Computational Methods for Identification of Novel Secondary Metabolite Biosynthetic Pathways by Genome Analysis

2013 ◽  
pp. 1642-1666
Author(s):  
Swadha Anand ◽  
Debasisa Mohanty
Keyword(s):  
Natural Product ◽  
Secondary Metabolite ◽  
Computational Methods ◽  
Rational Design ◽  
Genome Mining ◽  
Experimental Studies ◽  
Structural Features ◽  
Genome Sequences ◽  
Nonribosomal Peptide ◽  
Biosynthetic Engineering

Secondary metabolites belonging to polyketide and nonribosomal peptide families constitute a major class of natural products with diverse biological functions and a variety of pharmaceutically important properties. Experimental studies have shown that the biosynthetic machinery for polyketide and nonribosomal peptides involves multi-functional megasynthases like Polyketide Synthases (PKSs) and nonribosomal peptide synthetases (NRPSs) which utilize a thiotemplate mechanism similar to that for fatty acid biosynthesis. Availability of complete genome sequences for an increasing number of microbial organisms has provided opportunities for using in silico genome mining to decipher the secondary metabolite natural product repertoire encoded by these organisms. Therefore, in recent years there have been major advances in development of computational methods which can analyze genome sequences to identify genes involved in secondary metabolite biosynthesis and help in deciphering the putative chemical structures of their biosynthetic products based on analysis of the sequence and structural features of the proteins encoded by these genes. These computational methods for deciphering the secondary metabolite biosynthetic code essentially involve identification of various catalytic domains present in this PKS/NRPS family of enzymes; a prediction of various reactions in these enzymatic domains and their substrate specificities and also precise identification of the order in which these domains would catalyze various biosynthetic steps. Structural bioinformatics analysis of known secondary metabolite biosynthetic clusters has helped in formulation of predictive rules for deciphering domain organization, substrate specificity, and order of substrate channeling. In this chapter, the progress in development of various computational methods is discussed by different research groups, and specifically, the utility in identification of novel metabolites by genome mining and rational design of natural product analogs by biosynthetic engineering studies.

Computational Methods for Identification of Novel Secondary Metabolite Biosynthetic Pathways by Genome Analysis

2011 ◽  
pp. 380-405 ◽  
Author(s):  
Swadha Anand ◽  
Debasisa Mohanty
Keyword(s):  
Natural Product ◽  
Secondary Metabolite ◽  
Computational Methods ◽  
Rational Design ◽  
Genome Mining ◽  
Experimental Studies ◽  
Structural Features ◽  
Genome Sequences ◽  
Nonribosomal Peptide ◽  
Biosynthetic Engineering

Secondary metabolites belonging to polyketide and nonribosomal peptide families constitute a major class of natural products with diverse biological functions and a variety of pharmaceutically important properties. Experimental studies have shown that the biosynthetic machinery for polyketide and nonribosomal peptides involves multi-functional megasynthases like Polyketide Synthases (PKSs) and nonribosomal peptide synthetases (NRPSs) which utilize a thiotemplate mechanism similar to that for fatty acid biosynthesis. Availability of complete genome sequences for an increasing number of microbial organisms has provided opportunities for using in silico genome mining to decipher the secondary metabolite natural product repertoire encoded by these organisms. Therefore, in recent years there have been major advances in development of computational methods which can analyze genome sequences to identify genes involved in secondary metabolite biosynthesis and help in deciphering the putative chemical structures of their biosynthetic products based on analysis of the sequence and structural features of the proteins encoded by these genes. These computational methods for deciphering the secondary metabolite biosynthetic code essentially involve identification of various catalytic domains present in this PKS/NRPS family of enzymes; a prediction of various reactions in these enzymatic domains and their substrate specificities and also precise identification of the order in which these domains would catalyze various biosynthetic steps. Structural bioinformatics analysis of known secondary metabolite biosynthetic clusters has helped in formulation of predictive rules for deciphering domain organization, substrate specificity, and order of substrate channeling. In this chapter, the progress in development of various computational methods is discussed by different research groups, and specifically, the utility in identification of novel metabolites by genome mining and rational design of natural product analogs by biosynthetic engineering studies.

scholarly journals Draft Genome Sequences of Fungus Aspergillus calidoustus

2016 ◽  
Vol 4 (2) ◽  
Author(s):  
Fabian Horn ◽  
Jörg Linde ◽  
Derek J. Mattern ◽  
Grit Walther ◽  
Reinhard Guthke ◽  
...  
Keyword(s):  
Secondary Metabolite ◽  
Genome Sequence ◽  
Functional Annotation ◽  
Draft Genome ◽  
Genome Mining ◽  
Gene Clusters ◽  
Draft Genome Sequence ◽  
Genome Sequences

Here, we report the draft genome sequence of Aspergillus calidoustus (strain SF006504) . The functional annotation of A. calidoustus predicts a relatively large number of secondary metabolite gene clusters. The presented genome sequence builds the basis for further genome mining.

