Displaying publications 21 - 40 of 274 in total

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  1. Haider K, Sharma A, Yar MS, Yakkala PA, Shafi S, Kamal A
    PMID: 35084268 DOI: 10.1080/17460441.2022.2029842
    INTRODUCTION: Hyperactivated RAS signaling is reported in 13% of all human cancers, in which ~80% resulted due to KRAS mutations alone. Direct inhibition of KRAS is an important aspect in treating KRAS-related tumors. Despite the efforts of more than four decades, not many KRAS inhibitors have been successful in obtaining clinical approval, except the very recent FDA approval for sotorasib. In recent years, the understanding of structural insights and allosteric pocket identification at catalytic sites of KRAS are likely to provide an excellent opportunity for the development of much more effective clinical candidates.

    AREA COVERED: The presented review article mainly summarizes the developments of small molecule KRAS inhibitors as drug candidates and rational approaches that are being utilized for the selective targeting of KRAS signaling in the mutant cancer cells.

    EXPERT OPINION: After the initial success in targeting the mutant KRAS G12C variants, the search has been shifted to address the challenges concerning the resistance and efficacy of small molecule KRAS inhibitors. However, the contribution of other KRAS mutations at G12V, G13C, and G13D variants causing cancers is much higher than the mutations at G12C. In view of this aspect, specific attention is required to target all other mutations as well. Accordingly, for the development of KRAS targeted therapies, the design of small molecule inhibitors that can inhibit KRAS signaling and as well as target inhibition of other signaling pathways like RAS-SOS and RAS-PI3K has to be explored extensively.

  2. Ahmed S, Butterworth P, Barwick A, Sharma A, Hasan MZ, Nancarrow S
    Trials, 2022 Dec 16;23(1):1017.
    PMID: 36527100 DOI: 10.1186/s13063-022-06968-5
    BACKGROUND: Foot complications occur in conjunction with poorly controlled diabetes. Plantar forefoot ulceration contributes to partial amputation in unstable diabetics, and the risk increases with concomitant neuropathy. Reducing peak plantar forefoot pressure reduces ulcer occurrence and recurrence. Footwear and insoles are used to offload the neuropathic foot, but the success of offloading is dependent on patient adherence. This study aims to determine which design and modification features of footwear and insoles improve forefoot plantar pressure offloading and adherence in people with diabetes and neuropathy.

    METHODS: This study, involving a series of N-of-1 trials, included 21 participants who had a history of neuropathic plantar forefoot ulcers. Participants were recruited from two public hospitals and one private podiatry clinic in Sydney, New South Wales, Australia. This trial is non-randomised and unblinded. Participants will be recruited from three sites, including two high-risk foot services and a private podiatry clinic in Sydney, Australia. Mobilemat™ and F-Scan® plantar pressure mapping systems by TekScan® (Boston, USA) will be used to measure barefoot and in-shoe plantar pressures. Participants' self-reports will be used to quantify the wearing period over a certain period of between 2 and 4 weeks during the trial. Participant preference toward footwear, insole design and quality-of-life-related information will be collected and analysed. The descriptive and inferential statistical analyses will be performed using IBM SPSS Statistics (version 27). And the software NVivo (version 12) will be utilised for the qualitative data analysis.

    DISCUSSION: This is the first trial assessing footwear and insole interventions in people with diabetes by using a series of N-of-1 trials. Reporting self-declared wearing periods and participants' preferences on footwear style and aesthetics are the important approaches for this trial. Patient-centric device designs are the key to therapeutic outcomes, and this study is designed with that strategy in mind.

    TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12620000699965p. Registered on June 23, 2020.

