments with the most favorable predicted binding energies are validated by protein X-ray crystallography. The recent applications of SEED2XR to bromodomains demonstrate that the whole SEED2XR protocol can be carried out in about a week of working time, with hit rates ranging from 10% to 40%. Information on fragment-target interactions generated by the SEED2XR protocol or directly from SEED docking has been used for the discovery of hundreds of hits. ALTA is a computational protocol for screening which identifies candidate ligands that preserve the interactions between the optimal SEED fragments and the protein target. Medicinal chemistry optimization of ligands predicted by ALTA has resulted in pre-clinical candidates for protein kinases and bromodomains. The high-throughput, very low cost, sustainability, and high hit rate of the SEED-based protocols, unreachable by purely experimental techniques, make them perfectly suitable for both academic and industrial drug discovery research.

Solvation methods for protein-ligand docking

Hydration has a significant impact on ligand binding within protein active sites. Specific water molecules and their placement within protein active sites have been shown to make specific contributions to the energetics of protein-ligand binding and need consideration in the design of efficient binding ligands. These specific nonbulk water molecules and their interactions are different and have more significant impact in ligand design than the generalized bulk solvation of ligand-protein systems. Proper theoretical description of the solvation effects of water within a ligand-binding pocket is a significant computational challenge. Recently, new computational methods have been developed which can more accurately describe the contribution of waters within a protein ligand site and lead to improved and enhanced ligand design and ranking in computational docking and to greater enrichment.

Improvements, trends, and new ideas in molecular docking: 2012-2013 in review

Molecular docking is a computational method for predicting the placement of ligands in the binding sites of their receptor(s). In this review, we discuss the methodological developments that occurred in the docking field in 2012 and 2013, with a particular focus on the more difficult aspects of this computational discipline. The main challenges and therefore focal points for developments in docking, covered in this review, are receptor flexibility, solvation, scoring, and virtual screening. We specifically deal with such aspects of molecular docking and its applications as selection criteria for constructing receptor ensembles, target dependence of scoring functions, integration of higher-level theory into scoring, implicit and explicit handling of solvation in the binding process, and comparison and evaluation of docking and scoring methods.

Evaluation of a semi-automated workflow for fragment growing

Intelligent Automatic Design (IADE) is an expert system developed at Novartis to identify nonclassical bioisosteres. In addition to bioisostere searching, one could also use IADE to grow a fragment bound to a protein. Here we report an evaluation of IADE as a tool for fragment growing. Three examples from the literature served as test cases. In all three cases, IADE generated close analogues of the published compounds and reproduced their crystallographic binding modes. This exercise validated the use of the IADE system for fragment growing. We have also gained experience in optimizing the performance of IADE for this type of application.

Virtual fragment screening on GPCRs: a case study on dopamine D3 and histamine H4 receptors

Prospective structure based virtual fragment screening methodologies on two GPCR targets namely the dopamine D3 and the histamine H4 receptors with a library of 12,905 fragments were evaluated. Fragments were docked to the X-ray structure and the homology model of the D3 and H4 receptors, respectively. Representative receptor conformations for ensemble docking were obtained from molecular dynamics trajectories. In vitro confirmed hit rates ranged from 16% to 32%. Hits had high ligand efficiency (LE) values in the range of 0.31-0.74 and also acceptable lipophilic efficiency. The X-ray structure, the homology model and structural ensembles were all found suitable for docking based virtual screening of fragments against these GPCRs. However, there was little overlap among different hit sets and methodologies were thus complementary to each other.

Tranilast binds to aβ monomers and promotes aβ fibrillation

The antiallergy and potential anticancer drug tranilast has been patented for treating Alzheimer's disease (AD), in which amyloid β-protein (Aβ) plays a key pathogenic role. We used solution NMR to determine that tranilast binds to Aβ40 monomers with ∼300 μM affinity. Remarkably, tranilast increases Aβ40 fibrillation more than 20-fold in the thioflavin T assay at a 1:1 molar ratio, as well as significantly reducing the lag time. Tranilast likely promotes fibrillation by shifting Aβ monomer conformations to those capable of seed formation and fibril elongation. Molecular docking results qualitatively agree with NMR chemical shift perturbation, which together indicate that hydrophobic interactions are the major driving force of the Aβ-tranilast interaction. These data suggest that AD may be a potential complication for tranilast usage in elderly patients.