Highlight of my projects:
Computational study of potential galectin-3 inhibitors in the treatment of COVID-19
Galectin-3 is a carbohydrate-binding protein and the most studied member of the galectin family. It regulates several functions throughout the body, among which are inflammation and post-injury remodelling. Recent studies have highlighted the similarity between Galectin-3's carbohydrate recognition domain and the so-called "galectin fold" present on the N-terminal domain of the S1 sub-unit of the SARS-CoV-2 spike protein. Sialic acids binding to the N-terminal domain of the Spike protein are known to be crucial for viral entry into humans, and the role of Galectin-3 as a mediator of lung fibrosis has long been the object of study since its levels have been found to be abnormally high in alveolar macrophages following lung injury. In this context, the discovery of a double inhibitor may both prevent viral entry and reduce post-infection pulmonary fibrosis. In this study, we use a database of 56 compounds, among which 37 have known experimental affinity with Galectin-3. We carry out virtual screening of this database with respect to Galectin-3 and Spike protein. Several ligands are found to exhibit promising binding affinity and interaction with the Spike protein's N-terminal domain as well as with Galectin-3. This finding strongly suggests that existing Galectin-3 inhibitors possess dual-binding capabilities to disrupt Spike-ACE2 interactions. Herein we identify the most promising inhibitors of Galectin-3 and Spike proteins, of which five emerge as potential dual effective inhibitors. Our preliminary results warrant further in vitro and in vivo testing of these putative inhibitors against SARS-CoV-2 with the hope of being able to halt the spread of the virus in the future.
Computational determination of toxicity risks associated with a selection of approved drugs having demonstrated activity against the COVID-19
The emergence and rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2019 has caused an ongoing global pandemic of the severe pneumonia-like dis-ease coronavirus disease 2019 (COVID-19). Although vaccines are developed recently, they are not accessible to everyone and not everyone can receive these vaccines. Also, the typical timeline for approval of a new antiviral therapeutic agent can exceed 10 years. Thus, repurposing of known drugs could significantly expedite the development of new therapies for COVID-19. Here, we study the cardiotoxicity and toxicity profile of 90 potential drugs for COVID-19 treatment from two independent studies perpending the risks of repurposing and stratification of patients accordingly. Since most of the molecules identified in this study have already advanced into the clinic, their known pharmacological and human safety profiles will enable accelerated preclinical and clinical evaluation of these drugs for the treatment of COVID-19.
COVID-19 : ‘Invasion of the microtubule snatchers’ - therapeutic implications
The SARS-CoV-2 virus invades and proliferates within host cells by ‘hi-jacking’ biomolecular machinery, specifically gaining control of the microtubule cytoskeleton, like the strange ‘pods’ in the classic movie ‘Invasion of the body-snatchers’, who invaded human bodies and controlled brains, converting their behaviors to the pods’ own purposes. The SARS-CoV-2 virus co-opts the dynamic intra-cellular cytoskeletal network of microtubules, actin and the microtubule-organizing center (MTOC), enabling three factors leading to clinical pathology: 1) virus load due to intra-cellular trafficking, 2) cell-to-cell spread by filopodia, and 3) immune dysfunction, ranging from hyper-inflammatory cytokine storm, to ineffective or absent response. These factors all depend directly on microtubules and MTOC, suggesting possible benefit of therapies aimed not at the virus, but at microtubules and MTOC of the host cell on which the virus depends. These could include anti-microtubule drugs, as well as non-invasive, low intensity ultrasound (megahertz mechanical vibrations) applied externally to the vagus nerve at the neck, and/or spleen, both involved in mediating inflammatory response. Vagal stimulation reduces inflammation in humans, and in an animal model of inflammatory arthritis, low intensity ultrasound to the spleen improved systemic joint function significantly. Ultrasound imaging machines suitable for vagal/splenic ultrasound are available for clinical trials in every hospital. We recommend an alternative therapeutic approach in COVID-19 based on addressing and normalizing host cell microtubules and MTOCs co-opted by the SARS-CoV-2 virus.
