In silico evaluation for the potential naturally available drugs for breast cancer

Abstract

Breast cancer is one of the major causes of deaths in women. During the incidence of breast cancer, the HER-2 is amplified and over expressed. This transmembrane receptor is involved in the signal transduction pathway. The present article evaluates 14 naturally available breast cancer drugs, in silico and the ADMET studies were conducted. The HER-2, a validate breast cancer target was taken for the present study. The protein was prepared for docking on the Discovery Studio 2.5. About 14 ligand molecules were used to dock with HER-2 after they were prepared for docking. The ADMET assessment was also done. The dock results showed that the ligand 4′-epidoxorubicin to be the potential drug with the highest dock score of 49.386. Among the 14 naturally available breast cancer drugs, our results evaluated that 4′-epidoxorubicin as the best drug for breast cancer. Further, the ADMET studies give an idea about the drug molecules.     

Structure based virtual screening, 3D-QSAR,molecular dynamics and ADMET studies for selection of natural inhibitors against structural and non-structural targets of Chikungunya

The transmission of mosquito-borne Chikungunya virus (CHIKV) has large epidemics worldwide. Till date, there are neither anti-viral drugs nor vaccines available for the treatment of Chikungunya. Accumulated evidences suggest that some natural compounds i.e., Epigallocatechin gallate, Harringtonine, Apigenin, Chrysin, Silybin, etc. have the capability to inhibit CHIKV replication in vitro. Natural compounds are known to possess less or no side effects. Therefore, natural compound in its purified or crude extracts form could be the preeminent and safe mode of therapies for Chikungunya. Wet lab screening and identification of natural compounds against Chikungunya targets is a time consuming and expensive exercise. In the present study, we used in silico techniques like receptor-ligand docking, Molecular dynamic (MD), Three Dimensional Quantitative Structure Activity Relation (3D-QSAR) and ADME properties to screen out potential compounds. Aim of the study is to identify potential lead/s from natural sources using in silico techniques that can be developed as a drug like molecule against Chikungunya infection and replication. Three softwares were used for molecular docking studies. Potential ligands selected by docking studies were subsequently subjected 3D-QSAR studies to predict biological activity. Based on docking scores and pIC₅₀ value, potential anti-Chikungunya compounds were identified. Best docked receptor-ligands were also subjected to MD for more accurate estimation. Lipinski’s rule and ADME studies of the identified compounds were also studied to assess their drug likeness properties. Results of in silico findings, led to identification of few best fit compounds of natural origin against targets of Chikungunya virus which may lead to discovery of new drugs for Chikungunya.

Communicated by Ramaswamy H. Sarma     

In silico insights into the identification of potential novel angiogenic inhibitors against human VEGFR-2: a new SAR-based hierarchical clustering approach

Abstract

In this study, binding efficiency of new pyrrolopyrimidine structural analogs against human vascular endothelial growth factor receptor-2 (VEGFR-2) were elucidated using integrated in silico methods. Optimized high-resolution model of VEGFR-2 was generated and adopted for structure-based virtual screening approaches. Pyrrolopyrimidine inhibitor (CP15) associated compounds were screened from PubChem database and subjected to virtual screening and comparative docking methods against the receptor ligand-binding domain. Accordingly, high efficient compounds were clustered with similarity indices through PubChem structure cluster module using single-linkage algorithm. Moreover, pharmacokinetics including drug metabolism activities of high-binding leads under investigation was portrayed using ADMET and similarity ensemble analysis. Optimal energy orientations of the selected protein model have been shown to be reliable, and highly recommended for screening and docking studies. Docking and clustering strategies were shown that nineteen candidates as most effective binders for VEGFR-2 than CP15, and are grouped as three classes. Lys⁸⁶⁸, Glu⁸⁸⁵, Cys⁹¹⁹, His¹⁰²⁶, Arg¹⁰²⁷, Asp¹⁰⁴⁶, and Gly¹⁰⁴⁸ residues were predicted as novel hotspot residues, and participate in H-bonds, π-cation, π-stacking, halogen bonds, and salt-bridges formation with ligands. These additional bonds are contributing extent stability that holds the receptor structure at flexible state, this make difficult to any further conformational changes for evoking angiogenic signals. The ADMET and similarity ensemble analysis results were strongly indicated that thirteen candidates as best ligands for angiogenesis targets. Altogether, these findings indicate potential angiogenic templates and their binding levels with VEGFR-2; sorted viewpoints could be useful as a promising way to describe potential angiogenesis inhibitors with related molecular targets.     

