Computational Drug Designing and Prediction Of Important Parameters Using in silico Methods- A Review
Copyright© Bentham Science Publishers; For any queries, please email at epubbenthamscience.net..
BACKGROUND: Computational or in silico studies are undertaken to assess the drug like properties of lead compounds. These studies help in fast prediction of relevant properties.
OBJECTIVE: Through this review, an effort is made to encapsulate some of the important parameters which should be met by a compound for it to be considered as a potential drug candidate along with an overview of automated softwares which can be used for making various predictions.
METHODS: Drug uptake, its absorption, evacuation and associated hazardous effects are important factors for consideration in drug designing and should be known in early stages of drug development. Several important physicochemical properties like molecular weight, polar surface area (PSA), molecular flexibility etc. have to be taken into consideration in drug designing. Toxicological assessment is another important aspect of drug discovery which predicts the safety and adverse effects of a drug.
RESULTS: Additionally, bioactivity scores of probable drug leads against various human receptors can also be predicted to evaluate the probability of them to act as a potential drug candidate. The in vivo biological targets of a molecule can also be efficiently predicted by molecular docking studies.
CONCLUSION: Some important software like iGEMDOCK, AutoDock, OSIRIS property explorer, Molinspiration, MetaPrint2D, admetSAR and their working methodology and principle of working have been summarized in this review.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2019 |
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| Erschienen: |
2019 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:15 |
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| Enthalten in: |
Current computer-aided drug design - 15(2019), 5 vom: 27., Seite 384-397 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Khan, Tahmeena [VerfasserIn] |
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| Links: |
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| Themen: |
Bioactivity |
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| Anmerkungen: |
Date Completed 24.02.2020 Date Revised 24.02.2020 published: Print Citation Status MEDLINE |
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| doi: |
10.2174/1573399815666190326120006 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM295363541 |
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| 500 | |a Date Revised 24.02.2020 | ||
| 500 | |a published: Print | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright© Bentham Science Publishers; For any queries, please email at epubbenthamscience.net. | ||
| 520 | |a BACKGROUND: Computational or in silico studies are undertaken to assess the drug like properties of lead compounds. These studies help in fast prediction of relevant properties | ||
| 520 | |a OBJECTIVE: Through this review, an effort is made to encapsulate some of the important parameters which should be met by a compound for it to be considered as a potential drug candidate along with an overview of automated softwares which can be used for making various predictions | ||
| 520 | |a METHODS: Drug uptake, its absorption, evacuation and associated hazardous effects are important factors for consideration in drug designing and should be known in early stages of drug development. Several important physicochemical properties like molecular weight, polar surface area (PSA), molecular flexibility etc. have to be taken into consideration in drug designing. Toxicological assessment is another important aspect of drug discovery which predicts the safety and adverse effects of a drug | ||
| 520 | |a RESULTS: Additionally, bioactivity scores of probable drug leads against various human receptors can also be predicted to evaluate the probability of them to act as a potential drug candidate. The in vivo biological targets of a molecule can also be efficiently predicted by molecular docking studies | ||
| 520 | |a CONCLUSION: Some important software like iGEMDOCK, AutoDock, OSIRIS property explorer, Molinspiration, MetaPrint2D, admetSAR and their working methodology and principle of working have been summarized in this review | ||
| 650 | 4 | |a Journal Article | |
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| 700 | 1 | |a Joshi, Seema |e verfasserin |4 aut | |
| 700 | 1 | |a Khan, Abdul Rahman |e verfasserin |4 aut | |
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