Displaying publications 1 - 20 of 33 in total

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  1. Lu SJ, Salleh AH, Mohamad MS, Deris S, Omatu S, Yoshioka M
    Comput Biol Chem, 2014 12;53PB:175-183.
    PMID: 25462325 DOI: 10.1016/j.compbiolchem.2014.09.008
    Reconstructions of genome-scale metabolic networks from different organisms have become popular in recent years. Metabolic engineering can simulate the reconstruction process to obtain desirable phenotypes. In previous studies, optimization algorithms have been implemented to identify the near-optimal sets of knockout genes for improving metabolite production. However, previous works contained premature convergence and the stop criteria were not clear for each case. Therefore, this study proposes an algorithm that is a hybrid of the ant colony optimization algorithm and flux balance analysis (ACOFBA) to predict near optimal sets of gene knockouts in an effort to maximize growth rates and the production of certain metabolites. Here, we present a case study that uses Baker's yeast, also known as Saccharomyces cerevisiae, as the model organism and target the rate of vanillin production for optimization. The results of this study are the growth rate of the model organism after gene deletion and a list of knockout genes. The ACOFBA algorithm was found to improve the yield of vanillin in terms of growth rate and production compared with the previous algorithms.
  2. Ang SS, Salleh AB, Chor AL, Normi YM, Tejo BA, Rahman MB
    Comput Biol Chem, 2015 Jun;56:19-29.
    PMID: 25766878 DOI: 10.1016/j.compbiolchem.2015.02.015
    Cytochrome P450s are a superfamily of heme monooxygenases which catalyze a wide range of biochemical reactions. The reactions involve the introduction of an oxygen atom into an inactivated carbon of a compound which is essential to produce an intermediate of a hydroxylated product. The diversity of chemical reactions catalyzed by cytochrome P450s has led to their increased demand in numerous industrial and biotechnology applications. A recent study showed that a gene sequence encoding a CYP was found in the genome of Bacillus lehensis G1, and this gene shared structural similarity with the bacterial vitamin D hydroxylase (Vdh) from Pseudonocardia autotrophica. The objectives of present study was to mine, for a novel CYP from a new isolate B. lehensis G1 alkaliphile and determine the biological properties and functionalities of CYP in this bacterium. Our study employed the usage of computational methods to search for the novel CYP from CYP structural databases to identify the conserved pattern, functional domain and sequence properties of the uncharacterized CYP from B. lehensis G1. A computational homology model of the protein's structure was generated and a docking analysis was performed to provide useful structural knowledge on the enzyme's possible substrate and their interaction. Sequence analysis indicated that the newly identified CYP, termed CYP107CB2, contained the fingerprint heme binding sequence motif FxxGxxxCxG at position 336-345 as well as other highly conserved motifs characteristic of cytochrome P450 proteins. Using docking studies, we identified Ser-79, Leu-81, Val-231, Val-279, Val-383, Ala-232, Thr-236 and Thr-283 as important active site residues capable of stabilizing interactions with several potential substrates, including vitamin D3, 25-hydroxyvitamin D3 and 1α-hydroxyvitamin D3, in which all substrates docked proximally to the enzyme's heme center. Biochemical analysis indicated that CYP107CB2 is a biologically active protein to produce 1α,25-dihydroxyvitamin D3 from 1α-hydroxyvitamin D3. Based on these results, we conclude that the novel CYP107CB2 identified from B. lehensis G1 is a putative vitamin D hydroxylase which is possibly capable of catalyzing the bioconversion of parental vitamin D3 to calcitriol, or related metabolic products.
  3. Mienda BS, Shamsir MS, Illias RM
    Comput Biol Chem, 2016 Apr;61:130-7.
