Multitarget Compounds for Bipolar Disorder: From Rational Design to Preliminary Pharmacokinetic Evaluation.

Due to the complex and multifactorial nature of bipolar disorder (BD), single-target drugs have traditionally provided limited relief with no disease-modifying effects. In line with the polypharmacology paradigm, we attempted to overcome these limitations by devising two series of multitarget-directed ligands endowed with both a partial agonist profile at dopamine receptor D3 (D3R) and inhibitory activity against glycogen synthase kinase 3 beta (GSK-3ß). These are two structurally unrelated targets that play independent, yet connected, roles in cognition and mood regulation. Two compounds (7 and 10) emerged as promising D3R/GSK-3ß multitarget-directed ligands with nanomolar activity at D3R and low-micromolar inhibition of GSK-3ß, thereby confirming, albeit preliminarily, the feasibility of our strategy. Furthermore, 7 showed promising drug-like properties in stability and pharmacokinetic studies.

Multi-target dopamine D3 receptor modulators: Actionable knowledge for drug design from molecular dynamics and machine learning.

Local changes in the structure of G-protein coupled receptors (GPCR) binders largely affect their pharmacological profile. While the sought efficacy can be empirically obtained by introducing local modifications, the underlining structural explanation can remain elusive. Here, molecular dynamics (MD) simulations of the eticlopride-bound inactive state of the Dopamine D3 Receptor (D3DR) have been clustered using a machine learning-based approach in the attempt to rationalize the efficacy change in four congeneric modulators. Accumulating extended MD trajectories of receptor-ligand complexes, we observed how the increase in ligand flexibility progressively destabilized the crystal structure of the inactivated receptor. To prospectively validate this model, a partial agonist was rationally designed based on structural insights and computational modeling, and eventually synthesized and tested. Results turned out to be in line with the predictions. This case study suggests that the investigation of ligand flexibility in the framework of extended MD simulations can assist and inform drug design strategies, highlighting its potential role as a powerful in silico counterpart to functional assays.

Dynamic design: manipulation of millisecond timescale motions on the energy landscape of cyclophilin A.

Proteins need to interconvert between many conformations in order to function, many of which are formed transiently, and sparsely populated. Particularly when the lifetimes of these states approach the millisecond timescale, identifying the relevant structures and the mechanism by which they interconvert remains a tremendous challenge. Here we introduce a novel combination of accelerated MD (aMD) simulations and Markov state modelling (MSM) to explore these 'excited' conformational states. Applying this to the highly dynamic protein CypA, a protein involved in immune response and associated with HIV infection, we identify five principally populated conformational states and the atomistic mechanism by which they interconvert. A rational design strategy predicted that the mutant D66A should stabilise the minor conformations and substantially alter the dynamics, whereas the similar mutant H70A should leave the landscape broadly unchanged. These predictions are confirmed using CPMG and R1ρ solution state NMR measurements. By efficiently exploring functionally relevant, but sparsely populated conformations with millisecond lifetimes in silico, our aMD/MSM method has tremendous promise for the design of dynamic protein free energy landscapes for both protein engineering and drug discovery.

A computationally designed binding mode flip leads to a novel class of potent tri-vector cyclophilin inhibitors.

Cyclophilins (Cyps) are a major family of drug targets that are challenging to prosecute with small molecules because the shallow nature and high degree of conservation of the active site across human isoforms offers limited opportunities for potent and selective inhibition. Herein a computational approach based on molecular dynamics simulations and free energy calculations was combined with biophysical assays and X-ray crystallography to explore a flip in the binding mode of a reported urea-based Cyp inhibitor. This approach enabled access to a distal pocket that is poorly conserved among key Cyp isoforms, and led to the discovery of a new family of sub-micromolar cell-active inhibitors that offer unprecedented opportunities for the development of next-generation drug therapies based on Cyp inhibition. The computational approach is applicable to a broad range of organic functional groups and could prove widely enabling in molecular design.

Design, Synthesis, Structure-Activity Relationship Studies, and Three-Dimensional Quantitative Structure-Activity Relationship (3D-QSAR) Modeling of a Series of O-Biphenyl Carbamates as Dual Modulators of Dopamine D3 Receptor and Fatty Acid Amide Hydrolase.

We recently reported molecules designed according to the multitarget-directed ligand paradigm to exert combined activity at human fatty acid amide hydrolase (FAAH) and dopamine receptor subtype D3 (D3R). Both targets are relevant for tackling several types of addiction (most notably nicotine addiction) and other compulsive behaviors. Here, we report an SAR exploration of a series of biphenyl-N-[4-[4-(2,3-substituted-phenyl)piperazine-1-yl]alkyl]carbamates, a novel class of molecules that had shown promising activities at the FAAH-D3R target combination in preliminary studies. We have rationalized the structural features conducive to activities at the main targets and investigated activities at two off-targets: dopamine receptor subtype D2 and endocannabinoid receptor CB1. To understand the unexpected affinity for the CB1 receptor, we devised a 3D-QSAR model, which we then prospectively validated. Compound 33 was selected for PK studies because it displayed balanced affinities for the main targets and clear selectivity over the two off-targets. 33 has good stability and oral bioavailability and can cross the blood-brain barrier.

Applying a multitarget rational drug design strategy: the first set of modulators with potent and balanced activity toward dopamine D3 receptor and fatty acid amide hydrolase.

Combining computer-assisted drug design and synthetic efforts, we generated compounds with potent and balanced activities toward both D3 dopamine receptor and fatty acid amide hydrolase (FAAH) enzyme. By concurrently modulating these targets, our compounds hold great potential toward exerting a disease-modifying effect on nicotine addiction and other forms of compulsive behavior.

N-Hydroxyindole-based inhibitors of lactate dehydrogenase against cancer cell proliferation.

Current cancer research is being increasingly focused on the study of distinctive characters of tumour metabolism, resulting in a switch from oxidative phosphorylation to glycolysis (Warburg effect). Isoform 5 of human lactate dehydrogenase (hLDH5), which catalyzes the final step in the glycolytic cascade (pyruvate to lactate), constitutes a relatively new and untapped anti-cancer target. In this study, careful design and synthesis of a selected series of aryl-substituted N-hydroxyindole-2-carboxylates (NHIs) has led to several hLDH5-inhibitors, showing "first-in-class" potency and isoform selectivity. Enzyme kinetics studies indicated that these inhibitors exhibit a competitive mode of inhibition. Some representative examples were tested against two human pancreatic carcinoma cell lines, and displayed a good anti-proliferative activity, which was even more evident under hypoxic conditions.