cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24310794
title: Exploring bixin from <i>Bixa orellana</i> L. seeds: quantification and <i>in silico</i> insights into its anti-cancer potential

description: Bixin, the key pigment of <i>Bixa orellana</i> L., is an apo-carotenoid found in the seed arils. The present study aimed to quantitatively determine the bixin content of seeds and explore its anti-cancer activity through <i>in silico</i> studies. The bixin content from the seeds of the local genotype, TNMTP8, quantified by RP-HPLC was 4.58 mg per gram. The prediction of pharmacological activity suggested that bixin may serve as a BRAF, MMP9, TNF expression inhibitors, and TP53 expression enhancer. According to molecular docking analysis, bixin interacted with eight different skin cancer targets and had the lowest binding energy compared to the standard drug, 5-fluorouracil. The binding score between bixin and the targets ranged from −4.7 to −8.7 kcal/mol. The targets BRAF and SIRT3 interacted well with bixin, with binding energies as low as −8.3 and −8.7 kcal/mol, respectively. Hence, the dynamic behavior of these two docked complexes throughout a 500 ns trajectory run was investigated further. The Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF) values, and total contacts as a function of time recorded during scrutiny suggest that both complexes were stable. This was validated by post-molecular dynamics analysis using Molecular Mechanics Generalized Born Surface Area (MM-GBSA). Principal component analysis (PCA) was used to analyze the significant differences in motion exhibited by BRAF-Bixin and SIRT3-Bixin. The results showed that bixin is a promising source for potential treatment interventions in skin cancer therapies. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.24367748
title: Computational designing of the ligands of Protein L affinity chromatography based on molecular docking and molecular dynamics simulations

description: Protein L is a multidomain protein from <i>Peptostreptococcus magnus</i> with binding affinity to kappa light chain of human immunoglobulin (Ig) which is used for the purification of antibody fragments by affinity chromatography. The advances in protein engineering and computational biology approaches lead to the development of engineered affinity ligands with improved properties including binding affinity. In this study, molecular dynamics simulations (MDs) and Osprey software were used to design single B domains of the Protein L with higher affinity to antibody fragments. The modified B domains were then polymerized to ligand with six B domains by homology modeling methods. The results showed that single B domain mutants of MB1 (Thr865Trp) and MB2 (Thr847Met-Thr865Trp) had higher binding affinity to Fab compared to the wild single B domain. Also, MDs and molecular docking results showed that the polymerized Proteins L including the wild and mutated six B domains (6B0, 6B1, and 6B2) were stable during MDs and the two mutants of 6B1 and 6B2 showed higher binding affinity to Fab relative to the wild type. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.24420993
title: <i>In-silico</i> studies of <i>Brassica oleracea</i> active compounds and their role in thyroid peroxidase activity

description: Cabbage, a leafy vegetable that is widely consumed across the globe, holds a significant place within the Brassica family. For almost a century, its potential anti-thyroid effects have captured attention. The presence of compounds such as thiocyanate and goitrin in cabbage has been extensively investigated for their ability to impede sodium-iodide symporter and thyroid peroxidase (TPO) activities. The present study is focused on uncovering the active constituents in cabbage that could interact with TPO, while also examining their stability under cooking temperatures. Employing molecular docking and molecular dynamic simulation techniques, we quantified the binding strength of phytochemicals present in cabbage with the target. Out of the 60 compounds identified in cabbage leaves, only 18 exhibited docking scores surpassing those of the commercially available anti-thyroid drug, methimazole. These chosen compounds were studied for binding free energy and pharmacokinetic properties. A specific compound, gamma-Terpinene, classified as a monoterpene, emerged as noteworthy due to its alignment with all criteria and the highest observed binding free energy compared to others. Furthermore, we explored the stability of gamma-Terpinene at 373.15K (cooking temperature) and observed its susceptibility to degradation. This might contribute to the relatively diminished anti-thyroid effects of cabbage when consumed in cooked form. Consequently, our findings suggest that the consumption of cooked cabbage could be more conducive to maintaining normal thyroid function, as opposed to its raw counterpart. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.24420993.v1
title: <i>In-silico</i> studies of <i>Brassica oleracea</i> active compounds and their role in thyroid peroxidase activity

