Active site gate of M32 carboxypeptidases illuminated by crystal structure and molecular dynamics simulations

Sharma, Bhaskar; Jamdar, Sahayog N.; Ghosh, Biplab; Yadav, Pooja; Kumar, Ashwani; Kundu, Suman; Goyal, Venuka Durani; Makde, Ravindra D.

doi:10.1016/j.bbapap.2017.07.023

Cited by 8 publications

(11 citation statements)

References 35 publications

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“…Most M32 proteins are oligopeptidases and the length of their substrate is governed by the length of the active site groove, which closes upon substrate binding ( Sharma et al, 2017 ). The Arg (Arg92 in PfuCP), located at the back of the substrate groove, is 100% conserved in over 600 sequences of M32CPs ( Lee et al, 2009 ).…”

Section: Three-dimensional Structure Of Keratinolytic Enzymesmentioning

confidence: 99%

“…Thermus aquaticus (TaqCP), Pyrococcus furiosus (PfuCP), Leishmania major (LmaCP)). Hence, M32 subfamily I should be able to cleave only those substrates that are small enough to fit into the narrow substrate groove and allow the active site gate to be closed ( Sharma et al, 2017 ). Furthermore, TaqCP, PfuCP and LmaCP in subfamily I have broad substrate specificity with a C-terminal amino acid preference in the order basic > aliphatic > aromatic >> acidic and the substrate is limited to 7–15 residues ( Lee et al, 2009 ).…”

Section: Three-dimensional Structure Of Keratinolytic Enzymesmentioning

confidence: 99%

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Microbial enzymes catalyzing keratin degradation: Classification, structure, function

Qiu

Wilkens

Barrett

et al. 2020

Biotechnology Advances

142

103

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Keratin is an insoluble and protein-rich epidermal material found in e.g. feather, wool, hair. It is produced in substantial amounts as co-product from poultry processing plants and pig slaughterhouses. Keratin is packed by disulfide bonds and hydrogen bonds. Based on the secondary structure, keratin can be classified into α-keratin and β-keratin. Keratinases (EC 3.4.-.- peptide hydrolases) have major potential to degrade keratin for sustainable recycling of the protein and amino acids. Currently, the known keratinolytic enzymes belong to at least 14 different protease families: S1, S8, S9, S10, S16, M3, M4, M14, M16, M28, M32, M36, M38, M55 (MEROPS database). The various keratinolytic enzymes act via endo -attack (proteases in families S1, S8, S16, M4, M16, M36), exo -attack (proteases in families S9, S10, M14, M28, M38, M55) or by action only on oligopeptides (proteases in families M3, M32), respectively. Other enzymes, particularly disulfide reductases, also play a key role in keratin degradation as they catalyze the breakage of disulfide bonds for better keratinase catalysis. This review aims to contribute an overview of keratin biomass as an enzyme substrate and a systematic analysis of currently sequenced keratinolytic enzymes and their classification and reaction mechanisms. We also summarize and discuss keratinase assays, available keratinase structures and finally examine the available data on uses of keratinases in practical biorefinery protein upcycling applications.

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Section: Three-dimensional Structure Of Keratinolytic Enzymesmentioning

confidence: 99%

Section: Three-dimensional Structure Of Keratinolytic Enzymesmentioning

confidence: 99%

Microbial enzymes catalyzing keratin degradation: Classification, structure, function

Qiu

Wilkens

Barrett

et al. 2020

Biotechnology Advances

142

103

View full text Add to dashboard Cite

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“…However, a presumptive explanation can be put forward. As in the case of many other metallopeptidase inhibitors, it is likely that inhibition of trypanosomatid M32 MCPs occurs throughout the perturbation of the coordination sphere of the catalytic metal ion (presumably Zn 2+ in the case of Tc MCP-1 and Tb MCP-1, by extension from other M32 enzymes [31]). Typically, synthetic metallopeptidase inhibitors achieve preliminary affinity and target selectivity through the formation of stabilizing interactions with specific residues within the active site; while a ZBG is responsible for metal chelation, enhancing binding affinity, modulating selectivity and disrupting catalytic activity [32].…”

Section: Discussionmentioning

confidence: 99%

“…This is the most potent inhibitor described so far for an enzyme of the M32 family and seems a promising candidate for further structure-based optimization. The unusually high flexibility of the M32 MCPs around the active site [31, 34] prevented us to use a docking approach to get insights of the binding mode of this compound within Tc MCP-1 and Tb MCP-1 catalytic clefts. However, the TCMDC-143620 molecule seems able to form a variety of stabilizing interactions.…”