  3. Chattaraj B, Nandi A, Das A, Sharma A, Dey YN, Kumar D, et al.
    Front Pharmacol, 2022;13:982419.
    PMID: 36744215 DOI: 10.3389/fphar.2022.982419
    The decoction of the whole plant of Enhydra fluctuans is used ethno medicinally by various tribes for the treatment of kidney stones and urinary problems. However, no scientific studies were carried out to delineate its influence on urinary stone formation and crystallisation. Hence, the present study is proposed to investigate the effect of the aqueous extract of Enhydra fluctuans extract on in vitro crystallisation of calcium oxalate. The present study also evaluated. in silico studies of the metabolites with the target proteins present in the renal calcium oxalate stone matrix. The plant material was subjected to decoction to obtain an aqueous extract. The effect of the extract on calcium oxalate crystallization was evaluated by in vitro nucleation and aggregation assays. Further, the metabolites present in E. fluctuans were mined from the existing literature and their number was found to be 35. The selected 35 metabolites of E. fluctuans were subjected to molecular docking with the 5 proteins which are known to be responsible for calcium oxalate crystal growth. Results of in vitro studies indicated that the extract (50, 100, and 200 μg/mL) and standard drug cystone (1,000 μg/mL) exhibited an inhibitory role in the nucleation process where the percentage inhibitions were 52.69, 43.47, 21.98, and 31.67 μg/mL respectively. The results of molecular docking studies revealed that 2 out of 35 metabolites i.e. Baicalein-7-O-diglucoside and 4',5,6,7-Tetrahydroxy-8-methoxy isoflavone-7-O-beta-D- galactopyranosyl-(1→3)-O-beta-D-xylopyranosyl-(1→4)- O-alpha-L-rhamnopyranoside showed modulatory effects on the four renal stone matrix-associated protein (Human CTP: Phosphoethanolamine Cytidylyltransferase (Protein Data Bank ID: 3ELB), UDP glucose: glycoprotein glucosyltransferase 2 (Gene: UGGT2) (AlphaFold) and RIMS-binding protein 3A (Gene: RIMBP3) (AlphaFold), and Ras GTPase activating-like protein (PDB: 3FAY) based on their docking scores which indicates that they may inhibit the crystallization process. Findings from this study show that Enhydra fluctuans may be effective in the prevention of the crystallization of calcium oxalate. However, further, in vivo studies as well as molecular studies are needed to be conducted to confirm and strengthen its anti-urolithiatic activity and to elucidate the possible mechanism of action involved therein.
  4. Hai T, Alshahri AH, Mohammed AS, Sharma A, Almujibah HR, Mohammed Metwally AS, et al.
    Chemosphere, 2023 Sep;334:138980.
    PMID: 37207897 DOI: 10.1016/j.chemosphere.2023.138980
    The use of renewable fuels leads to reduction in the use of fossil fuels and environmental pollutants. In this study, the design and analysis of a CCPP based on the use of syngas produced from biomass is discussed. The studied system includes a gasifier system to produce syngas, an external combustion gas turbine and a steam cycle to recover waste heat from combustion gases. Design variables include syngas temperature, syngas moisture content, CPR, TIT, HRSG operating pressure, and PPTD. The effect of design variables on performance components such as power generation, exergy efficiency and total cost rate of the system is investigated. Also, through multi-objective optimization, the optimal design of the system is done. Finally, it is observed that at the final decisioned optimal point, the produced power is 13.4 MW, the exergy efficiency is 17.2%, and the TCR is 118.8 $/h.
  5. Sharma A, Sundaram S, Malviya R, Verma S, Fuloria NK, Fuloria S, et al.
    Infect Disord Drug Targets, 2023;23(3):e190922208916.
    PMID: 36121085 DOI: 10.2174/1871526522666220919105643
    The perspective of the people of Sub-Saharan Africa (SSA) toward both traditional and western healthcare systems varies. The goal of the current study is to examine the SSA's unique skin disease health care system. This study comprises numerous research that sought to examine how the general public feels about the SSA's current healthcare system. In this review, common skin conditions, such as atopic dermatitis, buruli ulcers, dermatophytosis, and scabies, are addressed. According to this report, government agencies must pay particular attention to skin illnesses in SSA and raise public awareness. Availability of medical care, socioeconomic factors, degree of education, and other factors influence patients' attitudes toward traditional and western health care differently in different geographic areas. Facts suggest that self-medication is the preference of the majority of patients before seeking dermatological care. The present study concludes that the magnitude of skin diseases is neglected or underestimated in many regions of SSA. Also, western healthcare facilities of many regions of SSA are not up to the mark. The present study recommends that proper access to the health care system and awareness about skin diseases through various government programs can be helpful in the regulation of skin disorders among people of SSA.
