# Recent Advances in the Heterologous Biosynthesis of Natural Products from _Streptomyces_
## 2 In Silico Prediction of BGCs  
Sequence analysis provides opportunities to produce novel secondary metabolites based on their genetic potential. The BGCs are chosen for their heterologous expression of the natural products by using bioinformatics tools. Nowadays, various bioinformatics tools are developed for analyzing the BGCs, such as antiSMASH [30], NaPDoS [31; 32], NRPSpredictor [33], ClusterFinder [34], PRISM [35], ClustScan [36], NP.searcher [37], EvoMining [38], ARTS [39], SBSPKS [40], BAGEL4 [41], RiPPER [42], NeuRiPP [43], RippMiner [44], and RODEO [45]. AntiSMASH, PRISM, and Clusterfinder are widely used to detect the secondary metabolite gene clusters. They are powerful tools for identifying the number of putative BGCs. These tools determine the BGCs of polyktetide synthase (PKS), nonribosomal peptide synthase (NRPS), hybrid, ribosomal synthesized and post-translationally modified peptide (RiPP), terpene, melanin, and siderophore [30; 34; 35]. For example, antiSMASH was used to identify the genome of _Streptomyces__actosus_ ATCC 25421, and the avermipeptin BGC achieved from that analysis was successfully expressed in _S. Iividans_ TK24 [46]. SBSPKS, NaPDoS, ClustScan, and NP.searcher focus on nonribosomal peptide and polyktetide biosynthetic pathways. SBSPKSv2 is a powerful web server. It facilitates the analysis and identification of not only NRPS/PKS domains but also other clusters with similar open reading frames (ORFs); three-dimensional modeling; chemical structure similarities; a simplified molecular-input line-entry system (SMILES) for starter, extender,intermediates, and final secondary metabolites; specificity prediction [40]. NaPDoS predicts and analyzes ketosynthase and the condensation domain from deoxyribonucleic acid (DNA) and protein sequences based on the domain phylogeny. This tool contributes to assessing the secondary metabolite gene diversity [31]. ClustScan and NP.searcher also predict NRPSs, PKSs, and hybrid NRPSs/PKSs. ClustScan can predict linear and cyclical structures of polyketides, while NP.searcher can predict the putative structure of both non-ribosomal peptides and polyketides. NRPSpredictor2 only works on NRPS to predict specific substrates of adenylation domains based on transductive support vector machines [33]. In contrast to PKS and NRPS BGCs, some RiPPs do not exhibit common genetic features for identification, where the gene encoding precursors are small in size and easily ignored [42]. Many bioinformatics tools were developed for predicting the precursor peptide sequences of RiPPs, such as BAGEL, RODEO, RiPPMiner, RiPPER, and NeuRiPP. BAGEL also enables the analysis of ORF predictions and facilitates discovering novel classes of peptides, and it is used to analyze small gene encoding for RiPPs [41]. RODEO mainly focuses on exploring certain RiPP classes [45]. RiPPMiner is an informatics tool for identifying the correct crosslink sequence in a core peptide of RiPPs [44]. RiPPER and NeuRiPP are new tools for identifying an RiPP precursor peptide family. The genes encoding for RiPP precursors are often missed in genome analysis. These tools are advantageous for predicting the novel RiPP classes because they identify precursor peptide events of unknown homology or novel RiPP structural classes [47]. Minimum Information about a BGC (MIBiG) is the global repository of microbial BGCs, which provides another useful resource for the accurate prediction and analysis of _Streptomyces_ BGCs. MBiG was established in 2015 with 1170 known BGCs; up to now, MBIGi contains 1923 known secondary metabolite BGCs [48; 49]. These resources provide new opportunities to discover _Streptomyces_ natural products using the bottom-up approach [1]. In addition to the exploration of unidentified or less studied resources, the metabolomics-based approach is based on reference compounds as potential biomarkers or the identification of molecular fingerprints that determine bioactivities has recently been used to identify new chemical diversities with versatile activities.