    PMID: 26878126 DOI: 10.1016/j.compbiolchem.2016.01.013
    The metabolic role of 6-phosphogluconate dehydrogenase (gnd) under anaerobic conditions with respect to succinate production in Escherichia coli remained largely unspecified. Herein we report what are to our knowledge the first metabolic gene knockout of gnd to have increased succinic acid production using both glucose and glycerol substrates in E. coli. Guided by a genome scale metabolic model, we engineered the E. coli host metabolism to enhance anaerobic production of succinic acid by deleting the gnd gene, considering its location in the boundary of oxidative and non-oxidative pentose phosphate pathway. This strategy induced either the activation of malic enzyme, causing up-regulation of phosphoenolpyruvate carboxylase (ppc) and down regulation of phosphoenolpyruvate carboxykinase (ppck) and/or prevents the decarboxylation of 6 phosphogluconate to increase the pool of glyceraldehyde-3-phosphate (GAP) that is required for the formation of phosphoenolpyruvate (PEP). This approach produced a mutant strain BMS2 with succinic acid production titers of 0.35gl(-1) and 1.40gl(-1) from glucose and glycerol substrates respectively. This work further clearly elucidates and informs other studies that the gnd gene, is a novel deletion target for increasing succinate production in E. coli under anaerobic condition using glucose and glycerol carbon sources. The knowledge gained in this study would help in E. coli and other microbial strains development for increasing succinate production and/or other industrial chemicals.
  4. Mohamed Salleh FH, Arif SM, Zainudin S, Firdaus-Raih M
    Comput Biol Chem, 2015 Dec;59 Pt B:3-14.
    PMID: 26278974 DOI: 10.1016/j.compbiolchem.2015.04.012
    A gene regulatory network (GRN) is a large and complex network consisting of interacting elements that, over time, affect each other's state. The dynamics of complex gene regulatory processes are difficult to understand using intuitive approaches alone. To overcome this problem, we propose an algorithm for inferring the regulatory interactions from knock-out data using a Gaussian model combines with Pearson Correlation Coefficient (PCC). There are several problems relating to GRN construction that have been outlined in this paper. We demonstrated the ability of our proposed method to (1) predict the presence of regulatory interactions between genes, (2) their directionality and (3) their states (activation or suppression). The algorithm was applied to network sizes of 10 and 50 genes from DREAM3 datasets and network sizes of 10 from DREAM4 datasets. The predicted networks were evaluated based on AUROC and AUPR. We discovered that high false positive values were generated by our GRN prediction methods because the indirect regulations have been wrongly predicted as true relationships. We achieved satisfactory results as the majority of sub-networks achieved AUROC values above 0.5.
  5. Mirza MU, Ahmad S, Abdullah I, Froeyen M
    Comput Biol Chem, 2020 Dec;89:107376.
    PMID: 32979815 DOI: 10.1016/j.compbiolchem.2020.107376
    Human ubiquitin carboxyl-terminal hydrolase-2 (USP2) inhibitors, such as thiopurine analogs, have been reported to inhibit SARS-CoV papain-like proteases (PLpro). The PLpro have significant functional implications in the innate immune response during SARS-CoV-2 infection and considered an important antiviral target. Both proteases share strikingly similar USP fold with right-handed thumb-palm-fingers structural scaffold and conserved catalytic triad Cys-His-Asp/Asn. In this urgency situation of COVID-19 outbreak, there is a lack of in-vitro facilities readily available to test SARS-CoV-2 inhibitors in whole-cell assays. Therefore, we adopted an alternate route to identify potential USP2 inhibitor through integrated in-silico efforts. After an extensive virtual screening protocol, the best compounds were selected and tested. The compound Z93 showed significant IC50 value against Jurkat (9.67 μM) and MOTL-4 cells (11.8 μM). The binding mode of Z93 was extensively analyzed through molecular docking, followed by MD simulations, and molecular interactions were compared with SARS-CoV-2. The relative binding poses of Z93 fitted well in the binding site of both proteases and showed consensus π-π stacking and H-bond interactions with histidine and aspartate/asparagine residues of the catalytic triad. These results led us to speculate that compound Z93 might be the first potential chemical lead against SARS-CoV-2 PLpro, which warrants in-vitro evaluations.
