Structure-based virtual screening of dipeptidyl peptidase 4 inhibitors and their in vitro analysis

Rahman, Shafiq Ur; Ali, Hafiz Saqib; Jafari, Behzad; Zaib, Sumera; Hameed, Abdul; Al-Kahraman, Yasser Msa; Langer, Peter; Iqbal, Jamshed

doi:10.1016/j.compbiolchem.2020.107326

Cited by 7 publications

(4 citation statements)

References 39 publications

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“…Diabetes is a metabolic disease characterized by the inability to regulate blood sugar levels. Therapeutics have been explored through liver fructose 1,6-bisphosphate inhibitors to control gluconeogenesis-mediated overproduction of glucose ( Proenca et al, 2020 ) and dipeptidyl peptidase 4 inhibitors to block degradation of incretins that stimulate decrease of blood glucose ( Rahman et al, 2020 ). Half-life extension of insulin determir by complex formation with human serum albumin has been examined as a platform for drug delivery ( Ryberg et al, 2020 ).…”

Section: Applications To Drug Discoverymentioning

confidence: 99%

Recent Developments in Free Energy Calculations for Drug Discovery

King

Aitchison

et al. 2021

Front. Mol. Biosci.

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The grand challenge in structure-based drug design is achieving accurate prediction of binding free energies. Molecular dynamics (MD) simulations enable modeling of conformational changes critical to the binding process, leading to calculation of thermodynamic quantities involved in estimation of binding affinities. With recent advancements in computing capability and predictive accuracy, MD based virtual screening has progressed from the domain of theoretical attempts to real application in drug development. Approaches including the Molecular Mechanics Poisson Boltzmann Surface Area (MM-PBSA), Linear Interaction Energy (LIE), and alchemical methods have been broadly applied to model molecular recognition for drug discovery and lead optimization. Here we review the varied methodology of these approaches, developments enhancing simulation efficiency and reliability, remaining challenges hindering predictive performance, and applications to problems in the fields of medicine and biochemistry.

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Section: Applications To Drug Discoverymentioning

confidence: 99%

Recent Developments in Free Energy Calculations for Drug Discovery

King

Aitchison

et al. 2021

Front. Mol. Biosci.

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“…A total of 1,149,497 published papers were assembled in the Web of Science Core Collection (WoSCC) until June 2023 on the topics of "diabetes", 930,263 of which have been published after the year 2000 The scientific community's interest in the management of this disease has grown considerably (about 40%), observing a significant increase in scientific publications from approximately 17,000 in the year 2000 to approximately 70,000 in the year 2022 (Figure 1). So, in the early stage of drug design, in silico requirements have been managed by using various computational approaches, such as pharmacophore modeling [28][29][30][31], quantitative structure-activity relationships (QSAR) [32][33][34][35], molecular docking [36][37][38][39], molecular dynamics simulation [40][41][42], DFT simulation [35,[43][44][45][46], etc. These techniques have generated notable interest by reducing the time required for experimental trials, as well as human and resource costs.…”

Section: Introductionmentioning

confidence: 99%

Dipeptidyl Peptidase 4 Inhibitors in Type 2 Diabetes Mellitus Management: Pharmacophore Virtual Screening, Molecular Docking, Pharmacokinetic Evaluations, and Conceptual DFT Analysis

Istrate,

Crisan

2023

Processes

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Dipeptidyl Peptidase 4 (DPP-4) expressed on the surface of many different cells is a promising target to develop new candidates for Type 2 diabetes mellitus (T2DM) management. In this light, we performed a computer-aided simulation involving 3-D pharmacophore screening, molecular docking, and drug-likeness assessment to identify novel potential DPP-4 inhibitors with an improved physicochemical profile to treat T2DM. In addition, global reactivity descriptors, including HOMO and LUMO energies, HOMO-LUMO gaps, and Fukui indices, were computed to confirm the essential structural features to achieve DPP-4 activity. The gathered outcomes recommend that eight out of 240 million compounds collected from eight pre-built databases (Molport, Chembl30, ChemDiv, ChemSpace, Mcule, Mcule-ultimate, LabNetwork, and ZINC) are drug-like and nontoxic, and may serve as starting points for designing novel, selective, and potent DPP-4 inhibitors. Furthermore, the success of the current workflow to identify DPP-4-potential inhibitors strengthens its potential efficiency to also predict natural compounds as novel adjutants or main therapy for T2DM or discover hit compounds of other targets.

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“…In the last few years, modern drug discovery has utilized structure-and ligand-based computer-aided drug design (CADD) to identify promising new chemical compounds. Allied to this, the virtual screening (VS) method is a valuable tool in theoretical simulation, calculation, and prediction, and could guide and assist in discovering new small compounds, which shortens the time for designing new drugs and reduces the costs of drug development [14,15].…”

Section: Introductionmentioning

confidence: 99%

“…Studies with VS have helped to identify new compounds with in vitro assays using a virtual screening of a compound library, which demonstrates the computational efficiency in identifying new compounds [14,15]. Therefore, in our study, a combination of both structure-and ligand-based screening techniques were used to select the best representatives of drugs derived from Menispermaceae and Apocynaceae families active against S. mansoni.…”

Section: Introductionmentioning

confidence: 99%

Computer-Assisted Discovery of Alkaloids with Schistosomicidal Activity

Menezes

Viana

Muratov

et al. 2022

CIMB

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Schistosomiasis is a chronic parasitic disease caused by trematodes of the genus Schistosoma; it is commonly caused by Schistosoma mansoni, which is transmitted by Bioamphalaria snails. Studies show that more than 200 million people are infected and that more than 90% of them live in Africa. Treatment with praziquantel has the best cost–benefit result on the market. However, hypersensitivity, allergy, and drug resistance are frequently presented after administration. From this perspective, ligand-based and structure-based virtual screening (VS) techniques were combined to select potentially active alkaloids against S. mansoni from an internal dataset (SistematX). A set of molecules with known activity against S. mansoni was selected from the ChEMBL database to create two different models with accuracy greater than 84%, enabling ligand-based VS of the alkaloid bank. Subsequently, structure-based VS was performed through molecular docking using four targets of the parasite. Finally, five consensus hits (i.e., five alkaloids with schistosomicidal potential), were selected. In addition, in silico evaluations of the metabolism, toxicity, and drug-like profile of these five selected alkaloids were carried out. Two of them, namely, 11,12-methylethylenedioxypropoxy and methyl-3-oxo-12-methoxy-n(1)-decarbomethoxy-14,15-didehydrochanofruticosinate, had plausible toxicity, metabolomics, and toxicity profiles. These two alkaloids could serve as starting points for the development of new schistosomicidal compounds based on natural products.

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Structure-based virtual screening of dipeptidyl peptidase 4 inhibitors and their in vitro analysis

Cited by 7 publications

References 39 publications

Recent Developments in Free Energy Calculations for Drug Discovery

Recent Developments in Free Energy Calculations for Drug Discovery

Dipeptidyl Peptidase 4 Inhibitors in Type 2 Diabetes Mellitus Management: Pharmacophore Virtual Screening, Molecular Docking, Pharmacokinetic Evaluations, and Conceptual DFT Analysis

Computer-Assisted Discovery of Alkaloids with Schistosomicidal Activity

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