Kaiser Jamil

Sequence-structure based phylogeny of GPCR Class A Rhodopsin receptors

Current methods of G protein coupled receptors (GPCRs) phylogenetic classification are sequence based and therefore inappropriate for highly divergent sequences, sharing low sequence identity. In this study, sequence structure profile based alignment generated by PROMALS3D was used to understand the GPCR Class A Rhodopsin superfamily evolution using the MEGA 5 software. Phylogenetic analysis included a combination of Neighbor-Joining method and Maximum Likelihood method, with 1000 bootstrap replicates. Our study was able to identify potential ligand association for Class A Orphans and putative/unclassified Class A receptors with no cognate ligand information: GPR21 and GPR52 with fatty acids; GPR75 with Neuropeptide Y; GPR82, GPR18, GPR141 with N-arachidonylglycine; GPR176 with Free fatty acids, GPR10 with Tachykinin & Neuropeptide Y; GPR85 with ATP, ADP & UDP glucose; GPR151 with Galanin; GPR153 and GPR162 with Adrenalin, Noradrenalin; GPR146, GPR139, GPR142 with Neuromedin, Ghrelin, Neuromedin U-25 & Thyrotropin-releasing hormone; GPR171 with ATP, ADP & UDP Glucose; GPR88, GPR135, GPR161, GPR101with 11-cis-retinal; GPR83 with Tackykinin; GPR148 with Prostanoids, GPR109b, GPR81, GPR31with ATP & UTP and GPR150 with GnRH I & GnRHII. Furthermore, we suggest that this study would prove useful in re-classification of receptors, selecting templates for homology modeling and identifying ligands which may show cross reactivity with other GPCRs as signaling via multiple ligands play a significant role in disease modulation.

Homology modelling and molecular docking of MDR1 with chemotherapeutic agents in non-small cell lung cancer.

MDR1, a protein commonly involved in drug transport, has been linked to multi drug resistance and disease progression in cancers such as non-small cell lung cancer. Hence, targeting this protein is essential for improving drug design and preventing adverse drug-drug interactions. The aim of the study was to examine chemotherapeutic drug binding to MDR1 and the interactions therein. We have used Schrödinger suite 2014, to perform homology modelling of human MDR1 based on Mouse MDR1, followed by Induced Fit Docking with Paclitaxel, Docetaxel, Gemcitabine, Carboplatin and Cisplatin drugs. Finally, we evaluated drug binding affinities using Prime/MMGBSA and using these scores we compared the affinities of combination therapies against MDR1. Analysis of the docking results showed Paclitaxel>Docetaxel>Gemcitabine>Carboplatin>Cisplatin as the order of binding affinities, with Paclitaxel having the best docking score. The combination drug binding affinity analysis showed Paclitaxel+Gemcitabine to have the best docking score and hence, efficacy. Through our investigation we have identified the residues Gln 195 and Gln 946 to be more frequently involved in drug binding interactions with MDR1. Our results suggest that, Paclitaxel or combination of Paclitaxel+Gemcitabine could serve as a suitable therapy against MDR1 in NSCLC patients. Thus, our study provides new insight into the possible repurposing of chemotherapeutic drugs in targeting elevated MDR1 levels in NSCLC patients, thereby ensuring better overall outcome. Further our study highlights the use of in silico methodologies in understanding drug binding to protein targets and its relevance to advancing lung cancer therapy.

Structure and putative signaling mechanism of Protease activated receptor 2 (PAR2) – A promising target for breast cancer

Experimental evidences have observed enhanced expression of protease activated receptor 2 (PAR2) in breast cancer consistently. However, it is not yet recognized as an important therapeutic target for breast cancer as the primary molecular mechanisms of its activation are not yet well-defined. Nevertheless, recent reports on the mechanism of GPCR activation and signaling have given new insights to GPCR functioning. In the light of these details, we attempted to understand PAR2 structure & function using molecular modeling techniques. In this work, we generated averaged representative stable models of PAR2, using protease activated receptor 1 (PAR1) as a template and selected conformation based on their binding affinity with PAR2 specific agonist, GB110. Further, the selected model was used for studying the binding affinity of putative ligands. The selected ligands were based on a recent publication on phylogenetic analysis of Class A rhodopsin family of GPCRs. This study reports putative ligands, their interacting residues, binding affinity and molecular dynamics simulation studies on PAR2-ligand complexes. The results reported from this study would be useful for researchers and academicians to investigate PAR2 function as its physiological role is still hypothetical. Further, this information may provide a novel therapeutic scheme to manage breast cancer.