  6. Sharma A, Sharma A, Averbukh M, Jately V, Rajput S, Azzopardi B, et al.
    Sci Rep, 2023 Jul 10;13(1):11134.
    PMID: 37429876 DOI: 10.1038/s41598-023-37824-4
    One of the greatest challenges for widespread utilization of solar energy is the low conversion efficiency, motivating the needs of developing more innovative approaches to improve the design of solar energy conversion equipment. Solar cell is the fundamental component of a photovoltaic (PV) system. Solar cell's precise modelling and estimation of its parameters are of paramount importance for the simulation, design, and control of PV system to achieve optimal performances. It is nontrivial to estimate the unknown parameters of solar cell due to the nonlinearity and multimodality of search space. Conventional optimization methods tend to suffer from numerous drawbacks such as a tendency to be trapped in some local optima when solving this challenging problem. This paper aims to investigate the performance of eight state-of-the-art metaheuristic algorithms (MAs) to solve the solar cell parameter estimation problem on four case studies constituting of four different types of PV systems: R.T.C. France solar cell, LSM20 PV module, Solarex MSX-60 PV module, and SS2018P PV module. These four cell/modules are built using different technologies. The simulation results clearly indicate that the Coot-Bird Optimization technique obtains the minimum RMSE values of 1.0264E-05 and 1.8694E-03 for the R.T.C. France solar cell and the LSM20 PV module, respectively, while the wild horse optimizer outperforms in the case of the Solarex MSX-60 and SS2018 PV modules and gives the lowest value of RMSE as 2.6961E-03 and 4.7571E-05, respectively. Furthermore, the performances of all eight selected MAs are assessed by employing two non-parametric tests known as Friedman ranking and Wilcoxon rank-sum test. A full description is also provided, enabling the readers to understand the capability of each selected MA in improving the solar cell modelling that can enhance its energy conversion efficiency. Referring to the results obtained, some thoughts and suggestions for further improvements are provided in the conclusion section.
  7. Sharma V, Singh A, Chauhan S, Sharma PK, Chaudhary S, Sharma A, et al.
    Curr Drug Deliv, 2023 Sep 05.
    PMID: 37670704 DOI: 10.2174/1567201821666230905090621
    Drug discovery and development (DDD) is a highly complex process that necessitates precise monitoring and extensive data analysis at each stage. Furthermore, the DDD process is both time-consuming and costly. To tackle these concerns, artificial intelligence (AI) technology can be used, which facilitates rapid and precise analysis of extensive datasets within a limited timeframe. The pathophysiology of cancer disease is complicated and requires extensive research for novel drug discovery and development. The first stage in the process of drug discovery and development involves identifying targets. Cell structure and molecular functioning are complex due to the vast number of molecules that function constantly, performing various roles. Furthermore, scientists are continually discovering novel cellular mechanisms and molecules, expanding the range of potential targets. Accurately identifying the correct target is a crucial step in the preparation of a treatment strategy. Various forms of AI, such as machine learning, neural-based learning, deep learning, and network-based learning, are currently being utilised in applications, online services, and databases. These technologies facilitate the identification and validation of targets, ultimately contributing to the success of projects. This review focuses on the different types and subcategories of AI databases utilised in the field of drug discovery and target identification for cancer.
  8. Sharma A, Adhikari R, Parajuli E, Buda M, Raut J, Gautam E, et al.
    PLoS One, 2023;18(11):e0267784.
    PMID: 37939081 DOI: 10.1371/journal.pone.0267784
    BACKGROUND: One of the important aftereffects of rapid global development is international mobility, which has placed the health of migrant workers as a key public health issue. A less-developed country, Nepal, with political instability and a significant lack of employment, could not remain untouched by this phenomenon of migration. Our goal was to identify and determine the predictors of anxiety, depression, and psychological wellbeing among Nepalese migrant workers in Gulf countries (United Arab Emirates, Saudi Arabia, Qatar, Oman, Kuwait, Bahrain) and Malaysia.

