{"product_id":"in-silico-strategies-for-prospective-drug-repositionings-hardcover","title":"In Silico Strategies for Prospective Drug Repositionings - Hardcover","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eLucreția Udrescu\u003c\/b\u003e (Guest Editor), \u003cb\u003eLudovic Kurunczi\u003c\/b\u003e (Guest Editor), \u003cb\u003ePaul Bogdan\u003c\/b\u003e (Guest Editor)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eThe discovery of new drugs is one of pharmaceutical research's most exciting and challenging tasks. Unfortunately, the conventional drug discovery procedure is chronophagous and seldom successful; furthermore, new drugs are needed to address our clinical challenges (e.g., new antibiotics, new anticancer drugs, new antivirals).\u003c\/p\u003e\u003cp\u003eWithin this framework, drug repositioning-finding new pharmacodynamic properties for already approved drugs-becomes a worthy drug discovery strategy.\u003c\/p\u003e\u003cp\u003eRecent drug discovery techniques combine traditional tools with in silico strategies to identify previously unaccounted properties for drugs already in use. Indeed, big data exploration techniques capitalize on the ever-growing knowledge of drugs' structural and physicochemical properties, drug-target and drug-drug interactions, advances in human biochemistry, and the latest molecular and cellular biology discoveries.\u003c\/p\u003e\u003cp\u003eFollowing this new and exciting trend, this book is a collection of papers introducing innovative computational methods to identify potential candidates for drug repositioning. Thus, the papers in the Special Issue \u003cem\u003eIn Silico Strategies for Prospective Drug Repositionings\u003c\/em\u003e introduce a wide array of in silico strategies such as complex network analysis, big data, machine learning, molecular docking, molecular dynamics simulation, and QSAR; these strategies target diverse diseases and medical conditions: COVID-19 and post-COVID-19 pulmonary fibrosis, non-small lung cancer, multiple sclerosis, toxoplasmosis, psychiatric disorders, or skin conditions.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 288\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.94 x 9.61 x 6.69 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e January 04, 2023\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":53207999119667,"sku":"9783036561349","price":109.44,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0300\/5595\/6612\/files\/00jc4PQEyn9783036561349_f235db21-7934-4535-82f9-0e48e2ff2775.webp?v=1775643723","url":"https:\/\/www.vysn.com\/en-ca\/products\/in-silico-strategies-for-prospective-drug-repositionings-hardcover","provider":"VYSN","version":"1.0","type":"link"}