Recent Trends in Computer-aided Drug Design for Anti-cancer Drug Discovery.

Cancer is considered one of the deadliest diseases globally, and continuous research is being carried out to find novel potential therapies for myriad cancer types that affect the human body. Researchers are hunting for innovative remedies to minimize the toxic effects of conventional therapies being driven by cancer, which is emerging as pivotal causes of mortality worldwide. Cancer progression steers the formation of heterogeneous behavior, including self-sustaining proliferation, malignancy, and evasion of apoptosis, tissue invasion, and metastasis of cells inside the tumor with distinct molecular features. The complexity of cancer therapeutics demands advanced approaches to comprehend the underlying mechanisms and potential therapies. Precision medicine and cancer therapies both rely on drug discovery. In vitro drug screening and in vivo animal trials are the mainstays of traditional approaches for drug development; however, both techniques are laborious and expensive. Omics data explosion in the last decade has made it possible to discover efficient anti-cancer drugs via computational drug discovery approaches. Computational techniques such as computer-aided drug design have become an essential drug discovery tool and a keystone for novel drug development methods. In this review, we seek to provide an overview of computational drug discovery procedures comprising the target sites prediction, drug discovery based on structure and ligand-based design, quantitative structure-activity relationship (QSAR), molecular docking calculations, and molecular dynamics simulations with a focus on cancer therapeutics. The applications of artificial intelligence, databases, and computational tools in drug discovery procedures, as well as successfully computationally designed drugs, have been discussed to highlight the significance and recent trends in drug discovery against cancer. The current review describes the advanced computer-aided drug design methods that would be helpful in the designing of novel cancer therapies.

In silico identification of novel stilbenes analogs for potential multi-targeted drugs against Alzheimer's disease.

CONTEXT: Alzheimer's disease (AD) is a chronic progressive neurodegenerative syndrome, which adversely disturbs cognitive abilities as well as intellectual processes and frequently occurs in the elderly. Inhibition of cholinesterase is a valuable approach to upsurge acetylcholine concentrations in the brain and persuades the development of multi-targeted ligands against cholinesterases. METHODS: The current study aims to determine the binding potential accompanied by antioxidant and anti-inflammatory activities of stilbenes-designed analogs against both cholinesterases (Acetylcholinesterase and butyrylcholinesterase) and neurotrophin targets for effective AD therapeutics. Docking results have shown that the WS6 compound exhibited the least binding energy - 10.1 kcal/mol with Acetylcholinesterase and - 7.8 kcal/mol with butyrylcholinesterase. The WS6 also showed a better binding potential with neurotrophin targets that are Brain-derived Neurotrophic Factor, Neurotrophin 4, Nerve Growth Factor, and Neurotrophin 3. The tested compounds particularly WS6 revealed significant antioxidant and anti-inflammatory activities through the comparative docking analysis with Fluorouracil and Melatonin as control drugs of antioxidants while Celecoxib and Anakinra as anti-inflammatory. The bioinformatics approaches including molecular docking calculations followed by the pharmacokinetics analysis and molecular dynamic simulations were accomplished to explore the capabilities of designed stilbenes as effective and potential leads. Root mean square deviation, root mean square fluctuations, and MM-GBSA calculations were performed through molecular dynamic simulations to extract the structural and residual variations and binding free energies through the 50-ns time scale.

Screening of Human Circular RNAs as Biomarkers for Early Onset Detection of Alzheimer's Disease.

