In this study, a molecular docking was performed on EGFR tyrosine kinase with plant phenolic compounds kaempferol, chrysophanol and emodin; identified from Cassia tora, an edible plant employed for eye diseases traditionally. The results illustrated that all the compounds have strong binding abilities with epidermal growth factor receptor and validated the reported anticataractogenic potential of C. tora leaves. Further, the compounds also satisfied the criteria for being a drug through its structural features. Taken together, it was proposed that the compounds; kaempferol, chrysophanol and emodin might be helpful for further drug design and development and could be employed as efficient lead compounds in ophthalmic drug formulations.
PfTopoVIB PfHsp90 ATP 143.657 (96) 129.333 (81) Radicicol 76.4008 (2) 91.7911 (9) Analog 1 105.184 (8) 92.585 (4) Analog 2 133.823 (9) No docked poses Analog 3 74.1867 (2) 89.926 (12) Analog 4 87.0343 (5) 92.2888 (7) Analog 5 88.8705 (2) 101.406 (14) Analog 6 108.647 (2) No docked poses Analog 7 77.5334 (2) No docked poses Analog 8 84.9003 (2) 98.4773 (7) Analog 9 87.3219 (2) 98.7025 (11) Analog 10 92.3465 (1) 104.188 (8) Analog 11 77.623 (4) 84.8962 (20) Analog 12 68.6989 (1) 93.066 (5) Analog 13 73.1041 (3) 89.7777 (2) Analog 14 82.7546 (3) 90.8558 (5) Analog 15 88.8888 (15) 96.9247 (52) Analog 16 76.4399 (2) 90.5099 (5) Analog 17 76.4532 (1) 95.5775 (20) Analog 18 76.0733 (1) 106.118 (5) Analog 19 No docked poses 96.8303 (13) Analog 20 No docked poses 66.8629 (2) Analog 21 77.4023 (5) 96.0849 (7) Analog 22 83.9107 (5) 105.157 (13) Analog 23 76.1084 (4) 86.745 (9) Analog 24 77.7701 (6) 84.7549 (6) Analog 25 88.8888 (15) 96.9247 (52) Analog 26 92.0622 (37) 106.204 (15) Analog 27 113.034 (92) 107.629 (90) Analog 28 126.111 (81) 111.54 (89) Analog 29 146.569 (91) 107.773 (30) Analog 30 116.084 (92) 121.593 (74) Analog 31 121.53 (95) 119.932 (38) Analog 32 No docked poses No docked poses Analog 33 124.066 (87) 99.2816 (89) Analog 34 111.149 (94) 113.188 (86) Analog 35 104.421(96) 113.064 (81) Analog 36 89.2511 (26) 80.1705 (2) Analog 37 87.3713 (14) 93.9307 (22) Analog 38 100.184 (58) 86.4046 (6) Analog 39 109.044 (21) 85.967 (21) Analog 40 91.7332 (27) 92.2866 (33) Analog 41 106.414 (52) 101.088 (37) Analog 42 95.2177 (19) 96.2555 (22) Analog 43 109.439 (11) 93.4571 (13) Analog 44 108.03 (67) 79.2665 (8) Analog 45 90.5919 (40) 92.064 (63) Analog 46 103.04 (56) 97.2199 (71) Analog 47 86.6312 (10) 96.4127 (15) Analog 48 103.04 (56) 97.2199 (71) Analog 49 98.6211 (17) 92.5781 (48) Analog 50 77.7701 (6) 84.7549 (6) Analog 51 76.1084 (4) 86.745 (9) Analog 52 120.296 (60) 115.213 (16) Analog 53 115.77 (62) 104.267 (23) Analog 54 86.4992 (2) 90.9012 (23) Analog 55 No docked poses 83.4545 (11) Analog 56 81.7324 (3) 87.2365 (17) Analog 57 No docked poses 94.1162 (15) Analog 58 69.6464 (2) 89.5652 (12) Analog 59 91.3509 (3) 98.6856 (6) Analog 60 103.441 (38) 105.537 (44) Analog 61 124.531 (85) 112.673 (81) Analog 62 105.573 (95) 108.981 (67) Analog 63 No docked poses No docked poses Analog 64 105.808 (96) 111.198 (79) Analog 65 127.171 (86) 107.959 (14) Analog 66 127.312 (77) 112.49 (11) Analog 67 134.451 (91) 118.745 (88) Analog 68 80.1883 (1) 80.9545 (6) Analog 69 94.0426 (26) 97.3786 (18) Analog 70 96.43 (16) 106.191 (27) Analog 71 106.638 (11) 114.339 (36) Analog 72 71.6177 (3) 89.3496 (9) Analog 73 78.2695 (5) 89.3019 (11) Analog 74 No docked poses 97.7812 (7) Analog 75 98.4877 (42) 124.62 (70) Analog 76 128.528 (91) 113.804 (85) Analog 77 103.528 (36) 89.1453 (3) Analog 78 126.025 (40) 91.7578 (8) Analog 79 130.084 (92) 58.4248 (1) Analog 80 119.39 (93) 126.137 (9) Analog 81 71.7722 (2) 90.548 (22) Analog 82 No docked poses 89.7058 (6) Analog 83 93.4051 (5) 106.048 (15) Analog 84 117.584 (6) 82.8479 (2) Analog 85 85.9...
