Designing drug candidates for rare diseases

Rare diseases, because of their nature are given less attention and as a result patients with such diseases have to undergo lot of hurdles to get proper treatment, even if any such treatment is available. There are several rare diseases for which no treatment is readily available and even it is ava...

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Main Author: Noorbatcha, Ibrahim Ali
Format: Conference or Workshop Item
Language:English
English
English
Published: 2012
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Online Access:http://irep.iium.edu.my/28253/2/Appointment__Dr_Ibrahim_SciCo_CADD2012.pdf
http://irep.iium.edu.my/28253/4/ProgramCADD2012_V12.pdf
http://irep.iium.edu.my/28253/1/CADD2012_RareDisease_Ibrahim_presentation.pptx
http://irep.iium.edu.my/28253/
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spelling my.iium.irep.282532014-01-15T01:29:30Z http://irep.iium.edu.my/28253/ Designing drug candidates for rare diseases Noorbatcha, Ibrahim Ali TP248.13 Biotechnology Rare diseases, because of their nature are given less attention and as a result patients with such diseases have to undergo lot of hurdles to get proper treatment, even if any such treatment is available. There are several rare diseases for which no treatment is readily available and even it is available, the treatment process is very expensive. Lysosomal storage disease is one of the rare diseases which have been proven to be fatal if not treated properly. Acid β-glucosidase (GlcCerase) is a lysosomal enzyme, which is important in biodegradation of blood cells in human body. Mutation of GlcCerase will lead to Gaucher disease; the most common lysosomal storage disease. Presently, two treatments are available for Gaucher disease patients. The first treatment is by enzyme replacement therapy using recombinant human GlcCerase (CerezymeTM) expressed in Chinese hamster ovary cells. The second treatment is by substrate reduction therapy, in which partial inhibition of glycosphingolipid synthesis is carried out (NBDNJ; ZavescaTM). Current treatment for Gaucher disease is costly. According to available data, the current treatment for Gaucher disease patients is can reach up to US$16,800 for every two weeks. Adding up to the problem, this enzyme replacement therapy, requires high dosage which will increase the overall cost for the treatment. These problems may lead to suffering of Gaucher disease patient which cannot afford the high cost treatment. To rectify the problem, new drugs with lower cost should be designed as an alternative for Gaucher disease patient. With the help of computational molecular modeling, new drug candidate for Gaucher disease treatment can be designed. In this research, we have designed a lead-candidate to act as a potential inhibitor, as a part of substrate reduction therapy for Gaucher disease by using computational docking approach. Lamarckian genetic algorithm is used to locate the potential inhibitor sites in the acid β-glucosidase and strength of the binding is evaluated using potential mean force (PMF) scores. Good correlation between experimental inhibition constant (Ki) and computational binding score is established with the correlation coefficient of 0.782. This correlation can be used to predict the unknown Ki value of the new ligand. 2012 Conference or Workshop Item REM application/pdf en http://irep.iium.edu.my/28253/2/Appointment__Dr_Ibrahim_SciCo_CADD2012.pdf application/pdf en http://irep.iium.edu.my/28253/4/ProgramCADD2012_V12.pdf application/pdf en http://irep.iium.edu.my/28253/1/CADD2012_RareDisease_Ibrahim_presentation.pptx Noorbatcha, Ibrahim Ali (2012) Designing drug candidates for rare diseases. In: Computer Aided Drug Design Seminar cum Workshop 2012 (CADD 2012), 3-7 December 2012, Puncak Alam, Selangor. (Unpublished)
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
English
English
topic TP248.13 Biotechnology
spellingShingle TP248.13 Biotechnology
Noorbatcha, Ibrahim Ali
Designing drug candidates for rare diseases
description Rare diseases, because of their nature are given less attention and as a result patients with such diseases have to undergo lot of hurdles to get proper treatment, even if any such treatment is available. There are several rare diseases for which no treatment is readily available and even it is available, the treatment process is very expensive. Lysosomal storage disease is one of the rare diseases which have been proven to be fatal if not treated properly. Acid β-glucosidase (GlcCerase) is a lysosomal enzyme, which is important in biodegradation of blood cells in human body. Mutation of GlcCerase will lead to Gaucher disease; the most common lysosomal storage disease. Presently, two treatments are available for Gaucher disease patients. The first treatment is by enzyme replacement therapy using recombinant human GlcCerase (CerezymeTM) expressed in Chinese hamster ovary cells. The second treatment is by substrate reduction therapy, in which partial inhibition of glycosphingolipid synthesis is carried out (NBDNJ; ZavescaTM). Current treatment for Gaucher disease is costly. According to available data, the current treatment for Gaucher disease patients is can reach up to US$16,800 for every two weeks. Adding up to the problem, this enzyme replacement therapy, requires high dosage which will increase the overall cost for the treatment. These problems may lead to suffering of Gaucher disease patient which cannot afford the high cost treatment. To rectify the problem, new drugs with lower cost should be designed as an alternative for Gaucher disease patient. With the help of computational molecular modeling, new drug candidate for Gaucher disease treatment can be designed. In this research, we have designed a lead-candidate to act as a potential inhibitor, as a part of substrate reduction therapy for Gaucher disease by using computational docking approach. Lamarckian genetic algorithm is used to locate the potential inhibitor sites in the acid β-glucosidase and strength of the binding is evaluated using potential mean force (PMF) scores. Good correlation between experimental inhibition constant (Ki) and computational binding score is established with the correlation coefficient of 0.782. This correlation can be used to predict the unknown Ki value of the new ligand.
format Conference or Workshop Item
author Noorbatcha, Ibrahim Ali
author_facet Noorbatcha, Ibrahim Ali
author_sort Noorbatcha, Ibrahim Ali
title Designing drug candidates for rare diseases
title_short Designing drug candidates for rare diseases
title_full Designing drug candidates for rare diseases
title_fullStr Designing drug candidates for rare diseases
title_full_unstemmed Designing drug candidates for rare diseases
title_sort designing drug candidates for rare diseases
publishDate 2012
url http://irep.iium.edu.my/28253/2/Appointment__Dr_Ibrahim_SciCo_CADD2012.pdf
http://irep.iium.edu.my/28253/4/ProgramCADD2012_V12.pdf
http://irep.iium.edu.my/28253/1/CADD2012_RareDisease_Ibrahim_presentation.pptx
http://irep.iium.edu.my/28253/
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