Designing of new multi-targeted inhibitors of spleen tyrosine kinase (Syk) and zeta-associated protein of 70kDa (ZAP-70) using hierarchical virtual screening protocol

Design, synthesis and anti-rheumatoid arthritis activity of target TLR4 inhibitors

A series of 1-(2-oxocyclohexyl)butane-1, 3-dione derivatives were designed and synthesized as TLR4 inhibitors by modifying the core structure of the lead compound ((6, 8-dioxo-1, 2, 3, 4, 6, 7, 8, 8a-octahydronaphthalen-2-yl) carbamate)). In vitro, compound 3p significantly inhibited the proliferation of rat synovial cells, inhibited the proliferation of LPS-induced RAW264.7 cells, and inhibited TLR4 activity, with IC50 values of 1.21 ± 0.09 μM, 0.73 ± 0.05 μM and 0.43 ± 0.03 μM, respectively, which was superior to the positive control methotrexate. In vivo anti-rheumatoid arthritis evaluation, compound 3p can significantly inhibit the inflammatory factors TNF-α, IL-1β and IL-6, so as to achieve the therapeutic purpose. In the preliminary mechanism study, compound 3p has obvious regulatory effects on the abnormal increase of TLR4, JAK2 and STAT3 protein and gene expression related to inflammatory signaling pathway in RAW264.7 cells. In summary, this study aims to develop more effective candidates for rheumatoid arthritis.

Design and Synthesis of Novel Double-Ring Conjugated Enones as Potent Anti-rheumatoid Arthritis Agents

Rheumatoid arthritis (RA) is a chronic and systemic disease of inflammatory synovitis with unknown etiology. In previous studies, we found that the double-ring conjugated enone structure has anti-rheumatoid arthritis activity and could effectively inhibit the proliferation of rat synovial cells in vitro and has good anti-inflammatory activity in vivo. Herein, we further modified the structure, which was a novel double-ring conjugated enone, to study its anti-rheumatoid arthritis activity. Results showed that the most potent compound 32 could effectively inhibit the proliferation of rat synovial cells in vitro and has better anti-inflammatory activity compared with that of the positive control methotrexate, as shown by in vivo activity evaluation. More interestingly, compound 32 could effectively inhibit the increase of TNF-α, IL-1β, and IL-6 induced by LPS and regulate the expression of TLR4, MyD88, NF-κB, and IκB in the signaling pathway of TLR4/NF-κB. Our results provided a promising starting point for the development of highly effective small molecules for the treatment of RA.

Some important inhibitors and mechanisms of rheumatoid arthritis

Rheumatoid arthritis is a chronic disease that seriously affects human health and quality of life, and it is one of the main causes of labor loss and disability. Many countries have listed rheumatoid arthritis as one of the national a key diseases to tackle. The pathogenesis of RA in humans is still unknown, and medical researchers believe that the pathogenesis of RA may be the result of a combination of genetic and environmental factors. RA is an incurable condition that can only be controlled and treated with conventional drugs. In this paper, the pathologic features and pathogenesis of RA were introduced, and the research progress of new anti-rheumatoid arthritis chemical drugs in recent years was reviewed.

Mechanistic insights on nsSNPs on binding site of renin and cytochrome P450 proteins: A computational perceptual study for pharmacogenomics evaluation

Past several decades, therapeutic investigations lead to the discovery of numerous antihypertensive drugs. Although it has been proved for their potency, altered efficacy is common norms in several conditions due to genetic variations. Cytochrome P450 plays a crucial role in drug metabolism and responsible for the pharmacokinetic and pharmacodynamic properties of the drug molecules. Here, we report the deleterious point mutations in the genes associated with the altered response of antihypertensive drug molecules and their metabolizers. Missense variants were filtered as potential nonsynonymous single nucleotide polymorphisms among the available data for the target genes (REN, CYP2D6, CYP3A4). The key objective of the work is to identify the deleterious single nucleotide polymorphisms (SNPs) responsible for the drug response and metabolism for the application of personalized medication. The molecular docking studies revealed that Aliskiren and other clinically approved drug molecules have a high binding affinity with both wild and mutant structures of renin, CYP2D6, and CYP3A4 proteins. The docking (Glide XP) score was observed to have in the range of -8.896 to -11.693 kcal/mol. The molecular dynamics simulation studies were employed to perceive the structural changes and conformational deviation through various analyses. Each studied SNPs was observed to have disparate scoring in the binding affinity to the specific drug molecules. As a prospective plan, we assume this study might be applied to identify the risky SNPs associated with hypertension from the patients to recommend the suitable drug for personalized hypertensive treatment. Further, extensive clinical pharmacogenomics studies are required to support the findings.