  6. Wei LK, Quan LS
    Comput Biol Chem, 2019 Dec;83:107116.
    PMID: 31561071 DOI: 10.1016/j.compbiolchem.2019.107116
    According to the Trial of Org 10172 in Acute Stroke Treatment, ischemic stroke is classified into five subtypes. However, the predictive biomarkers of ischemic stroke subtypes are still largely unknown. The utmost objective of this study is to map, construct and analyze protein-protein interaction (PPI) networks for all subtypes of ischemic stroke, and to suggest the predominant biological pathways for each subtypes. Through 6285 protein data retrieved from PolySearch2 and STRING database, the first PPI networks for all subtypes of ischemic stroke were constructed. Notably, F2 and PLG were identified as the critical proteins for large artery atherosclerosis (LAA), lacunar, cardioembolic, stroke of other determined etiology (SOE) and stroke of undetermined etiology (SUE). Gene ontology and DAVID analysis revealed that GO:0030193 regulation of blood coagulation and GO:0051917 regulation of fibrinolysis were the important functional clusters for all the subtypes. In addition, inflammatory pathway was the key etiology for LAA and lacunar, while FOS and JAK2/STAT3 signaling pathways might contribute to cardioembolic stroke. Due to many risk factors associated with SOE and SUE, the precise etiology for these two subtypes remained to be concluded.
  7. Anwar F, Saleem U, Ahmad B, Ashraf M, Rehman AU, Froeyen M, et al.
    Comput Biol Chem, 2020 Dec;89:107378.
    PMID: 33002716 DOI: 10.1016/j.compbiolchem.2020.107378
    Neurodegenerative diseases have complex etiology and pose a challenge to scientists to develop simple and cost-effective synthetic compounds as potential drug candidates for such diseases. Here, we report an extension of our previously published in silico screening, where we selected four new compounds as AChE inhibitors. Further, based on favorable binding possess, MD simulation and MMGBSA, two most promising compounds (3a and 3b) were selected, keeping in view the ease of synthesis and cost-effectiveness. Due to the critical role of BChE, LOX and α-glucosidase in neurodegeneration, the selected compounds were also screened against these enzymes. The IC50 values of 3a against AChE and BChE found to be 12.53 and 352.42 μM, respectively. Moderate to slight inhibitions of 45.26 % and 28.68 % were presented by 3a against LOX and α-glucosidase, respectively, at 0.5 mM. Insignificant inhibitions were observed with 3b against the four selected enzymes. Further, in vivo trial demonstrated that 3a could significantly diminish AChE levels in the mice brain as compared to the control. These findings were in agreement with the histopathological analysis of the brain tissues. The results corroborate that selected compounds could serve as a potential lead for further development and optimization as AChE inhibitors to achieve cost-effective anti-Alzheimer's drugs.
  8. Lim LWK, Kamar CKA, Roja JS, Chung HH, Liao Y, Lam TT, et al.
    Comput Biol Chem, 2020 Dec;89:107403.
    PMID: 33120127 DOI: 10.1016/j.compbiolchem.2020.107403
    The Blueline Rasbora (Rasbora sarawakensis) is a small ray-finned fish categorized under the genus Rasbora in the Cyprinidae family. In this study, the complete mitogenome sequence of R. sarawakensis was sequenced using four primers targeting overlapping regions. The mitogenome is 16,709 bp in size, accommodating 22 transfer RNA genes, 13 protein-coding genes, two ribosomal RNA genes and a putative control region. Identical gene organisation was detected between this species and other genus counterparts. The heavy strand houses 28 genes while the light strand stores the other nine genes. Most protein-coding genes employ ATG as start codon, excluding COI gene, which utilizes GTG instead. The central conserved sequence blocks (CSB-F, CSB-E and CSB-D), variable sequence blocks (CSB-3, CSB-2 and CSB-1) as well as the terminal associated sequence (TAS) are conserved in the control region. The maximum likelihood phylogenetic tree revealed the divergence of R. sarawakensis from the basal region of the Rasbora clade, where its evolutionary relationships with R. maculatus and R. pauciperforata are poorly resolved as indicated by the low bootstrap values. This work acts as steppingstone towards further molecular evolution and population genetics studies of Rasbora genus in future.
