Waqasuddin Khan

Molecular and structural determinants of adamantyl susceptibility to HLA-DRs allelic variants: an in silico approach to understand the mechanism of MLEs

Class II major histocompatibility complex (MHC II) molecules as expressed by antigen-presenting cells are heterodimeric cell-surface glycoprotein receptors that are fundamental in initiating and propagating an immune response by presenting tumor-associated antigenic peptides to CD4+/TH cells. The loading efficiency of such peptides can be improved by small organic compounds (MHC Loading Enhancers—MLEs), that convert the non-receptive peptide conformation of MHC II to a peptide-receptive conformation. In a reversible reaction, these compounds open up the binding site of MHC II molecules by specific interactions with a yet undefined pocket. Here, we performed molecular docking and molecular dynamics simulation studies of adamantyl compounds on the predicted cavity around the P1 pocket of 2 allelic variants of HLA-DRs. The purpose was to investigate the suitability of adamantyl compounds as MLEs at the dimorphic β86 position. Docking studies revealed that besides numerous molecular interactions formed by the adamantyl compounds, Asnβ82, Tyrβ83, and Thrβ90 are the crucial amino acid residues that are characterized as the “sensors” of peptide loading. Molecular dynamics simulation studies exposed the dynamical structural changes that HLA-DRs adopted as a response to binding of 3-(1-adamantyl)-5-hydrazidocarbonyl-1H-pyrazole (AdCaPy). The conformations of AdCaPy complexed with the Glyβ86 HLA-DR allelic variant are well correlated with the stabilized form of peptide-loaded HLA-DRs, further confirming the role of AdCaPy as a MLE. Hydrogen bonding interaction analysis clearly demonstrated that after making suitable contacts with AdCaPy, HLA-DR changes its local conformation. However, AdCaPy complexed with HLA-DR having Valβ86 at the dimorphic position did not accommodate AdCaPy as MLE due to steric hindrance caused by the valine.

Metabolic pathway analysis approach: Identification of novel therapeutic target against methicillin resistant Staphylococcus aureus

Multiple Drug Resistant (MDR) bacteria are no more inhibited by the front line antibiotics due to extreme resistance. Methicillin Resistant Staphylococcus aureus (MRSA) is one of the MDR pathogens notorious for its widespread infection around the world. The high resistance acquired by MRSA needs a serious concern and efforts should be carried out for the discovery of better therapeutics. With this aim, we designed a comparison of the metabolic pathways of the pathogen, MRSA strain 252 (MRSA252) with the human host (i.e., Homo sapiens) by using well-established in silico methods. We identified several metabolic pathways unique to MRSA (i.e., absent in the human host). Furthermore, a subtractive genomics analysis approach was applied for retrieval of proteins only from the unique metabolic pathways. Subsequently, proteins of unique MRSA pathways were compared with the host proteins. As a result, we have shortlisted few unique and essential proteins that could act as drug targets against MRSA. We further assessed the druggability potential of the shortlisted targets by comparing them with the DrugBank Database (DBD). The identified drug targets could be useful for an effective drug discovery phase. We also searched the sequences of unique as well as essential enzymes from MRSA in Protein Data Bank (PDB). We shortlisted at least 12 enzymes for which there was no corresponding deposition in PDB, reflecting that their crystal structures are yet to be solved! We selected Glutamate synthase out of those 12 enzymes owing to its participation in significant metabolic pathways of the pathogen e.g., Alanine, Aspartate, Glutamate and Nitrogen metabolism and its evident suitability as drug target among other MDR bacteria e.g., Mycobacteria. Due to the unavailability of any crystal structure of Glutamate synthase in PDB, we generated the 3D structure by homology modeling. The modeled structure was validated by multiple analysis tools. The active site of Glutamate synthase was identified by not only superimposing the template structure (PDB ID: 1E0A) over each other but also by the Parallel-ProBiS algorithm. The identified active site was further validated by cross-docking the co-crystallized ligand (2-oxoglutaric acid; AKG) of PDB ID: 1LLW. It was concluded that the comparative metabolic in silico analysis together with structure-based methods provides an effective approach for the identification of novel antibiotic targets against MRSA.

In vitro and in silico exploration of IL-2 inhibition by small drug-like molecules

Interleukin-2 (IL-2) is an immunoregulatory cytokine produced by T lymphocytes in response to antigen. It is a potent growth and differentiation factor for several cell-types and is structurally related to the four-helix bundle family of cytokines. Here, we report IL-2 inhibitory potential and computational studies on different series of chalcones, benzothiazepines, semicarbazones, and dihydropyrimidines. These compounds were synthesized in wet lab and were then tested for their potency as IL-2 inhibitors through in vitro T cell proliferation, IL-2 cytokine production as well as their effect on oxidative burst. Compounds that showed significant suppressive activity were further evaluated for their cytotoxicity on normal two cell lines. Most of the chalcones were found to have a powerful inhibitory effect on T-lymphocytes proliferation and cytokine production. Among the aza heterocycles benzothiazepines, benzoxazepines, and benzodiazepinones were found to be the strongest IL-2 inhibitors. Molecular docking and MD simulation studies were carried out to correlate experimental and theoretical results whereby a good correlation was observed which indicated that computational studies could provide an alternate tool for the identification and designing of more potent IL-2 inhibitors.