Circular RNAs (circRNAs) are a distinctive type of endogenous non-coding RNAs, and their regulatory roles in neurological disorders have received immense attention. CircRNAs significantly contribute to the regulation of gene expression and progression of neurodegenerative disorders including Alzheimer's disease (AD). The current study aimed to identify circRNAs as prognostic and potential biomarkers in AD. The differentially expressed circRNAs among subjective cognitive decline, amnestic mild cognitive impairment, and age-matched normal donors were determined through Arraystar Human circRNA Array V2 analysis. The annotations of circRNAs-microRNA interactions were predicted by employing Arraystar's homemade microRNAs (miRNA) target prediction tool. Bioinformatics analyses comprising gene ontology enrichment, KEGG pathway, and network analysis were conducted. Microarray analysis revealed the 33 upregulated and 11 downregulated differentially expressed circRNAs (FC ≥ 1.5 and p-values ≤ 0.05). The top 10 differentially expressed upregulated and downregulated circRNAs have been chosen for further expression validation through quantitative real-time PCR and subsequently, hsa-circRNA_001481 and hsa_circRNA_000479 were confirmed experimentally. Bioinformatics analyses determined the circRNA-miRNA-mRNA interactions and microRNA response elements to inhibit the expression of miRNAs and mRNA targets. Gene ontology enrichment and KEGG pathways analysis revealed the functional clustering of target mRNAs suggesting the functional verification of these two promising circRNAs. It is concluded that human circRNA_001481 and circRNA_000479 could be utilized as potential biomarkers for the early onset detection of AD and the development of effective therapeutics.

Molecular markers for the detection of pathogenic and food poisoning potential of methicillin resistant Staphylococcus aureus isolated from wounds of hospitalized patients.

Pathogenic strains of Staphylococcus aureus are mostly resistant to methicillin and they can cause severe infections. The current study was planned to assess the food poisoning potential of pathogenic, methicillin resistant Staphylococcus aureus by molecular detection of enterotoxin A (Eta) gene. A total of 100 septic wound samples from patients admitted in surgical ward (n=50) and burn unit (n=50) of Mayo Hospital Lahore were collected aseptically. These samples were processed primarily for bacterial growth on nutrient agar and purified on mannitol salt agar where twenty (20) samples showed pin-point colonies with yellow discoloration of media. Moreover, isolates were further characterized on the basis of microscopic appearance and biochemical assays where fourteen (14) isolates were declared Staphylococcus. DNA of these isolates were subjected to 16S rRNA gene amplification and sequences of S. aureus were submitted to NCBI GenBank viz., MW344063.1, MW341438.1, MW344064.1, MW344065.1, MW341439.1, MW341440.1, MW345971.1, MW345972.1, MW345973.1, MW716458.1. All the isolates (n=10) demonstrated molecular confirmation of pathogenicity and methicillin resistance by amplification of Coa and mecA gene. Out of these ten isolates, three amplified enterotoxin A (Eta) gene were confirmed. It is concluded that enterotoxin A of S. aureus which causes food poisoning is present in pathogenic, methicillin resistant S. aureus isolated from various wounds infections.

Early Detection of Iron Overload Cardiomyopathy in Transfusion Dependent Thalassemia Patients in Sulaimaniyah City, Iraq.

Background: Lifelong blood transfusion is recommended for patients with transfusion-dependent thalassemia (TDT) that lead to iron overload and results in cardiomyopathy (CM). Aim: To assess the accuracy of several electrocardiographic (ECG) data in patients at high risk of arrhythmia, early detection of structural and functional changes in left atrium and ventricle using ECG and echocardiography (two dimensional, M-mode echocardiography along with Doppler studies), and to observe the correlations between plasma B-type atrial natriuretic peptide (BNP)/serum ferritin and ECG with Doppler as well as echocardiographic changes in patients with TDT. Methods: The current prospective case-control study included 75 TDT patients and 74 control subjects with the mean age of 9.55 and 9.93 years, respectively. Participants were assessed for the socio-demographic, physical examinations, serum ferritin, plasma BNP, ECG, 2D echocardiography, and tissue/pulse wave Doppler. Results: The mean of serum ferritin and plasma BNP were significantly (p<0.001) higher in the cases (1475.19 ng/mL and 47.63 pg/mL, respectively) than controls (41.3 ng/mL and BNP 23.37 pg/mL, respectively). ECG findings showed significant higher P-wave dispersion, QRS duration, QT duration and dispersion, and JTc dispersion in cases than controls. Echocardiography findings revealed diastolic dysfunction with preserved ejection fraction (EF) in thalassemia cases, as well as significant higher left ventricular (LV) mass, LV internal diameters during systole and diastole (LVIDs and d) and LV posterior wall thickness during diastole (LVPWd) in cases than controls (p<0.05). Also, a significant (p<0.05) correlation between BNP and QT dispersion was found in patients. Conclusion: These findings suggest the usefulness of ECG, 2D echocardiographic, Doppler studies and plasma BNP, with no significant beneficial effect of serum ferritin level in detecting early cardiac changes in patients with TDT.