  9. Lee VS, Sukumaran SD, Tan PK, Kuppusamy UR, Arumugam B
    Comput Biol Chem, 2021 Jun;92:107501.
    PMID: 33989998 DOI: 10.1016/j.compbiolchem.2021.107501
    Naturally occurring proteins are emerging as novel therapeutics in the protein-based biopharmaceutical industry for the treatment of diabetes and obesity. However, proteins are not suitable for oral delivery due to short half-life, reduced physical and chemical stability and low permeability across the membrane. Chemical modification has been identified as a formulation strategy to enhance the stability and bioavailability of protein drugs. The present study aims to study the effect of charge-specific modification of basic amino acids (Lys, Arg) and guanidination on the interaction of insulin with its receptor using molecular modelling. Our investigation revealed that the guanidination of insulin (Lys-NHC = NHNH2) enhanced and exerted stronger binding of the protein to its receptor through electrostatic interaction than native insulin (Lys-NH3+). Point mutations of Lys and Arg (R22, K29; R22K, K29; R22, K29R; R22K, K29R) were attempted and the effects on the interaction and stability between insulin/modified insulins and insulin receptor were also analyzed in this study. The findings from the study are expected to provide a better understanding of the possible mechanism of action of the modified protein at a molecular level before advancing to real experiments.
  10. Ahmad Nadzirin I, Chor ALT, Salleh AB, Rahman MBA, Tejo BA
    Comput Biol Chem, 2021 Jun;92:107487.
    PMID: 33957477 DOI: 10.1016/j.compbiolchem.2021.107487
    Rheumatoid arthritis (RA) is an inflammatory autoimmune disease affecting about 0.24 % of the world population. Protein arginine deiminase type 4 (PAD4) is believed to be responsible for the occurrence of RA by catalyzing citrullination of proteins. The citrullinated proteins act as autoantigens by stimulating an immune response. Citrullinated α-enolase has been identified as one of the autoantigens for RA. Hence, α-enolase serves as a suitable template for design of potential peptide inhibitors against PAD4. The binding affinity of α-enolase-derived peptides and PAD4 was virtually determined using PatchDock and HADDOCK docking programs. Synthesis of the designed peptides was performed using a solid phase peptide synthesis method. The inhibitory potential of each peptide was determined experimentally by PAD4 inhibition assay and IC50 measurement. PAD4 assay data show that the N-P2 peptide is the most favourable substrate among all peptides. Further modification of N-P2 by changing the Arg residue to canavanine [P2 (Cav)] rendered it an inhibitor against PAD4 by reducing the PAD4 activity to 35 % with IC50 1.39 mM. We conclude that P2 (Cav) is a potential inhibitor against PAD4 and can serve as a starting point for the development of even more potent inhibitors.
  11. James SA, Yam WK
    Comput Biol Chem, 2021 Jun;92:107499.
    PMID: 33932782 DOI: 10.1016/j.compbiolchem.2021.107499
    Rhinoviruses (RV), especially Human rhinovirus (HRVs) have been accepted as the most common cause for upper respiratory tract infections (URTIs). Pleconaril, a broad spectrum anti-rhinoviral compound, has been used as a drug of choice for URTIs for over a decade. Unfortunately, for various complications associated with this drug, it was rejected, and a replacement is highly desirable. In silico screening and prediction methods such as sub-structure search and molecular docking have been widely used to identify alternative compounds. In our study, we have utilised sub-structure search to narrow down our quest in finding relevant chemical compounds. Molecular docking studies were then used to study their binding interaction at the molecular level. Interestingly, we have identified 3 residues that is worth further investigation in upcoming molecular dynamics simulation systems of their contribution in stable interaction.