3D-QSAR pharmacophore-based virtual screening,molecular docking and molecular dynamics simulation toward identifying lead compounds for NS2B–NS3 protease inhibitors

NS2B–NS3 protease has been identified to serve as lead drug design target due to its significant role in West Nile viral (WNV) and dengue virus (DENV) reproduction and replication. There are currently no approved chemotherapeutic drugs and effective vaccines to inhibit DENV and WNV infections. In this work, 3D-QSAR pharmacophore model has been developed to discover potential inhibitory candidates. Validation through Fischer’s model and decoy test indicate that the developed 3D pharmacophore model is highly predictive for DENV inhibitors, which was then employed to screen ZINC chemical library to obtain reasonable hits. Following ADMET filtering, 15 hits were subjected to further filter through molecular docking and CoMFA modeling. Finally, top three hits were identified as lead compounds or potential inhibitory candidates with IC₅₀ values of ～0.4637?µM and fitness of ～57.73. It is implied from CoMFA modeling that substituents at the side site of benzotriazole such as a p-nitro group (e.g. biphenyl head) and a carbonyl (e.g. carboxylate function) at the side site of furan or amino group may improve bioactivity of ZINC85645245, respectively. Molecular dynamics simulations (MDS) were performed to discover new interactions and reinforce the binding modes from docking for the hits also. The QSAR and MDS results obtained from this work should be useful in determining structural requirements for inhibitor development as well as in designing more potential inhibitors for NS2B–NS3 protease.     

Structure-based in-silico rational design of a selective peptide inhibitor for thymidine monophosphate kinase of mycobacterium tuberculosis

Tuberculosis still remains one of the most deadly infectious diseases. The emergence of drug resistant strains has fuelled the quest for novel drugs and drug targets for its successful treatment. Thymidine monophosphate kinase (TMPK) lies at the point where the salvage and de novo synthetic pathways meet in nucleotide synthesis. TMPK in M.tb has emerged as an attractive drug target since blocking it will affect both the pathways involved in the thymidine triphosphate synthesis. Moreover, the unique differences at the active site of TMPK enzyme in M.tb and humans can be exploited for the development of ideal drug candidates. Based on a detailed evaluation of known inhibitors and available three-dimensional structures of TMPK, several peptidic inhibitors were designed. In silico docking and selectivity analysis of these inhibitors with TMPK from M.tb and human was carried out to examine their differential binding at the active site. The designed tripeptide, Trp-Pro-Asp, was found to be most selective for M.tb. The ADMET analysis of this peptide indicated that it is likely to be a drug candidate. The tripeptide so designed is a suitable lead molecule for the development of novel TMPK inhibitors as anti-tubercular drugs.     

QSAR and Docking Studies on Capsazepine Derivatives for Immunomodulatory and Anti-Inflammatory Activity

Capsazepine, an antagonist of capsaicin, is discovered by the structure and activity relationship. In previous studies it has been found that capsazepine has potency for immunomodulation and anti-inflammatory activity and emerging as a favourable target in quest for efficacious and safe anti-inflammatory drug. Thus, a 2D quantitative structural activity relationship (QSAR) model against target tumor necrosis factor-α (TNF-α) was developed using multiple linear regression method (MLR) with good internal prediction (r² = 0.8779) and external prediction (r² _pred = 0.5865) using Discovery Studio v3.5 (Accelrys, USA). The predicted activity was further validated by in vitro experiment. Capsazepine was tested in lipopolysaccharide (LPS) induced inflammation in peritoneal mouse macrophages. Anti-inflammatory profile of capsazepine was assessed by its potency to inhibit the production of inflammatory mediator TNF-α. The in vitro experiment indicated that capsazepine is an efficient anti-inflammatory agent. Since, the developed QSAR model showed significant correlations between chemical structure and anti-inflammatory activity, it was successfully applied in the screening of forty-four virtual derivatives of capsazepine, which finally afforded six potent derivatives, CPZ-29, CPZ-30, CPZ-33, CPZ-34, CPZ-35 and CPZ-36. To gain more insights into the molecular mechanism of action of capsazepine and its derivatives, molecular docking and in silico absorption, distribution, metabolism, excretion and toxicity (ADMET) studies were performed. The results of QSAR, molecular docking, in silico ADMET screening and in vitro experimental studies provide guideline and mechanistic scope for the identification of more potent anti-inflammatory & immunomodulatory drug.     

