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Biology subjects

Moholkar, V. S.

Publications and source records attributed to Moholkar, V. S..

3 recordsLinked to original sources

Ultrasound-Assisted Hydrolysis of Food Waste using Glucoamylase: Statistical Optimization and Mechanistic Analysis with Molecular Simulations

Food waste represents a promising and cost-effective resource for synthesizing value-added products through a fermentative pathway. Preceding fermentation, the hydrolysis of food waste into monomeric sugars is a crucial step. This study presents a comprehensive investigation of food waste hydrolysis, encompassing experimental and computational approaches, using glucoamylase (GLCM) enzyme. Initial optimization of hydrolysis parameters was conducted through the Box-Behnken design of experiments, resulting in a total reducing sugar yield (TRS) of 263.4 mg/g biomass under optimized conditions within 42 hours. Sonication of hydrolysis mixture at 35 kHz at 20% duty cycle, yielded a 4x reduction in hydrolysis time with 22% enhancement in TRS yield (320 mg/g biomass). Analysis of GLCMs secondary structure revealed sonication-induced changes through FTIR spectra deconvolution in both control and test experiments. Sonication led to a reduction in -helix content and an increase in random coil content. Molecular dynamics simulations, including molecular docking, unveiled the majority of amino acid residues associated with the GLCM binding pocket in the -helix and random coil regions. Consequently, sonication widened the binding pockets, facilitating easier transport of substrate and product. This effect translated into improved reaction kinetics in food waste hydrolysis. Research HighlightsO_LIStatistical optimization of food waste hydrolysis: TRS yield = 263.4 mg/g in 42 h C_LIO_LI4x reduction of hydrolysis time, 22% rise in TRS yield with 35 kHz sonication C_LIO_LISonication reduced -helix content & increased random coil content of glucoamylase C_LIO_LIMolecular docking simulation to deduce mechanism of ultrasound-assisted hydrolysis C_LIO_LIMD simulations reveal widening of binding pockets and enhancing catalytic efficiency C_LI

biochemistry↗

Acetone-Butanol-Ethanol (ABE) fermentation with Clostridial Co-cultures for Enhanced Biobutanol Production

This study investigates acetone-butanol-ethanol (ABE) fermentation, a process using solventogenic Clostridium species to produce acetone, butanol, and ethanol. Recent biotechnological advancements, such as omics, systems biology, and metabolic engineering, have reignited interest in butanol production, responding to the increasing gasoline costs and the demand for sustainable energy systems. This study unravels the distinct physiological attributes of C. acetobutylicum (Cac) and C. pasteurianum (Cpa), significantly impacting sustainable bioenergy technologies. Employing response surface methodology (RSM), we embarked on a comprehensive statistical optimization journey in the co-culture system, Cac MTCC 11274 and Cpa MTCC 116, enhancing biobutanol production from mixed substrates. A spectrum of process parameters was scrutinized, encompassing the ratio of Cac and Cpa inoculum, sodium concentration, and the ratio of xylose to glucose. Statistical analysis revealed salt concentrations profound influence on biomass, total alcohol, and butanol production. The culmination of these endeavors yielded highly promising outcomes: a butanol concentration of 12.1 {+/-} 0.45 g L-1 (model prediction: 11.87 g L-1), biomass of 4.15 {+/-} 0.03 (model prediction: 4.06 OD600), and ABE concentration of 23.1 {+/-} 0.55 g L-1 (model prediction: 22.45 g L-1). These results represent a significant leap forward in bioenergy technologies, offering both practical insights and sustainable solutions for enhanced biofuel production.

microbiology↗

Computational investigations in inhibition of alcohol/aldehyde dehydrogenase in lignocellulosic hydrolysates

Second generation alcoholic biofuels synthesis from lignocellulosic biomass (LB) consists three steps viz., pre-treatment, detoxification, and fermentation. This dilute acid pre-treatment process generates several compounds like acids, aldehydes, ketones, oxides and their phenolic derivatives that are potential inhibitors of some of the crucial enzymes in the metabolic pathway of ABE fermentation. With application of hybrid quantum mechanics/ molecular mechanics (QM/MM) approach, our aim is to discern the molecular mechanism of inhibition of key AADs across solventogenic species. The objectives of present study are: (1) identification and homology modelling of key AADs; (2) validation, quality assessment and physiochemical characterization of the modelled enzymes; (3) identification, construction and optimization of chemical structure of potent microbial inhibitors in LH; and (4) applications of hybrid QM/MM simulations to profile the molecular interactions between microbial inhibitors and key AADs. Our computational investigation has revealed various important facets of inhibition of the AAD enzymes, which could guide structural biologist in designing efficient and robust enzymes. Moreover, our methodology also provides a general framework which could applied for deciphering the molecular mechanism of inhibition behaviour of other enzymes. HighlightsO_LIHomology modelling of 7 alcohol/aldehyde dehydrogenase (AAD) in solventogenic Clostridia C_LIO_LIIdentification and structural optimization of potent microbial inhibitors in lignocellulosic hydrolysates C_LIO_LIQM/MM simulations to profile the molecular interactions between 10 inhibitors and 7 AADs C_LIO_LIDiscernment of the molecular mechanism of inhibition of key alcohol/aldehyde dehydrogenase C_LIO_LIA methodological framework for deciphering the molecular mechanism of enzyme inhibition C_LI

bioinformatics↗