Pharmacophore modeling, molecular docking and molecular dynamics simulation for screening and identifying anti-dengue phytocompounds

Dengue is a fast spreading mosquito borne viral disease that poses a serious threat to human health. Lack of therapeutic drugs and vaccines signify that more resources need to be explored. Accumulated evidence has suggested that plants offer a vast reservoir for antiviral drug discovery which are safe for human consumption. Plant-based drug discovery is a complex and time-consuming process as plants possess rich repository of chemically diverse compounds. Various in silico methods can make this process simple and economic. We, therefore, performed pharmacophore mapping, molecular docking, molecular dynamics (MD) simulations and ADME (absorption, distribution, metabolism, excretion) prediction to screen potential candidates against dengue. In particular, combined pharmacophore mapping and molecular docking were used to prioritize the potentially active ligands from a ligand library. Biological activities of plant based ligands were predicted using 3D-QSAR pharmacophore modeling. Interaction between proteins, namely, envelope G protein, NS2B/NS3 protease, NS5 methyltransferase, NS1, NS5 polymerase and active plant-based ligands (pIC50 > 5.1) were analyzed using molecular docking. Best docked complex, namely, envelope G protein-mulberroside C, NS2B-NS3 protease-curcumin, NS5 methyltransferase-chebulic acid, NS1-mulberroside A, NS5 methyltransferase-punigluconin and NS5 methyltransferase-chebulic acid were further subjected to MD simulations study to assess the fluctuation and conformational changes during protein-ligand interaction. ADME studies were performed to assess their drug-likeness properties. Collectively, these in silico results helped to identify the potential plant-based hits against the various receptors of dengue virus which can be further validated by bioactivity-based experiments.Communicated by Ramaswamy H. Sarma.

Computational studies on N-phenyl pyrrole derivatives as MmpL3 inhibitors in Mycobacterium tuberculosis

The fight against tuberculosis (TB) is a time immemorial one and the emergence of new drug resistant strains of Mycobacterium tuberculosis keeps throwing new challenges to the scientific community immersed in finding mechanisms to control this dreaded disease. Computer aided drug designing (CADD) is one of the several approaches that can assist in identifying the potent actives against Mycobacterium. In this work, a series of 109 known Mycobacterial membrane proteins large 3 (MmpL3) inhibitors were pooled and atom based 3D QSAR analysis was performed to understand the structural features essential for inhibitory activity against the MmpL3, known to be a key player in transporting substances critical for cell wall integrity of Mycobacterium. The data set employed was randomly split into training set and test set molecules. The training set of 74 molecules was used to derive CoMFA and CoMSIA models that were statistically reliable (CoMFA: q²_loo = 0.53; r²_ncv = 0.93 and CoMSIA: q²_loo = 0.60; r²_ncv = 0.93). The derived models also exhibited good external predictive ability (CoMFA: r²_pred = 0.78 and CoMSIA: r²_pred = 0.79). The results are quite encouraging and information derived from these analyses was applied to design new molecules. The designed molecule showed appreciable predicted activity values and reasonably good ADMET profile. The strategy used in designing new molecules can be pursued in the hunt for new chemical entities targeting MmpL3, expanding the existing arsenal against TB.

Molecular dynamics and integrated pharmacophore-based identification of dual [Formula: see text] inhibitors

Despite increase in the understanding of the pathogenesis of rheumatoid arthritis (RA), it remains a tough challenge. The advent of kinases involved in key intracellular pathways in pathogenesis of RA may provide a new phase of drug discovery for RA. The present study is aimed to identify dual JAK3/[Formula: see text] inhibitors by developing an optimum pharmacophore model integrating the information revealed by ligand-based pharmacophore models and structure-based pharmacophore models (SBPMs). For JAK3 inhibitors, the addition of an aromatic ring feature and for [Formula: see text] the addition of a hydrophobic feature proposed by SBPMs lead to five-point pharmacophore (i.e., AADHR.54 (JAK3)) and six-point pharmacophore (i.e., AAAHRR.45 ([Formula: see text])). The obtained pharmacophores were validated and used for virtual screening and then for docking-based screening. Molecules were further evaluated for ADME properties, and their docked protein complexes were subjected to MM-GBSA energy calculations and molecular dynamic simulations. The top two hit compounds with novel scaffolds 2-oxo-1,2-dihydroquinoline and benzo[d]oxazole showed inhibitory activity for JAK3 and [Formula: see text].

