Exploring the origin of phosphodiesterase inhibition via proteochemometric modeling

Rasti, Behnam; Schaduangrat, Nalini; Shahangian, S. Shirin; Nantasenamat, Chanin

doi:10.1039/c7ra02332d

Cited by 10 publications

(6 citation statements)

References 60 publications

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“…As the great positive impact of the GRINDs on PCM modeling and their informative structural aspects in inhibitor design have been already shown, we applied these MIF‐based type of descriptors to explore the origin of TS inhibition. DRY, N1, O, and TIP probes were used to produce MIFs followed by calculation of GRid‐INdependent Descriptors.…”

Section: Resultsmentioning

confidence: 99%

“…[1] So far, PCM has been successfully applied with regard to many protein families including G proteincoupled receptors, [2,3] proteases, [4,5] kinases, [6][7][8] cytochrome P450, [9,10] carbonic anhydrase, [11,12] and phosphodiesterase. [13] Inhibition of folate-dependent enzymes, including thymidylate synthase (TS) and dihydrofolate reductase (DHFR), has long been considered as a promising strategy for the treatment of hyperproliferative disorders such as cancer and infectious diseases. [14] TS catalyzes the reductive methylation of deoxyuridylate (dUMP) to deoxythymidylate (dTMP).…”

Section: Introductionmentioning

confidence: 99%

“…As an extension of the traditional quantitative structure–activity relationship (QSAR) models, proteochemometrics (PCM) is a ligand‐target modeling approach, where the bioactivity of multiple ligands against multiple proteins is modeled simultaneously to analyze the interaction space of ligands across protein targets . So far, PCM has been successfully applied with regard to many protein families including G protein‐coupled receptors, proteases, kinases, cytochrome P450, carbonic anhydrase, and phosphodiesterase . Inhibition of folate‐dependent enzymes, including thymidylate synthase (TS) and dihydrofolate reductase (DHFR), has long been considered as a promising strategy for the treatment of hyperproliferative disorders such as cancer and infectious diseases .…”

Section: Introductionmentioning

confidence: 99%

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Proteochemometric modeling of the origin of thymidylate synthase inhibition

Rasti

Shahangian

2018

Chem Biol Drug Des

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Due to its crucial role in DNA synthesis, thymidylate synthase (TS) has been considered as a potential therapeutic target. Inhibition of the enzyme is a promising strategy for the treatment of some hyperproliferative diseases, including infections. As TS species-specific inhibitors would be able to distinguish between the host and the pathogens, developing highly selective inhibitors is of great clinical importance. TS is among the most highly conserved enzymes over evolutionary history, making the design of its species-selective inhibitor significantly challenging. The chemical interaction space, governed by a set of non-selective TS inhibitors, has been explored for human TS and its homologous proteins in both Toxoplasma gondii and Escherichia coli using proteochemometrics modeling (PCM). Validity, robustness, and prediction power of the PCM model have been assessed applying a diverse set of internal/external validation approaches. Our PCM model has provided major structural information, which is indeed of great help to design new TS species-specific inhibitors with the simultaneous inhibition ability toward both T. gondii and E. coli. To show applicability of the PCM model, new compounds have been designed based on structural information provided by the constructed model. Final results have been very promising with regard to selectivity ratios of the designed compounds for different TS isoforms, confirming the applicability of the PCM model.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Proteochemometric modeling of the origin of thymidylate synthase inhibition

Rasti

Shahangian

2018

Chem Biol Drug Des

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“…One major strength of PCM is that it does not require structural information of proteins to provide specific information about their functions . Since its first introduction by Lapinsh et al in 2001, the approach has been successfully applied to investigate different protein families such as cytochrome P450, kinases, melanocortin receptors, G protein‐coupled receptors, HIV proteases, aromatases, carbonic anhydrases, and phosphodiesterases . Herein, we have applied a unified PCM model to investigate the interaction space and selectivity of a set of inhibitors toward different families of DHFR.…”