The Life Cycle and in silico Elucidation of Non-structural Replicating Proteins of HCV Through a Pharmacoinformatics Approach.

BACKGROUND: Hepatitis C virus (HCV) is an enveloped and positive-stranded RNA virus that is a major causative agent of chronic liver diseases worldwide. HCV has become the main cause of liver transplantations and there is no effective drug for all hepatitis genotypes. Elucidation of the life cycle and non-structural proteins of HCV, involved in viral replication, are attractive targets for the development of antiviral drugs.. METHODS: In this work, pharmacoinformatics approaches coupled with docking analyses were applied on HCV non-structural proteins to identify the novel potential hits and HCV drugs. Molecular docking analyses were carried out on HCV-approved drugs, followed by the ligandbased pharmacophore generation to screen the antiviral libraries for novel potential hits. RESULTS: Virtual screening technique has top-ranked five novel compounds (ZINC00607900, ZINC03635748, ZINC03875543, ZINC04097464, and ZINC12503102) along with their least binding energies (-8.0 kcal/mol, -6.1 kcal/mol, -7.5 kcal/mol, -7.4 kcal/mol, and -7.3 kcal/mol, respectively) and stability with the non-structural proteins target. CONCLUSION: These promising hits exhibited better absorption and ADMET properties as compared to the selected drug molecules. These potential compounds extracted from in silico approach may be significant in drug design and development against Hepatitis and other liver diseases.

A Computational Approach to Modeling an Antagonistic Angiogenic VEGFR1-IL2 Fusion Protein for Cancer Therapy.

In cancer treatment, immunotherapy has great potential for improving the prognosis of patients with hematologic and solid malignancies. In this study, various bioinformatics tools and servers were used to design an antiangiogenic fusion protein. After comprehensive evaluation, an antiangiogenic fusion protein was designed using a soluble extracellular domain of human vascular endothelial growth factor receptor 1 (sVEGFR-1) and human interleukin-2 (IL-2) joined by a flexible linker. The final construct was composed of 875 amino acids. The secondary structure of the fusion protein, obtained by CFSSP, PSIPRED, and SOPMA tools, consisted of 14.17% helices, 29.71% extended strands, 4.69% beta turns and 51.43% random coils. Tertiary structure prediction by Raptor X showed that the fusion protein comprises 3 domains with 875 modeled amino acids, out of which 26 positions (2%) were considered disordered. The Ramachandran plot revealed 89.3%, 7.1%, and 3.6% amino acid residues in favored, allowed, and outlier regions, respectively. Physical features of the Molecular Dynamic (MD) simulated system such as root mean square deviation, root mean square fluctuation, solvent-on hand surface region, and radius of gyration identified the fusion construct as a stable and compact protein with few fluctuations in its overall structure. Docking of the fusion protein showed that interaction between sVEGFR-1/VEGFA and IL-2/IL-2R still exists. In silico analysis revealed that the fusion protein comprising IL-2 and sVEGFR-1 has stable structure and the selected linker can efficiently separate the two domains. These observations may be helpful in determining protein stability prior to protein expression.

Distribution and antibiotic sensitivity pattern of Mycobacterium tuberculosis isolates from children, enrolled in a tertiary care hospital.

The present study was planned to assess the distribution of tuberculosis in children and evaluate the antimycobacterial sensitivity pattern of Mycobacterium tuberculosis (MTB) isolates from pediatric patients. A total number of 1718 pediatric patients suspected of Mycobacterium tuberculosis were enrolled in the Institute of Child Health and Children's Hospital, Lahore during 2016-17. Out of 1718, only 710 different types of samples were tested for MTB. The samples were processed using bacteriology and GeneXpert along with the chest X-ray and clinical picture of the patients. The sensitivity pattern of Streptomycin, Isoniazid, Rifampicin and Ethambutol (SIRE) was determined using BACTEC MGIT 960. Total patients were divided into four groups including group A (birth to 12 months), B (1 to 5 years), C (6 to 10 years), and D (11 to 15 years). Out of 710, 106 (55 females and 51 males) were declared positive and 604 negative for tuberculosis. Out of 106 positive cases, 89 (83.96%) were sensitive to Rifampicin and 17 (16.04%) were resistant. Only, 04 (3.77%) were resistant to both Rifampicin and Isoniazid and declared as multidrug-resistant (MDR). It was concluded that children of age 11 to 15 years were more prone to MTB and a minimum percentage of MDR isolates was recorded in age group A (birth to 12 months).

