{"doi":"10.5772/intechopen.96749","title":"Metabolic Network Modeling for Rational Drug Design against <i>Candida albicans</i>","abstract":"<jats:p>The growing evidences of Candida albicans (C. albicans) infections are slowly becoming a threat to public health. Moreover, prevalence of antifungal resistant strains of C. albicans has emphasized the need for identification of potent targets for rational drug designing. In this aspect, traditional methods for target identification with validation have been found to be expensive and time-consuming. To overcome the concern, genome scale metabolic model construction provides a promising platform that allows novel target identification in combination with subtractive genome analysis. Thus, the chapter details current advancement in model construction, target identification and validation. In brief, it elucidates the overall strategies of C. albicans metabolome draft preparation, gap filling, curation of model, simulation followed by model validation, target identification and host pathogen interaction analysis. Finally, several examples of successful metabolic model construction and their utility in rational drug designing also have been discussed.</jats:p>","journal":"Infectious Diseases","year":2021,"id":672219,"datarank":0.10397207708399181,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"self_citation_contribution":0.10397207708399181,"citation_network_contribution":0.0,"self_endowment_contribution":0.10397207708399181,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1106120,"name":"Dibyabhaba Pradhan","orcid":"0000-0002-2459-5032","position":1,"is_corresponding":false},{"id":618880,"name":"Harpreet Singh","orcid":"0000-0003-1526-0916","position":2,"is_corresponding":false},{"id":1756273,"name":"Arun Kumar Jain","orcid":null,"position":3,"is_corresponding":false},{"id":1756274,"name":"Luqman Ahmad Khan","orcid":null,"position":4,"is_corresponding":false},{"id":1425446,"name":"Rashi Verma","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Metabolic Network Modeling for Rational Drug Design against <i>Candida albicans</i>","abstract":"<jats:p>The growing evidences of Candida albicans (C. albicans) infections are slowly becoming a threat to public health. Moreover, prevalence of antifungal resistant strains of C. albicans has emphasized the need for identification of potent targets for rational drug designing. In this aspect, traditional methods for target identification with validation have been found to be expensive and time-consuming. To overcome the concern, genome scale metabolic model construction provides a promising platform that allows novel target identification in combination with subtractive genome analysis. Thus, the chapter details current advancement in model construction, target identification and validation. In brief, it elucidates the overall strategies of C. albicans metabolome draft preparation, gap filling, curation of model, simulation followed by model validation, target identification and host pathogen interaction analysis. Finally, several examples of successful metabolic model construction and their utility in rational drug designing also have been discussed.</jats:p>","is_dataset_classified":null,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"19965766","pmcid":null,"openalex_id":"https://openalex.org/W3154231546","authors":[],"funders":[],"total_grants":0,"fwci":0.5428,"citation_percentile":0.60238273,"influential_citations":0,"citation_trend":[{"year":2024,"count":1}],"oa_status":"hybrid","license":"cc-by","oa_locations":[{"url":"https://doi.org/10.5772/intechopen.96749","host_type":"book series"},{"url":"https://doi.org/10.5772/intechopen.96749","host_type":"publisher"},{"url":"http://www.intechopen.com/download/pdf/76299","host_type":"publisher"},{"url":"http://www.intechopen.com/articles/show/title/metabolic-network-modeling-for-rational-drug-design-against-candida-albicans","host_type":"repository"}],"fields_of_study":["Microbial Metabolic Engineering and Bioproduction","Enzyme Catalysis and Immobilization","Microbial Natural Products and Biosynthesis"],"mesh_terms":[],"keywords":["Candida albicans","Identification (biology)","Computational biology","Rational design","Corpus albicans","Antifungal","Biology","Microbiology","Genetics"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Good health and well-being"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-16T08:11:07.239303Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}