Abstract:A general computational scheme to evaluate the effects of single point mutations on ligand binding is reported. This scheme is applied to characterize agonist binding to the A2A adenosine receptor, and is found to accurately explain how point mutations of different nature affect the binding affinity of a potent agonist.
“…This protocol, based on free energy perturbation of residue sidechains, can be used to identify the molecular interactions that are gained or lost as a result of the point mutation. Since the corresponding shifts in ligand binding free energy are related to molecular interactions, as demonstrated on 34 of the A2AAR mutants described in this review [24,26]. are exceptions bearing structurally simple, monocyclic cores.…”
Section: Arsmentioning
confidence: 88%
“…Mutations on the orthosteric site, which represent 80% of the collected mutational data on ARs, have been characterized in more detail than the mutations on the allosteric or G protein sites described in the next sections. Indeed, In silico site-directed mutagenesis simulations of several A2AAR orthosteric-site mutants (Box 1) provided a nice complement to the structural analysis of static crystal structures discussed above, revealing non-evident effects like water-mediated interactions or the role of mutations which are not in direct contact with the ligand [24,26]. 8…”
Section: Triggering Receptor Activation: Residues Involved In Agonistmentioning
confidence: 99%
“…These different sources of experimental data can be integrated in computational models, which are used to elucidate the molecular determinants of ligand binding and receptor function [24]. In the ARs, protocols like proteochemometrics (PCM) [25] or free energy perturbation (FEP) [24,26] have successfully filled the gap between affinity and structural data (Box 1).…”
The four adenosine receptors (ARs), A, A, A, and A, constitute a subfamily of G protein-coupled receptors (GPCRs) with exceptional foundations for structure-based ligand design. The vast amount of mutagenesis data, accumulated in the literature since the 1990s, has been recently supplemented with structural information, currently consisting of several inactive and active structures of the A and inactive conformations of the A ARs. We provide the first integrated view of the pharmacological, biochemical, and structural data available for this receptor family, by mapping onto the relevant crystal structures all site-directed mutagenesis data, curated and deposited at the GPCR database (available through http://www.gpcrdb.org). This analysis provides novel insights into ligand binding, allosteric modulation, and signaling of the AR family.
“…This protocol, based on free energy perturbation of residue sidechains, can be used to identify the molecular interactions that are gained or lost as a result of the point mutation. Since the corresponding shifts in ligand binding free energy are related to molecular interactions, as demonstrated on 34 of the A2AAR mutants described in this review [24,26]. are exceptions bearing structurally simple, monocyclic cores.…”
Section: Arsmentioning
confidence: 88%
“…Mutations on the orthosteric site, which represent 80% of the collected mutational data on ARs, have been characterized in more detail than the mutations on the allosteric or G protein sites described in the next sections. Indeed, In silico site-directed mutagenesis simulations of several A2AAR orthosteric-site mutants (Box 1) provided a nice complement to the structural analysis of static crystal structures discussed above, revealing non-evident effects like water-mediated interactions or the role of mutations which are not in direct contact with the ligand [24,26]. 8…”
Section: Triggering Receptor Activation: Residues Involved In Agonistmentioning
confidence: 99%
“…These different sources of experimental data can be integrated in computational models, which are used to elucidate the molecular determinants of ligand binding and receptor function [24]. In the ARs, protocols like proteochemometrics (PCM) [25] or free energy perturbation (FEP) [24,26] have successfully filled the gap between affinity and structural data (Box 1).…”
The four adenosine receptors (ARs), A, A, A, and A, constitute a subfamily of G protein-coupled receptors (GPCRs) with exceptional foundations for structure-based ligand design. The vast amount of mutagenesis data, accumulated in the literature since the 1990s, has been recently supplemented with structural information, currently consisting of several inactive and active structures of the A and inactive conformations of the A ARs. We provide the first integrated view of the pharmacological, biochemical, and structural data available for this receptor family, by mapping onto the relevant crystal structures all site-directed mutagenesis data, curated and deposited at the GPCR database (available through http://www.gpcrdb.org). This analysis provides novel insights into ligand binding, allosteric modulation, and signaling of the AR family.