    METHODS: A descriptive cross-sectional study was used to collect information from 502 Nepalese migrant workers in the arrival section of Tribhuvan International Airport from May to June 2019 using purposive sampling. Workers with a minimum work experience of 6 months and above were included in the study. A structured questionnaire with socio-demographic items was used along with the Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI) and WHO (five) wellbeing scale for measuring the subjective psychological wellbeing and screening for depression.

    RESULTS: The mean age of the respondents was 32.97 years. Majority (41.8%) of the respondents had work experience in Qatar and 63.7% had work experience of 1-5 years. The results suggested that 14.4% had mild to severe depression while 4.4% had a moderate level of anxiety. The WHO5 wellbeing index score suggested that 14.1% of the respondents had a score below 13, which is suggestive of poor psychological wellbeing. Further, the country of work (p = 0.043), sleeping hours (p = 0.001), occupation (p = 0.044), working hours (p = 0.000), water intake (p = 0.010) and anxiety level (p = 0.000) were found to be significantly associated with depression score. Similarly, sleeping hours (p = 0.022), occupation (p = 0.016), working hours (p = 0.000), water intake (p = 0.010), and anxiety level (0.000) were significantly associated with the WHO5 wellbeing score.

    CONCLUSIONS: Nepalese migrant workers in the Gulf countries (United Arab Emirates, Saudi Arabia, Qatar, Oman, Kuwait, Bahrain) and Malaysia bear an important burden of psychological morbidities. This highlights the need to prioritize the migrant worker's mental health by Nepal as well as Gulf countries and Malaysia.

  9. Sharma A, Batra J, Stuchlik O, Reed MS, Pohl J, Chow VTK, et al.
    Front Microbiol, 2020;11:581867.
    PMID: 33101257 DOI: 10.3389/fmicb.2020.581867
    Influenza A virus (IAV) poses a major threat to global public health and is known to employ various strategies to usurp the host machinery for survival. Due to its fast-evolving nature, IAVs tend to escape the effect of available drugs and vaccines thus, prompting the development of novel antiviral strategies. High-throughput mass spectrometric screen of host-IAV interacting partners revealed host Filamin A (FLNA), an actin-binding protein involved in regulating multiple signaling pathways, as an interaction partner of IAV nucleoprotein (NP). In this study, we found that the IAV NP interrupts host FLNA-TRAF2 interaction by interacting with FLNA thus, resulting in increased levels of free, displaced TRAF2 molecules available for TRAF2-ASK1 mediated JNK pathway activation, a pathway critical to maintaining efficient viral replication. In addition, siRNA-mediated FLNA silencing was found to promote IAV replication (87% increase) while FLNA-overexpression impaired IAV replication (65% decrease). IAV NP was observed to be a crucial viral factor required to attain FLNA mRNA and protein attenuation post-IAV infection for efficient viral replication. Our results reveal FLNA to be a host factor with antiviral potential hitherto unknown to be involved in the IAV replication cycle thus, opening new possibilities of FLNA-NP interaction as a candidate anti-influenza drug development target.
  10. Chindera K, Mahato M, Kumar Sharma A, Horsley H, Kloc-Muniak K, Kamaruzzaman NF, et al.
    Sci Rep, 2016;6:23121.
    PMID: 26996206 DOI: 10.1038/srep23121
    To combat infection and antimicrobial resistance, it is helpful to elucidate drug mechanism(s) of action. Here we examined how the widely used antimicrobial polyhexamethylene biguanide (PHMB) kills bacteria selectively over host cells. Contrary to the accepted model of microbial membrane disruption by PHMB, we observed cell entry into a range of bacterial species, and treated bacteria displayed cell division arrest and chromosome condensation, suggesting DNA binding as an alternative antimicrobial mechanism. A DNA-level mechanism was confirmed by observations that PHMB formed nanoparticles when mixed with isolated bacterial chromosomal DNA and its effects on growth were suppressed by pairwise combination with the DNA binding ligand Hoechst 33258. PHMB also entered mammalian cells, but was trapped within endosomes and excluded from nuclei. Therefore, PHMB displays differential access to bacterial and mammalian cellular DNA and selectively binds and condenses bacterial chromosomes. Because acquired resistance to PHMB has not been reported, selective chromosome condensation provides an unanticipated paradigm for antimicrobial action that may not succumb to resistance.
