Identification of potential mutational hotspots in serratiopeptidase to address its poor pH tolerance issue

Abstract

Serratiopeptidase is the multifunctionality metalloendopeptidase extensively employed in biopharmaceutical and industrial biotechnology. Despite its poor pH tolerance, serratiopeptidase must withstand the highly acidic environment of the gastrointestinal tract to be used as a potent anti-inflammatory and analgesic medication. In earlier studies, post-translational deamination related mutations showed alteration in the net charge of protein’s surface. Therefore, the current study aimed to enhance the acid resistance of serratiopeptidase via implementing computational interventions to screen out the most stable mutational hotspot. The methodology used in this study is as follows: (a) Higher accessibility to surface (b) 4 Å away from active site region to avoid interference with its proteolytic activity, and (c) By converting non-conserved amide residues to acidic residues. A docking study has been conducted to establish the substrate specificity and binding affinity to native and mutant proteins. The docking outcomes were then validated using molecular dynamic simulations to clarify each mutant’s molecular stability and conformation while preserving their activity. The results showed that N412D is the best-screened mutant with negative electrostatic potential that can alter the overall charge on the protein’s surface with increased H⁺ ions. Alteration in overall charge leads to protein surface more acidic that causes a common ion effect in stomach pH and act as a buffer which could stabilize the serratiopeptidase amid extreme pH.

Communicated by Ramaswamy H. Sarma

Keywords:

• Anti-inflammatory
• Serratiopeptidase
• N412D
• In-silico mutagenesis
• Electrostatic potential

Acknowledgment

We gratefully acknowledge to the Director, CSIR-Institute of Himalayan Bioresource Technology, Palampur for providing the facilities to carry out this work. The CSIR support in the form of project MLP: 0201 for bioinformatics studies is highly acknowledged. AD expresses gratitude to the Indian Council of Medical Research, New Delhi, India for providing Junior Research Fellowship. This manuscript represents CSIR-IHBT Communication No. 5136.

Consent for publication

All the authors have read and approved the manuscript in all respects for publication.

Disclosure statement

No potential conflict of interest was reported by the authors.

Authors contribution

RP conceived of and designed the study. AD and RP analyzed and interpreted the data. RP and AD critically revised it for important intellectual content.

Additional information

Funding

Council of Scientific and Industrial Research, India, Grant Number: MLP-0201. Indian Council of Medical Research, New Delhi, India, (Fellowship Award: JRF-2019 HRD-41).