Structure-based 3D-QSAR models and dynamics analysis of novel N-benzyl pyridinone as p38α MAP kinase inhibitors for anticytokine activity

A novel series of anticytokine N-benzyl pyridinone derivatives that targets p38α MAP kinase has been analyzed by utilizing a combination of molecular modeling techniques. Statistically significant structure-based 3D-QSAR models were generated for both CoMFA and CoMSIA, and validated through acceptable predictive ability to support both internal and external set of compounds. Structural changes within the protein key backbone residues (Met109 and Gly110), DFG loop position, and side chain movements (Lys53 and Asn114) as resulted by different substituents on these inhibitors were also examined by molecular dynamics simulation. The protocol applied in this study could be helpful to rationalize potent compounds with better inhibitory activity and selectivity profiles against p38α MAP kinase.

3D Structure Prediction of Human β1-Adrenergic Receptor via Threading-Based Homology Modeling for Implications in Structure-Based Drug Designing

Dilated cardiomyopathy is a disease of left ventricular dysfunction accompanied by impairment of the β1-adrenergic receptor (β1-AR) signal cascade. The disturbed β1-AR function may be based on an elevated sympathetic tone observed in patients with heart failure. Prolonged adrenergic stimulation may induce metabolic and electrophysiological disturbances in the myocardium, resulting in tachyarrhythmia that leads to the development of heart failure in human and sudden death. Hence, β1-AR is considered as a promising drug target but attempts to develop effective and specific drug against this tempting pharmaceutical target is slowed down due to the lack of 3D structure of Homo sapiens β1-AR (hsβADR1). This study encompasses elucidation of 3D structural and physicochemical properties of hsβADR1 via threading-based homology modeling. Furthermore, the docking performance of several docking programs including Surflex-Dock, FRED, and GOLD were validated by re-docking and cross-docking experiments. GOLD and Surflex-Dock performed best in re-docking and cross docking experiments, respectively. Consequently, Surflex-Dock was used to predict the binding modes of four hsβADR1 agonists. This study provides clear understanding of hsβADR1 structure and its binding mechanism, thus help in providing the remedial solutions of cardiovascular, effective treatment of asthma and other diseases caused by malfunctioning of the target protein.

Binding site identification and role of permanent water molecule of PIM-3 kinase: A molecular dynamics study.

The kinome is a protein kinase complement of the human genome, categorized as serine/threonine and tyrosine kinases. These kinases catalyze phosphorylation reaction by using ATP as phosphoryl donor. Proviral Integration Site for Moloney Murine Leukemia Virus (PIM) kinase encodes serine/threonine protein kinases that recognized as proto-oncogene, responsible for rapid growth of cancerous cells. It is implicated in cell survival and function via cell cycle progression and its metabolism. PIM-3, sub-member of PIM kinases is a proto-oncogene, its overexpression inhibits apoptosis, and results in progression of hepatocellular carcinoma. PIM-3 is considered as a promising drug target but attempts to develop its specific inhibitors is slowed down due to the lack of 3D structure by any experimental technique. In silico techniques generally facilitate scientist to explore hidden structural features in order to improve drug discovery. In the present study, homology modeling, molecular docking and MD simulation techniques were utilized to explore the structure and dynamics of PIM-3 kinase. Induction of water molecules during molecular docking simulation explored differences in the hinge region between PIM-1 and PIM-3 kinases that may be responsible for specificity. Furthermore, role of water molecules in the active site was also explored via radial distribution function (RDF) after a 10 ns molecular dynamics (MD) simulations. Generated RDF plots exhibited the importance of water for inhibitor binding through their bridging capability that links the ligand with binding site residues.

Computational identification of potential drug targets against Mycobacterium leprae

Leprosy is caused by Mycobacterium leprae a major health concern in several countries of the world particularly in Asia and Africa. The preventive measurement has been adopted by the combined efforts of the leprosy burden countries and WHO. However, the situation is getting worse due to the emergence of the resistant strains of the M. leprae. The continuous efforts are underway to discover new chemical agent as a therapeutic to cure the diseases caused by the resistant pathogens of bacterial origins. The resistant pathogens are still growing on alarming rate. In order to overcome the resistant pathogens, a relatively newer approach has been applied since last decade. One of them involves the computational subtractive genomics, in which the complete proteome of the bacterial pathogen is step-wise reduced to few potential drug targets. The steps include the finding of non-host proteins, essentiality of the proteins to the pathogens and involvement of the shortlisted proteins in essential metabolic pathways of the pathogen, which are necessary for the bacterial survival. In the current study, we applied computational subtractive genomics on complete proteome of the M. leprae and ended up with 16 hypothetical proteins as potential drug targets against which new active molecules can be proposed to ameliorate the activity to cure the disease associated with them. The study is innovative and has a potential to improve the research directions in unraveling the novel cure of leprosy.