Email-Based Remote Computing for Molecular Docking Jobs
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Solution Overview
Problem
Current methods for remote computing in molecular docking and dynamics require significant technical expertise and are limited by the need for constant connectivity, lacking efficient offline processing and user-friendly job submission mechanisms.
Innovation Solution
An automated method and system that allows users to submit molecular docking and dynamics jobs via email, utilizing a remote computing platform with action tags for job processing, semantic analysis, and automated monitoring, enabling offline processing and simplified data retrieval without requiring extensive technical knowledge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional remote computing methods are used for molecular docking and dynamics, then computational tasks can be performed on remote servers, but significant technical expertise is required and constant connectivity is needed
Solution Approach 1:
The patent introduces an email-based intermediary system that mediates between the user and the remote computing platform. Users send jobs via email attachments (PDB files, coordinate files, etc.) to a remote server, which automatically processes the requests and returns results through email. This intermediary email system abstracts away the technical complexity of traditional remote computing protocols, making the system accessible to users without specialized knowledge.
Solution Approach 2:
The system implements automated job processing where the remote server autonomously receives email attachments, parses the computational parameters, executes molecular docking and dynamics simulations, and automatically sends results back to users. The system self-manages the entire workflow without requiring users to interact with complex command-line interfaces or monitoring tools, thereby eliminating the need for constant connectivity and technical expertise.
2Productivity
If traditional remote computing systems are used, then computational resources can be accessed remotely, but constant connectivity and manual monitoring are required
Solution Approach 1:
The system performs preliminary actions by automatically processing jobs in the background without requiring user presence. When a user sends an email with job parameters and attachments, the remote server immediately begins processing the molecular docking and dynamics simulations. The system proactively manages job queuing, resource allocation, and result compilation, eliminating the need for users to manually monitor or intervene in the computational process.
Solution Approach 2:
The system implements automated feedback loops where the remote server continuously monitors job progress and automatically communicates status updates to users via email. Upon completion, results are automatically packaged and returned to the user's email address. This feedback mechanism eliminates the need for users to repeatedly check system status or manually retrieve results, significantly reducing time loss associated with manual monitoring.
3Ease of operation
If email-based job submission is implemented, then user-friendly access is provided, but secure data transmission and processing must be ensured
Solution Approach 1:
The patent creates a secure computational environment where sensitive molecular data and computational results are processed in an isolated, controlled manner. The email-based submission system acts as a secure interface, with the remote server processing attachments in isolated environments and automatically deleting temporary files after result generation. This inert processing environment protects data integrity and security while maintaining ease of access through familiar email protocols.
Data Source
AI summary
An automated method for remote computing of molecular docking and dynamics from one or more jobs in a network of plurality of users. The invention employs a system to execute the method comprising at least one user device, a remote computing server and a remote database. The job defining action tags are received and scanned by the remote server. A semantic analysis is performed on the jobs to distinguish between customized and non-customized tasks. A data analysis of the jobs is packaged in a compressed format. The user is continually updated of the job status. A public link is generated and sent to the user to download the results. The link is disabled after the downloading of the results to ensure the security of the data. The method avoids any duplication of jobs and can be performed even when the user is offline.