  11. Sharma A, Kamble SH, León F, Chear NJ, King TI, Berthold EC, et al.
    Drug Test Anal, 2019 Aug;11(8):1162-1171.
    PMID: 30997725 DOI: 10.1002/dta.2604
    Kratom (Mitragyna speciosa) is a psychoactive plant popular in the United States for the self-treatment of pain and opioid addiction. For standardization and quality control of raw and commercial kratom products, an ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was developed and validated for the quantification of ten key alkaloids, namely: corynantheidine, corynoxine, corynoxine B, 7-hydroxymitragynine, isocorynantheidine, mitragynine, mitraphylline, paynantheine, speciociliatine, and speciogynine. Chromatographic separation of diastereomers, or alkaloids sharing same ion transitions, was achieved on an Acquity BEH C18 column with a gradient elution using a mobile phase containing acetonitrile and aqueous ammonium acetate buffer (10mM, pH 3.5). The developed method was linear over a concentration range of 1-200 ng/mL for each alkaloid. The total analysis time per sample was 22.5 minutes. The analytical method was validated for accuracy, precision, robustness, and stability. After successful validation, the method was applied for the quantification of kratom alkaloids in alkaloid-rich fractions, ethanolic extracts, lyophilized teas, and commercial products. Mitragynine (0.7%-38.7% w/w), paynantheine (0.3%-12.8% w/w), speciociliatine (0.4%-12.3% w/w), and speciogynine (0.1%-5.3% w/w) were the major alkaloids in the analyzed kratom products/extracts. Minor kratom alkaloids (corynantheidine, corynoxine, corynoxine B, 7-hydroxymitragynine, isocorynantheidine) were also quantified (0.01%-2.8% w/w) in the analyzed products; however mitraphylline was below the lower limit of quantification in all analyses.
  12. Sharma A, Ong JW, Loke MF, Chua EG, Lee JJ, Choi HW, et al.
    Microorganisms, 2021 May 31;9(6).
    PMID: 34073047 DOI: 10.3390/microorganisms9061193
    The ongoing COVID-19 pandemic is a clear and present threat to global public health. Research into how the causative SARS-CoV-2 virus together with its individual constituent genes and proteins interact with target host cells can facilitate the development of improved strategies to manage the acute and long-term complications of COVID-19. In this study, to better understand the biological roles of critical SARS-CoV-2 proteins, we determined and compared the host transcriptomic responses of the HL-CZ human pro-monocytic cell line upon transfection with key viral genes encoding the spike S1 subunit, S2 subunit, nucleocapsid protein (NP), NSP15 (endoribonuclease), and NSP16 (2'-O-ribose-methyltransferase). RNA sequencing followed by gene set enrichment analysis and other bioinformatics tools revealed that host genes associated with topologically incorrect protein, virus receptor activity, heat shock protein binding, endoplasmic reticulum stress, antigen processing and presentation were up-regulated in the presence of viral spike S1 expression. With spike S2 expression, pro-monocytic genes associated with the interferon-gamma-mediated signaling pathway, regulation of phosphatidylinositol 3-kinase activity, adipocytokine signaling pathway, and insulin signaling pathway were down-regulated, whereas those associated with cytokine-mediated signaling were up-regulated. The expression of NSP15 induced the up-regulation of genes associated with neutrophil degranulation, neutrophil-mediated immunity, oxidative phosphorylation, prion disease, and pathways of neurodegeneration. The expression of NSP16 resulted in the down-regulation of genes associated with S-adenosylmethionine-dependent methyltransferase activity. The expression of NP down-regulated genes associated with positive regulation of neurogenesis, nervous system development, and heart development. Taken together, the complex transcriptomic alterations arising from these viral-host gene interactions offer useful insights into host genes and their pathways that potentially contribute to SARS-CoV-2 pathogenesis.
  13. Singh D, Yeou Chear NJ, Narayanan S, Leon F, Sharma A, McCurdy CR, et al.
    J Ethnopharmacol, 2020 Mar 01;249:112462.
    PMID: 31816368 DOI: 10.1016/j.jep.2019.112462
    ETHNOPHARMACOLOGICAL RELEVANCE: Kratom (Mitragyna speciosa) is a native medicinal plant of Southeast Asia widely reported to be used to reduce opioid dependence and mitigate withdrawal symptoms. There is also evidence to suggest that opioid poly-drug users were using kratom to abstain from opioids.