Improving Compound Quality through in vitro and in silico Physicochemical Profiling

Many compounds entering clinical studies do not survive the numerous hurdles for a good pharmacological lead to a drug on the market. The reasons for attrition have been widely studied which resulted in more early attention to compound quality related to physical chemistry, drug metabolism and pharmacokinetics (DMPK), and toxicology/safety. This paper will briefly review current physicochemical in vitro assays and in silico predictions to support compound and library design through to lead optimization. The most important physicochemical properties include lipophilicity (log P/D), pK_a, solubility, and permeability. These drive key ADMET properties such as absorption, cell penetration, access to the brain, volume of distribution, plasma protein binding, metabolism, and toxicity, as well as biopharmaceutical behavior. Much data are now available from medium‐ to high‐throughput physchem and ADMET in vitro assays, either in the public domain (see, e.g., PubChem, PubMed) or in drug companies' in‐house databases. Such data are increasingly being computer‐modelled and used in predictive chemistry. New pipelining technology makes it easier to build and update QSAR models so that such models can use the latest available data to produce robust local and global predictive in silico ADMET models.     

Computational identification of putative common genomic drug and vaccine targets in Mycoplasma genitalium

Mycoplasma genitalium is an obligate intracellular bacterium that is responsible for several sexually transmitted infections, including non-gonococcal urethritis in men and several inflammatory reproductive tract syndromes in women. Here, we applied subtractive genomics and reverse vaccinology approaches for in silico prediction of potential vaccine and drug targets against five strains of M. genitalium. We identified 403 genes shared by all five strains, from which 104 non-host homologous proteins were selected, comprising of 44 exposed/secreted/membrane proteins and 60 cytoplasmic proteins. Based on the essentiality, functionality, and structure-based binding affinity, we finally predicted 19 (14 novel) putative vaccine and 7 (2 novel) candidate drug targets. The docking analysis showed six molecules from the ZINC database as promising drug candidates against the identified targets. Altogether, both vaccine candidates and drug targets identified here may contribute to the future development of therapeutic strategies to control the spread of M. genitalium worldwide.     

Repurposing of phytomedicine-derived bioactive compounds with promising anti-SARS-CoV-2 potential: Molecular docking,MD simulation and drug-likeness/ADMET studies

In view of the potential of traditional plant-based remedies (or phytomedicines) in the management of COVID-19, the present investigation was aimed at finding novel anti-SARS-CoV-2 molecules by in silico screening of bioactive phytochemicals (database) using computational methods and drug repurposing approach. A total of 160 compounds belonging to various phytochemical classes (flavonoids, limonoids, saponins, triterpenoids, steroids etc.) were selected (as initial hits) and screened against three specific therapeutic targets (Mpro/3CLpro, PLpro and RdRp) of SARS-CoV-2 by docking, molecular dynamics simulation and drug-likeness/ADMET studies. From our studies, six phytochemicals were identified as notable ant-SARS-CoV-2 agents (best hit molecules) with promising inhibitory effects effective against protease (Mpro and PLpro) and polymerase (RdRp) enzymes. These compounds are namely, ginsenoside Rg2, saikosaponin A, somniferine, betulinic acid, soyasapogenol C and azadirachtin A. On the basis of binding modes and dynamics studies of protein–ligand intercations, ginsenoside Rg2, saikosaponin A, somniferine were found to be the most potent (in silico) inhibitors potentially active against Mpro, PLpro and RdRp, respectively. The present investigation can be directed towards further experimental studies in order to confirm the anti-SARS-CoV-2 efficacy along with toxicities of identified phytomolecules.     