A new protein characterization and classification method using geometrical features for 3D face analysis: an example of tubulin structures
Figure 1. Effects of applying different descriptors (a) F_den2 ,(b) sing (c) , S_mean , (d) 〖k_1〗_mean ,(e) 〖k_2〗_median , (f), g_mean ,and (g) H_meanto a human face (left column) and to the tubulin protein (right column)
This paper reports on the results of research aimed to translate biometric 3D face recognition concepts and algorithms into the field of protein biophysics in order to precisely and rapidly classify morphological features of protein surfaces. Both human faces and protein surfaces are free-forms and some descriptors used in differential geometry can be used to describe them applying the principles of feature extraction developed for computer vision and pattern recognition. The first part of this study focused on building the protein dataset using a simulation tool and performing feature extraction using novel geometrical descriptors. The second part tested the method on two examples, first involved a classification of tubulin isotypes and the second compared tubulin with the FtsZ protein, which is its bacterial analogue. An additional test involved several unrelated proteins. Different classification methodologies have been used: a classic approach with a Support Vector Machine (SVM) classifier and an unsupervised learning with a k-means approach. The best result was obtained with SVM and the radial basis function (RBF) kernel. The results are significant and competitive with the state-of-the-art protein classification methods. This leads to a new methodological direction in protein structure analysis.
Proteins: Structure, Function, and Bioinformatics, (Published on 11 August 2020, https://doi.org/10.1002/prot.25993)
Molecular docking studies of novel series of double-modified colchicine derivatives as anticancer agents
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Colchicine is a well-known compound with strong antiproliferative activity that has had limited use in chemotherapy because of its toxicity. In order to create more potent anticancer agents, a series of novel colchicine derivatives have been obtained by simultaneous modification at different positions and characterized by spectroscopic methods. All the synthesized compounds have been tested in vitro to evaluate their cytotoxicity toward A549, MCF-7, LoVo, LoVo/DX and BALB/3T3 cell lines. Additionally, the activity of the studied compounds was investigated using computational methods involving molecular docking of the colchicine derivatives to β-tubulin. Molecular modeling studies of the obtained compounds revealed their possible binding modes into the colchicine binding site of tubulin.
Simulations of mechanical unfolding of disordered proteins complementing single molecule experiments performed with optical tweezers
A key molecular feature of neurodegenerative diseases is that certain proteins (e.g. α-synuclein in Parkinson) ‘misfold’, forming incorrect structures that spread within and between neurons. These misfolded proteins are neurotoxic and aggregate into amyloid fibres deposited in the brain. However, it is challenging to determine the structures and interactions that drive the early stages of aggregation because they are transient and obscured in a heterogeneous mixture of disordered states. To overcome the challenge posed by oligomers, in a multidisciplinary collaboration with Dr. Michael Woodside’s Lab, applied a novel approach to studying early-stage aggregation by comparing results from single-molecule force spectroscopy experiments and Steered molecular dynamics (SMD) simulations to deduce structural features present in α-synuclein oligomers. The force experiments allow us to filter our simulated pulling trajectories to identify experimentally relevant transitions, while our simulations provide atomic-level. We used this combined approach to compare our experimental and simulated results to identify structural interfaces present in oligomers (i.e. Tetramers) that we will target in our next phase of drug design work with virtual screening. I also screened different compound libraries by docking compounds against inter-domain interfaces which can provide critical drug targets to inhibit the formation of larger oligomers and thereby arrest the aggregation process at an earlier stage. Hit compounds will be tested for effectiveness using fluorescence assays sensitive to single oligomers, then structurally optimized in silico to generate lead compounds with good drug-like qualities, preparing them for additional pre-clinical trials in vitro and in vivo in future work.