    AIM OF THE STUDY: To determine the patterns and reasons for kratom use among current and former opioid poly-drug users in Malaysia.

    MATERIALS AND METHODS: A total of 204 opioid poly-drug users (142 current users vs. 62 former users) with current kratom use history were enrolled into this cross-sectional study. A validated UPLC-MS/MS method was used to evaluate the alkaloid content of a kratom street sample.

    RESULTS: Results from Chi-square analysis showed that there were no significant differences in demographic characteristics between current and former opioid poly-drug users except with respect to marital status. Current users had higher odds of being single (OR: 2.2: 95%CI: 1.21-4.11; p 

  14. Kamaruzaman NH, Mohd Noor NN, Radin Mohamed RMS, Al-Gheethi A, Ponnusamy SK, Sharma A, et al.
    Environ Res, 2022 Feb 03;209:112831.
    PMID: 35123962 DOI: 10.1016/j.envres.2022.112831
    The abundance of antibiotic-resistant bacteria in the prawn pond effluents can substantially impact the natural environment. The settlement ponds, which are the most common treatment method for farms wastewater, might effectively reduce the suspended solids and organic matter. However, the method is insufficient for bacterial inactivation. The current paper seeks to highlight the environmental issue associated with the distribution of antibiotic resistant bacteria (ARB) from prawn farm wastewater and their impact on the microbial complex community in the surface water which receiving these wastes. The inactivation of antibiotic-resistant bacteria in prawn wastewater is strongly recommended because the presence of antibiotic-resistant bacteria in the environment causes water pollution and public health issues. The nanoparticles are more efficient for bacterial inactivation. They are widely accepted due to their high chemical and mechanical stability, broad spectrum of radiation absorption, high catalytic activity, and high antimicrobial activity. Many studies have examined the use of fungi or plants extract to synthesis zinc oxide nanoparticles (ZnO NPs). It is evident from recent papers in the literature that green synthesized ZnO NPs from microbes and plant extracts are non-toxic and effective. ZnO NPs inactivate the bacterial cells as a function for releasing reactive oxygen species (ROS) and zinc ions. The inactivation of antibiotic-resistant bacteria tends to be more than 90% which exhibit strong antimicrobial behavior against bacterial species.
  15. Sharma A, Singh A, Dar MA, Kaur RJ, Charan J, Iskandar K, et al.
    J Infect Public Health, 2022 Feb;15(2):172-181.
    PMID: 34972026 DOI: 10.1016/j.jiph.2021.12.008
    Antimicrobial Resistance (AMR) is significant challenge humanity faces today, with many patients losing their lives every year due to AMR. It is more widespread and has shown a higher prevalence in low- and middle-income countries (LMICs) due to lack of awareness and other associated reasons. WHO has suggested some crucial guidelines and specific strategies such as antimicrobial stewardship programs taken at the institutional level to combat AMR. Creating awareness at the grassroots level can help to reduce the AMR and promote safe and effective use of antimicrobials. Control strategies in curbing AMR also comprise hygiene and sanitation as microbes travel from contaminated surroundings to the human body surface. As resistance to multiple drugs increases, vaccines can play a significant role in curbing the menace of AMR. This article summarizes the current surveillance practices and applied control measures to tackle the hostility in these countries with particular reference to the role of antimicrobial stewardship programs and the responsibilities of regulatory authorities in managing the situation.
  16. Tsapaki V, Faruque Ghulam M, Lim ST, Ngo Minh H, Nwe N, Sharma A, et al.
    Heart Asia, 2011;3(1):16-24.
    PMID: 27325974 DOI: 10.1136/ha.2009.001180
    Increasing use of interventional procedures in cardiology with unknown levels of radiation protection in many countries of Asia-Pacific region necessitates the need for status assessment. The study was part of an International Atomic Energy Agency (IAEA) project for achieving improved radiation protection in interventional cardiology (IC) in developing countries.
  17. Dixit R, Khambhati K, Supraja KV, Singh V, Lederer F, Show PL, et al.
    Bioresour Technol, 2023 Feb;370:128522.
    PMID: 36565819 DOI: 10.1016/j.biortech.2022.128522
    Machine learning (ML) applications have become ubiquitous in all fields of research including protein science and engineering. Apart from protein structure and mutation prediction, scientists are focusing on knowledge gaps with respect to the molecular mechanisms involved in protein binding and interactions with other components in the experimental setups or the human body. Researchers are working on several wet-lab techniques and generating data for a better understanding of concepts and mechanics involved. The information like biomolecular structure, binding affinities, structure fluctuations and movements are enormous which can be handled and analyzed by ML. Therefore, this review highlights the significance of ML in understanding the biomolecular interactions while assisting in various fields of research such as drug discovery, nanomedicine, nanotoxicity and material science. Hence, the way ahead would be to force hand-in hand of laboratory work and computational techniques.
  18. Kumar R, Khan FU, Sharma A, Siddiqui MH, Aziz IB, Kamal MA, et al.
    Environ Sci Pollut Res Int, 2021 Sep;28(34):47641-47650.
    PMID: 33895950 DOI: 10.1007/s11356-021-14028-9