  12. Hayat K, Tariq U, Wong QA, Quah CK, Majid ASA, Nazari V M, et al.
    Comput Biol Chem, 2021 Oct;94:107567.
    PMID: 34500323 DOI: 10.1016/j.compbiolchem.2021.107567
    Benzimidazolium salts (3-6) were synthesized as stable N-Heterocyclic Carbene (NHC) precursors and their selenium-NHC compounds/Selenones (7-10) were prepared using water as a solvent. Characterization of each of the synthesized compounds was carried out by various analytical and spectroscopic (FT-IR, 1H-, 13C NMR) methods. X-ray crystallographic analyses of single crystals obtained for salts 3 and 5 were carried out. Synthesized salts and their Se-NHCs were tested in-vitro for their anticancer potential against Cervical Cancer Cell line from Henrietta Lacks (HeLa), Breast cancer cell line (MDA-MB-231), Adenocarcinoma cell line (A549) and human normal endothelial cell line (EA.hy926). MTT assay was used for analysis and compared with standard drug 5-flourouracil. Benzimidazolium salts (3-6) and their selenium counter parts (7-10) were found potent anticancer agents. Salt 3-5 were found to be potent anticancer against HeLa with IC50 values 0.072, 0.017 and 0.241 μM, respectively, which are less than standard drug (4.9 μM). The Se-NHCs (7-10) had also shown significant anticancer potential against HeLa with IC50 values less than standard drug. Salts 3, 4 against EA.hy926, compounds 3,5,6, and 10 against MDA-MB-321, and compounds 4, 10 against A-549 cell line were found more potent anticancer agents with IC50 values less than standard drug. Molecular docking for (7-10) showed their good anti-angiogenic potential having low binding energy and significant inhibition constant values with VEGFA (vascular endothelial growth factor), EGF (human epidermal growth factor), COX1 (cyclooxygenase-1) and HIF (hypoxia inducible factor).
  13. Al-Qattan MN, Mordi MN, Mansor SM
    Comput Biol Chem, 2016 10;64:237-249.
    PMID: 27475235 DOI: 10.1016/j.compbiolchem.2016.07.007
    BACKGROUND: Glutathione-s-transferases (GSTs) are enzymes that principally catalyze the conjugation of electrophilic compounds to the endogenous nucleophilic glutathione substrate, besides, they have other non-catalytic functions. The Plasmodium falciparum genome encodes a single isoform of GST (PfGST) which is involved in buffering the toxic heme, thus considered a potential anti-malarial target. In mammals several classes of GSTs are available, each of various isoforms. The human (human GST Pi-1 or hGSTP1) and mouse (murine GST Mu-1 or mGSTM1) GST isoforms control cellular apoptosis by interaction with signaling proteins, thus considered as potential anti-cancer targets. In the course of GSTs inhibitors development, the models of ligands interactions with GSTs are used to guide rational molecular modification. In the absence of X-ray crystallographic data, enzyme kinetics and molecular docking experiments can aid in addressing ligands binding modes to the enzymes.

    METHODS: Kinetic studies were used to investigate the interactions between the three GSTs and each of glutathione, 1-chloro-2,4-dinitrobenzene, cibacron blue, ethacrynic acid, S-hexyl glutathione, hemin and protoporphyrin IX. Since hemin displacement is intended for PfGST inhibitors, the interactions between hemin and other ligands at PfGST binding sites were studied kinetically. Computationally determined binding modes and energies were interlinked with the kinetic results to resolve enzymes-ligands interaction models at atomic level.