“…1. The mutations and binding modes were further examined in silico using a ligand-steered homology modeling approach 27 , in this case based on cycles of molecular dynamics (MD) and free energy perturbation (FEP) on selected alanine mutations 28–30 used as a scoring function. From these results, a common interaction profile for the selected GPR139 agonists was confirmed.Figure 1Structure of the GPR139 agonists studied herein.…”
GPR139 is an orphan G protein-coupled receptor expressed in the brain, in particular in the habenula, hypothalamus and striatum. It has therefore been suggested that GPR139 is a possible target for metabolic disorders and Parkinson’s disease. Several surrogate agonist series have been published for GPR139. Two series published by Shi et al. and Dvorak et al. included agonists 1a and 7c respectively, with potencies in the ten-nanomolar range. Furthermore, Isberg et al. and Liu et al. have previously shown that tryptophan (Trp) and phenylalanine (Phe) can activate GPR139 in the hundred-micromolar range. In this study, we produced a mutagenesis-guided model of the GPR139 binding site to form a foundation for future structure-based ligand optimization. Receptor mutants studied in a Ca2+ assay demonstrated that residues F1093×33, H1875×43, W2416×48 and N2717×38, but not E1083×32, are highly important for the activation of GPR139 as predicted by the receptor model. The initial ligand-receptor complex was optimized through free energy perturbation simulations, generating a refined GPR139 model in agreement with experimental data. In summary, the GPR139 reference surrogate agonists 1a and 7c, and the endogenous amino acids l-Trp and l-Phe share a common binding site, as demonstrated by mutagenesis, ligand docking and free energy calculations.
“…A similar approach using a X‐ray structure in combination with known activity data for a range of ligands was reported by Van Westen et al Over thousands of compounds screened, very high affinity adenosine ligands were identified, including the 2‐amino‐1,3,5‐triazine. In addition, a virtual screening campaign was reported to achieve agonists in the receptor . In Figure it is possible to observe the scaffolds achieved among the variety of virtual screening campaigns herein highlighted.…”
all approved immune checkpoint modulators in the clinic are monoclonal antibodies. These have revolutionized cancer therapy because of their remarkable clinical activity. However, their failure to show response in most patients, their required administration by an intravenous injection and the induction of severe immune-related adverse effects, 1-3 constitute some of their important drawbacks.In this context, considerable research effort is being deployed to find the next generation of effective cancer immunotherapeutics. Pioneering efforts include the design of novel immune modulatory small molecules (synthetic and natural products) to specifically target emerging pathways responsible for immune evasion. Small molecules are more affordable and may become invaluable alternatives to monoclonal antibodies. However, small-molecule drug discovery is a complex and challenging multidimensional process, focusing on multiple aspects, as the activity, efficacy, pharmacokinetics, pharmacodynamics, and safety of potential novel candidates. The average length of time from hit discovery to the approval of a new drug is at least 14 years, encompassing the investment of billions of dollars. To circumvent and accelerate this lengthy and costly drug discovery and development process, over the past two decades, drug designers have been exploring computational-aided drug design (CADD) tools to design and identify new drug-like chemical entities that can overcome clinical attrition and lack of efficiency.Revolutionary and accelerated performance hardware architectures, including graphical processor units, innovative algorithms and software advances are now available for high-level computations in a time-affordable way pushing the frontiers of computationally driven drug discovery in the rational search for novel bioactive compounds in modern medicinal chemistry.CADD methodologies can be divided in structure-and ligand-based drug design (SBDD and LBDD). Protein three-dimensional (3D) structures are the basis for structure-based drug design. Once the 3D structure of a protein target is available, the SBDD is usually elected to develop therapeutic agents and to understand the mode of action, as well as, the metabolic process. SBDD embraces several methodologies, namely structure-based virtual screening (SBVS), de novo design or pharmacophore generation. A rational SBDD approach is based on the deep understanding of the key interactions between small molecules (or proteins) and their targets, applying techniques, such as molecular docking and molecular dynamics (Scheme 1).Broadly used for SBVS, molecular docking methods explore the ligand conformations adopted within the binding sites of macromolecular targets (search algorithm) and estimate the ligand-receptor affinities (scoring functions). Molecular docking is nowadays one of the elected methods to use in SBVS with a huge rate of success. However, molecular docking works on rigid structures forgetting structural flexibility and structural rearrangements. Although this is a generally ...
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