Virtual screening and in vitro assay of potential drug like inhibitors from spices against glutathione-S-transferase of filarial nematodes

Glutathione-S-transferase(s) (GST) enzyme from Brugia malayi has been exploited as a target in lymphatic filariasis therapeutics. An active GST is a homodimer of a 208 residue long monomer consisting of two domains, a smaller α/β domain and a larger α domain. The components of the glutathione (GSH) system, mainly GST enzymes, are critical antioxidant and detoxification system responsible for the long-term existence of filarial worms in mammalian host; hence they are major chemotherapeutic targets in filarial species. In the present study, 58 phytochemicals from 10 plants, predicted and reported to have potential nematicidal activity and ADMET satisfaction, have been docked to GST enzyme of B. malayi to assess their binding affinity and consequently their inhibitory activity. A comparative study has been made with commonly employed chemotherapeutic GST inhibitors such as cibacron-blue, butylated hydroxyanisole, hexyl glutathione and ethacrynic acid. In vitro effects of potential drug like compound from in silico results have been done for validation of docking studies. In vitro assay revealed efficacy in GST inhibition in the following compounds: linalool (97.50%), alpha-pinene (90.00%), strychnine (87.49%), vanillin (84.99%), piperine (79.99%), isoeugenol (62.49%), curcumin (57.49%), beta-caryophyllene (39.50%), cinnamic acid (27.49%), capsaicin (19.99%), citronellol (19.99%) and geraniol (17.49%). An online database () has been developed, which will serve as a useful repository of information on GST inhibitors for future development of drugs against filarial nematodes. These findings thus suggest that the above phytochemicals could be potentially developed as lead molecules for targeting GST of lymphatic filarial parasites.     

Profiling Auspicious Butyrylcholinesterase Inhibitory Activity of Two Herbal Molecules: Hyperforin and Hyuganin C

Cholinergic therapy based on cholinesterase (ChE) inhibitory drugs is the mainstay for the treatment of Alzheimer's disease. Therefore, an extensive research has been continuing for the discovery of drug candidates as inhibitors of acetyl‐ and butyrylcholinesterase. In this study, two natural molecules, e. g. hyperforin and hyuganin C were tested in vitro for their AChE and BChE inhibitory activity. Both of the compounds were ineffective against AChE, whereas hyperforin (IC₅₀=141.60±3.39 μm ) and hyuganin C (IC₅₀=38.86±1.69 μm ) were found to be the highly active inhibitors of BChE as compared to galantamine (IC₅₀=46.58±0.91 μm ) which was used as the reference. Then, these molecules were further proceeded to molecular docking experiments in order to establish their interactions at the active site of BChE. The molecular docking results indicated that both of them are able to block the access to key residues in the catalytic triad of the enzyme, while they complement some of the hydrophobic residues of the cavity, what is consistent with our in vitro data. While both compounds were predicted as mutagenic, only hyuganin C showed hepatotoxicity in in silico analysis. According to whole outcomes that we obtained, particularly hyuganin C besides hyperforin are the promising BChE inhibitors, which can be the promising compounds for AD therapy.     

Identification of potential inhibitors of Fasciola gigantica thioredoxin1: computational screening,molecular dynamics simulation,and binding free energy studies

Fasciola gigantica is the causative organism of fascioliasis and is responsible for major economic losses in livestock production globally. F. gigantica thioredoxin1 (FgTrx1) is an important redox-active enzyme involved in maintaining the redox homeostasis in the cell. To identify a potential anti-fasciolid compound, we conducted a structure-based virtual screening of natural compounds from the ZINC database (n = 1,67,740) against the FgTrx1 structure. The ligands were docked against FgTrx1 and 309 ligands were found to have better docking score. These compounds were evaluated for Lipinski and ADMET prediction, and 30 compounds were found to fit well for re-docking studies. After refinement by molecular docking and drug-likeness analysis, three potential inhibitors (ZINC15970091, ZINC9312362, and ZINC9312661) were identified. These three ligands were further subjected to molecular dynamics simulation (MDS) to compare the dynamics and stability of the protein structure after binding of the ligands. The binding free energy analyses were calculated to determine the intermolecular interactions. The results suggested that the two compounds had a binding free energy of –82.237, and –109.52 kJ.mol^?1 for compounds with IDs ZINC9312362 and ZINC9312661, respectively. These predicted compounds displayed considerable pharmacological and structural properties to be drug candidates. We concluded that these two compounds could be potential drug candidates to fight against F. gigantica parasites.     