    RESULTS: The results showed that hemin and cibacron blue have different binding modes in the three GSTs. Hemin has two binding sites (A and B) with two binding modes at site-A depending on presence of GSH. None of the ligands were able to compete hemin binding to PfGST except ethacrynic acid. Besides bind differently in GSTs, the isolated anthraquinone moiety of cibacron blue is not maintaining sufficient interactions with GSTs to be used as a lead. Similarly, the ethacrynic acid uses water bridges to mediate interactions with GSTs and at least the conjugated form of EA is the true hemin inhibitor, thus EA may not be a suitable lead.

    CONCLUSIONS: Glutathione analogues with bulky substitution at thiol of cysteine moiety or at γ-amino group of γ-glutamine moiety may be the most suitable to provide GST inhibitors with hemin competition.

  14. Solayman M, Saleh MA, Paul S, Khalil MI, Gan SH
    Comput Biol Chem, 2017 Jun;68:175-185.
    PMID: 28359874 DOI: 10.1016/j.compbiolchem.2017.03.005
    Polymorphisms of the ADIPOR2 gene are frequently linked to a higher risk of developing diseases including obesity, type 2 diabetes and cardiovascular diseases. Though mutations of the ADIPOR2 gene are detrimental, there is a lack of comprehensive in silico analyses of the functional and structural impacts at the protein level. Considering the involvement of ADIPOR2 in glucose uptake and fatty acid oxidation, an in silico functional analysis was conducted to explore the possible association between genetic mutations and phenotypic variations. A genomic analysis of 82 nonsynonymous SNPs in ADIPOR2 was initiated using SIFT followed by the SNAP2, nsSNPAnalyzer, PolyPhen-2, SNPs&GO, FATHMM and PROVEAN servers. A total of 10 mutations (R126W, L160Q, L195P, F201S, L235R, L235P, L256R, Y328H, E334K and Q349H) were predicted to have deleterious effects on the ADIPOR2 protein and were therefore selected for further analysis. Theoretical models of the variants were generated by comparative modeling via MODELLER 9.16. A protein structural analysis of these amino acid variants was performed using SNPeffect, I-Mutant, ConSurf, Swiss-PDB Viewer and NetSurfP to explore their solvent accessibility, molecular dynamics and energy minimization calculations. In addition, FTSite was used to predict the ligand binding sites, while NetGlycate, NetPhos2.0, UbPerd and SUMOplot were used to predict post-translational modification sites. All of the variants showed increased free energy, though F201S exhibited the highest energy increase. The root mean square deviation values of the modeled mutants strongly indicated likely pathogenicity. Remarkably, three binding sites were detected on ADIPOR2, and two mutations at positions 328 and 201 were found in the first and second binding pockets, respectively. Interestingly, no mutations were found at the post-translational modification sites. These genetic variants can provide a better understanding of the wide range of disease susceptibility associated with ADIPOR2 and aid the development of new molecular diagnostic markers for these diseases. The findings may also facilitate the development of novel therapeutic elements for associated diseases.
  15. Chan Mun Wei J, Zhao Z, Li SC, Ng YK
    Comput Biol Chem, 2018 Jun;74:428-433.
    PMID: 29625871 DOI: 10.1016/j.compbiolchem.2018.03.010
    DNA fingerprinting, also known as DNA profiling, serves as a standard procedure in forensics to identify a person by the short tandem repeat (STR) loci in their DNA. By comparing the STR loci between DNA samples, practitioners can calculate a probability of match to identity the contributors of a DNA mixture. Most existing methods are based on 13 core STR loci which were identified by the Federal Bureau of Investigation (FBI). Analyses based on these loci of DNA mixture for forensic purposes are highly variable in procedures, and suffer from subjectivity as well as bias in complex mixture interpretation. With the emergence of next-generation sequencing (NGS) technologies, the sequencing of billions of DNA molecules can be parallelized, thus greatly increasing throughput and reducing the associated costs. This allows the creation of new techniques that incorporate more loci to enable complex mixture interpretation. In this paper, we propose a computation for likelihood ratio that uses NGS (next generation sequencing) data for DNA testing on mixed samples. We have applied the method to 4480 simulated DNA mixtures, which consist of various mixture proportions of 8 unrelated whole-genome sequencing data. The results confirm the feasibility of utilizing NGS data in DNA mixture interpretations. We observed an average likelihood ratio as high as 285,978 for two-person mixtures. Using our method, all 224 identity tests for two-person mixtures and three-person mixtures were correctly identified.