Appraisal of anti-mycobacterial potential against MDR-MTB in pediatric patients, cytotoxicity and mutagenicity of Aloe vera and Allium sativum.

The purpose of the studies was to evaluate an in-vitro anti-mycobacterial activity of Aloe vera and Allium sativum against MDR-MTB, their cytotoxicity and mutagenicity. Four extracts of Aloe vera and Allium sativum were prepared by Soxhlet apparatus and their minimum inhibitory concentrations (MIC's) were determined by BACTEC MGIT960 system against multi drug resistant Mycobacterium tuberculosis (MDR-MTB) isolates, collected from pediatric patients. Fractions of Aloe vera and Allium sativum extracts were separated using glass column chromatography, followed by evaluation of cytotoxicity and mutagenicity by tetrazolium salt (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and Ames test, respectively. Out of four extracts, ethanol extracts of Aloe vera and Allium sativum exhibited activity at MIC 5mg/mL to 7mg/mL and 3mg/mL to 5mg/mL, respectively and IC50 by MTT assay for combination of all fractions were 278.3mcg/100µL and 270.8mcg/100µL and in Ames assay M.I of TA98 were 0.14 and 0.07 and M.I of TA100 were 1.14 and 0.44, respectively. Aloe vera and Allium sativum extracts showed anti-mycobacterial activity against MDR-MTB isolates so, MIC of ethanol extracts of each plant and fractions of column chromatography had been checked. The MTT and Ames tests depicted that ethanol extracts of Aloe vera and Allium sativum were non-cytotoxic and non-mutagenic, and can be used in treatment of patients suffering from MDR-MTB.

Isolation, Characterization, and Genome Sequence Analysis of a Novel Lytic Phage, Xoo-sp15 Infecting Xanthomonas oryzae pv. oryzae.

Xanthomonas oryzae pv. oryzae (X. oryzae) is a bacterial pathovar of rice diseases all over the world. Owing to emerging antibacterial resistance, phage therapies have gained significant attention to treat various bacterial infections. Nevertheless, comprehensive research is needed for their use as a safe biocontrol agent. In this study, isolation and characterization of a novel phage Xoo-sp15, that infects X. oryzae was ascertained through experimental and bioinformatics analyses to determine its virulent potency and reliability. High throughput sequencing demonstrated that Xoo-sp15 has a dsDNA genome with a total size of 157,091 bp and 39.9% GC content lower than its host (63.6%). Morphological and phylogenetic analyses characterized it as a new member of the Bastille-like group within the family Herelleviridae. In silico analysis revealed that it contains 229 open reading frames and 16 tRNAs. Additionally, this novel phage does not contain any resistant determinants and can infect nine X. oryzae strains. Therefore, Xoo-sp15 has the potential to serve as a novel candidate for phage therapy.

Anti-aging Natural Compounds and their Role in the Regulation of Metabolic Pathways Leading to Longevity.

Aging is an unavoidable process, leading to cell senescence due to physiochemical changes in an organism. Anti-aging remedies have always been of great interest since ancient times. The purpose of anti-aging activities is to increase the life span and the quality of life. Anti-aging activities are primarily involved in the therapies of age-related disorders such as Parkinson's Disease (PD), Alzheimer's Disease (AD), cardiovascular diseases, cancer, and chronic obstructive pulmonary diseases. These diseases are triggered by multiple factors that are involved in numerous molecular pathways including telomere shortening, NF-κB pathway, adiponectin receptor pathway, insulin, and IGF signaling pathway, AMPK, mTOR, and mitochondria dysfunction. Natural products are known as effective molecules to delay the aging process through influencing metabolic pathways and thus ensure an extended lifespan. These natural compounds are being utilized in drug design and development through computational and high throughput techniques for effective pro-longevity drugs. A comprehensive study on natural compounds demonstrating their anti-aging activities along with databases of natural products for drug designing was executed and summarized in this review article.