Design,Synthesis, Calculation and Biological Activity Studies Based on Privileged Coumarin Derivatives as Multifunctional Anti-AD Lead Compound

Coumarins and their derivatives possessed a variety of biological activities and some of coumarin-based drugs have been approved by the US Food and Drug Administration. Alzheimer's disease (AD) has caused great losses to human society. However, due to its complex pathogenesis, the ideal therapeutic approach has not been found yet. Free radical scavenging activity which is one of the main activities of coumarin core structure is closely related to other anti-AD activities. Therefore, in this work coumarins were chosen as privileged lead compounds for the development of anti-AD drugs based on strategy of multi-target directed ligands (MTDLs). Derivatives 1 – 3 which could modulate multiple targets simultaneously, including ROS, cholinesterase, βamyloid (Aβ) aggregation, and metal dyshomeostasis were designed and for the first time synthesized. Their anti-AD activities were studied both in vitro and in silico. Results showed that 1 – 3 possessed potent antioxidant activities and 7-OH group did change the electron distribution of the molecule and enhance the antioxidant activities. They also have good inhibition activities on acetylcholinesterase (AChE) and Aβ aggregation and compound 1 had the strongest AChE inhibitory effect among the three compounds (AChE IC₅₀=11.15 μM). Compound 1 – 3 could also selectively chelate with Cu²⁺ and Al³⁺ to regulate the metal homeostasis. In silico simulations, including molecular docking and prediction of ADMET performance, indicated that 1 – 3 could interact with target proteins and cross the blood brain barrier. In conclusion, 1 – 3 could be promising MTDLs applied as anti-AD candidate drugs.     

2D QSAR,Design, and in Silico Analysis of Thiophene-Tethered Lactam Derivatives as Antimicrobial Agents

Background : A very high rate of resistance causes health-care-associated and community-acquired infections. E. coli is one of the nine pathogens of highest concern to most of the antibiotics and other class of antimicrobials. Objective : The objective of the present study is to develop novel thiophene derivatives using 2D QSAR and in silico approach for E. coli resistance. Methods : Substituted thiophene series reported by Nishu Singla et al., were taken for QSAR analysis. From the results, a set of 15 new compounds were designed. A complete in silico analysis has been done using PADEL, Autodock vina, Swiss ADME, Protox II software. Results : The designed compounds obey the Lipinski's rule of five and were known to have excellent inhibitory action (pIC₅₀ values −0.87 to −1.46) which is similar to the most active compound of the data set (pIC₅₀ −0.69) taken for the study. The bioavailability score (0.65) with no toxicity representing that the designed compounds are suitable for oral administration. Conclusion : The designed compounds are inactive for mutagenicity and cytotoxicity and ADMET studies states that these molecules are likely to be orally bioavailable and could be easily transported, diffused, and absorbed. So, the designed compounds will definitely serve as a lead antibacterial agent for E. coli resistance.     

Deciphering PPARγ activation in cardiometabolic syndrome: studies by in silico and in vivo experimental assessment

Cardiometabolic syndrome (CMetS) is a consolidation of metabolic disorders characterized by insulin resistance, dyslipidemia and hypertension. Curcumin, a natural bioactive compound, has been shown to possess notable anti-oxidant activity and it has also been included as a super natural herb in the super natural herbs database. Most of the beneficial effects of Curcumin are possibly due to activation of the nuclear receptor, peroxisome proliferator-activated receptor gamma (PPARγ). The present study investigates molecular interactions of curcumin with PPARγ protein through molecular docking and molecular dynamics (MD) simulation studies. Further, effect of curcumin on high fat diet induced CMetS was studied in rats along with western blot for PPARγ and nuclear factor-κB (NF-κB) expressions and histopathological studies. Computational studies presented several significant molecular interactions of curcumin including Ser289, His323, His449 and Tyr473 of PPARγ. The in vivo results further confirmed that curcumin was able to ameliorate the abnormal changes and also, increased PPARγ expressions. The results confirm our hypothesis that activation of PPARγ by curcumin possesses the therapeutic potential to ameliorate the altered levels of metabolic changes in rats in the treatment of CMetS. This is the first report of CMetS treatment by curcumin and study of its underlying mechanism through in silico as well as in vivo experiments.     