  16. Lim LWK, Chung HH, Chong YL, Lee NK
    Comput Biol Chem, 2018 Jun;74:132-141.
    PMID: 29602043 DOI: 10.1016/j.compbiolchem.2018.03.019
    The race for the discovery of enhancers at a genome-wide scale has been on since the commencement of next generation sequencing decades after the discovery of the first enhancer, SV40. A few enhancer-predicting features such as chromatin feature, histone modifications and sequence feature had been implemented with varying success rates. However, to date, there is no consensus yet on the single enhancer marker that can be employed to ultimately distinguish and uncover enhancers from the enormous genomic regions. Many supervised, unsupervised and semi-supervised computational approaches had emerged to complement and facilitate experimental approaches in enhancer discovery. In this review, we placed our focus on the recently emerged enhancer predictor tools that work on general enhancer features such as sequences, chromatin states and histone modifications, eRNA and of multiple feature approach. Comparisons of their prediction methods and outcomes were done across their functionally similar counterparts. We provide some recommendations and insights for future development of more comprehensive and robust tools.
  17. Zengin G, Rodrigues MJ, Abdallah HH, Custodio L, Stefanucci A, Aumeeruddy MZ, et al.
    Comput Biol Chem, 2018 Dec;77:178-186.
    PMID: 30336375 DOI: 10.1016/j.compbiolchem.2018.10.005
    The genus Silene is renowned in Turkey for its traditional use as food and medicine. Currently, there are 138 species of Silene in Turkey, amongst which have been several studies for possible pharmacological potential and application in food industry. However, there is currently a paucity of data on Silene salsuginea Hub.-Mor. This study endeavours to access its antioxidant, enzyme inhibitory, and anti-inflammatory properties. Besides, reversed-phase high-performance liquid chromatography-diode array detector (RP-HPLC-DAD) was used to detect phenolic compounds, and molecular docking was performed to provide new insights for tested enzymes and phenolics. High amounts of apigenin (534 μg/g extract), ferulic acid (452 μg/g extract), p-coumaric acid (408 μg/g extract), and quercetin (336 μg/g extract) were detected in the methanol extract while rutin (506 μg/g extract) was most abundant in the aqueous extract. As for their biological properties, the methanol extract exhibited the best antioxidant effect in the DPPH and CUPRAC assays, and also the highest inhibition against tyrosinase. The aqueous extract was the least active enzyme inhibitor but showed the highest antioxidant efficacy in the ABTS, FRAP, and metal chelating assays. At a concentration of 15.6 μg/mL, the methanol extract resulted in a moderate decrease (25.1%) of NO production in lipopolysaccharide-stimulated cells. Among the phenolic compounds, epicatechin, (+)-catechin, and kaempferol showed the highest binding affinity towards the studied enzymes in silico. It can be concluded that extracts of S. salsuginea are a potential source of functional food ingredients but need further analytical experiments to explore its complexity of chemical compounds and pharmacological properties as well as using in vivo toxicity models to establish its maximum tolerated dose.
  18. Al-Nema M, Gaurav A, Akowuah G
    Comput Biol Chem, 2018 Dec;77:52-63.