    We are exposed to various chemical compounds present in the environment, cosmetics, and drugs almost every day. Mutagenicity is a valuable property that plays a significant role in establishing a chemical compound's safety. Exposure and handling of mutagenic chemicals in the environment pose a high health risk; therefore, identification and screening of these chemicals are essential. Considering the time constraints and the pressure to avoid laboratory animals' use, the shift to alternative methodologies that can establish a rapid and cost-effective detection without undue over-conservation seems critical. In this regard, computational detection and identification of the mutagens in environmental samples like drugs, pesticides, dyes, reagents, wastewater, cosmetics, and other substances is vital. From the last two decades, there have been numerous efforts to develop the prediction models for mutagenicity, and by far, machine learning methods have demonstrated some noteworthy performance and reliability. However, the accuracy of such prediction models has always been one of the major concerns for the researchers working in this area. The mutagenicity prediction models were developed using deep neural network (DNN), support vector machine, k-nearest neighbor, and random forest. The developed classifiers were based on 3039 compounds and validated on 1014 compounds; each of them encoded with 1597 molecular feature vectors. DNN-based prediction model yielded highest prediction accuracy of 92.95% and 83.81% with the training and test data, respectively. The area under the receiver's operating curve and precision-recall curve values were found to be 0.894 and 0.838, respectively. The DNN-based classifier not only fits the data with better performance as compared to traditional machine learning algorithms, viz., support vector machine, k-nearest neighbor, and random forest (with and without feature reduction) but also yields better performance metrics. In current work, we propose a DNN-based model to predict mutagenicity of compounds.
  19. Wee MXJ, Chin BLF, Saptoro A, Yiin CL, Chew JJ, Sunarso J, et al.
    Front Chem Sci Eng, 2023 May 29.
    PMID: 37359292 DOI: 10.1007/s11705-022-2230-7
    The Association of Southeast Asian Nations is blessed with agricultural resources, and with the growing population, it will continue to prosper, which follows the abundance of agricultural biomass. Lignocellulosic biomass attracted researchers' interest in extracting bio-oil from these wastes. However, the resulting bio-oil has low heating values and undesirable physical properties. Hence, co-pyrolysis with plastic or polymer wastes is adopted to improve the yield and quality of the bio-oil. Furthermore, with the spread of the novel coronavirus, the surge of single-use plastic waste such as disposable medical face mask, can potentially set back the previous plastic waste reduction measures. Therefore, studies of existing technologies and techniques are referred in exploring the potential of disposable medical face mask waste as a candidate for co-pyrolysis with biomass. Process parameters, utilisation of catalysts and technologies are key factors in improving and optimising the process to achieve commercial standard of liquid fuel. Catalytic co-pyrolysis involves a series of complex mechanisms, which cannot be explained using simple iso-conversional models. Hence, advanced conversional models are introduced, followed by the evolutionary models and predictive models, which can solve the non-linear catalytic co-pyrolysis reaction kinetics. The outlook and challenges for the topic are discussed in detail.
  20. Sharma T, Xia C, Sharma A, Raizada P, Singh P, Sharma S, et al.
    Bioengineered, 2022 Apr;13(4):10518-10539.
    PMID: 35443858 DOI: 10.1080/21655979.2022.2062526
    Enzymes of commercial importance, such as lipase, amylase, laccase, phytase, carbonic anhydrase, pectinase, maltase, glucose oxidase etc., show multifunctional features and have been extensively used in several fields including fine chemicals, environmental, pharmaceutical, cosmetics, energy, food industry, agriculture and nutraceutical etc. The deployment of biocatalyst in harsh industrial conditions has some limitations, such as poor stability. These drawbacks can be overcome by immobilizing the enzyme in order to boost the operational stability, catalytic activity along with facilitating the reuse of biocatalyst. Nowadays, functionalized polymers and composites have gained increasing attention as an innovative material for immobilizing the industrially important enzyme. The different types of polymeric materials and composites are pectin, agarose, cellulose, nanofibers, gelatin, and chitosan. The functionalization of these materials enhances the loading capacity of the enzyme by providing more functional groups to the polymeric material and hence enhancing the enzyme immobilization efficiency. However, appropriate coordination among the functionalized polymeric materials and enzymes of interest plays an important role in producing emerging biocatalysts with improved properties. The optimal coordination at a biological, physical, and chemical level is requisite to develop an industrial biocatalyst. Bio-catalysis has become vital aspect in pharmaceutical and chemical industries for synthesis of value-added chemicals. The present review describes the current advances in enzyme immobilization on functionalized polymers and composites. Furthermore, the applications of immobilized enzymes in various sectors including bioremediation, biosensor and biodiesel are also discussed.
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