Understanding the structure-activity relationship of betulinic acid derivatives as anti-HIV-1 agents by using 3D-QSAR and docking

Novel anti-HIV-1 agents derived from betulinic acid have been greatly concerned. 3D-QSAR and molecular docking studies were applied to rationalize the structural requirements responsible for the anti-HIV activity of these compounds. The CoMFA and CoMSIA models resulted from 28 molecules gave r _cv² values of 0.599 and 0.630, r ² values of 0.994 and 0.958, respectively. To estimate the predictive ability of the 3D-QSAR model, an external validation was employed. Based on the contour maps generated from both CoMFA and CoMSIA, we have identified some key features in the betulinic acid derivatives that are responsible for the anti-HIV activity. Molecular docking was used to explore the binding mode between these derivatives and HIV gp120. We have therefore designed a series of novel betulinic acid derivatives by utilizing the SAR results revealed in the present study, which were predicted with excellent potencies in the developed models. The results provide a valuable method to design new betulinic acid derivatives as anti-HIV-1 agents.     

In silico discovery of potential drug molecules to improve the treatment of isoniazid-resistant Mycobacterium tuberculosis

The emergence of multidrug-resistant Mycobacterium tuberculosis (M.tb) has become one of the major hurdles in the treatment of tuberculosis (TB). Drug-resistant M.tb has evolved with various strategies to avoid killing by the anti-tubercular drugs. Thus, there is a rising need to develop effective anti-TB drugs to improve the treatment of these strains. Traditional drug design approach has earned little success due to time and the cost involved in the process of development of anti-infective drugs. Numerous reports have demonstrated that several mutations in the drug target sites cause emergence of drug-resistant M.tb strains. In this study, we performed computational mutational analysis of M.tb inhA, fabD, and ahpC genes, which are the primary targets for first-line isoniazid (INH) drug. In silico virtual drug screening was performed to identify the potent drugs from a ChEMBL compound library to improve the treatment of INH-resistant M.tb. Further, these compounds were analyzed for their binding efficiency against active drug binding cavity of M.tb wild-type and mutant InhA, FabD and AhpC proteins. The drug efficacy of predicted lead compounds was verified by molecular docking using M.tb wild-type and mutant InhA, FabD and AhpC protein template models. Different in silico and pharmacophore analysis predicted three potent lead compounds with better drug-like properties against both M.tb wild-type and mutant InhA, FabD, and AhpC proteins as compared to INH drug, and thus may be considered as effective drugs for the treatment of INH-resistant M.tb strains. We hypothesize that this work may accelerate drug discovery process for the treatment of drug-resistant TB.

Communicated by Ramaswamy H. Sarma     

In silico studies on marine actinomycetes as potential inhibitors for Glioblastoma multiforme

Glioblastoma multiforme (GBM) is considered to be the most common and often deadly disorder which affects the brain. It is caused by the over expression of proteins such as ephrin type-A receptor 2 (EphA2), epidermal growth factor receptor (EGFR) and EGFRvIII. These 3 proteins are considered to be the potential therapeutic targets for GBM. Among these, EphA2 is reported to be over-expressed in ˜90% of GBM. Herein we selected 35 compounds from marine actinomycetes, 5 in vitro and in vivo studied drug candidates and 4 commercially available drugs for GBM which were identified from literature and analysed by using comparative docking studies. Based on the glide scores and other in silico parameters available in Schrödinger, two selected marine actinomycetes compounds which include Tetracenomycin D and Chartreusin exhibited better binding energy among all the compounds studied in comparative docking. In this study we have demonstrated the inhibition of the 3 selected targets by the two bioactive compounds from marine actinomycetes through in-silico docking studies. Furthermore molecular dynamics simulation were also been performed to check the stability and the amino acids interacted with the 3 molecular targets (EphA2 receptor, EGFR, EGFRvIII) for GBM. Our results suggest that Tetracinomycin D and Chartreusin are the novel and potential inhibitor for the treatment of GBM.     

Structure based design of compounds from natural sources for diabetes and inflammation

Medicinal plants and marine sources are important elements of indigenous medical systems worldwide. The natural drugs from medicinal plants and marine sources have received considerable interest in treatment of diabetes and inflammation. Based on literature, alpha glucosidase, aldose reductase and PTP1B enzymes were chosen as anti-diabetes targets and PLA₂ was chosen for the anti-inflammatory target. In our study, plant and bromophenols (BPs) inhibitors were screened using High Throughput Virtual screening (HTVS) followed by Induced Fit Docking (IFD) studies were carried out against diabetes and inflammation targets. The IFD result of natural inhibitors has showed favorable docking score, glide energy and hydrogen bonds interactions with the active site residues. Some of the natural inhibitors successively satisfied all the in silico parameters among the others and seem to be potent inhibitors against diabetes and inflammation.