FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4312217681> ?p ?o ?g. }

• W4312217681 abstract "Computer-aided drug designing is a promising approach to defeating the dry pipeline of drug discovery. It aims at reduced experimental efforts with cost-effectiveness. Naturally occurring large molecules with molecular weight higher than 500 Dalton such as cationic peptides, cyclic peptides, glycopeptides and lipopeptides are a few examples of large molecules which have successful applications as the broad spectrum antibacterial, anticancer, antiviral, antifungal and antithrombotic drugs. Utilization of microbial metabolites as potential drug candidates incur cost effectiveness through large scale production of such molecules rather than a synthetic approach. Computational studies on such compounds generate tremendous possibilities to develop novel leads with challenges to handle these complex molecules with available computational tools. The opportunities begin with the desired structural modifications in the parent drug molecule. Virtual modifications followed by molecular interaction studies at the target site through molecular modeling simulations and identification of structure-activity relationship models to develop more prominent and potential drug molecules. Lead optimization studies to develop novel compounds with increased specificity and reduced off targeting is a big challenge computationally for large molecules. Prediction of optimized pharmacokinetic properties facilitates development of a compound with lower toxicity as compared to the natural compounds. Generating the library of compounds and studies for target specificity and ADMET (Absorption, Distribution, Metabolism, Excretion and Toxicity) for large molecules are laborious and incur huge cost and chemical wastage through in-vitro methods. Hence, computational methods need to be explored to develop novel compounds from natural large molecules with higher specificity. This review article is focusing on possible challenges and opportunities in the pathway of computer-aided drug discovery of large molecule therapeutics." @default.
• W4312217681 created "2023-01-04" @default.
• W4312217681 creator A5023393332 @default.
• W4312217681 creator A5071837638 @default.
• W4312217681 date "2022-12-20" @default.
• W4312217681 modified "2023-09-30" @default.
• W4312217681 title "Opportunistic Challenges of Computer-aided Drug Discovery of Lipopeptides: New Insights for Large Molecule Therapeutics" @default.
• W4312217681 cites W1577207729 @default.
• W4312217681 cites W1844502413 @default.
• W4312217681 cites W1860382351 @default.
• W4312217681 cites W1963509429 @default.
• W4312217681 cites W1965694039 @default.
• W4312217681 cites W1975447903 @default.
• W4312217681 cites W1977694121 @default.
• W4312217681 cites W1981987799 @default.
• W4312217681 cites W1988710527 @default.
• W4312217681 cites W1989784369 @default.
• W4312217681 cites W1989814214 @default.
• W4312217681 cites W1992450378 @default.
• W4312217681 cites W1997325165 @default.
• W4312217681 cites W1999642796 @default.
• W4312217681 cites W2001827734 @default.
• W4312217681 cites W2008173042 @default.
• W4312217681 cites W2009933778 @default.
• W4312217681 cites W2017793317 @default.
• W4312217681 cites W2019054625 @default.
• W4312217681 cites W2031390939 @default.
• W4312217681 cites W2033882981 @default.
• W4312217681 cites W2039978498 @default.
• W4312217681 cites W2045478673 @default.
• W4312217681 cites W2050000500 @default.
• W4312217681 cites W2054070723 @default.
• W4312217681 cites W2060581674 @default.
• W4312217681 cites W2064705056 @default.
• W4312217681 cites W2066364629 @default.
• W4312217681 cites W2068351024 @default.
• W4312217681 cites W2081665565 @default.
• W4312217681 cites W2090288316 @default.
• W4312217681 cites W2100947872 @default.
• W4312217681 cites W2105649494 @default.
• W4312217681 cites W2112411768 @default.
• W4312217681 cites W2118571345 @default.
• W4312217681 cites W2119306425 @default.
• W4312217681 cites W2125426232 @default.
• W4312217681 cites W2131192673 @default.
• W4312217681 cites W2137992445 @default.
• W4312217681 cites W2151389386 @default.
• W4312217681 cites W2154708789 @default.
• W4312217681 cites W2195266655 @default.
• W4312217681 cites W2410925385 @default.
• W4312217681 cites W2522332139 @default.
• W4312217681 cites W2530826395 @default.
• W4312217681 cites W2549608367 @default.
• W4312217681 cites W2566470886 @default.
• W4312217681 cites W2566499580 @default.
• W4312217681 cites W2586724023 @default.
• W4312217681 cites W2595851904 @default.
• W4312217681 cites W2724823461 @default.
• W4312217681 cites W2737732597 @default.
• W4312217681 cites W2739980134 @default.
• W4312217681 cites W2745913634 @default.
• W4312217681 cites W2748645000 @default.
• W4312217681 cites W2766605359 @default.
• W4312217681 cites W2769533173 @default.
• W4312217681 cites W2780474114 @default.
• W4312217681 cites W2784348652 @default.
• W4312217681 cites W2793900929 @default.
• W4312217681 cites W2800027457 @default.
• W4312217681 cites W2800677598 @default.
• W4312217681 cites W2802653208 @default.
• W4312217681 cites W2805720704 @default.
• W4312217681 cites W2807152882 @default.
• W4312217681 cites W2888386703 @default.
• W4312217681 cites W2890850288 @default.
• W4312217681 cites W2901719664 @default.
• W4312217681 cites W2911608373 @default.
• W4312217681 cites W2937307539 @default.
• W4312217681 cites W2945669687 @default.
• W4312217681 cites W2945779280 @default.
• W4312217681 cites W2949718649 @default.
• W4312217681 cites W2990363083 @default.
• W4312217681 cites W853235284 @default.
• W4312217681 cites W936159182 @default.
• W4312217681 doi "https://doi.org/10.18502/ajmb.v15i1.11419" @default.
• W4312217681 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36789119" @default.
• W4312217681 hasPublicationYear "2022" @default.
• W4312217681 type Work @default.
• W4312217681 citedByCount "0" @default.
• W4312217681 crossrefType "journal-article" @default.
• W4312217681 hasAuthorship W4312217681A5023393332 @default.
• W4312217681 hasAuthorship W4312217681A5071837638 @default.
• W4312217681 hasBestOaLocation W43122176812 @default.
• W4312217681 hasConcept C103697762 @default.
• W4312217681 hasConcept C161624437 @default.
• W4312217681 hasConcept C185592680 @default.
• W4312217681 hasConcept C21951064 @default.
• W4312217681 hasConcept C2780035454 @default.
• W4312217681 hasConcept C41008148 @default.
• W4312217681 hasConcept C55493867 @default.
• W4312217681 hasConcept C69366308 @default.

• next