Tyrosine kinase inhibitors reduce glucose uptake by binding to an exofacial site on hGLUT-1: Effects on 18F-FDG PET uptake
TKIs were designed to compete with ATP for the ATP binding pocket of a variety of tyrosine kinases that are expressed in different tumor types. Treatment with some TKIs caused changes in blood glucose levels and the mechanism(s) underlying these changes remain unclear. Effect of several classes of TKIs on glucose uptake studies using [3H]2-DG were examined in FaDu cells. Molecular modeling studies using different conformations of hGLUT1 were used to study interaction of TKIs with hGLUT1. Several classes of TKIs inhibited glucose uptake in FaDu cells and the inhibition was competitive in nature. IC50 values for inhibition of glucose uptake were within the pharmacological levels of TKI concentrations present in tissues. Molecular modeling studies identified the binding site interactions and binding energies.
These findings suggest that TKIs can interact with hGLUT1 present in various cell types in blood and tissues resulting in changes in glucose levels in patient populations treated with these TKIs. Some of the effects are direct and some are both direct and indirect.
These findings suggest that TKIs can interact with hGLUT1 present in various cell types in blood and tissues resulting in changes in glucose levels in patient populations treated with these TKIs. Some of the effects are direct and some are both direct and indirect.
Computer-aided drug discovery to design personalized medicine
Figure 1. In precision medicine, patients with tumors that share the same genetic change such as mutations is treated with the drug which targets that specific change, regardless of the specific cancer type.
Personalized Cancer Treatment by Optimization of Chemotherapy through Drug Target Profiling:
Although there are now many options for treatment available for most types of cancer, determining the medication that will most improve the chances of response and decrease the chances of toxicity for a given patient is still an elusive goal. Given my interest in this area and my expertise in drug design techniques, I have recently begun participation in this research project targeting the use of drug discovery to design personalized medicine. In addition to the differences between individuals at the DNA level, it should be noted, each tumour has its own unique DNA profile. I am taking advantage of these genetic mutations in the tumours in order to identify a “signature” that will allow the best possible chemotherapy selection to improve the odds of a positive response to medication and to reduce the odds of recurrence. Simulations based on drug design techniques will assist to screen for all possible mutations that could determine how hundreds of available chemotherapy drugs might be predetermined to succeed or to fail. This will allow me to optimize the choice of a medication that may currently be approved, for example, in breast cancer in a patient who has, for example, lung cancer, if their tumour DNA signature suggests that this is the best option for success. In this way, I can uncover new applications of existing anti-cancer medications in order to maximize their utility for cancer treatment.
Although there are now many options for treatment available for most types of cancer, determining the medication that will most improve the chances of response and decrease the chances of toxicity for a given patient is still an elusive goal. Given my interest in this area and my expertise in drug design techniques, I have recently begun participation in this research project targeting the use of drug discovery to design personalized medicine. In addition to the differences between individuals at the DNA level, it should be noted, each tumour has its own unique DNA profile. I am taking advantage of these genetic mutations in the tumours in order to identify a “signature” that will allow the best possible chemotherapy selection to improve the odds of a positive response to medication and to reduce the odds of recurrence. Simulations based on drug design techniques will assist to screen for all possible mutations that could determine how hundreds of available chemotherapy drugs might be predetermined to succeed or to fail. This will allow me to optimize the choice of a medication that may currently be approved, for example, in breast cancer in a patient who has, for example, lung cancer, if their tumour DNA signature suggests that this is the best option for success. In this way, I can uncover new applications of existing anti-cancer medications in order to maximize their utility for cancer treatment.
Highlight of my projects at Ingenuity Lab, Department of Chemical and Materials Engineering, University of Alberta:
Hybrid System Project: Engineered beta-sheet peptide interaction with Aqpz membrane protein
Figure 1. Model of AqpZ Aquaporin, peptide and Beta sheet
b-strand peptides can be used to stabilize integral membrane proteins (IMPs); sequestering the hydrophobic surfaces by forming ordered, stabilizing β-barrel-like structures. Ingenuity Lab is able to design and build hybrid systems crosslinking functionalized b-strand:protein complex to a variety of matrix materials, such as polymers and biofilms as protein-incorporating biomimetic membranes for industrial purposes.