Drug Targets for Cell Cycle Dysregulators in Leukemogenesis: In Silico Docking Studies

Alterations in cell cycle regulating proteins are a key characteristic in neoplastic proliferation of lymphoblast cells in patients with Acute Lymphoblastic Leukemia (ALL). The aim of our study was to investigate whether the routinely administered ALL chemotherapeutic agents would be able to bind and inhibit the key deregulated cell cycle proteins such as - Cyclins E1, D1, D3, A1 and Cyclin Dependent Kinases (CDK) 2 and 6. We used Schrödinger Glide docking protocol to dock the chemotherapeutic drugs such as Doxorubicin and Daunorubicin and others which are not very common including Clofarabine, Nelarabine and Flavopiridol, to the crystal structures of these proteins. We observed that the drugs were able to bind and interact with cyclins E1 and A1 and CDKs 2 and 6 while their docking to cyclins D1 and D3 were not successful. This binding proved favorable to interact with the G1/S cell cycle phase proteins that were examined in this study and may lead to the interruption of the growth of leukemic cells. Our observations therefore suggest that these drugs could be explored for use as inhibitors for these cell cycle proteins. Further, we have also highlighted residues which could be important in the designing of pharmacophores against these cell cycle proteins. This is the first report in understanding the mechanism of action of the drugs targeting these cell cycle proteins in leukemia through the visualization of drug-target binding and molecular docking using computational methods.

Promoter Hypermethylation of the ATM Gene as a Novel Biomarker for Breast Cancer

Background: Breast cancer may be induced by activation of protooncogenes to oncogenes and in many cases inactivation of tumor suppressor genes. Ataxia telangiectasia mutated (ATM) is an important tumor suppressor gene which plays central roles in the maintenance of genomic integrity by activating cell cycle checkpoints and promoting repair of double-strand breaks of DNA. In breast cancer, decrease ATM expression correlates with a poor outcome; however, the molecular mechanisms underlying downregulation are still unclear. Promoter hypermethylation may contribute in downregulation. Hence the present investigation was designed to evaluate promoter methylation and expression of the ATM gene in breast cancer cases, and to determine links with clinical and demographic manifestations, in a South Indian population. Methods: Tumor biopsy samples were collected from 50 pathologically confirmed sporadic breast cancer cases. DNA was isolated from tumor and adjacent non-tumorous regions, and sodium bisulfite conversion and methylation-specific PCR were performed using MS-PCR primers for the ATM promoter region. In addition, ATM mRNA expression was also analyzed for all samples using real-time PCR. Results: Fifty eight percent (58%) of cancer tissue samples showed promoter hypermethylation for the ATM gene, in contrast to only 4.44% of normal tissues (p= 0.0001). Furthermore, ATM promoter methylation was positively associated with age (p = 0.01), tumor size (p=0.045) and advanced stage of disease i.e. stages III and IV (p =0.019). An association between promoter hypermethylation and lower expression of ATM mRNA was also found (p=0.035). Conclusion: We report for the first time that promoter hypermethylation of ATM gene may be useful as a potential new biomarker for breast cancer, especially in the relatively young patients.

Screening of phytochemicals against protease activated receptor 1 (PAR1), a promising target for cancer

Abstract Context: Drug resistance and drug-associated toxicity are the primary causes for withdrawal of many drugs, although patient recovery is satisfactory in many instances. Interestingly, the use of phytochemicals in the treatment of cancer as an alternative to synthetic drugs comes with a host of advantages; minimum side effects, good human absorption and low toxicity to normal cells. Protease activated receptor 1 (PAR1) has been established as a promising target in many diseases including various cancers. Strong evidences suggest its role in metastasis also. Objective: There are no natural compounds known to inhibit its activity, so we aimed to identify phytochemicals with antagonist activity against PAR1. Methods: We screened phytochemicals from Naturally Occurring Plant-based Anticancer Compound-Activity-Target database (NPACT, http://crdd.osdd.net/raghava/npact/) against PAR1 using virtual screening workflow of Schrödinger software. It analyzes pharmaceutically relevant properties using Qikprop and calculates binding energy using Glide at three accuracy levels (high-throughput virtual screening, standard precision and extra precision). Results and conclusion: Our study led to the identification of phytochemicals, which showed interaction with at least one experimentally determined active site residue of PAR1, showed no violations to Lipinskis rule of five along with predicted high human absorption. Furthermore, structural interaction fingerprint analysis indicated that the residues H255, D256, E260, S344, V257, L258, L262, Y337 and S344 may play an important role in the hydrogen bond interactions of the phytochemicals screened. Of these residues, H255 and L258 residues were experimentally proved to be important for antagonist binding. The residues Y183, L237, L258, L262, F271, L332, L333, Y337, L340, A349, Y350, A352, and Y353 showed maximum hydrophobic interactions with the phytochemicals screened. The results of this work suggest that phytochemicals Reissantins D, 24,25-dihydro-27-desoxywithaferin A, Isoguaiacin, 20-hydroxy-12-deoxyphorbol angelate, etc. could be potential antagonist of PAR1. However, further experimental studies are necessary to validate their antagonistic activity against PAR1.

