Problem Scenario
Protein kinases have been an important target for drug discovery, with 71 FDA-approved small-molecule kinase inhibitors as of May 2021, accounting for approximately 30% of approved small-molecule therapeutics in the past two decades. There are over 500 protein kinases in humans, collectively known as the kinome, with only a minority of these kinases explored as primary drug targets in clinical studies. In the past 20 years, the increased access to high-resolution kinase structures and the availability of high-throughput, whole-kinome “profiling” techniques have enabled a deeper knowledge of the basic structure and function of human kinases. This has led to a further understanding of various signaling pathways and their roles in normal physiology, carcinogenesis, and cancer progression. These advances have accelerated the discovery of novel kinase targets, particularly in those treatment-resistant cancer types, and have aided the development of next-generation kinase inhibitors.
Table 1. Protein kinase targets and known inhibitors
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Protein
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UNP ID
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Known Inhibitor
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Groups
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JAK1
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P23458
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Golidocitinib
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A, B, C, D, Z
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AKT1
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P31749
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Capivasertib
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E, F, G, H, I
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CDK6
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Q00534
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Palbociclib
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J, K, L, M, N
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ABL
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P00519
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Dasatinib
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O, P, Q, R, S
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BTK
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Q06187
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Remibrutinib
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T, U, V, W, X, Y
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Many kinases already have approved drugs to treat different diseases. This project aims to find new effective bioactive chemicals for protein kinase targets using in silico approaches to develop an effective treatment for cancers characterized by kinase abnormalities. Please choose one protein kinase from Table 1 as your research target. Marketed anti-cancer standard drugs shall be used for comparative evaluation. Specifically, you will perform. virtual screening through LBDD method (e.g. MOE pharmacophore module) and SBDD method (e.g. Autodock VINA). From the analysis of screening results of these two methods, you will get a shortlist with at least 10 candidate molecules for your target, and assess their bioavailability and toxicity profiles using ADMETlab 3.0 web server. Finally, you will use the molecular dynamics method to analyze the interaction between protein structure and one of the best candidate molecules in your list, with the known drug as the reference.
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Hints: The study can be divided into the following subtasks. But these are just for your reference to what you might need to do to draw a conclusion. You can do whatever you think is appropriate to achieve the goal.
Task 1. Collect the protein target information from the databases (e.g. UniProt, PDB), and organize it into a table. Utilize a crystal complex structure with a known substrate (ATP or ADP) or known inhibitor to find the potential binding pocket. Report your key results and explain. The key residues and hotspot for drug design should be exhibited in the figures.
Task 2. Take the suitable dataset to do the pharmacophore modeling with MOE pharmacophore module. Use the pharmacophore model obtained to screen the small molecule library in datafiles. Choose the top e.g. 100 candidate molecules from the screening results. Report your key findings and explain.
Task 3. Use the potential binding pocket from Task 1 as the binding site to do the virtual screening with AutoDock VINA. Process the preparation process for the candidate molecules from Task 2 as the virtual screening library. Select the top e.g. 10 candidate molecules from docking and analysis the docking results. Compare the binding conformation and key interactions with known ligand-protein complex structure. Report your key findings and explain.
Task 4. Take the top 10 molecules from TASK 3 to analysis their bioavailability and toxicity profiles on ADMETlab 3.0 web server. Report your key findings and explain. Select the best one candidate molecule comprehensively from docking results from Task 3 and the property results in this TASK, and explain your results.
Task 5. Take the best one candidate molecule from TASK 4 to conduct molecular dynamics (MD) simulation to further study the interaction between protein pocket and the candidate molecule. Utilize the known inhibitor complex system (from docking or PDB database) as a reference system to conduct MD simulation parallelly.
Task 6. Analyze MD trajectories using VMD to observe the stability of ligand binding and key interactions within the complex, to calculate hydrogen bonds between compound and protein during MD simulation. Observe the conformational changes between the docking result and the final conformation of MD simulation. Plot the comparation and explain. Calculate the Root-mean-square deviation (RMSD) of proteins and compounds for both candidate system and known inhibitor system, along with the Root-mean-square fluctuation (RMSF) of protein residues with Gromacs for a more in-depth analysis of the interaction for each system.
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Prepare Your Report
The report does not necessarily follow the organization of a real scientific publication. Nevertheless, the report should consist of but not limited to the following sections: background, methods, results and discussion.
Hints on Sections of the Report:
Background: You may provide an overview of, but not limited to, the status quo of JAK1 inhibitory drugs and rationales of designing new ones, pros and cons of commonly used VS methods and/or technologies, aims of your study, preliminary findings, etc. (Recommended word limit: 400)
Methods: Briefly describe the operations you conduct for each task. Provide a rational explanation for your methods and settings. Please note that this section mustn’t be like a lab protocol. Specifically, descriptions of computational methods employed should be given in detail sufficient to enable experienced computational workers to repeat them. There should be a precise description of any computer software used, including any version or revision numbers, and the type of computer used. You should describe in general terms the facilities provided by the software and present a concise account of how you used the computer package, sufficient for someone else to understand what you did, but not detailed step-by-step instructions. You might wish to describe any limitations of the software which affected how you used it. (Recommended word limit: 1,000)
Results: Report your key findings. You might also use figures and/or tables to summarize them.
Discussion: Explain your findings and interpret. Refer to Task 4 and Task 5 for an example. Results and discussion sections may also be combined together. (Word limit for these two sections: 1,600)
The report should not exceed 10 pages or 3,500 words (excluding references). Make sure that you follow the general style. guide of academic writing.
File Format: Your report should be in single-column WORD format.
Font: The font size for the main text should be 11 points. The same font type and size should be used for the entire report (with possible exception for figures and tables – should be 9 points). The following fonts are acceptable: Times New Roman, Helvetica and Tahoma.
Line Spacing: The text should be 1.5 lines-spaced throughout with the following exceptions:
§ Captions for figures/tables – should be single-spaced
§ Footnotes – should be single-spaced
Paragraph Spacing: Your report should have no extra spacing after paragraphs.
Figures and Tables:
§ Position and numbering - Figures and tables should be positioned closed to where their information is used, and numbered in the order that they appear in the text. Figures should be wrapped in line with text.
§ Captions - All figures and tables need captions which usually spend one sentence to clarify the function of the figure/table. Other sentence(s) will give information about how to read the figure. Captions should be placed below figures and above table.
Footnote: Footnotes should appear at the bottom of each page for easy reference and not at the end of the report.
Reference List: Your list of works cited should begin at the end of the report on a new page with the uppercase bold title, REFERENCES. The reference list should be formatted in Harvard style.