ProSynn

An educational game for learning protein synthesis through interactive gameplay.

Gameplay Video
ProSynn application screenshots

Overview

ProSynn is an interactive educational game designed to make learning protein synthesis more engaging through gameplay.

Developed during my undergraduate biotechnology studies, the application transforms the biological process of translation into a timed game. Players match mRNA codons with their corresponding amino acids to synthesize proteins while managing a limited number of mistakes.

The application was developed using the Unity game engine and deployed across Android, Windows, and Linux.

My Contributions

  • Designed and developed the complete educational game from concept to implementation.
  • Translated the biological process of protein synthesis into interactive gameplay mechanics.
  • Implemented the game logic, scoring, timers, and player feedback.
  • Designed the user interaction and visual presentation of the application.
  • Developed and packaged the application for multiple platforms.

System

The game focuses on the translation stage of protein synthesis.

Players are presented with mRNA codons and must correctly identify the corresponding amino acids. Correct matches contribute toward protein synthesis, while incorrect choices consume one of the player’s limited attempts.

The game supports 10, 20, and 30-second gameplay modes, with the objective of synthesizing as many proteins as possible within the selected time limit.

The core gameplay loop is:

mRNA Codon → Amino Acid Selection → Correct/Incorrect Feedback → Protein Synthesis → Score

Players are allowed a maximum of two mistakes before the game ends.

Technical Highlights

  • Engine: Unity 5.4.2f2
  • Platforms: Android, Windows, Linux
  • Domain: Biotechnology / Educational Technology
  • Core Mechanic: mRNA codon → amino acid matching
  • Gameplay: Timed protein synthesis challenge
  • Game Modes: 10, 20, and 30 seconds
  • Game Logic: Scoring, mistake tracking, timers, and game-state management
  • Educational Focus: Interactive learning of protein translation

Team

Sumit Patidar · Archit · Vaibhav