COVID-19 severity in relation to sociodemographics and vitamin D use.

Most COVID-19 cases are treated as outpatients, while the majority of studies on COVID-19 focus on inpatients. Little is known about the self-reporting and self-rating of the disease's symptoms, and the associations of prophylactic use of dietary supplements with COVID-19 severity have not been addressed. The aims of this study are to evaluate COVID-19 severity and to relate them to sociodemographic characteristics and prophylactic dietary supplements. An observational patient-based study conducted through an online questionnaire on recovered COVID-19 patients. The patients were assessed for several severity parameters, sociodemographic parameters, and prophylactic dietary supplement use. A total of 428 patients were evaluated. Age and presence of comorbidities had positive associations with the severity parameters. The severe infection group had the highest proportion of patients stressed about COVID-19 (P < 0.05). Cigarette, but not hookah, smoking was significantly associated with less severe symptoms. Vitamin D negatively predicted disease severity (P < 0.05). In conclusion, stress, age, and presence of comorbidities were the most important positive predictors of COVID-19 severity, while prophylactic vitamin D use and smoking were significant negative predictors. The use of protective measures and other prophylactic dietary supplements was not significantly associated with symptom severity.

Immunoinformatics and Molecular Docking Studies Predicted Potential Multiepitope-Based Peptide Vaccine and Novel Compounds against Novel SARS-CoV-2 through Virtual Screening.

BACKGROUND: Coronaviruses (CoVs) are enveloped positive-strand RNA viruses which have club-like spikes at the surface with a unique replication process. Coronaviruses are categorized as major pathogenic viruses causing a variety of diseases in birds and mammals including humans (lethal respiratory dysfunctions). Nowadays, a new strain of coronaviruses is identified and named as SARS-CoV-2. Multiple cases of SARS-CoV-2 attacks are being reported all over the world. SARS-CoV-2 showed high death rate; however, no specific treatment is available against SARS-CoV-2. METHODS: In the current study, immunoinformatics approaches were employed to predict the antigenic epitopes against SARS-CoV-2 for the development of the coronavirus vaccine. Cytotoxic T-lymphocyte and B-cell epitopes were predicted for SARS-CoV-2 coronavirus protein. Multiple sequence alignment of three genomes (SARS-CoV, MERS-CoV, and SARS-CoV-2) was used to conserved binding domain analysis. RESULTS: The docking complexes of 4 CTL epitopes with antigenic sites were analyzed followed by binding affinity and binding interaction analyses of top-ranked predicted peptides with MHC-I HLA molecule. The molecular docking (Food and Drug Regulatory Authority library) was performed, and four compounds exhibiting least binding energy were identified. The designed epitopes lead to the molecular docking against MHC-I, and interactional analyses of the selected docked complexes were investigated. In conclusion, four CTL epitopes (GTDLEGNFY, TVNVLAWLY, GSVGFNIDY, and QTFSVLACY) and four FDA-scrutinized compounds exhibited potential targets as peptide vaccines and potential biomolecules against deadly SARS-CoV-2, respectively. A multiepitope vaccine was also designed from different epitopes of coronavirus proteins joined by linkers and led by an adjuvant. CONCLUSION: Our investigations predicted epitopes and the reported molecules that may have the potential to inhibit the SARS-CoV-2 virus. These findings can be a step towards the development of a peptide-based vaccine or natural compound drug target against SARS-CoV-2.

Genomic analysis of bacteriophage Xoo-sp13 infecting Xanthomonas oryzae pv. oryzae.

Xanthomonas oryzae pv. oryzae is a bacterial pathogen that gives rise to diseases in rice all over the world. A bacteriophage infecting this bacterium was isolated from rice fields in China. Here, we report the complete genome sequence of this phage, which has a linear dsDNA genome of 309,023 bp and a G + C content of 42.43%. It contains 401 open reading frames and encodes 28 tRNAs. It belongs to the family Myoviridae and has a broad host range, making it a possible candidate for phage therapy.

Sequence Analysis of a Jumbo Bacteriophage, Xoo-sp14, That Infects Xanthomonas oryzae pv. oryzae.