description: Cabbage, a leafy vegetable that is widely consumed across the globe, holds a significant place within the Brassica family. For almost a century, its potential anti-thyroid effects have captured attention. The presence of compounds such as thiocyanate and goitrin in cabbage has been extensively investigated for their ability to impede sodium-iodide symporter and thyroid peroxidase (TPO) activities. The present study is focused on uncovering the active constituents in cabbage that could interact with TPO, while also examining their stability under cooking temperatures. Employing molecular docking and molecular dynamic simulation techniques, we quantified the binding strength of phytochemicals present in cabbage with the target. Out of the 60 compounds identified in cabbage leaves, only 18 exhibited docking scores surpassing those of the commercially available anti-thyroid drug, methimazole. These chosen compounds were studied for binding free energy and pharmacokinetic properties. A specific compound, gamma-Terpinene, classified as a monoterpene, emerged as noteworthy due to its alignment with all criteria and the highest observed binding free energy compared to others. Furthermore, we explored the stability of gamma-Terpinene at 373.15K (cooking temperature) and observed its susceptibility to degradation. This might contribute to the relatively diminished anti-thyroid effects of cabbage when consumed in cooked form. Consequently, our findings suggest that the consumption of cooked cabbage could be more conducive to maintaining normal thyroid function, as opposed to its raw counterpart. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.24310796
title: Silibinin: an inhibitor for a high-expressed BCL-2A1/BFL1 protein, linked with poor prognosis in breast cancer

description: Breast cancer (BC) accounts for 30% of all diagnosed cases of cancer in women and remains a leading cause of cancer-related deaths among women worldwide. The current study looks for a protein from the anti-apoptotic/pro-survival BCL-2 family whose overexpression reduces survivability in BC patients and a potential inhibitor for the protein. We found BCL-2A1/BFL1 protein with high expression linked to low survivability in BC. The protein shows prognosis in 8 out of 29 categories, whereas no other family member manifests this property. Out of 7379 compounds, three small molecules (CHEMBL9509, CHEMBL2104550 and CHEMBL3545011) form an H-bond with BCL-2A1/BFL1 protein’s unique residue Cys55. Of the three small molecules, we found CHEMBL9509 (Silibinin) to be a potent inhibitor. The compound forms a stable H-bond with the residue Cys55 with the lowest binding energy compared to the other two compounds. It remains stable in the BH3 binding region for more than 100 ns, whereas the other two detach from the region. Additionally, the compound is found to be better than Venetoclax and Nematoclax. We firmly believe in the compound CHEMBL9509 potency to halt BC's progression by inhibiting the BCL-2A1/BFL1 protein, increasing patients’ survivability. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.24310796.v1
title: Silibinin: an inhibitor for a high-expressed BCL-2A1/BFL1 protein, linked with poor prognosis in breast cancer

description: Breast cancer (BC) accounts for 30% of all diagnosed cases of cancer in women and remains a leading cause of cancer-related deaths among women worldwide. The current study looks for a protein from the anti-apoptotic/pro-survival BCL-2 family whose overexpression reduces survivability in BC patients and a potential inhibitor for the protein. We found BCL-2A1/BFL1 protein with high expression linked to low survivability in BC. The protein shows prognosis in 8 out of 29 categories, whereas no other family member manifests this property. Out of 7379 compounds, three small molecules (CHEMBL9509, CHEMBL2104550 and CHEMBL3545011) form an H-bond with BCL-2A1/BFL1 protein’s unique residue Cys55. Of the three small molecules, we found CHEMBL9509 (Silibinin) to be a potent inhibitor. The compound forms a stable H-bond with the residue Cys55 with the lowest binding energy compared to the other two compounds. It remains stable in the BH3 binding region for more than 100 ns, whereas the other two detach from the region. Additionally, the compound is found to be better than Venetoclax and Nematoclax. We firmly believe in the compound CHEMBL9509 potency to halt BC's progression by inhibiting the BCL-2A1/BFL1 protein, increasing patients’ survivability. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.24310790
title: Free energy landscape and thermodynamics properties of novel mutations in PncA of pyrazinamide resistance isolates of <i>Mycobacterium tuberculosis</i>

