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Current Status of Computer-Aided Drug Design for Type 2 Diabetes

View Article: PubMed Central

ABSTRACT

Background: Diabetes is a metabolic disorder that requires multiple therapeutic approaches. The pancreas loses its functionality to properly produce the insulin hormone in patients with diabetes mellitus. In 2012, more than one million people worldwide died as a result of diabetes, which was the eighth leading cause of death.

Objective: Most drugs currently available and approved by the U.S. Food and Drug Administration cannot reach an adequate level of glycemic control in diabetic patients, and have many side effects; thus, new classes of compounds are required. Efforts based on computer-aided drug design (CADD) can mine a large number of databases to produce new and potent hits and minimize the requirement of time and dollars for new discoveries.

Methods: Pharmaceutical sciences have made progress with advances in drug design concepts. Virtual screening of large databases is most compatible with different computational methods such as molecular docking, pharmacophore, quantitative structure-activity relationship, and molecular dynamic simulation. Contribution of these methods in selection of antidiabetic compounds has been discussed.

Results: The Computer-Aided Drug Design (CADD) approach has contributed to successful discovery of novel anti-diabetic agents. This mini-review focuses on CADD approach on currently approved drugs and new therapeutic agents-in-development that may achieve suitable glucose levels and decrease the risk of hypoglycemia, which is a major obstacle to glucose control and a special concern for therapies that increase insulin levels.

Conclusion: Drug design and development for type 2 diabetes have been actively studied. However, a large number of antidiabetic drugs are still in early stages of development. The conventional target- and structure-based approaches can be regarded as part of the efforts toward therapeutic mechanism-based drug design for treatment of type 2 diabetes. It is expected that further improvement in CADD approach will enhance the new discoveries.

No MeSH data available.


Schematic representation of protein secondary structure complex used in the case studies. (A) Crystallographic structure of GK complexed with 6-({(2S)-3-cyclopentyl-2-[4-(trifluoromethyl)- 1H-imidazol-1-yl]propanoyl}amino)pyridine- 3-carboxylic acid molecule (PDB id: 3VF6, 1.86 Å). (B) The crystal structure of murine 11β-HSD1 complexed with corticosterone molecule (PDB id: 1Y5R, 3.0 Å). (C) Crystallographic structure of DPP-IV complexed with 5-aminomethyl-6-(2,4-dichloro-phenyl)-2-(3,5-dimethoxy-phenyl)-pyrimidin-4-ylamine (PDB id: 1RWQ, 2.2 Å). (D) Crystallographic structure of PTP1B complexed with bis (Para-Phosphophenyl) methane (BPPM) molecule (PDB id: 1AAX, 1.9 Å). (E) Crystallographic structure of PTP1B complexed with bis (Para-Phosphophenyl) methane (BPPM) molecule (PDB id: 1AAX, 1.9 Å).
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Figure 6: Schematic representation of protein secondary structure complex used in the case studies. (A) Crystallographic structure of GK complexed with 6-({(2S)-3-cyclopentyl-2-[4-(trifluoromethyl)- 1H-imidazol-1-yl]propanoyl}amino)pyridine- 3-carboxylic acid molecule (PDB id: 3VF6, 1.86 Å). (B) The crystal structure of murine 11β-HSD1 complexed with corticosterone molecule (PDB id: 1Y5R, 3.0 Å). (C) Crystallographic structure of DPP-IV complexed with 5-aminomethyl-6-(2,4-dichloro-phenyl)-2-(3,5-dimethoxy-phenyl)-pyrimidin-4-ylamine (PDB id: 1RWQ, 2.2 Å). (D) Crystallographic structure of PTP1B complexed with bis (Para-Phosphophenyl) methane (BPPM) molecule (PDB id: 1AAX, 1.9 Å). (E) Crystallographic structure of PTP1B complexed with bis (Para-Phosphophenyl) methane (BPPM) molecule (PDB id: 1AAX, 1.9 Å).

Mentions: Inhibition of dipeptidyl peptidase-IV (DPP-IV) does not cause weight gain, hypoglycemia and exhaustion of beta cells, and it has emerged as a promising approach for the treatment of patients with type 2 diabetes [56]. DPP-IV stimulates glucose dependent insulin release and suppression of elevated glucagon levels by prolonging the half-life of endogenous GLP-1. Recently, several DPP-IV inhibitors have been approved in the U.S. and Europe (Table 1). The withdrawal of glitazones from the market as well as concerns related to usage of sitagliptin raised a concern about long-term use of new anti-diabetic drugs. Previous knowledge has been used as a requirement to develop novel and safe clinical candidates for the treatment of type 2 diabetes using a structure-based virtual screening technique. Screening of the MDPI database was performed using structure-based virtual screening tools to identify DPP-IV inhibitors. The crystal structure of DPP-IV (PDB id: 1RWQ) was available in a protein drug bank [57] shown in Fig. 6 (C). After filtration of compounds from the MDPI database, docking operations were performed by Glide [32, 58], using three consecutive protocols: virtual high throughput screening, standard precision and extra precision docking. Docking results were further validated by redocking on DPP-IV enzyme using GOLD [33] software and select best hits for biological evaluation. Three of them were active at low μM concentrations. The 3-(1-hydrazinyl-1-(phenylamino) ethyl)-4-hydroxy-1-methylquinolin-2(1H)-one was most potent hit with an IC50 of 0.73 μM shown in Fig. 4. These compounds were then evaluated for their glucose-lowering effects in glucose-fed hyperglycemic female Wistar rats and confirmed to be potential anti-diabetic agents [59].