Section: Introductionmentioning

confidence: 99%

Probing the origin of dihydrofolate reductase inhibition via proteochemometric modeling

Hariri

Ghasemi

Shirini

et al. 2018

Journal of Chemometrics

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Dihydrofolate reductase (DHFR) is an essential enzyme in the folate metabolism pathway and an important target of antineoplastic, antimicrobial, antiprotozoal, and antiinflammatory drugs. Despite the clinical effectiveness of current antifolate treatments, new drugs are needed to be designed due to developing resistance of this enzyme through multiple‐site mutagenesis. Understanding the factors affecting the ligand binding selectivity profiles among DHFR families is critical for the design of novel potent and selective inhibitors, with the least side effects, against DHFR of pathogens. Hybrid scaffolds containing pyrimidine ring are effective in DHFR inhibition. In this study, using proteochemometric (PCM) modeling, we designed and evaluated new potent pyrimidine scaffold‐based inhibitors via 3‐dimensional alignment‐free GRid‐INdependent Descriptors (GRIND), VolSurf molecular, and sequence‐based (z‐scale) descriptors to provide ligand and receptor descriptors, respectively. Validation and robustness of the model were confirmed by venetian blinds cross‐validation and Y‐scrambling approaches, respectively. Applicability domain (AD) analysis was performed to estimate the likelihood of reliable prediction for compounds. To show the applicability of the PCM model, new ligands were designed using structural data retrieved from this model. Inhibitory activities of the designs were then predicted, and selectivity ratio profiles were investigated. Finally, potent and highly selective inhibitors were identified regarding the protozoan parasite Toxoplasma gondii, followed by evaluating the ADMET parameters of the ligands.

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“…To investigate the selectivity, proteochemometrics (PCM) approach can be applied since it considers interaction space of different ligands across multiple receptors ( 13 ). PCM investigations have so far shed light on valuable information regarding major protein families such as G protein-coupled receptors ( 14 ), proteases ( 15 ), thymidylate synthase ( 16 ), cytochrome P450 ( 17 ), CA ( 18 19 ) and phosphodiesterase ( 20 ). In the present study, we have developed a PCM model in which we applied different combinations of z-scale and molecular interaction field (MIF) based descriptors to investigate the chemical interaction space between six isoforms of CA and a series of sulfonamide-derivatives inhibitors.…”

Section: Introductionmentioning

confidence: 99%

Probing the chemical interaction space governed by 4-amino-substituted benzenesulfonamides and carbonic anhydrase isoforms

Rasti¹,

Heravi²

2018

Res Pharma Sci

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Isoform diversity, critical physiological roles and involvement in major diseases/disorders such as glaucoma, epilepsy, Alzheimer's disease, obesity, and cancers have made carbonic anhydrase (CA), one of the most interesting case studies in the field of computer aided drug design. Since applying non-selective inhibitors can result in major side effects, there have been considerable efforts so far to achieve selective inhibitors for different isoforms of CA. Using proteochemometrics approach, the chemical interaction space governed by a group of 4-amino-substituted benzenesulfonamides and human CAs has been explored in the present study. Several validation methods have been utilized to assess the validity, robustness and predictivity power of the proposed proteochemometric model. Our model has offered major structural information that can be applied to design new selective inhibitors for distinct isoforms of CA. To prove the applicability of the proposed model, new compounds have been designed based on the offered discriminative structural features.

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Exploring the origin of phosphodiesterase inhibition via proteochemometric modeling

Cited by 10 publications

References 60 publications

Proteochemometric modeling of the origin of thymidylate synthase inhibition

Proteochemometric modeling of the origin of thymidylate synthase inhibition

Probing the origin of dihydrofolate reductase inhibition via proteochemometric modeling

Probing the chemical interaction space governed by 4-amino-substituted benzenesulfonamides and carbonic anhydrase isoforms

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