Peptides are increasingly used as inhibitors of various disease specific targets. Several naturally occurring and synthetically developed peptides are undergoing clinical trials. Our work explores the possibility of reusing the non-expressing DNA sequences to predict potential drugtarget specific peptides. Recently, we experimentally demonstrated the artificial synthesis of novel proteins from non-coding regions of Escherichia coli genome. In this study, a library of synthetic peptides (Synpeps) was constructed from 2500 intergenic E. coli sequences and screened against Beta-secretase 1 protein, a known drug target for Alzheimer's disease (AD). Secondary and tertiary protein structure predictions followed by proteinprotein docking studies were performed to identify the most promising enzyme inhibitors. Interacting residues and favorable binding poses of lead peptide inhibitors were studied. Though initial results are encouraging, experimental validation is required in future to develop efficient target specific inhibitors against AD.
Expression of synthetic proteins from intergenic regions of and their functional association was recently demonstrated (Dhar et al. in J Biol Eng 3:2, 2009. doi:10.1186/1754-1611-3-2). This gave birth to the question: if one can make 'user-defined' genes from non-coding genome-how big is the artificially translatable genome? (Dinger et al. in PLoS Comput Biol 4, 2008; Frith et al. in RNA Biol 3(1):40-48, 2006a; Frith et al. in PLoS Genet 2(4):e52, 2006b). To answer this question, we performed a bioinformatics study of all reported intergenic sequences, in search of novel peptides and proteins, unexpressed by nature. Overall, 2500 intergenic sequences were computationally translated into 'protein sequence equivalents' and matched against all known proteins. Sequences that did not show any resemblance were used for building a comprehensive profile in terms of their structure, function, localization, interactions, stability so on. A total of 362 protein sequences showed evidence of stable tertiary conformations encoded by the intergenic sequences of genome. Experimental studies are underway to confirm some of the key predictions. This study points to a vast untapped repository of functional molecules lying undiscovered in the non-expressed genome of various organisms.
Neurodegenerative diseases are multifactorial nervous system deteriorating conditions that concern over 30 million aging populations worldwide. The effect of protein malfunction or defective trafficking is neurodegenerative disease, such as Alzheimer disease [AD], Parkinson’s disease [PD], Huntington's and Amyotrophic lateral sclerosis disorders. Furthermore, mitochondrial dysfunction, oxidative stress / age-linked environmental factors have also been involved. Prolonged use of synthetic medications could lead to adverse side effects for these illnesses. Henceforth herbal therapy attracts much attention rather than a pharmaceutical therapy is favoured. Indeed, several research studies have identified use of medicinal plants and their components for drug production, and recently more than 100 new medicines are now being established clinically. Accumulative data shows that nutraceuticals property is critical for cognition optimisation and risk mitigation. The study explores the role of phytochemical based antioxidants in cognitive and adverse signal transduction events, with a special focus on the Mediterranean diet [MeDi] comprising bioactive compounds like - xanthophyll carotenoids and omega-3 fatty acids. These phytochemical compounds are capable of improving cognition, considering their selective brain involvement and their specifically oxidative damage and inflammation. The objective of this study is to detail the molecular mechanisms of some Ayurvedic plants signal transduction and locations of operation. It is hoped that this review further helps to examine a new therapeutic recommendations and further research in clinical trials on the use of poly-herbal Ayurvedic medicine for the treatment and prevention of dementia. It is expected to increase the ease in the usage of Ayurveda-based knowledge base combined with combined scientific and high-performance screening strategies in the drug research and development campaign, while offering new practical guidelines for neurosurgical diseases linked to age.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
334 Leonard St
Brooklyn, NY 11211
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.