description: Pyrazinamide (PZA) is one of the first-line antituberculosis therapy, active against non-replicating <i>Mycobacterium tuberculosis</i> (Mtb). The conversion of PZA into pyrazinoic acid (POA), the active form, required the activity of <i>pncA</i> gene product pyrazinamidase (PZase) activity. Mutations occurred in <i>pncA</i> are the primary cause behind the PZA resistance. However, the resistance mechanism is important to explore using high throughput computational approaches. Here we aimed to explore the mechanism of PZA resistance behind novel P62T, L120R, and V130M mutations in PZase using 200 ns molecular dynamics (MD) simulations. MD simulations were performed to observe the structural changes for these three mutants (MTs) compared to the wild types (WT). Root means square fluctuation, the radius of gyration, free energy landscape, root means square deviation, dynamic cross-correlation motion, and pocket volume were found in variation between WT and MTs, revealing the effects of P62T, L120R, and V130M. The free energy conformational landscape of MTs differs significantly from the WT system, lowering the binding of PZA. The geometric shape complementarity of the drug (PZA) and target protein (PZase) further confirmed that P62T, L120R, and V130M affect the protein structure. These effects on PZase may cause vulnerability to convert PZA into POA. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.24310790.v1
title: Free energy landscape and thermodynamics properties of novel mutations in PncA of pyrazinamide resistance isolates of <i>Mycobacterium tuberculosis</i>

description: Pyrazinamide (PZA) is one of the first-line antituberculosis therapy, active against non-replicating <i>Mycobacterium tuberculosis</i> (Mtb). The conversion of PZA into pyrazinoic acid (POA), the active form, required the activity of <i>pncA</i> gene product pyrazinamidase (PZase) activity. Mutations occurred in <i>pncA</i> are the primary cause behind the PZA resistance. However, the resistance mechanism is important to explore using high throughput computational approaches. Here we aimed to explore the mechanism of PZA resistance behind novel P62T, L120R, and V130M mutations in PZase using 200 ns molecular dynamics (MD) simulations. MD simulations were performed to observe the structural changes for these three mutants (MTs) compared to the wild types (WT). Root means square fluctuation, the radius of gyration, free energy landscape, root means square deviation, dynamic cross-correlation motion, and pocket volume were found in variation between WT and MTs, revealing the effects of P62T, L120R, and V130M. The free energy conformational landscape of MTs differs significantly from the WT system, lowering the binding of PZA. The geometric shape complementarity of the drug (PZA) and target protein (PZase) further confirmed that P62T, L120R, and V130M affect the protein structure. These effects on PZase may cause vulnerability to convert PZA into POA. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.24297157
title: VinaLigGen: a method to generate LigPlots and retrieval of hydrogen and hydrophobic interactions from protein-ligand complexes

description: Developments in the field of computational structural biology and with increasing computing speeds have encouraged researchers in studying large compound libraries during the virtual screening. After performing molecular docking, the consideration of vina score in filtering the compounds without collecting the hydrogen bond or hydrophobic interaction between protein and ligand complex leads to missing multiple good lead molecules. The tools used for virtual screening in drug design and discovery studies were previously designed and developed for small datasets. LigPlots were used to generate 2-dimensional (2D) interaction maps of protein-ligand complexes. These maps depict diverse bonds like hydrogen and hydrophobic interactions in varied colors for all ligand conformations within the library. However, handling large numbers of protein-ligand complexes can make this process quite laborious. The development of a tool is strongly required or an implementation of automation to generate all the interaction details has a strong demand. This paper describes an implementation of an automation technique on the executable programs like ligplot.exe, hbplus.exe and hbadd.exe to obtain the 2D interaction map (LigPlots) of the protein and ligand complex (*.ps) and hydrogen bonds and hydrophobic interactions in *.csv format for molecules to be considered for virtual screening by using some sorting & searching algorithms and python’s file handling functions, and it also mentions the program’s limitations and availability of the program. The program can be found on github. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.24297157.v1
title: VinaLigGen: a method to generate LigPlots and retrieval of hydrogen and hydrophobic interactions from protein-ligand complexes

