On-the-Fly Integration of Data from a Spin-Diffusion-Based NMR Experiment into Protein-Ligand Docking

VirtualFlow Ants-Ultra-Large Virtual Screenings with Artificial Intelligence Driven Docking Algorithm Based on Ant Colony Optimization

The docking program PLANTS, which is based on ant colony optimization (ACO) algorithm, has many advanced features for molecular docking. Among them are multiple scoring functions, the possibility to model explicit displaceable water molecules, and the inclusion of experimental constraints. Here, we add support of PLANTS to VirtualFlow (VirtualFlow Ants), which adds a valuable method for primary virtual screenings and rescoring procedures. Furthermore, we have added support of ligand libraries in the MOL2 format, as well as on the fly conversion of ligand libraries which are in the PDBQT format to the MOL2 format to endow VirtualFlow Ants with an increased flexibility regarding the ligand libraries. The on the fly conversion is carried out with Open Babel and the program SPORES. We applied VirtualFlow Ants to a test system involving KEAP1 on the Google Cloud up to 128,000 CPUs, and the observed scaling behavior is approximately linear. Furthermore, we have adjusted several central docking parameters of PLANTS (such as the speed parameter or the number of ants) and screened 10 million compounds for each of the 10 resulting docking scenarios. We analyzed their docking scores and average docking times, which are key factors in virtual screenings. The possibility of carrying out ultra-large virtual screening with PLANTS via VirtualFlow Ants opens new avenues in computational drug discovery.

Determination of protein-ligand binding modes using fast multi-dimensional NMR with hyperpolarization

Elucidation of small molecule-protein interactions provides essential information for understanding biological processes such as cellular signaling, as well as for rational drug development. Here, multi-dimensional NMR with sensitivity enhancement by dissolution dynamic nuclear polarization (D-DNP) is shown to allow the determination of the binding epitope of folic acid when complexed with the target dihydrofolate reductase. Protein signals are selectively enhanced by polarization transfer from the hyperpolarized ligand. A pseudo three-dimensional data acquisition with ligand-side Hadamard encoding results in protein-side [13C, 1H] chemical shift correlations that contain intermolecular nuclear Overhauser effect (NOE) information. A scoring function based on this data is used to select pre-docked ligand poses. The top five poses are within 0.76 Å root-mean-square deviation from a reference structure for the encoded five protons, showing improvements compared with the poses selected by an energy-based scoring function without experimental inputs. The sensitivity enhancement provided by the D-DNP combined with multi-dimensional NMR increases the speed and potentially the selectivity of structure elucidation of ligand binding epitopes.

Predictive Power of Different Types of Experimental Restraints in Small Molecule Docking: A Review

Incorporating experimental restraints is a powerful method of increasing accuracy in computational protein small molecule docking simulations. Different algorithms integrate distinct forms of biochemical data during the docking and/or scoring stages. These so-called hybrid methods make use of receptor-based information such as nuclear magnetic resonance (NMR) restraints or small molecule-based information such as structure-activity relationships (SARs). A third class of methods directly interrogates contacts between the protein receptor and the small molecule. This work reviews the current state of using such restraints in docking simulations, evaluates their feasibility across broad systems, and identifies potential areas of algorithm development.

NMR studies of ligand binding

NMR spectroscopy is an established tool in drug discovery, but its strength is commonly regarded to be largely confined to the early stages of hit discovery and fragment based drug design, where NMR offers unique capabilities of characterizing the binding modes of ligand molecules that bind sufficiently weakly to be in rapid exchange between bound and free state. Here we, first, provide a meta-review of recent reviews on NMR studies of ligand binding and, second, review recent progress towards NMR characterization of the ligand binding mode in stable protein-ligand complexes, with particular emphasis on the global positioning system (GPS) approach enabled by paramagnetic lanthanide tags.

Nanodiscs for INPHARMA NMR Characterization of GPCRs: Ligand Binding to the Human A2A Adenosine Receptor

G-protein-coupled-receptors (GPCRs) are of fundamental importance for signal transduction through cell membranes. This makes them important drug targets, but structure-based drug design (SBDD) is still hampered by the limitations for structure determination of unmodified GPCRs. We show that the interligand NOEs for pharmacophore mapping (INPHARMA) method can provide valuable information on ligand poses inside the binding site of the unmodified human A_2A adenosine receptor reconstituted in nanodiscs. By comparing experimental INPHARMA spectra with back-calculated spectra based on ligand poses obtained from molecular dynamics simulations, a complex structure for A_2A R with the low-affinity ligand 3-pyrrolidin-1-ylquinoxalin-2-amine was determined based on the X-ray structure of ligand ZM-241,358 in complex with a modified A_2A R.