    PMID: 30240986 DOI: 10.1016/j.compbiolchem.2018.09.001
    The major complaint that most of the schizophrenic patients' face is the cognitive impairment which affects the patient's quality of life. The current antipsychotic drugs treat only the positive symptoms without alleviating the negative or cognitive symptoms of the disease. In addition, the existing therapies are known to produce extrapyramidal side effects that affect the patient adherence to the treatment. PDE10A inhibitor is the new therapeutic approach which has been proven to be effective in alleviating the negative and cognitive symptoms of the disease. A number of PDE10A inhibitors have been developed, but no inhibitor has made it beyond the clinical trials so far. Thus, the present study has been conducted to identify a PDE10A inhibitor from natural sources to be used as a lead compound for the designing of novel selective PDE10A inhibitors. Ligand and structure-based pharmacophore models for PDE10A inhibitors were generated and employed for virtual screening of universal natural products database. From the virtual screening results, 37 compounds were docked into the active site of the PDE10A. Out of 37 compounds, three inhibitors showed the highest affinity for PDE10A where UNPD216549 showed the lowest binding energy and has been chosen as starting point for designing of novel PDE10A inhibitors. The structure-activity-relationship studies assisted in designing of selective PDE10A inhibitors. The optimization of the substituents on the phenyl ring resulted in 26 derivatives with lower binding energy with PDE10A as compared to the lead compound. Among these, MA 8 and MA 98 exhibited the highest affinity for PDE10A with binding energy (-10.90 Kcal/mol).
  19. Abbasi MA, Hassan M, Ur-Rehman A, Siddiqui SZ, Hussain G, Shah SAA, et al.
    Comput Biol Chem, 2018 Dec;77:72-86.
    PMID: 30245349 DOI: 10.1016/j.compbiolchem.2018.09.007
    The heterocyclic compounds have been extensively reported for their bioactivity potential. The current research work reports the synthesis of some new multi-functional derivatives of 2-furoic piperazide (1; 1-(2-furoyl)piperazine). The synthesis was initiated by reacting the starting compound 1 with 3,5-dichloro-2-hydroxybenzenesulfonyl chloride (2) in a basic, polar and protic medium to obtain the parent sulfonamide 3 which was then treated with different electrophiles, 4a-g, in a polar and aprotic medium to acquire the designed molecules, 5a-g. These convergent derivatives were evaluated for their inhibitory potential against α-glucosidase, acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) enzymes. Acarbose was used as a reference standard for α-glucosidase inhibition while eserine for AChE and BChE inhibition. Some of the synthesized compounds were identified as promising inhibitors of these three enzymes and their bioactivity potentials were also supported by molecular docking study. The most active compounds among the synthetic analogues might be helpful in drug discovery and development for the treatment of type 2 diabetes and Alzhiemer's diseases.
  20. Alam MS, Saleh MA, Mozibullah M, Riham AT, Solayman M, Gan SH
    Comput Biol Chem, 2021 Dec;95:107587.
    PMID: 34710812 DOI: 10.1016/j.compbiolchem.2021.107587
    Human dihydrofolate reductase (DHFR) is a conserved enzyme that is central to folate metabolism and is widely targeted in pathogenic diseases as well as cancers. Although studies have reported the fact that genetic mutations in DHFR leads to a rare autosomal recessive inborn error of folate metabolism and drug resistance, there is a lack of an extensive study on how the deleterious non-synonymous SNPs (nsSNPs) disrupt its phenotypic effects. In this study, we aim at discovering the structural and functional consequences of nsSNPs in DHFR by employing a combined computational approach consisting of ten recently developed in silico tools for identification of damaging nsSNPs and molecular dynamics (MD) simulation for getting deeper insights into the magnitudes of damaging effects. Our study revealed the presence of 12 most deleterious nsSNPs affecting the native phenotypic effects, with three (R71T, G118D, Y122D) identified in the co-factor and ligand binding active sites. MD simulations also suggested that these three SNPs particularly Y122D, alter the overall structural flexibility and dynamics of the native DHFR protein which can provide more understandings into the crucial roles of these mutants in influencing the loss of DHFR function.
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