description: Developments in the field of computational structural biology and with increasing computing speeds have encouraged researchers in studying large compound libraries during the virtual screening. After performing molecular docking, the consideration of vina score in filtering the compounds without collecting the hydrogen bond or hydrophobic interaction between protein and ligand complex leads to missing multiple good lead molecules. The tools used for virtual screening in drug design and discovery studies were previously designed and developed for small datasets. LigPlots were used to generate 2-dimensional (2D) interaction maps of protein-ligand complexes. These maps depict diverse bonds like hydrogen and hydrophobic interactions in varied colors for all ligand conformations within the library. However, handling large numbers of protein-ligand complexes can make this process quite laborious. The development of a tool is strongly required or an implementation of automation to generate all the interaction details has a strong demand. This paper describes an implementation of an automation technique on the executable programs like ligplot.exe, hbplus.exe and hbadd.exe to obtain the 2D interaction map (LigPlots) of the protein and ligand complex (*.ps) and hydrogen bonds and hydrophobic interactions in *.csv format for molecules to be considered for virtual screening by using some sorting & searching algorithms and python’s file handling functions, and it also mentions the program’s limitations and availability of the program. The program can be found on github. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.24412057
title: Networkodynamic approach to perceive the key phytoconstituents of <i>E. officinalis</i> (Amla) as natural BACE1 inhibitors: an <i>in-silico</i> study

description: Alzheimer’s disease (AD) is a deteriorating neural disorder, and currently, available drugs are ineffective in its treatment. <i>Emblica officinalis</i> (Amla) is widely recognised in the Indian medicinal system for ameliorative effects in managing diabetes, hyperlipidaemia and neurological diseases. Thus, we aimed to identify the active phytoconstituents of <i>E. officinalis</i> and their role in inhibiting the potential targets for the possible treatment of AD. The network pharmacology approach, gene ontology, molecular docking and molecular dynamics simulation (MDS) studies were performed. A total of 36 bioactive components in <i>E. officinalis</i>, 95 predicted anti-AD targets, and 3398 AD-related targets were identified from different databases. The network analysis showed that BACE1, ABCB1 and AChE, CA2 are the most potential AD targets. Based on gene ontology and topology analysis results, BACE1 was a significant target related to AD pathways, and quercetin, kaempferol and myricetin showed the highest interaction with target genes. The molecular docking results found that rutin and quercetin displayed better binding affinities −7.5, −5.67 kcal/mol than the BACE1 bound internal ligand. Furthermore, MDS results suggested that quercetin and rutin could be potential inhibitors against BACE-1 protein and may have therapeutic effects in treating AD. Such promising results could be further helpful in new drug discovery against AD. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.24412057.v1
title: Networkodynamic approach to perceive the key phytoconstituents of <i>E. officinalis</i> (Amla) as natural BACE1 inhibitors: an <i>in-silico</i> study