The diverse bioactivity of α-mangostin and its therapeutic implications

2021 ◽  
Vol 13 (19) ◽  
pp. 1679-1694
Author(s):  
Tejashri Chavan ◽  
Aaron Muth
Keyword(s):  
Biological Activity ◽  
Natural Product ◽  
Secondary Metabolite ◽  
Bacterial Growth ◽  
Biological Effects ◽  
Structural Features ◽  
Therapeutic Implications ◽  
Specific Disease ◽  
Disease States ◽  
Key Pathways

α-Mangostin is a xanthone natural product isolated as a secondary metabolite from the mangosteen tree. It has attracted a great deal of attention due to its wide-ranging effects on certain biological activity, such as apoptosis, tumorigenesis, proliferation, metastasis, inflammation, oxidation, bacterial growth and metabolism. This review focuses on the key pathways directly affected by α-mangostin and how this varies between disease states. Insight is also provided, where investigated, into the key structural features of α-mangostin that produce these biological effects. The review then sheds light on the utility of α-mangostin as a investigational tool for certain diseases and demonstrate how future derivatives may increase selectivity and potency for specific disease states.

Amruthapala (Decalepis arayalpathra (J. Joseph and V. Chandras.) Venter): A Comprehensive Review on Diversity, Therapeutic Uses, and Valorization of Bioactive Constituents

2019 ◽  
Vol 20 (5) ◽  
pp. 376-389 ◽  
Author(s):  
Sonali Mishra ◽  
Nupur Srivastava ◽  
Velusamy Sundaresan ◽  
Karuna Shanker
Keyword(s):  
Secondary Metabolite ◽  
Current Knowledge ◽  
Experimental Studies ◽  
Critical Discussion ◽  
Future Research ◽  
Bioactive Constituents ◽  
Medicinal Uses ◽  
Comprehensive Review ◽  
Therapeutic Uses ◽  
Decalepis Arayalpathra

Background: Decalepis arayalpathra (J. Joseph and V. Chandras.) Venter is used primarily for nutrition besides its therapeutic values. Traditional preparations/formulations from its tuber are used as a vitalizer and blood purifier drink. The folklore medicinal uses cover inflammation, cough, wound healing, antipyretic, and digestive system management. A comprehensive review of the current understanding of the plant is required due to emerging concerns over its safety and efficacy. Objective: The systematic collection of the authentic information from different sources with the critical discussion is summarised in order to address various issues related to botanical identity, therapeutic medicine, nutritional usage, phytochemical, and pharmacological potentials of the D. arayalpathra. Current use of traditional systems of medicine can be used to expand future research opportunities. Materials and Methods: Available scripted information was collected manually, from peered review research papers and international databases viz. Science Direct, Google Scholar, SciFinder, Scopus, etc. The unpublished resources which were not available in database were collected through the classical books of ‘Ayurveda’ and ‘Siddha’ published in regional languages. The information from books, Ph.D. and MSc dissertations, conference papers and government reports were also collected. We thoroughly screened the scripted information of classical books, titles, abstracts, reports, and full-texts of the journals to establish the reliability of the content. Results: Tuber bearing vanilla like signature flavor is due to the presence of 2-hydroxy-4-methoxybenzaldehyde (HMB). Among five other species, Decalepis arayalpathra (DA) has come under the ‘critically endangered’ category, due to over-exploitation for traditional, therapeutic and cool drink use. The experimental studies proved that it possesses gastro-protective, anti-tumor, and antiinflammatory activities. Some efforts were also made to develop better therapeutics by logical modifications in 2-Hydroxy-4-methoxy-benzaldehyde, which is a major secondary metabolite of D. arayalpathra. ‘Amruthapala’ offers the enormous opportunity to develop herbal drink with health benefits like gastro-protective, anti-oxidant and anti-inflammatory actions. Results: The plant has the potential to generate the investigational new lead (IND) based on its major secondary metabolite i.e. 2-Hydroxy-4-methoxy-benzaldehyde. The present mini-review summarizes the current knowledge on Decalepis arayalpathra, covering its phytochemical diversity, biological potentials, strategies for its conservation, and intellectual property rights (IPR) status. Chemical Compounds: 2-hydroxy-4-methoxybenzaldehyde (Pubchem CID: 69600), α-amyrin acetate (Pubchem CID: 293754), Magnificol (Pubchem CID: 44575983), β-sitosterol (Pubchem CID: 222284), 3-hydroxy-p-anisaldehyde (Pubchem CID: 12127), Naringenin (Pubchem CID: 932), Kaempferol (Pubchem CID: 5280863), Aromadendrin (Pubchem CID: 122850), 3-methoxy-1,2-cyclopentanedione (Pubchem CID: 61209), p-anisaldehyde (Pubchem CID: 31244), Menthyl acetate (Pubchem CID: 27867), Benzaldehyde (Pubchem CID: 240), p-cymene (Pubchem CID: 7463), Salicylaldehyde (Pubchem CID: 6998), 10-epi-γ-eudesmol (Pubchem CID: 6430754), α -amyrin (Pubchem CID: 225688), 3-hydroxy-4-methoxy benzaldehyde (Pubchem CID: 12127).