Current Status of Computer-Aided Drug Design for Type 2 Diabetes
Schematic representation of protein secondary structure complex used in the case studies. (A) Crystallographic structure of GK complexed with 6-({(2S)-3-cyclopentyl-2-[4-(trifluoromethyl)- 1H-imidazol-1-yl]propanoyl}amino)pyridine- 3-carboxylic acid molecule (PDB id: 3VF6, 1.86 Å). (B) The crystal structure of murine 11β-HSD1 complexed with corticosterone molecule (PDB id: 1Y5R, 3.0 Å). (C) Crystallographic structure of DPP-IV complexed with 5-aminomethyl-6-(2,4-dichloro-phenyl)-2-(3,5-dimethoxy-phenyl)-pyrimidin-4-ylamine (PDB id: 1RWQ, 2.2 Å). (D) Crystallographic structure of PTP1B complexed with bis (Para-Phosphophenyl) methane (BPPM) molecule (PDB id: 1AAX, 1.9 Å). (E) Crystallographic structure of PTP1B complexed with bis (Para-Phosphophenyl) methane (BPPM) molecule (PDB id: 1AAX, 1.9 Å).
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Figure 6: Schematic representation of protein secondary structure complex used in the case studies. (A) Crystallographic structure of GK complexed with 6-({(2S)-3-cyclopentyl-2-[4-(trifluoromethyl)- 1H-imidazol-1-yl]propanoyl}amino)pyridine- 3-carboxylic acid molecule (PDB id: 3VF6, 1.86 Å). (B) The crystal structure of murine 11β-HSD1 complexed with corticosterone molecule (PDB id: 1Y5R, 3.0 Å). (C) Crystallographic structure of DPP-IV complexed with 5-aminomethyl-6-(2,4-dichloro-phenyl)-2-(3,5-dimethoxy-phenyl)-pyrimidin-4-ylamine (PDB id: 1RWQ, 2.2 Å). (D) Crystallographic structure of PTP1B complexed with bis (Para-Phosphophenyl) methane (BPPM) molecule (PDB id: 1AAX, 1.9 Å). (E) Crystallographic structure of PTP1B complexed with bis (Para-Phosphophenyl) methane (BPPM) molecule (PDB id: 1AAX, 1.9 Å).
Mentions: Inhibition of dipeptidyl peptidase-IV (DPP-IV) does not cause weight gain, hypoglycemia and exhaustion of beta cells, and it has emerged as a promising approach for the treatment of patients with type 2 diabetes [56]. DPP-IV stimulates glucose dependent insulin release and suppression of elevated glucagon levels by prolonging the half-life of endogenous GLP-1. Recently, several DPP-IV inhibitors have been approved in the U.S. and Europe (Table 1). The withdrawal of glitazones from the market as well as concerns related to usage of sitagliptin raised a concern about long-term use of new anti-diabetic drugs. Previous knowledge has been used as a requirement to develop novel and safe clinical candidates for the treatment of type 2 diabetes using a structure-based virtual screening technique. Screening of the MDPI database was performed using structure-based virtual screening tools to identify DPP-IV inhibitors. The crystal structure of DPP-IV (PDB id: 1RWQ) was available in a protein drug bank [57] shown in Fig. 6 (C). After filtration of compounds from the MDPI database, docking operations were performed by Glide [32, 58], using three consecutive protocols: virtual high throughput screening, standard precision and extra precision docking. Docking results were further validated by redocking on DPP-IV enzyme using GOLD [33] software and select best hits for biological evaluation. Three of them were active at low μM concentrations. The 3-(1-hydrazinyl-1-(phenylamino) ethyl)-4-hydroxy-1-methylquinolin-2(1H)-one was most potent hit with an IC50 of 0.73 μM shown in Fig. 4. These compounds were then evaluated for their glucose-lowering effects in glucose-fed hyperglycemic female Wistar rats and confirmed to be potential anti-diabetic agents [59].

View Article: PubMed Central

ABSTRACT

Background: Diabetes is a metabolic disorder that requires multiple therapeutic approaches. The pancreas loses its functionality to properly produce the insulin hormone in patients with diabetes mellitus. In 2012, more than one million people worldwide died as a result of diabetes, which was the eighth leading cause of death.

Objective: Most drugs currently available and approved by the U.S. Food and Drug Administration cannot reach an adequate level of glycemic control in diabetic patients, and have many side effects; thus, new classes of compounds are required. Efforts based on computer-aided drug design (CADD) can mine a large number of databases to produce new and potent hits and minimize the requirement of time and dollars for new discoveries.

Methods: Pharmaceutical sciences have made progress with advances in drug design concepts. Virtual screening of large databases is most compatible with different computational methods such as molecular docking, pharmacophore, quantitative structure-activity relationship, and molecular dynamic simulation. Contribution of these methods in selection of antidiabetic compounds has been discussed.

Results: The Computer-Aided Drug Design (CADD) approach has contributed to successful discovery of novel anti-diabetic agents. This mini-review focuses on CADD approach on currently approved drugs and new therapeutic agents-in-development that may achieve suitable glucose levels and decrease the risk of hypoglycemia, which is a major obstacle to glucose control and a special concern for therapies that increase insulin levels.

Conclusion: Drug design and development for type 2 diabetes have been actively studied. However, a large number of antidiabetic drugs are still in early stages of development. The conventional target- and structure-based approaches can be regarded as part of the efforts toward therapeutic mechanism-based drug design for treatment of type 2 diabetes. It is expected that further improvement in CADD approach will enhance the new discoveries.

No MeSH data available.