SAR-Guided Scoring Function and Mutational Validation Reveal the Binding Mode of CGS-8216 at the α1+/γ2- Benzodiazepine Site

Alchemical free energy simulations without speed limits. A generic framework to calculate free energy differences independent of the underlying molecular dynamics program

We describe the theory of the so‐called common‐core/serial‐atom‐insertion (CC/SAI) approach to compute alchemical free energy differences and its practical implementation in a Python package called Transformato. CC/SAI is not tied to a specific biomolecular simulation program and does not rely on special purpose code for alchemical transformations. To calculate the alchemical free energy difference between several small molecules, the physical end‐states are mutated into a suitable common core. Since this only requires turning off interactions, the setup of intermediate states is straightforward to automate. Transformato currently supports CHARMM and OpenMM as back ends to carry out the necessary molecular dynamics simulations, as well as post‐processing calculations. We validate the method by computing a series of relative solvation free energy differences.

Structure-Guided Computational Methods Predict Multiple Distinct Binding Modes for Pyrazoloquinolinones in GABAA Receptors

Pyrazoloquinolinones (PQs) are a versatile class of GABAA receptor ligands. It has been demonstrated that high functional selectivity for certain receptor subtypes can be obtained by specific substitution patterns, but so far, no clear SAR rules emerge from the studies. As is the case for many GABAA receptor targeting chemotypes, PQs can interact with distinct binding sites on a given receptor pentamer. In pentamers of αβγ composition, such as the most abundant α1β2γ2 subtype, many PQs are high affinity binders of the benzodiazepine binding site at the extracellular α+/γ2- interfaces. There they display a functionally near silent, flumazenil-like allosteric activity. More recently, interactions with extracellular α+/β- interfaces have been investigated, where strong positive modulation can be steered toward interesting subtype preferences. The most prominent examples are functionally α6-selective PQs. Similar to benzodiazepines, PQs also seem to interact with sites in the transmembrane domain, mainly the sites used by etomidate and barbiturates. This promiscuity leads to potential contributions from multiple sites to net modulation. Developing ligands that interact exclusively with the extracellular α+/β- interfaces would be desired. Correlating functional profiles with binding sites usage is hampered by scarce and heterogeneous experimental data, as shown in our meta-analysis of aggregated published data. In the absence of experimental structures, bound states can be predicted with pharmacophore matching methods and with computational docking. We thus performed pharmacophore matching studies for the unwanted sites, and computational docking for the extracellular α1,6+/β3- interfaces. The results suggest that PQs interact with their binding sites with diverse binding modes. As such, rational design of improved ligands needs to take a complex structure-activity landscape with branches between sub-series of derivatives into account. We present a workflow, which is suitable to identify and explore potential branching points on the structure-activity landscape of any small molecule chemotype.

Demystifying the Molecular Basis of Pyrazoloquinolinones Recognition at the Extracellular α1+/β3- Interface of the GABAA Receptor by Molecular Modeling

GABA_A receptors are pentameric ligand-gated ion channels that serve as major inhibitory neurotransmitter receptors in the mammalian brain and the target of numerous clinically relevant drugs interacting with different ligand binding sites. Here, we report an in silico approach to investigate the binding of pyrazoloquinolinones (PQs) that mediate allosteric effects through the extracellular α+/β- interface of GABA_A receptors. First, we docked a potent prototype of PQs into the α1+/β3- site of a homology model of the human α1β3γ2 subtype of the GABA_A receptor. Next, for each docking pose, we computationally derived protein-ligand complexes for 18 PQ analogs with known experimental potency. Subsequently, binding energy was calculated for all complexes using the molecular mechanics-generalized Born surface area method. Finally, docking poses were quantitatively assessed in the light of experimental data to derive a binding hypothesis. Collectively, the results indicate that PQs at the α1+/β3- site likely exhibit a common binding mode that can be characterized by a hydrogen bond interaction with β3Q64 and hydrophobic interactions involving residues α1F99, β3Y62, β3M115, α1Y159, and α1Y209. Importantly, our results are in good agreement with the recently resolved cryo-Electron Microscopy structures of the human α1β3γ2 and α1β2γ2 subtypes of GABA_A receptors.

Rigorous sampling of docking poses unveils binding hypothesis for the halogenated ligands of L-type Amino acid Transporter 1 (LAT1)

L-type Amino acid Transporter 1 (LAT1) plays a significant role in the growth and propagation of cancer cells by facilitating the cross-membrane transport of essential nutrients, and is an attractive drug target. Several halogen-containing L-phenylalanine-based ligands display high affinity and high selectivity for LAT1; nonetheless, their molecular mechanism of binding remains unclear. In this study, a combined in silico strategy consisting of homology modeling, molecular docking, and Quantum Mechanics-Molecular Mechanics (QM-MM) simulation was applied to elucidate the molecular basis of ligand binding in LAT1. First, a homology model of LAT1 based on the atomic structure of a prokaryotic homolog was constructed. Docking studies using a set of halogenated ligands allowed for deriving a binding hypothesis. Selected docking poses were subjected to QM-MM calculations to investigate the halogen interactions. Collectively, the results highlight the dual nature of the ligand-protein binding mode characterized by backbone hydrogen bond interactions of the amino acid moiety of the ligands and residues I63, S66, G67, F252, G255, as well as hydrophobic interactions of the ligand’s side chains with residues I139, I140, F252, G255, F402, W405. QM-MM optimizations indicated that the electrostatic interactions involving halogens contribute to the binding free energy. Importantly, our results are in good agreement with the recently unraveled cryo-Electron Microscopy structures of LAT1.