Oxindole-based SYK and JAK3 dual inhibitors for rheumatoid arthritis: designing, synthesis and biological evaluation

Aim: Autoimmune disorders have complex pathophysiology and focus is laid on the development of multitargeted agents. Two well-established kinases: SYK and JAK3, were considered to design dual inhibitors as potential therapeutics using various molecular-modeling approaches. Mehodology: Pharmacophore models for SYK and JAK3 were generated using oxindole-based inhibitors. Furthermore, an in-house database was designed that was screened against the best selected models. The obtained hits were employed for docking analysis and subjected to MM-GBSA analysis and molecular dynamic simulation. Results: Top five oxindole derivatives were synthesized and evaluated for in vitro SYK and JAK3 activity. The most active compound 4a was evaluated for in vivo antiarthritic activity. It showed significant anti-arthritic activity. Conclusion: Thus, the designed inhibitors resulted in potential therapeutic agents for rheumatoid arthritis.

Ligand-based and e-pharmacophore modeling, 3D-QSAR and hierarchical virtual screening to identify dual inhibitors of spleen tyrosine kinase (Syk) and janus kinase 3 (JAK3)

The clinical efficacy of multiple kinase inhibitors has caught the interest of Pharmaceutical and Biotech researchers to develop potential drugs with multi-kinase inhibitory activity for complex diseases. In the present work, we attempted to identify dual inhibitors of spleen tyrosine kinase (Syk) and janus kinase 3 (JAK3), keys players in immune signaling, by developing ideal pharmacophores integrating Ligand-based pharmacophore models (LBPMs) and Structure-based pharmacophore models (SBPMs), thereby projecting the optimum pharmacophoric required for inhibition of both the kinases. The four point LBPM; ADPR.14 suggested the presence of one hydrogen bond acceptor, one hydrogen bond donor, one positive ionizable, and one ring aromatic feature for Syk inhibitory activity and AADH.54 proposed the necessity of two hydrogen bond acceptor, one hydrogen bond donor, and one hydrophobic feature for JAK3 inhibitory activity. To our interest, SBPMs identified additional ring aromatic features required for inhibition of both the kinases. For Syk inhibitory activity, the hydrogen bond acceptor feature indicated by LBPM was devoid of forming hydrogen bonding interaction with the hinge region amino acid residue (Ala451). Thus merging the information revealed by both LBPMs and SBPMs, ideal pharmacophore models i.e. ADPRR.14 (Syk) and AADHR.54 (JAK3) were generated. These models after rigorous statistical validation were used for screening of Asinex database. The systematic virtual screening protocol, including pharmacophore and docking-based screening, ADME property, and MM-GBSA energy calculations, retrieved final 10 hits as dual inhibitors of Syk and JAK3. Final 10 hits thus obtained can aid in the development of potential therapeutic agents for autoimmune disorders. Also the top two hits were evaluated against both the enzymes.

Identification of new dual spleen tyrosine kinase (Syk) and phosphoionositide-3-kinase δ (PI3Kδ) inhibitors using ligand and structure-based integrated ideal pharmacophore models

Owing to the complex pathophysiology of autoimmune disorders, it is very challenging to develop successful treatment strategies. Single-target agents are not desired therapeutics for such multi-factorial disorders. Considering the current need for the treatment of complex autoimmune disorders, dual inhibitors of Syk and PI3Kδ have been designed using ligand and structure-based molecular modelling strategies. In the present work, structure and ligand-based pharmacophore modelling was implemented for a varied set of Syk and PI3Kδ inhibitors. Ligand-based pharmacophore models (LBPMs) were developed for two kinases: ADPR.14 (r(2)train = 0.809) for Syk, comprising one hydrogen bond acceptor, one hydrogen bond donor, one positive ionisable and one ring aromatic feature, and for PI3Kδ: AAARR.45 (r(2)train = 0.942) consisting of three hydrogen bond acceptor and two ring aromatic features. The generated e-pharmacophore models revealed an additional ring aromatic and hydrophobic feature important for Syk and PI3Kδ inhibition, respectively. Subsequently, LBPMs were modified resulting in APDRR.14 hypothesis for Syk inhibitors and AAAHRR.45 hypothesis for PI3Kδ inhibitors employed for virtual screening. Thus, the combination of ligand and structure-based pharmacophore modelling helped in developing ideal pharmacophore models that may be an efficient tool for the designing of novel dual inhibitors of Syk and PI3Kδ.

Identifying the structural features and diversifying the chemical domain of peripherally acting CB1 receptor antagonists using molecular modeling techniques

A four featured pharmacophore and predictive 3D-QSAR models were developed which were used for virtual screening of the Asinex database to get chemically diverse hits of peripherally active CB1 receptor antagonists.