Understanding the mechanism underlying b-strand formation and b-strand:protein complexes at the molecular level is essential to control the formation and orientation of the embedded complex in the hybrid device. In this study, AqpZ, the water channel from E. coli, is used as a model protein. We employed a systematic computational approach including protein-protein docking and Molecular Dynamics simulations to study the b-strand formation and interaction with protein, paving the way to rationally design b-strand peptide variants with improved stoichiometric and oriented crosslinking ability on AQP’s.
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Understanding the mechanism underlying b-strand formation and b-strand:protein complexes at the molecular level is essential to control the formation and orientation of the embedded complex in the hybrid device. In this study, AqpZ, the water channel from E. coli, is used as a model protein. We employed a systematic computational approach including protein-protein docking and Molecular Dynamics simulations to study the b-strand formation and interaction with protein, paving the way to rationally design b-strand peptide variants with improved stoichiometric and oriented crosslinking ability on AQP’s.
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(Nano Bio-material): Selective adsorption of peptides on MoS2 surface with biomining applications
Figure 2. Top view and side view of a binding peptide on MoS2 surface.
One of the most pressing challenges of our time is the extraction and recycling of valuable rare metals from mixtures in mines and consumer wastes in a more cost-effective and environmentally friendly way. In this study, we aimed to separate out valuable rare metals from the mixtures by designing the peptides with specific recognition ability to bind to individual metals as smart biomaterials. Phage display combinational technology is used to engineer materials by selecting a highly competitive peptide binder among a population of billions. The positive output of our experimental work motivated us to investigate and study the microscopic mechanism of binding of experimentally selected adhesion peptides on MoS2 surfaces by means of molecular dynamics (MD) calculations, paving the way to engineering peptide sequences with enhanced affinity to a given surface. For each surface-peptide combination, peptide interactions with the surface, peptide conformations in solution, binding geometrics and adsorption energy on the basis of NPT and NVT calculations will be calculated. The analysis involves the visual inspection of molecular conformations over the entire simulation time and the distance of individual residues of the peptides from the surface. To our knowledge, the presented work reveals for the first time the interactions of the peptide with Molybdenum disulfide surface and can play an important role to gain insight in to the interaction mechanism between peptide and the surface to finely tune the biomolecule specificity toward a desired binder.
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Molecular Dynamics Simulations and Structural Analysis to understand the Functional Impact of Recombinant Terminal Deoxynucleotidyl Transferase Enzyme Tagging
Figure 3. TDT structure with different domains
Terminal deoxynucleotidylt ransferase (TdT) is the only known DNA polymerase that elongates DNA strands in a template-independent manner. TDT catalyzes addition of random nucleotides to DNA primer in the presence of dNTPs and metal ions, thereby assisting antigenic variation in the vertebrate adaptive immune system by V(D)J recombination. Insertions/deletions are common evolutionary tools employed to change the structural and functional repertory of protein domains. In this study, we investigate three different tagging of TDT and their effect on the activity and stability of the TDT to get insight about the experiments done in our group.
Here are some of the projects I conducted during my PhD:
Heterogeneous Metal-Free Hydrogenation over Defect-Laden Hexagonal Boron Nitride
Figure 4. The barrier (in electronvolts) for each elementary reaction step is calculated using the climbing image nudged elastic band method(63) and is shown by the number (eV) between the states.
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Figure 5. Electronic density cross sections plotted along the vertical plane, passing through the center of the two carbon atoms of ethane. It can be seen that the electronic density of ethene on dh-BN exhibits a similar structure to that of C3H6, indicating a reduction of the bond order of the C–C bond in the adsorbed ethene.
