Lignocellulosic biomass: a sustainable platform for the production of bio-based chemicals and polymers

The demand for petroleum dependent chemicals and materials has been increasing despite the dwindling of their fossil resources. As the dead-end of petroleum based industry has started to appear, today's modern society has to implement alternative energy and valuable chemical resources immediately. Owing to the importance of lignocellulosic biomass being the most abundant and bio-renewable biomass on earth, this critical review provides insights into the potential of lignocellulosic biomass as an alternative platform to fossil resources. In this context, over 200 value-added compounds, which can be derived from lignocellulosic biomass by various treatment methods, are presented with their references. Lignocellulosic biomass based polymers and their commercial importance are also reported mainly in the frame of these compounds. This review article aims to draw the map of lignocellulosic biomass derived chemicals and their synthetic polymers, and to reveal the scope of this map in today's modern chemical and polymer industry.

The traditional computational modeling of protein structure, dynamics, and interactions remains difficult for many protein systems. It is mostly due to the size of protein conformational spaces and required simulation time scales that are still too large to be studied in atomistic detail. Lowering the level of protein representation from all-atom to coarse-grained opens up new possibilities for studying protein systems. In this review we provide an overview of coarse-grained models focusing on their design, including choices of representation, models of energy functions, sampling of conformational space, and applications in the modeling of protein structure, dynamics, and interactions. A more detailed description is given for applications of coarse-grained models suitable for efficient combinations with all-atom simulations in multiscale modeling strategies.

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Coarse-Grained Protein Models and Their Applications

Protection of environment is of immediate concern and this can only be achieved by avoiding the use of chemicals for fuel production. Lignocellulosic waste is becoming popular as a feedstock for biofuel production. The can be converted into usable form for biofuel production by using a suitable pretreatment method. Different pretreatment methods have been used by researchers which are physical, chemical, physico-chemical, biological and combined pretreatments. Evidently chemical pretreatment is found to be more expensive as a large amount of chemicals are used for pretreating the lignocellulosic substrate. It has been shown that combined pretreatments are more effective as compared to single pretreatment and there is an extensive scope of combinations which can also be applied in future. Recent review critically discusses and compares different pretreatment methods, biomass resources, chemical composition of different agricultural biomass and the use of this biomass for bioenergy generation. Various pretreatment processes used for bio-hydrogen, bio-methane, bio-ethanol, bio-methanol bio-butanol and bio-diesel production are also discussed.

Pretreatment of lignocellulosic wastes for biofuel production: A critical review

From machine learning to deep learning: progress in machine intelligence for rational drug discovery.

Butanol is an industrial commodity and also considered to be a more promising gasoline substitute compared to ethanol. Renewed attention has been paid to solvents (acetone, butanol and ethanol) production from the renewable and inexpensive substrates, for example, lignocellulose, on account of the depletion of oil resources, increasing gasoline prices and deteriorating environment. Limited to current tools for genetic manipulation, it is difficult to develop a genetically engineered microorganism with combined ability of lignocellulose utilization and solvents production. Mixed culture of cellulolytic microorganisms and solventogenic bacteria provides a more convenient and feasible approach for ABE fermentation due to the potential for synergistic utilization of the metabolic pathways of two organisms. But few bacteria pairs succeeded in producing biobutanol of high titer or high productivity without adding butyrate. The aim of this work was to use Clostridium cellulovorans 743B to saccharify lignocellulose and produce butyric acid, instead of adding cellulase and butyric acid to the medium, so that the soluble sugars and butyric acid generated can be subsequently utilized by Clostridium beijerinckii NCIMB 8052 to produce butanol in one pot reaction. A stable artificial symbiotic system was constructed by co-culturing a celluloytic, anaerobic, butyrate-producing mesophile (C. cellulovorans 743B) and a non-celluloytic, solventogenic bacterium (C. beijerinckii NCIMB 8052) to produce solvents by consolidated bioprocessing (CBP) with alkali extracted deshelled corn cobs (AECC), a low-cost renewable feedstock, as the sole carbon source. Under optimized conditions, the co-culture degraded 68.6 g/L AECC and produced 11.8 g/L solvents (2.64 g/L acetone, 8.30 g/L butanol and 0.87 g/L ethanol) in less than 80 h. Besides, a real-time PCR assay based on the 16S rRNA gene sequence was performed to study the dynamics of the abundance of each strain during the co-culturing process, which figured out the roles of each strain at different periods in the symbiosis. Our work illustrated the great potential of artificial symbiosis in biofuel production from lignocellulosic biomass by CBP. The dynamics of the abundance of C. beijerinckii and C. cellulovorans revealed mechanisms of cooperation and competition between the two strains during the co-culture process.

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Artificial symbiosis for acetone-butanol-ethanol (ABE) fermentation from alkali extracted deshelled corn cobs by co-culture of Clostridium beijerinckii and Clostridium cellulovorans

Introduction: Quantitative structure–activity relationship (QSAR) modeling is one of the most popular computer-aided tools employed in medicinal chemistry for drug discovery and lead optimization. It is especially powerful in the absence of 3D structures of specific drug targets. QSAR methods have been shown to draw public attention since they were first introduced.Areas covered: In this review, the authors provide a brief discussion of the basic principles of QSAR, model development and model validation. They also highlight the current applications of QSAR in different fields, particularly in virtual screening, rational drug design and multi-target QSAR. Finally, in view of recent controversies, the authors detail the challenges faced by QSAR modeling and the relevant solutions. The aim of this review is to show how QSAR modeling can be applied in novel drug discovery, design and lead optimization.Expert opinion: QSAR should intentionally be used as a powerful tool for fragment-based drug design platform...

Mianbin Wu

Papers

Artificial symbiosis for acetone-butanol-ethanol (ABE) fermentation from alkali extracted deshelled corn cobs by co-culture of Clostridium beijerinckii and Clostridium cellulovorans

Quantitative structure-activity relationship: promising advances in drug discovery platforms.

Natural products from Bacillus subtilis with antimicrobial properties

Advancement of multi-target drug discoveries and promising applications in the field of Alzheimer's disease.

Efficient production of xylitol from hemicellulosic hydrolysate using engineered Escherichia coli.