Pharmacophore approaches in protein kinase inhibitors design

Protein kinases constitute a superfamily of therapeutic targets for a number of human and animal diseases that include more than 500 members accordingly to sequencing data of the human genome. The well characterized nature of protein kinases makes them excellent targets for drug development. Pharmacophore approaches have become one of the major tools in the area of drug discovery. Application of pharmacophore modeling approaches allows reducing of expensive overall cost associated with drug development project. Pharmacophore models are important functional groups of atoms in the proper spatial position for interaction with target protein. Various ligand-based and structure-based methods have been developed for pharmacophore model generation. Despite the successes in pharmacophore models generation these approaches have not reached their full capacity in application for drug discovery. In the following review, we summarize the published data on pharmacophore models for inhibitors of tyrosine protein kinases (EGFR, HER2, VEGFR, JAK2, JAK3, Syk, ZAP-70, Tie2) and inhibitors of serine/threonine kinases (Clk, Dyrk, Chk1, IKK2, CDK1, CDK2, PLK, JNK3, GSK3, mTOR, p38 MAPK, PKB). Here, we have described the achievements of pharmacophore modeling for protein kinase inhibitors, which provide key points for further application of generated pharmacophore hypotheses in virtual screening, de novo design and lead optimization.

Pharmacophore and docking-based virtual screening approach for the design of new dual inhibitors of Janus kinase 1 and Janus kinase 2

Janus kinase 1 and 2, non-receptor protein tyrosine kinases, are implicated in various cancerous diseases. Involvement of these two enzymes in the pathways that stimulate cell proliferation in cancerous conditions makes them potential therapeutic targets for designing new dual-targeted agents for the treatment of cancer. In the present study, two separate pharmacophore models were developed and the best models for JAK1 (AAADH.25) and JAK2 (ADRR.92) were selected on the basis of their external predictive ability. Both models were subjected to a systematic virtual screening (VS) protocol using a PHASE database of 1.5 million molecules. The hits retrieved in VS were investigated for ADME properties to avoid selection of molecules with a poor pharmacokinetic profile. The molecules considered to be within the range of acceptable limits of ADME properties were further employed for docking simulations with JAK1 and JAK2 proteins to explore the final hits that possess structural features of both pharmacophore models as well as display essential interactions with both of them. Thus, the new molecules obtained in this way should show inhibitory activity against JAK1 and JAK2 and may serve as novel therapeutic agents for the treatment of cancerous disease conditions.

Imidazo[1,2-a]pyrazine inhibitors of phosphoinositide 3-kinase alpha (PI3Kα): 3D-QSAR analysis utilizing the Hybrid Monte Carlo algorithm to refine receptor-ligand complexes for molecular alignment

Phosphoinositide 3-kinase alpha (PI3Kα) is a lipid kinase involved in several cellular functions such as cell growth, proliferation, differentiation and survival, and its anomalous regulation leads to cancerous conditions. PI3Kα inhibition completely blocks the cancer signalling pathway, hence it can be explored as an important therapeutic target for cancer treatment. In the present study, docking analysis of 49 selective imidazo[1,2-a]pyrazine inhibitors of PI3Kα was carried out using the QM-Polarized ligand docking (QPLD) program of the Schrödinger software, followed by the refinement of receptor-ligand conformations using the Hybrid Monte Carlo algorithm in the Liaison program, and alignment of refined conformations of inhibitors was utilized for the development of an atom-based 3D-QSAR model in the PHASE program. Among the five generated models, the best model was selected corresponding to PLS factor 2, displaying the highest value of Q(2)test (0.650). The selected model also displayed high values of r(2)train (0.917), F-value (166.5) and Pearson-r (0.877) and a low value of SD (0.265). The contour plots generated for the selected 3D-QSAR model were correlated with the results of docking simulations. Finally, this combined information generated from 3D-QSAR and docking analysis was used to design new congeners.

Glutamine: fructose-6-phosphate amidotransferase (GFAT): homology modelling and designing of new inhibitors using pharmacophore and docking based hierarchical virtual screening protocol

Glutamine: fructose-6-phosphate amidotransferase (GFAT), also termed GFPT1 and GFAT1, catalyzes the first committed step of the hexosamine biosynthesis pathway in mammals and consequently plays an important role in type 2 diabetes. In the present study, a combination of pharmacophore modelling, homology modelling, and molecular docking analysis was performed to design new glutamine competitive inhibitors of human GFAT, and to investigate important interaction details of inhibitor molecules. A pharmacophore model of GFAT inhibitors was developed, subsequently validated, and utilized for the screening by the PHASE database to identify new molecules. Afterwards, homology modelling was performed to construct the glutamine-binding site of the GFAT protein. The modelled active site was utilized to dock the studied molecules to investigate important receptor-ligand interactions and to scrutinize database-screened molecules on the basis of essential interactions. This systematic in silico protocol helped us to identify new molecules that would be explored for the treatment of type 2 diabetes and its complications.