Quantumzyme Corp. (OTC: QTZM), a biotransformation company focused on sustainable enzyme-based solutions, announced the publication of its latest research in the Journal of Molecular Graphics & Modelling. The peer-reviewed study describes the Company’s application of a fully in silico enzyme engineering approach to support the design and evaluation of biocatalysts prior to laboratory validation.
The publication examines whether enzyme variants can be computationally optimized before experimental testing. In the study, Quantumzyme applied virtual screening and computational modeling techniques to evaluate transaminase enzyme variants used in the asymmetric synthesis of L-HPE, a chiral intermediate relevant to certain ACE inhibitor drug manufacturing processes. Rather than relying exclusively on traditional experimental iteration, the research employed large-scale virtual screening and ranking methodologies to assess enzyme–substrate interactions, catalytic alignment, and structural stability under defined simulation conditions. The approach enabled the identification of enzyme candidates for subsequent experimental consideration.
“Publishing this research in the Journal of Molecular Graphics & Modelling represents an important scientific milestone for Quantumzyme,” said Naveen Kulkarni, Chief Executive Officer of Quantumzyme Corp. “This study contributes to the growing body of evidence supporting computational enzyme engineering as a complementary tool in biocatalyst development. At Quantumzyme, we are focused on integrating computational modeling with experimental workflows. By evaluating enzyme variants virtually prior to laboratory testing, we aim to improve research efficiency and better inform downstream validation efforts. This publication reflects our continued commitment to advancing digital methodologies in enzyme engineering. While further laboratory validation and scale-up studies are required, we believe computational biocatalysis represents an important component of future sustainable pharmaceutical manufacturing strategies.”
The study underscores the expanding role of computational modeling in biocatalysis research. By supporting early-stage evaluation and hypothesis testing, in silico methodologies may help reduce experimental iteration and improve the prioritization of enzyme candidates for laboratory study. The publication does not represent regulatory approval, commercial validation, or confirmation of manufacturing readiness. Additional experimental testing, optimization, and scale-up would be required before any potential industrial application. The full paper is available at ScienceDirect.
Quantumzyme further announced that it has been informed that the Financial Industry Regulatory Authority (FINRA) has received all information necessary to complete its review of the Company’s previously announced corporate name change and corresponding trading symbol request. Based on current communications, the Company understands that FINRA’s review process is progressing and anticipates that, subject to FINRA’s final approval, the name change and new trading symbol are expected in the coming days. Regulatory processes remain outside of the Company’s control, and no assurance can be given regarding the exact timing or approval of the request. Upon effectiveness, the Company intends to issue a separate announcement confirming the official name and ticker symbol change.
Quantumzyme Corp. is a biotransformation company focused on advancing sustainable enzyme-based solutions for pharmaceutical manufacturing. Specializing in green chemistry, the Company applies quantum mechanics, molecular modeling, AI-driven simulations, and computational enzyme engineering to develop biocatalysts designed to enhance efficiency, reduce waste, and support environmentally responsible production. By integrating computational modeling with laboratory validation, Quantumzyme aims to deliver scalable, cost-effective biocatalysis solutions that improve industrial sustainability.
