Molecular simulations were used to design large scale loop motions in the enzyme cyclophilin A and NMR and biophysical methods were employed to validate the models.
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. Concurrently modulating these targets, our compounds hold a great potential toward exerting a disease-modifying effect on nicotine addiction and other forms of compulsive behavior.
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 CB To understand the unexpected affinity for the CB 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.
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 inter-convert 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 accurately and reliably exploring functionally relevant, but sparsely populated conformations with milli-second 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.
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