scholarly journals Chitin Degradation Machinery and Secondary Metabolite Profiles in the Marine Bacterium Pseudoalteromonas rubra S4059

Marine Drugs ◽  
2021 ◽  
Vol 19 (2) ◽  
pp. 108
Author(s):  
Xiyan Wang ◽  
Thomas Isbrandt ◽  
Mikael Lenz Strube ◽  
Sara Skøtt Paulsen ◽  
Maike Wennekers Nielsen ◽  
...  
Keyword(s):  
Secondary Metabolite ◽  
Genetic Manipulation ◽  
Genome Mining ◽  
Hydrolytic Enzymes ◽  
Metabolite Profile ◽  
Chitinolytic Enzyme ◽  
Chitin Degradation ◽  
Metabolite Profiles ◽  
Bioactive Potential ◽  
Pseudoalteromonas Rubra

Genome mining of pigmented Pseudoalteromonas has revealed a large potential for the production of bioactive compounds and hydrolytic enzymes. The purpose of the present study was to explore this bioactivity potential in a potent antibiotic and enzyme producer, Pseudoalteromonas rubra strain S4059. Proteomic analyses (data are available via ProteomeXchange with identifier PXD023249) indicated that a highly efficient chitin degradation machinery was present in the red-pigmented P. rubra S4059 when grown on chitin. Four GH18 chitinases and two GH20 hexosaminidases were significantly upregulated under these conditions. GH19 chitinases, which are not common in bacteria, are consistently found in pigmented Pseudoalteromonas, and in S4059, GH19 was only detected when the bacterium was grown on chitin. To explore the possible role of GH19 in pigmented Pseudoalteromonas, we developed a protocol for genetic manipulation of S4059 and deleted the GH19 chitinase, and compared phenotypes of the mutant and wild type. However, none of the chitin degrading ability, secondary metabolite profile, or biofilm-forming capacity was affected by GH19 deletion. In conclusion, we developed a genetic manipulation protocol that can be used to unravel the bioactive potential of pigmented pseudoalteromonads. An efficient chitinolytic enzyme cocktail was identified in S4059, suggesting that this strain could be a candidate with industrial potential.

scholarly journals Three-Dimensional Structures of Carbohydrates and Where to Find Them

2020 ◽  
Vol 21 (20) ◽  
pp. 7702 ◽  
Author(s):  
Sofya I. Scherbinina ◽  
Philip V. Toukach
Keyword(s):  
Experimental Data ◽  
Molecular Modeling ◽  
Computational Methods ◽  
Three Dimensional ◽  
Structural Diversity ◽  
Structural Data ◽  
Structural Features ◽  
Data Validation ◽  
Data Generation ◽  
Efficient Treatment

Analysis and systematization of accumulated data on carbohydrate structural diversity is a subject of great interest for structural glycobiology. Despite being a challenging task, development of computational methods for efficient treatment and management of spatial (3D) structural features of carbohydrates breaks new ground in modern glycoscience. This review is dedicated to approaches of chemo- and glyco-informatics towards 3D structural data generation, deposition and processing in regard to carbohydrates and their derivatives. Databases, molecular modeling and experimental data validation services, and structure visualization facilities developed for last five years are reviewed.

scholarly journals The Tripod for Bacterial Natural Product Discovery: Genome Mining, Silent Pathway Induction, and Mass Spectrometry-Based Molecular Networking

mSystems ◽  
2018 ◽  
Vol 3 (2) ◽  
Author(s):  
Daniela B. B. Trivella ◽  
Rafael de Felicio
Keyword(s):  
Mass Spectrometry ◽  
Natural Products ◽  
Natural Product ◽  
Biosynthetic Pathway ◽  
Genome Mining ◽  
Chemical Compounds ◽  
Gene Clusters ◽  
Tandem Mass ◽  
Molecular Networking ◽  
Natural Product Discovery

ABSTRACT Natural products are the richest source of chemical compounds for drug discovery. Particularly, bacterial secondary metabolites are in the spotlight due to advances in genome sequencing and mining, as well as for the potential of biosynthetic pathway manipulation to awake silent (cryptic) gene clusters under laboratory cultivation. Further progress in compound detection, such as the development of the tandem mass spectrometry (MS/MS) molecular networking approach, has contributed to the discovery of novel bacterial natural products. The latter can be applied directly to bacterial crude extracts for identifying and dereplicating known compounds, therefore assisting the prioritization of extracts containing novel natural products, for example. In our opinion, these three approaches—genome mining, silent pathway induction, and MS-based molecular networking—compose the tripod for modern bacterial natural product discovery and will be discussed in this perspective.

Sign in / Sign up

Export Citation Format

Share Document