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Catalytic hydrogenation is an important process used for the production of everything from foods to fuels. Until recently, catalytic heterogeneous hydrogenation over a metal-free solid was unknown; implementation of such a system would eliminate the health, environmental, and economic concerns associated with metal-based catalysts. Here, we report good hydrogenation rates and yields for a metal-free heterogeneous hydrogenation catalyst as well as its unique hydrogenation mechanism.Temperature-programmed desorption of ethene over processed h-BN indicates the formation of a highly defective structure. Solid-state NMR (SSNMR) measurements of dh-BN with high and low propene surface coverages show four different binding modes. The introduction of defects into h-BN creates regions of electronic deficiency and excess.Catalytic hydrogenation of olefins was achieved over defect-laden h-BN (dh-BN) in a reactor designed to maximize the defects in h-BN sheets. Density functional theory calculations show that both the alkene and hydrogen-bond order are reduced over four specific defects: boron substitution for nitrogen (BN), vacancies (VB and VN), and Stone–Wales defects. SSNMR and binding-energy calculations show that VN are most likely the catalytically active sites. This work shows that catalytic sites can be introduced into a material previously thought to be catalytically inactive through the production of defects.
The role of Van der Wasls interaction in the self assembly
Figure 6. (a) Top and side view of the BDA molecule. binding energy and the molecule–surface separation d on the molecule tilt angle calculated within (b) GGA-PBE and (c) nonlocal vdW-DF
methods.
Recently, the electronic properties and alignment of tetramethyl-1,4-benzenediamine (TMBDA), 1,4-benzenediamine (BDA) and tetrafluro-1,4-benzenediamine (TFBDA) molecules were studied experimentally. Discrepancies were found for both the binding energy and the molecule tilt angle with respect to the surface, when results were compared with density functional theory calculations. We have included the effect of vdW interactions both between the molecules and the Au(111) surface and find binding energies which are in very good agreement with experiments. We also find that at low coverages each of these molecules would adsorb almost parallel to the surface. N-Au bond lengths and charge redistribution on adsorption of the molecules are also analyzed. Our calculations are based on DFT using vdW-DF exchange correlation functionals. For BDA (since we are aware of experimental data), we show that for higher coverage, inclusion of intermolecular van der Waals interaction leads to tilting of the molecules with respect to the surface and formation of line structures. Our results demonstrate the central role played by intermolecular interaction in pattern formation on this surface.
Predictive modeling of functional materials
Single layer molybdenum disulfide (MoS2): A promising 2D material
Figure 7. Side view and top view of single layer MoS2
Molybdenum disulfide is an intriguing material. It is a prototypical semiconducting material consists of stacked hexagonal S-Mo-S layers. These layers, conventionally referred to as monolayers, are weakly bound by van der Waals forces. In a manner similar to that common in the production of graphene, MoS2 samples consisting of a single or a few monolayers can be produced by micromechanical exfoliation. Owing to their atomic-scale thickness, two-dimensional materials such as graphene and MoS2 have significant potential for application in the next generation of nano-electronics. Because monolayer MoS2 has a direct bandgap, it can be used to construct inter-band tunnel FETs, which provide lower power consumption than classical transistors. Monolayer MoS2 could also complement graphene in applications that require thin transparent semiconductors, as do optoelectronics, spintronics and energy harvesting.
One of the fundamental challenges in MoS2 technology is the growth process, in as much as any practical application requires the development of techniques that can produce large quantities of single-layer MoS2 in a controlled manner. Predictive modeling (in which theory and computation work hand-in-hand with experiments) can play a helpful role in bringing to light the fundamental processes that facilitate layer-by-layer growth of MoS2.
One of the fundamental challenges in MoS2 technology is the growth process, in as much as any practical application requires the development of techniques that can produce large quantities of single-layer MoS2 in a controlled manner. Predictive modeling (in which theory and computation work hand-in-hand with experiments) can play a helpful role in bringing to light the fundamental processes that facilitate layer-by-layer growth of MoS2.
