Evidence map›Paper›PMID 41923293›Full record

ArticleChemistryOpen2026

Computer-Based Design to Improve Bacillus thuringiensis Chitinase for Industrial Applications.

S G Sree Agash, G Chandrasekhar, A S Vinutha, S Akshay, P Kanishk, R Rajasekaran

Abstract read
In one paragraph

Article in ChemistryOpen, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

S G Sree AgashQuantitative Biology Lab, Department of Integrative Biology, School of Bio Sciences and Technology, Vellore Institute of Technology (VIT Deemed to be University), Vellore, India.
G ChandrasekharQuantitative Biology Lab, Department of Integrative Biology, School of Bio Sciences and Technology, Vellore Institute of Technology (VIT Deemed to be University), Vellore, India.
A S VinuthaQuantitative Biology Lab, Department of Integrative Biology, School of Bio Sciences and Technology, Vellore Institute of Technology (VIT Deemed to be University), Vellore, India.
S AkshayQuantitative Biology Lab, Department of Integrative Biology, School of Bio Sciences and Technology, Vellore Institute of Technology (VIT Deemed to be University), Vellore, India.
P KanishkQuantitative Biology Lab, Department of Integrative Biology, School of Bio Sciences and Technology, Vellore Institute of Technology (VIT Deemed to be University), Vellore, India.
R RajasekaranQuantitative Biology Lab, Department of Integrative Biology, School of Bio Sciences and Technology, Vellore Institute of Technology (VIT Deemed to be University), Vellore, India.ORCID 0000-0001-8734-3556

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chitin serves as a vital biopolymer across multiple industrial biotechnology sectors, and its extraction from seashell waste through enzymatic bioconversion offers an efficient and environmentally sustainable approach. Chitinase plays a key role in this process; however, strategies to enhance its catalytic performance remain limited. In this study, in silico site-directed mutagenesis was employed to improve the enzyme's activity while preserving its structural stability. Mutation sites were identified within the catalytic domain based on high mutability scores and functional relevance. Six hotspot mutations V215A, V215F, S262G, R264H, F288L, and G291A were selected for further evaluation. Interaction analyses revealed that the beneficial mutants demonstrated stronger substrate affinity compared to the native enzyme. Furthermore, molecular orbital analysis indicated that substrate binding to these mutants, particularly the G291A variant, exhibited enhanced nucleophilic and electrophilic characteristics. Notably, the G291A mutant showed reduced activation energy of 49.53 kcal/mol, in contrast to 97 kcal/mol for the native enzyme, signifying improved catalytic efficiency. Overall, this study highlights the potential of computationally guided site-directed mutagenesis as a rational approach for optimizing chitinase activity and advancing enzyme engineering for bioconversion applications.

Indexed as

Bacillus thuringiensisChitinasesComputer-Aided DesignCatalytic DomainModels, MolecularMutagenesis, Site-DirectedProtein EngineeringChitinaseschitinchitinasenucleophilicityreaction coordinatessite‐directed mutagenesis

Identifiers

PMID41923293
PMCPMC13045421

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.