A jumbo bacteriophage, Xoo-sp14, infecting Xanthomonas oryzae pv. oryzae was isolated from rice fields in China. Here, we report the complete genome sequence of this phage, revealing that it had a linear double-stranded DNA (dsDNA) molecule 232,104 bp long, with a G+C content of 58%. It has 251 annotated protein-coding sequences.

Structural Genomics of repA, repB 1-Carrying IncFIB Family pA1705-qnrS, P911021-tetA, and P1642-tetA, Multidrug-Resistant Plasmids from Klebsiella pneumoniae.

BACKGROUND: Multidrug-resistant plasmids carrying replication genes have been widely present in various strains of Klebsiella pneumoniae. RepA and repB1 were found in plasmids belong to the IncFIB, but their detailed structural and genomic characterization was not reported yet. This is the first study that delivers structural and functional insights of repA- and repB1-carrying IncFIB plasmids. METHODS: Klebsiella pneumoniae strains A1705, 911021, and 1642 were isolated from the human urine samples and bronchoalveolar fluids collected from different hospitals of China. Antibacterial susceptibility and plasmid transfer ability were tested to characterize the resistant phenotypes mediated by the pA1705-qnrS, p911021-tetA, and p1642-tetA. The complete nucleotide sequences of these plasmids were determined through high-throughput sequencing technology and comparative genomic analyses of plasmids belong to the same incompatibility group were executed to extract the genomic variations and features. RESULTS: The pA1705-qnrS, p911021-tetA, and p1642-tetA are defined as non-conjugative plasmids, having two replication genes, repA and repB1 associated with IncFIB family, and unknown incompatible group, respectively. Comparative genomic analysis revealed that relatively small backbones of IncFIB plasmids integrated massive accessory module at one "hotspot" that was located between orf312 and repB1. These IncFIB plasmids exhibited the distinct profiles of accessory modules including one or two multidrug-resistant regions, many complete and remnant mobile elements comprising integrons, transposons and insertion sequences. The clusters of resistant genes were recognized in this study against different classes of antibiotics including ß-lactam, phenicol, aminoglycoside, tetracycline, quinolone, trimethoprim, sulfonamide, tunicamycin, and macrolide. It has been observed that all resistant genes were located in multidrug resistance regions. CONCLUSION: It is concluded that multidrug-resistant repA and repB1-carrying IncFIB plasmids are a key source to mediate the resistance through mobile elements among Klebsiella pneumoniae. Current findings provide a deep understanding of horizontal gene transfer among plasmids of the IncFIB family via mobile elements that will be utilized in further in vitro studies.

In Silico identification of angiotensin-converting enzyme inhibitory peptides from MRJP1.

Hypertension is considered as one of the most common diseases that affect human beings (both male and female) due to its high prevalence and also extending widely to both industrialize and developing countries. Angiotensin-converting enzyme (ACE) has a significant role in the regulation of blood pressure and ACE inhibition with inhibitory peptides is considered as a major target to prevent hypertension. In the current study, a blood pressure regulating honey protein (MRJP1) was examined to identify the ACE inhibitory peptides. The 3D structure of MRJP1 was predicted by utilizing the threading approach and further optimized by performing molecular dynamics simulation for 30 nanoseconds (ns) to improve the quality factor up to 92.43%. Root mean square deviation and root mean square fluctuations were calculated to evaluate the structural features and observed the fluctuations in the timescale of 30 ns. AHTpin server based on scoring vector machine of regression models, proteolysis and structural characterization approaches were implemented to identify the potential inhibitory peptides. The anti-hypertensive peptides were scrutinized based on the QSAR models of anti-hypertensive activity and the molecular docking analyses were performed to explore the binding affinities and potential interacting residues. The peptide "EALPHVPIFDR" showed the strong binding affinity and higher anti-hypertensive activity along with the global energy of -58.29 and docking score of 9590. The aromatic amino acids especially Tyr was observed as the key residue to design the dietary peptides and drugs like ACE inhibitors.

Ligand-Based Pharmacophore Modeling and Virtual Screening to Discover Novel CYP1A1 Inhibitors.

