2011
DOI: 10.1002/cbic.201000459
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Differentiating Serine and Cysteine Protease Mechanisms by New Covalent QSAR Descriptors

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Cited by 16 publications
(28 citation statements)
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“…This is further supported by our previous theoretical studies of thiolate reactivity towards different electrophiles,30 and the conclusions derived from experimental kinetic studies of papain 31. We also demonstrated that with a weak Cys nucleophile in Cathepsin K, the binding trend of CS of RCA inhibitors is dominated by the change in pK a of the oxygen atom in TC(OH), which is accounted for by the covalent descriptor W2 13. The QSAR models presented in this work are generated for reversible covalent ketoamide inhibitors of cathepsin K (Figure 10).…”
Section: Resultssupporting
confidence: 84%
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“…This is further supported by our previous theoretical studies of thiolate reactivity towards different electrophiles,30 and the conclusions derived from experimental kinetic studies of papain 31. We also demonstrated that with a weak Cys nucleophile in Cathepsin K, the binding trend of CS of RCA inhibitors is dominated by the change in pK a of the oxygen atom in TC(OH), which is accounted for by the covalent descriptor W2 13. The QSAR models presented in this work are generated for reversible covalent ketoamide inhibitors of cathepsin K (Figure 10).…”
Section: Resultssupporting
confidence: 84%
“…13), the W2 index accounts for two energetic effects – formation of the enzyme-inhibitor covalent bond and PA/pK a of TC(OH). The latter effect dominates the biding trend of RCA inhibitors with a weak Cys nucleophile 13. Therefore, W2 plays an exclusive role in the QSAR models of cysteine proteases.…”
Section: Resultsmentioning
confidence: 99%
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“…We have recently introduced two types of QSAR descriptors, W1 and W2. [18] They quantitatively account for the en- Abstract: Most CADD tools handle non-covalent enzyme inhibitors, despite the growing interest of the pharma industry in covalent inhibitors. We have recently introduced an enzyme mechanism-based method, EMBM, as a computational tool for binding trend analysis and prediction of chemical sites (CS) of reversible covalent enzyme inhibitors.…”
Section: Introductionmentioning
confidence: 99%