Section: Discussionmentioning

confidence: 99%

Potent and selective inhibitors for M32 metallocarboxypeptidases identified from high-throughput screening of anti-kinetoplastid chemical boxes

et al. 2019

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Enzymes of the M32 family are Zn-dependent metallocarboxypeptidases (MCPs) widely distributed among prokaryotic organisms and just a few eukaryotes including Trypanosoma brucei and Trypanosoma cruzi , the causative agents of sleeping sickness and Chagas disease, respectively. These enzymes are absent in humans and several functions have been proposed for trypanosomatid M32 MCPs. However, no synthetic inhibitors have been reported so far for these enzymes. Here, we present the identification of a set of inhibitors for Tc MCP-1 and Tb MCP-1 (two trypanosomatid M32 enzymes sharing 71% protein sequence identity) from the GlaxoSmithKline HAT and CHAGAS chemical boxes; two collections grouping 404 compounds with high antiparasitic potency, drug-likeness, structural diversity and scientific novelty. For this purpose, we adapted continuous fluorescent enzymatic assays to a medium-throughput format and carried out the screening of both collections, followed by the construction of dose-response curves for the most promising hits. As a result, 30 micromolar-range inhibitors were discovered for one or both enzymes. The best hit, TCMDC-143620, showed sub-micromolar affinity for Tc MCP-1, inhibited Tb MCP-1 in the low micromolar range and was inactive against angiotensin I-converting enzyme (ACE), a potential mammalian off-target structurally related to M32 MCPs. This is the first inhibitor reported for this family of MCPs and considering its potency and specificity, TCMDC-143620 seems to be a promissory starting point to develop more specific and potent chemical tools targeting M32 MCPs from trypanosomatid parasites.

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“…Molecular Modeling has been widely used to decode the nature of the dynamical events involved in structure-function relationship of naturally-occurring biological macromolecules. From short to large scale motions, theoretical (e.g., Molecular Dynamics (MD) simulations and Normal Modes Analysis) studies constantly provide evidence on how the dynamics of the protein host is influenced by the presence or absence of substrates and/or inhibitors as well as the tight relationship between these changes and the accessibility to catalytically efficient configurations (Dutta and Mishra, 2017; Sen et al, 2017; Sharma et al, 2017; Wilson and Wetmore, 2017; Wilson et al, 2017; Kamariah et al, 2018; Luirink et al, 2018; Rout et al, 2018; Schlee et al, 2018). It is therefore a legitimate question to use computation to assess to what extent bridging chemical and biological entities disturb the natural conformational space of the biomolecules and how damaging/beneficial this can be for catalysis.…”

Section: Introductionmentioning

confidence: 99%

The Effect of Cofactor Binding on the Conformational Plasticity of the Biological Receptors in Artificial Metalloenzymes: The Case Study of LmrR

et al. 2019

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The design of Artificial Metalloenzymes (ArMs), which result from the incorporation of organometallic cofactors into biological structures, has grown steadily in the last two decades and important new-to-Nature reactions have been reached. These type of exercises could greatly benefit from an understanding of the structural impact that the inclusion of organometallic moieties may have on the biological host. To date though, our understanding of this phenomenon is highly partial. This lack of knowledge is one of the elements that condition that first-generation ArMs generally display relatively poor catalytic profiles. In this work, we approach this matter by assessing the dynamics and stability of a series of ArMs resulting from the inclusion, via different anchoring strategies, of a variety of organometallic cofactors into the Lactococcal multidrug resistance regulator (LmrR) protein. To this aim, we coupled standard force field-based techniques such as Protein-Ligand Docking and Molecular Dynamics simulations with a variety of trajectory convergence analyses, capable of assessing both the stability and flexibility of the different systems under study upon the binding of cofactors. Together with the experimental evidence obtained in other studies, we provide an overview on how these changes can affect the catalytic outcomes obtained from the different ArMs. Fundamentally, our results show that the convergence analysis used in this work can assess how the inclusion of synthetic metallic cofactors in proteins can condition different structural modulations of their host. Those conformational modifications are key to the success of the desired catalytic activity and their proper identification can be wisely used to improve the quality and the rate of success of the ArMs.

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Active site gate of M32 carboxypeptidases illuminated by crystal structure and molecular dynamics simulations

Cited by 8 publications

References 35 publications

Microbial enzymes catalyzing keratin degradation: Classification, structure, function

Microbial enzymes catalyzing keratin degradation: Classification, structure, function

Potent and selective inhibitors for M32 metallocarboxypeptidases identified from high-throughput screening of anti-kinetoplastid chemical boxes

The Effect of Cofactor Binding on the Conformational Plasticity of the Biological Receptors in Artificial Metalloenzymes: The Case Study of LmrR

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