scholarly journals Systems multiple molecule drug design with less side-effects via drug data mining and genome-wide data identification

2018 ◽  
Vol 11 (6) ◽  
Author(s):  
Bor Sen Chen
Keyword(s):  
Data Mining ◽  
Side Effects ◽  
Drug Design ◽  
Genome Wide ◽  
Genome Wide Data

scholarly journals In Silico Analysis of P450s and Their Role in Secondary Metabolism in the Bacterial Class Gammaproteobacteria

Molecules ◽  
2021 ◽  
Vol 26 (6) ◽  
pp. 1538
Author(s):  
Ntombizethu Nokuphiwa Msomi ◽  
Tiara Padayachee ◽  
Nomfundo Nzuza ◽  
Puleng Rosinah Syed ◽  
Justyna Dorota Kryś ◽  
...  
Keyword(s):  
Data Mining ◽  
Secondary Metabolism ◽  
Bacterial Species ◽  
In Silico Analysis ◽  
Cytochrome P450 Enzymes ◽  
Genome Data ◽  
Genome Wide ◽  
Genome Wide Data ◽  
The Impact ◽  
Silico Analysis

The impact of lifestyle on shaping the genome content of an organism is a well-known phenomenon and cytochrome P450 enzymes (CYPs/P450s), heme-thiolate proteins that are ubiquitously present in organisms, are no exception. Recent studies focusing on a few bacterial species such as Streptomyces, Mycobacterium, Cyanobacteria and Firmicutes revealed that the impact of lifestyle affected the P450 repertoire in these species. However, this phenomenon needs to be understood in other bacterial species. We therefore performed genome data mining, annotation, phylogenetic analysis of P450s and their role in secondary metabolism in the bacterial class Gammaproteobacteria. Genome-wide data mining for P450s in 1261 Gammaproteobacterial species belonging to 161 genera revealed that only 169 species belonging to 41 genera have P450s. A total of 277 P450s found in 169 species grouped into 84 P450 families and 105 P450 subfamilies, where 38 new P450 families were found. Only 18% of P450s were found to be involved in secondary metabolism in Gammaproteobacterial species, as observed in Firmicutes as well. The pathogenic or commensal lifestyle of Gammaproteobacterial species influences them to such an extent that they have the lowest number of P450s compared to other bacterial species, indicating the impact of lifestyle on shaping the P450 repertoire. This study is the first report on comprehensive analysis of P450s in Gammaproteobacteria.

scholarly journals SpermatogenesisOnline 1.0: a resource for spermatogenesis based on manual literature curation and genome-wide data mining

2012 ◽  
Vol 41 (D1) ◽  
pp. D1055-D1062 ◽  
Author(s):  
Yuanwei Zhang ◽  
Liangwen Zhong ◽  
Bo Xu ◽  
Yifan Yang ◽  
Rongjun Ban ◽  
...  
Keyword(s):  
Data Mining ◽  
Genome Wide ◽  
Genome Wide Data ◽  
Literature Curation

Recent Advances in the Rational Drug Design Based on Multi-target Ligands

2020 ◽  
Vol 27 (28) ◽  
pp. 4720-4740 ◽  
Author(s):  
Ting Yang ◽  
Xin Sui ◽  
Bing Yu ◽  
Youqing Shen ◽  
Hailin Cong
Keyword(s):  
Drug Resistance ◽  
Clinical Practice ◽  
Side Effects ◽  
Drug Design ◽  
Rational Drug Design ◽  
Health Conditions ◽  
Pharmacokinetic Parameters ◽  
Single Target ◽  
Rational Drug ◽  
Huge Challenge

Multi-target drugs have gained considerable attention in the last decade owing to their advantages in the treatment of complex diseases and health conditions linked to drug resistance. Single-target drugs, although highly selective, may not necessarily have better efficacy or fewer side effects. Therefore, more attention is being paid to developing drugs that work on multiple targets at the same time, but developing such drugs is a huge challenge for medicinal chemists. Each target must have sufficient activity and have sufficiently characterized pharmacokinetic parameters. Multi-target drugs, which have long been known and effectively used in clinical practice, are briefly discussed in the present article. In addition, in this review, we will discuss the possible applications of multi-target ligands to guide the repositioning of prospective drugs.

SARS-CoV-2 Biology Insights, Part I. Genome-wide structure and druggability: literature review (Preprint)

2020 ◽  
Author(s):  
Laura Lafon-Hughes
Keyword(s):  
Side Effects ◽  
Literature Review ◽  
Host Cell ◽  
Nucleoside Analogs ◽  
Viral Proteins ◽  
Therapeutic Strategies ◽  
Adverse Side Effects ◽  
Viral Proteases ◽  
Genome Wide ◽  
Therapeutic Alternatives

BACKGROUND COVID-19 pandemic prompts the study of coronavirus biology and search of putative therapeutic strategies. OBJECTIVE To compare SARS-CoV-2 genome-wide structure and proteins with other coronaviruses, focusing on putative coronavirus-specific or SARS-CoV-2 specific therapeutic designs. METHODS The genome-wide structure of SARS-CoV-2 was compared to that of SARS and other coronaviruses in order to gain insights, doing a literature review through Google searches. RESULTS There are promising therapeutic alternatives. Host cell targets could be modulated to hamper viral replication, but targeting viral proteins directly would be a better therapeutic design, since fewer adverse side effects would be expected. CONCLUSIONS Therapeutic strategies (Figure 1) could include the modulation of host targets (PARPs, kinases) , competition with G-quadruplexes or nucleoside analogs to hamper RDRP. The nicest anti-CoV options include inhibitors of the conserved essential viral proteases and drugs that interfere ribosome slippage at the -1 PRF site.

scholarly journals Genetic analysis of amyotrophic lateral sclerosis identifies contributing pathways and cell types

2021 ◽  
Vol 7 (3) ◽  
pp. eabd9036
Author(s):  
Sara Saez-Atienzar ◽  
Sara Bandres-Ciga ◽  
Rebekah G. Langston ◽  
Jonggeol J. Kim ◽  
Shing Wan Choi ◽  
...  
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Membrane Trafficking ◽  
Molecular Mechanisms ◽  
Cell Types ◽  
Polygenic Risk Score ◽  
Genome Wide ◽  
Genome Wide Data ◽  
Data Driven Approach ◽  
Single Nucleus ◽  
Lateral Sclerosis

Despite the considerable progress in unraveling the genetic causes of amyotrophic lateral sclerosis (ALS), we do not fully understand the molecular mechanisms underlying the disease. We analyzed genome-wide data involving 78,500 individuals using a polygenic risk score approach to identify the biological pathways and cell types involved in ALS. This data-driven approach identified multiple aspects of the biology underlying the disease that resolved into broader themes, namely, neuron projection morphogenesis, membrane trafficking, and signal transduction mediated by ribonucleotides. We also found that genomic risk in ALS maps consistently to GABAergic interneurons and oligodendrocytes, as confirmed in human single-nucleus RNA-seq data. Using two-sample Mendelian randomization, we nominated six differentially expressed genes (ATG16L2, ACSL5, MAP1LC3A, MAPKAPK3, PLXNB2, and SCFD1) within the significant pathways as relevant to ALS. We conclude that the disparate genetic etiologies of this fatal neurological disease converge on a smaller number of final common pathways and cell types.

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