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. 2023 Sep 28;14(10):1434-1440.
doi: 10.1021/acsmedchemlett.3c00335. eCollection 2023 Oct 12.

Design and Optimization of Novel Competitive, Non-peptidic, SARS-CoV-2 Mpro Inhibitors

Affiliations

Design and Optimization of Novel Competitive, Non-peptidic, SARS-CoV-2 Mpro Inhibitors

Leon Jacobs et al. ACS Med Chem Lett. .

Abstract

The SARS-CoV-2 main protease (Mpro) has been proven to be a highly effective target for therapeutic intervention, yet only one drug currently holds FDA approval status for this target. We were inspired by a series of publications emanating from the Jorgensen and Anderson groups describing the design of potent, non-peptidic, competitive SARS-CoV-2 Mpro inhibitors, and we saw an opportunity to make several design modifications to improve the overall pharmacokinetic profile of these compounds without losing potency. To this end, we created a focused virtual library using reaction-based enumeration tools in the Schrödinger suite. These compounds were docked into the Mpro active site and subsequently prioritized for synthesis based upon relative binding affinity values calculated by FEP+. Fourteen compounds were selected, synthesized, and evaluated both biochemically and in cell culture. Several of the synthesized compounds proved to be potent, competitive Mpro inhibitors with improved metabolic stability profiles.

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Conflict of interest statement

The authors declare no competing financial interest.

Figures

Figure 1
Figure 1
Evolution of the Jorgensen compounds from poorly potent perampanel to highly potent derivatives.
Figure 2
Figure 2
An example of a highly potent Jorgensen compound (A) and conversion of this compound to the 2-pyridone (B), which by relative binding free energy calculations (FEP+) performed significantly better than the alternate 4-pyridone (C).
Figure 3
Figure 3
We envisaged being able to attain phenol 5 as our point of late-stage diversification. Various purchasable R-groups amenable to attachment by SN2 substitution (chlorides, bromides, iodides) or by way of a Mitsunobu reaction (alcohols) were scrutinized by modeling for optimal S4 pocket occupancy (Glide-SP) and by free energy perturbation methods (FEP+) to calculate relative binding energies for compound ranking.
Figure 4
Figure 4
Simpler compounds (6 and 7) not containing an S4 binding pocket moiety were evaluated by FEP+ and synthesized to thoroughly investigate which pyridone would be most effective in the S1′ pocket, as this would set the stage for further synthesis.
Scheme 1
Scheme 1
Reagents and conditions: a) Pd(PPh3)4, NaHCO3, 9, DME/water, 93%; b) 10% Pd/C, H2, MeOH/THF (1:1), 92%; c) CuI, K3PO4, N-(2-cyanophenyl)picolinamide, 11, DMSO, 41%; d) Cu(OAc)2, TMEDA, 14, DMSO, 95%; e) TMSCl, NaI, MeCN, 62%.
Scheme 2
Scheme 2
Reagents and conditions: a) Pd(PPh3)4, NaHCO3, 9, DME/water, 86%; b) 10% Pd/C, H2, MeOH/THF (1:1), 27%; c) CuI, K3PO4, N-(2-cyanophenyl)picolinamide, 11, DMSO, 35%; d) Cu(OAc)2, TMEDA, 14, DMSO, 81%; e) TMSCl, NaI, MeCN, 94%.
Scheme 3
Scheme 3
Reagents and conditions: a) CuI, K3PO4, N-(2-cyanophenyl)picolinamide, 21, DMSO, 46%; b) Cu(OAc)2, TMEDA, 14, DMSO, 90%; c) 10% Pd/C, H2, MeOH/THF (1:1), 95%; d) K2CO3, R-X, DMF; e) DIAD, PPh3, R-OH, THF; f) TMSCl, NaI, MeCN.
Scheme 4
Scheme 4
Reagents and conditions: a) CuI, K3PO4, N-(2-cyanophenyl)picolinamide, 21, DMSO, 18%; b) Cu(OAc)2, TMEDA, 14, DMSO, 87%; c) 10% Pd/C, H2, MeOH/THF (1:1), 85%; d) K2CO3, 49, DMF, 84%; e) TMSCl, NaI, MeCN, 45%.
Figure 5
Figure 5
Calculated binding free energy values (ΔGFEP+) plotted against experimentally determined binding free energy values (ΔGEXP).

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