Backgound: Cytochrome P450, family 1, subfamily A, polypeptide 1 (CYP1A1) is an imperative enzyme due to its immersion in the biotransformation of a wide range of drugs and other xenobiotics. The involvement of enzymes in drug metabolism indicates an effective drug target for the development of novel therapeutics. The discovery of CYP1A1 specific inhibitors would be of particular relevance for the clinical pharmacology. METHODS: In the current work, in silico approaches were utilized to identify the novel potential compounds through a diverse set of reported inhibitors against CYP1A1. A dataset of reported compounds against CYP1 belongs to 10 different classes (alkaloids, coumarins, flavonoids, natural compounds, synthetic inhibitors, drugs, MBI's, PAHs, naphthoquinone and stilbenoids) was retrieved and utilized for the comparative molecular docking analyses followed by pharmacophore modeling. The total eleven novel compounds were scrutinized on the basis of the highest binding affinities and least binding energy values. RESULTS: ZINC08792486 compound attained the highest gold fitness score of 90.11 against CYP1A1 among all the scrutinized molecules. CONCLUSION: It has been elucidated that the residues Phe-224, Gly-316 and Ala-317 were conserved in all ligand-receptor interactions and critical for the development of effective therapies. The ADMET property analyses also predict better absorption and distribution of the selected hits that may be used in the future for in vitro validations and drug development.

A review of computational algorithms for CpG islands detection.

CpG islands are generally known as the epigenetic regulatory regions in accordance with histone modifications, methylation, and promoter activity. There is a significant need for the exact mapping of DNA methylation in CpG islands to understand the diverse biological functions. However, the precise identification of CpG islands from the whole genome through experimental and computational approaches is still challenging. Numerous computational methods are being developed to detect the CpG-enriched regions, effectively, to reduce the time and cost of the experiments. Here, we review some of the latest computational CpG detection methods that utilize clustering, patterns and physical-distance like parameters for CpG island detection. The comparative analyses of the methods relying on different principles and parameters allow prioritizing the algorithms for specific CpG associated datasets to achieve higher accuracy and sensitivity. A number of computational tools based on the window, Hidden Markov Model, density and distance-/length-based algorithms are being applied on human or mammalian genomes for accurate CpG detection. Comparative analyses of CpG island detection algorithms facilitate to prefer the method according to the target genome and required parameters to attain higher accuracy, specificity, and performance. There is still a need for efficient computational CpG detection methods with lower false-positive results. This review provides a better understanding about the principles of tools that will assist to prioritize and develop the algorithms for accurate CpG islands detection.

Pharmacoinformatics and molecular docking reveal potential drug candidates against Schizophrenia to target TAAR6.

Schizophrenia (SZ) is a complex disabling disorder that leads to the mental disability and afflicts 1% of the world's total population and placed in top ten medical disorders. In current work, bioinformatics analyses were carried out on Trace amine (TA)-associated receptor 6 (TAAR6) to recognize the potential drugs and compounds against SZ. Comparative modeling and threading-based approaches were utilized for the structure prediction of TAAR6. Fifty-nine predicted structures were evaluated by various model assessment techniques and final model having only eight amino acids in the outlier region and 98.5% overall quality factor was chosen for further pharmacoinformatics and molecular docking analyses. From an extensive literature review, 11 Food and Drug Administration (FDA) approved drugs were analyzed by computational techniques and Aripiprazole was found as the most effective drug against SZ by targeting TAAR6. Here, we report five novel molecules which exhibited the highest binding affinity, effective drug properties, and interestingly, observed better results than the approved selected drugs against SZ by targeting TAAR6. The docking analyses revealed that Arg-92, Trp-98, Gln-191, Thr-192, Ala-290, Cys-291, Tyr-293, and Glu-294 residues were observed as critical interacting residues in receptor-ligand interactions. Absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties, Lipinski rule of five, highest binding affinity coupled with virtual screening (VS), and pharmacophore modeling approach illustrated that aripiprazole (-8.6 kcal/mol) and TAAR6_0094 (-9.3 kcal/mol) are potential inhibitors for targeting TAAR6. It is suggested that schizophrenic patients have to use Aripiprazole for the medication of SZ by targeting TAAR6 and develop effective therapies by utilizing scrutinized novel compound.