An MoSx Structure with High Affinity for Adsorbate Interaction
Figure 8. a) STM image of MoSx structures. Models of b) MoS2 /Cu(111), c) sulfur-terminated copper (S–Cu), and d) Mo2S3 structure at the focus of this manuscript. Models: Cu=brown, S=yellow, Mo=green/blue
We undertake to predict and reveal the novel MoSx structure on Cu(111) surfaces using the predictive modeling procedure. We found a novel MoSx surface structure on copper, which we propose to have the composition (Mo2S3 or Mo2S5), whose ability to interact and activate adsorbates far exceeds that of MoS2 while proving to be of similar thermal stability and recoverable after adsorption through annealing. We theoretically calculate vibrational mode frequencies and intensities of these two candidate compositions in order to find the stable structure and the fingerprint frequencies required for identification by experiment.
Mo6S6 Nanoswires
Figure 9. Mo6S6 nanowires on Cu(111)
Based on density functional theory (DFT) predictions and scanning tunneling microscopy (STM) measurements we report the possibility of using the Cu(111) surface for growth of molybdenum sulfide nanowires (Mo6S6). Strong substrate interactions coupled with small lattice mismatch lead to epitaxial growth of the nanowires parallel to a set of substrate high symmetry directions. We observe a propensity for creation of aligned and equally spaced arrays of nanowires and use DFT to elucidate interaction strength both in the absence and presence of the substrate.
Electronic transport properties of single layer MoS2
Figure 10. One of the interfaces of MoS2-Au used for approximation of Schottky barriers
In the light of recent experimental findings, we discuss ab-initio density functional theory (DFT) calculations in combination with the non-equilibrium Green’s function method to examine the effect of Au contacts on the electronic transport properties of single layer MoS2. Our results indicate that Au, the most common contact metal in this system, forms a tunnel barrier at the interface, which causes electron injection into MoS2. The ultimate of this systematic study is to calculate the Schottky barriers for different interfaces of MoS2 and Au contact, a fundamental understanding of which is critical to successful manufacturing of MoS2 transistors. Charge density analysis, transmission spectra, and I-V curves will be reported and discussed as a function of MoS2 and Au interfaces of varying geometry.
Atomic Diffusion on dislocated and stepped surfaces
Figure 11. Schematic cross-section of slab containing a dislocation: (a) in a tensilely strained system (b) in a compressively strained system.
We apply molecular dynamics and molecular static methods to study the effect of misfit dislocations on adatom diffusion in close proximity to the dislocation core in heteroepitaxial systems, using many-body interaction potentials.The misfit dislocations are created with the core located at the interface between the Cu film and the Ni substrate, using the repulsive biased potential method described earlier. We find that presence of the defect under the surface strongly affects the adatom trajectory, creating anisotropy in atomic diffusion, independent of the thickness of the Cu film. The results demonstrate that the dislocation network is as a promising template for steering growth of adislands toward predetermined nucleation sites an efficient way for self-assembly. Engineering of ordered self-assembled nano-patterns plays an increasingly important role in design and development of functional nanometer-scale materials and devices, as an alternative to conventional costly and time-consuming top-down approaches and to artificially drawing nanostructures by atomic manipulation with a scanning tunneling microscopy tip or through electron-beam lithography.
Figure 12. Magnesium step
In this project, We discuss the diffusion of single metal Mg atoms on flat and stepped metal surfaces of Mg(0001). The ultimate goal of the study is to derive insights into possible growth mechanisms for Mg surface by means of calculating the diffusion barriers both at terraces and near step edges, and hence determine the so-called E-S barriers. E-S [25, 26], which are the key parameter for atomic mass transport at step-edges. We also report the stacking fault of Mg(0001) that originates from the famous Fridel oscillations on Mg(0001) surface. The results contribute towards an understanding of the role of these mechanisms in controlling the growth on these surfaces.