description: Alzheimer’s disease (AD) is a deteriorating neural disorder, and currently, available drugs are ineffective in its treatment. <i>Emblica officinalis</i> (Amla) is widely recognised in the Indian medicinal system for ameliorative effects in managing diabetes, hyperlipidaemia and neurological diseases. Thus, we aimed to identify the active phytoconstituents of <i>E. officinalis</i> and their role in inhibiting the potential targets for the possible treatment of AD. The network pharmacology approach, gene ontology, molecular docking and molecular dynamics simulation (MDS) studies were performed. A total of 36 bioactive components in <i>E. officinalis</i>, 95 predicted anti-AD targets, and 3398 AD-related targets were identified from different databases. The network analysis showed that BACE1, ABCB1 and AChE, CA2 are the most potential AD targets. Based on gene ontology and topology analysis results, BACE1 was a significant target related to AD pathways, and quercetin, kaempferol and myricetin showed the highest interaction with target genes. The molecular docking results found that rutin and quercetin displayed better binding affinities −7.5, −5.67 kcal/mol than the BACE1 bound internal ligand. Furthermore, MDS results suggested that quercetin and rutin could be potential inhibitors against BACE-1 protein and may have therapeutic effects in treating AD. Such promising results could be further helpful in new drug discovery against AD. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.27879571
title: A new multi-epitope vaccine candidate based on S and M proteins is effective in inducing humoral and cellular immune responses against SARS-CoV-2 variants: an <i>in silico</i> design approach

description: Available COVID-19 vaccines are primarily based on SARS-CoV-2 spike protein (S). Due to the emergence of new SARS-CoV-2 variants, other virus proteins with more conservancy, such as Membrane (M) protein, are desired for vaccine development. The reverse vaccinology approach was employed to design a multi-epitope SARS-CoV-2 vaccine candidate based on S and M proteins. Cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), linear B-lymphocyte (LBL) and conformational B-lymphocyte (CBL) of S and M proteins were predicted and screened to choose the best epitopes. A multi-epitope vaccine candidate was constructed using selected CTL, HTL and LBL epitopes. The efficiency of the construct in binding to some immune receptors and an RBD-potent neutralizing monoclonal antibody (bebtelovimab) was predicted, and its immunogenicity was simulated. Finally, <i>in silico</i> cloning of the constructed gene was performed. The potency of our construct as a SARS-CoV-2 vaccine was validated using several bioinformatics tools. The simulation results showed that the construct can induce both cellular and humoral immune responses by producing appropriate cytokines, and it can even create an excellent immune memory response. Furthermore, the designed construct interacts with innate immune receptors such as TLR2 and TLR4 and the terminal variable domain of bebtelovimab with high affinity. We developed a multi-epitope construct based on the S and M proteins of the SARS-CoV-2 virus with high immunogenicity potential using the most up-to-date immunoinformatics and computational biology approaches. The actual efficiency of this multi-epitope vaccine should be further evaluated <i>via in vitro</i> and <i>in vivo</i> studies. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.27879571.v1
title: A new multi-epitope vaccine candidate based on S and M proteins is effective in inducing humoral and cellular immune responses against SARS-CoV-2 variants: an <i>in silico</i> design approach

description: Available COVID-19 vaccines are primarily based on SARS-CoV-2 spike protein (S). Due to the emergence of new SARS-CoV-2 variants, other virus proteins with more conservancy, such as Membrane (M) protein, are desired for vaccine development. The reverse vaccinology approach was employed to design a multi-epitope SARS-CoV-2 vaccine candidate based on S and M proteins. Cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), linear B-lymphocyte (LBL) and conformational B-lymphocyte (CBL) of S and M proteins were predicted and screened to choose the best epitopes. A multi-epitope vaccine candidate was constructed using selected CTL, HTL and LBL epitopes. The efficiency of the construct in binding to some immune receptors and an RBD-potent neutralizing monoclonal antibody (bebtelovimab) was predicted, and its immunogenicity was simulated. Finally, <i>in silico</i> cloning of the constructed gene was performed. The potency of our construct as a SARS-CoV-2 vaccine was validated using several bioinformatics tools. The simulation results showed that the construct can induce both cellular and humoral immune responses by producing appropriate cytokines, and it can even create an excellent immune memory response. Furthermore, the designed construct interacts with innate immune receptors such as TLR2 and TLR4 and the terminal variable domain of bebtelovimab with high affinity. We developed a multi-epitope construct based on the S and M proteins of the SARS-CoV-2 virus with high immunogenicity potential using the most up-to-date immunoinformatics and computational biology approaches. The actual efficiency of this multi-epitope vaccine should be further evaluated <i>via in vitro</i> and <i>in vivo</i> studies. Communicated by Ramaswamy H. Sarma