Among the ten different adenylyl cyclase isoforms, studies with knockout animals indicate that inhibition of AC1 can relieve pain and reduce behaviors linked to opioid dependence. We previously identified ST034307 as a selective inhibitor of AC1. The development of an AC1-selective inhibitor now provides the opportunity to further study the therapeutic potential of inhibiting this protein in pre-clinical animal models of pain and related adverse reactions. In the present study we have shown that ST034307 relives pain in mouse models of formalin-induced inflammatory pain, acid-induced visceral pain, and acid-depressed nesting. In addition, ST034307 did not cause analgesic tolerance after chronic dosing. We were unable to detect ST034307 in mouse brain following subcutaneous injections but showed a significant reduction in cAMP concentration in dorsal root ganglia of the animals. Considering the unprecedented selectivity of ST034307, we also report the predicted molecular interaction between ST034307 and AC1. Our results indicate that AC1 inhibitors represent a promising new class of analgesic agents that treat pain and do not result in tolerance or cause disruption of normal behavior in mice. In addition, we outline a unique binding site for ST034307 at the interface of the enzyme’s catalytic domain.
In recent years, the development of high-throughput technologies for obtaining sequence data leveraged the possibility of analysis of protein data in silico. However, when it comes to viral polyprotein interaction studies, there is a gap in the representation of those proteins, given their size and length. The prepare for studies using state-of-the-art techniques such as Machine Learning, a good representation of such proteins is a must. We present an alternative to this problem, implementing a fragmentation and modeling protocol to prepare those polyproteins in the form of peptide fragments. Such procedure is made by several scripts, implemented together on the workflow we call PolyPRep, a tool written in Python script and available in GitHub. This software is freely available only for noncommercial users.
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