Pharmacological fingerprint of antipsychotic drugs at the serotonin 5-HT2A receptor.

The intricate involvement of the serotonin 5-HT2A receptor (5-HT2AR) both in schizophrenia and in the activity of antipsychotic drugs is widely acknowledged. The currently marketed antipsychotic drugs, although effective in managing the symptoms of schizophrenia to a certain extent, are not without their repertoire of serious side effects. There is a need for better therapeutics to treat schizophrenia for which understanding the mechanism of action of the current antipsychotic drugs is imperative. With bioluminescence resonance energy transfer (BRET) assays, we trace the signaling signature of six antipsychotic drugs belonging to three generations at the 5-HT2AR for the entire spectrum of signaling pathways activated by serotonin (5-HT). The antipsychotic drugs display previously unidentified pathway preference at the level of the individual Gα subunits and ß-arrestins. In particular, risperidone, clozapine, olanzapine and haloperidol showed G protein-selective inverse agonist activity. In addition, G protein-selective partial agonism was found for aripiprazole and cariprazine. Pathway-specific apparent dissociation constants determined from functional analyses revealed distinct coupling-modulating capacities of the tested antipsychotics at the different 5-HT-activated pathways. Computational analyses of the pharmacological and structural fingerprints support a mechanistically based clustering that recapitulate the clinical classification (typical/first generation, atypical/second generation, third generation) of the antipsychotic drugs. The study provides a new framework to functionally classify antipsychotics that should represent a useful tool for the identification of better and safer neuropsychiatric drugs and allows formulating hypotheses on the links between specific signaling cascades and in the clinical outcomes of the existing drugs.

Discovery of ICOS-Targeted Small Molecules Using Pharmacophore-Based Screening.

There are currently no small molecules clinically approved as immune checkpoint modulators. Besides possessing oral bioavailability, cell-penetrating capabilities and enhanced tumor penetration compared to monoclonal antibodies (mAbs), small molecules are amenable to pharmacokinetic optimization, which allows adopting flexible dosage regimens that may avoid immune-related adverse events associated with mAbs. The interaction of inducible co-stimulator (ICOS) with its ligand (ICOS-L) plays key roles in T-cell differentiation and activation of T-cell to B-cell functions. This study represents the development and validation of a virtual screening strategy to identify small molecules that bind a novel druggable binding pocket in human ICOS. We used a lipophilic canyon in the apo-structure of ICOS and the ICOS/ICOS-L interface individually as templates for molecular dynamics simulation to generate 3D pharmacophores subsequently used for virtual screening campaigns. Our strategy was successful finding a first-in-class small molecule ICOS binder (5P, KD value=108.08±26.76 µM) and validating biophysical screening platforms for ICOS-targeted small molecules. We anticipate that future structural optimization of 5P will result in the discovery of high affinity chemical ligands for ICOS.

Discovery of Small-Molecule TIM-3 Inhibitors for Acute Myeloid Leukemia Using Pharmacophore-Based Virtual Screening.

T-cell immunoglobulin and mucin domain 3 (TIM-3) is a negative immune checkpoint that represents a promising target for cancer immunotherapy. Although encouraging results have been observed for TIM-3 inhibition in the context of acute myeloid leukemia (AML), targeting TIM-3 is currently restricted to monoclonal antibodies (mAbs). To fill this gap, we implemented a pharmacophore-based screening approach to identify small-molecule TIM-3 inhibitors. Our approach resulted in the identification of hit compounds with TIM-3 binding affinity. Subsequently, we used the structure-activity relationship (SAR) by a catalog approach to identify compound A-41 with submicromolar TIM-3 binding affinity. Remarkably, A-41 demonstrated the ability to block TIM-3 interactions with key ligands and inhibited the immunosuppressive function of TIM-3 using an in vitro coculture assay. This work will pave the way for future drug discovery efforts aiming at the development of small-molecule inhibitors TIM-3 for AML.

Designed multiple ligands for the treatment of type 2 diabetes mellitus and its complications: Discovery of (5-arylidene-4-oxo-2-thioxothiazolidin-3-yl)alkanoic acids active as novel dual-targeted PTP1B/AKR1B1 inhibitors.

Type 2 diabetes mellitus (T2DM) is a serious chronic disease with an alarmingly growing worldwide prevalence. Current treatment of T2DM mainly relies on drug combinations in order to control blood glucose levels and consequently prevent the onset of hyperglycaemia-related complications. The development of multiple-targeted drugs recently emerged as an attractive alternative to drug combinations for the treatment of complex diseases with multifactorial pathogenesis, such as T2DM. Protein tyrosine phosphatase 1B (PTP1B) and aldose reductase (AKR1B1) are two enzymes crucially involved in the development of T2DM and its chronic complications and, therefore, dual inhibitors targeted to both these enzymes could provide novel agents for the treatment of this complex pathological condition. In continuing our search for dual-targeted PTP1B/AKR1B1 inhibitors, we designed new (5-arylidene-4-oxo-2-thioxothiazolidin-3-yl)alkanoic acids. Among them, 3-(4-phenylbutoxy)benzylidene derivatives 6f and 7f, endowed with interesting inhibitory activity against both targets, proved to control specific cellular pathways implicated in the development of T2DM and related complications.

Mind the Gap-Deciphering GPCR Pharmacology Using 3D Pharmacophores and Artificial Intelligence.

G protein-coupled receptors (GPCRs) are amongst the most pharmaceutically relevant and well-studied protein targets, yet unanswered questions in the field leave significant gaps in our understanding of their nuanced structure and function. Three-dimensional pharmacophore models are powerful computational tools in in silico drug discovery, presenting myriad opportunities for the integration of GPCR structural biology and cheminformatics. This review highlights success stories in the application of 3D pharmacophore modeling to de novo drug design, the discovery of biased and allosteric ligands, scaffold hopping, QSAR analysis, hit-to-lead optimization, GPCR de-orphanization, mechanistic understanding of GPCR pharmacology and the elucidation of ligand-receptor interactions. Furthermore, advances in the incorporation of dynamics and machine learning are highlighted. The review will analyze challenges in the field of GPCR drug discovery, detailing how 3D pharmacophore modeling can be used to address them. Finally, we will present opportunities afforded by 3D pharmacophore modeling in the advancement of our understanding and targeting of GPCRs.