Biased signaling: potential agonist and antagonist of PAR2

Protease activated receptor 2 (PAR2) has emerged as one of the promising therapeutic targets to inhibit rapidly metastasizing breast cancer cells. However, its elusive molecular mechanism of activation and signaling has made it a difficult target for drug development. In this study, in silico methods were used to unfold PAR2 molecular mechanism of signaling based on the concept of GPCR receptor plasticity. Although, there are no conclusive evidences of the presence of specific endogenous ligands for PAR2, the efficacy of synthetic agonist and antagonist in PAR2 signaling has opened up the possibilities of ligand-mediated signaling. Furthermore, it has been proved that ligands specific for one GPCR can induce signaling in GPCRs belonging to other subfamilies. Therefore, the aim of this study was to identify potential agonists and antagonists from the GPCR ligand library (GLL), which may induce biased signaling in PAR2 using the concept of existence of multiple ligand-stabilized receptor conformations. The results of our in silico study suggest that PAR2 may show biased signaling mainly with agonists of serotonin type 1, β-adrenergic type 1,3 and antagonists of substance K (NK1), serotonin type 2, dopamine type 4, and thromboxane receptors. Further, this study also throws light on the putative ligand-specific conformations of PAR2. Thus, the results of this study provide structural insights to putative conformations of PAR2 and also gives initial clues to medicinal chemists for rational drug design targeting this challenging receptor.

In silico evidence of signaling pathways of notch mediated networks in leukemia

Notch signaling plays a critical role in cell fate determination and maintenance of progenitors in many developmental systems. Notch receptors have been shown to be expressed on hematopoietic progenitor cells as well as to various degrees in peripheral blood T and B lymphocytes, monocytes, and neutrophils. Our aim was to understand the protein interaction network, using Notch1 protein name as query in STRING database and we generated a model to assess the significance of Notch1 associated proteins in Acute Lymphoblastic Leukemia (ALL). We further analyzed the expression levels of the genes encoding hub proteins, using Oncomine database, to determine their significance in leukemogenesis. Of the forty two hub genes, we observed that sixteen genes were underexpressed and eleven genes were overexpressed in T-cell Acute Lymphoblastic samples in comparison to their expression levels in normal cells. Of these, we found three novel genes which have not been reported earlier- KAT2B, PSEN1 (underexpressed) and CDH2 (overexpressed).These three identified genes may provide new insights into the abnormal hematopoietic process observed in Leukemia as these genes are involved in Notch signaling and cell adhesion processes. It is evident that experimental validation of the protein interactors in leukemic cells could help in the identification of new diagnostic markers for leukemia.

Protease activated receptor-2 (PAR2): possible target of phytochemicals

The use of phytochemicals either singly or in combination with other anticancer drugs comes with an advantage of less toxicity and minimal side effects. Signaling pathways play central role in cell cycle, cell growth, metabolism, etc. Thus, the identification of phytochemicals with promising antagonistic effect on the receptor/s playing key role in single transduction may have better therapeutic application. With this background, phytochemicals were screened against protease-activated receptor 2 (PAR2). PAR2 belongs to the superfamily of GPCRs and is an important target for breast cancer. Using in silico methods, this study was able to identify the phytochemicals with promising binding affinity suggesting their therapeutic potential in the treatment of breast cancer. The findings from this study acquires importance as the information on the possible agonists and antagonists of PAR2 is limited due its unique mechanism of activation.

TNF-alpha −308G/A and −238G/A polymorphisms and its protein network associated with type 2 diabetes mellitus

Several reports document the role of tumor necrosis factor alpha (TNF-α) and lipid metabolism in the context of acute inflammation as a causative factor in obesity-associated insulin resistance and as one of the causative parameter of type 2 diabetes mellitus (T2DM). Our aim was to investigate the association between −308G/A and −238G/A polymorphisms located in the promoter region of the TNF-α gene in T2DM in the Indian population with bioinformatics analysis of TNF-α protein networking with an aim to find new target sites for the treatment of T2DM. Demographics of 100 diabetes patients and 100 healthy volunteers were collected in a structured proforma and 3 ml blood samples were obtained from the study group, after approval of Institutional Ethics Committee of the hospital (IEC). The information on clinical parameters was obtained from medical records. Genomic DNA was extracted; PCR–RFLP was performed using TNF-α primers specific to detect the presence of SNPs. Various bioinformatics tools such as STRING software were used to determine its network with other associated genes. The PCR–RFLP studies showed that among the −238G/A types the GG genotype was 87%, GA genotype was 12% and AA genotype was 1%. Almost a similar pattern of results was obtained with TNF-α −308G/A polymorphism. The results obtained were evaluated statistically to determine the significance. By constructing TNF-α protein interaction network we could analyze ontology and hubness of the network to identify the networking of this gene which may influence the functioning of other genes in promoting T2DM. We could identify new targets in T2DM which may function in association with TNF-α. Through hub analysis of TNF-α protein network we have identified three novel proteins RIPK1, BIRC2 and BIRC3 which may contribute to TNF-mediated T2DM pathogenesis. In conclusion, our study indicated that some of the genotypes of TNF-α −308G/A, −238G/A were not significantly associated to type 2 diabetes mellitus, but TNF-α −308G/A polymorphism was reported to be a potent risk factor for diabetes in higher age (>45) groups. Also, the novel hub proteins may serve as new targets against TNF-α T2DM pathogenesis.