Kallyope
Deciphering the gut-brain axis through AI-driven drug discovery for transformative therapeutics.

The industry-standard open-source engine for molecular docking and computational drug discovery.
AutoDock is a suite of automated docking tools designed to predict how small molecules, such as substrates or drug candidates, bind to a receptor of known 3D structure. The suite comprises two main programs: AutoDock 4 (AD4) and AutoDock Vina. As of 2026, AutoDock remains the most cited docking software in the world, maintaining its market relevance through the AutoDock-GPU implementation which leverages OpenCL and CUDA for massive parallelization. Its technical architecture utilizes a Lamarckian Genetic Algorithm (LGA) and an empirical force field to identify low-energy binding poses. The integration of AutoDock-Vina has significantly improved speed and accuracy by employing an iterated local search global optimizer. For the 2026 drug discovery landscape, AutoDock is a foundational layer often integrated into AI-driven pipelines where machine learning models (like GNina or DiffDock) post-process its physics-based candidate poses. It supports flexible side-chain modeling and covalent docking, making it indispensable for academic research and initial-stage pharmaceutical lead identification where high-throughput virtual screening (HTVS) efficiency is paramount.
Combines a genetic algorithm (global search) with a local search method to find optimal binding poses efficiently.
Deciphering the gut-brain axis through AI-driven drug discovery for transformative therapeutics.
Accelerating drug discovery through an end-to-end generative AI pipeline for target identification, molecular design, and clinical trial prediction.
The industry-standard interactive visualization tool for integrated exploration of large-scale genomic datasets.
Unlocking the causal biology of disease through Gemini Digital Twins.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
An OpenCL/CUDA port of AutoDock 4 that parallelizes the LGA across thousands of GPU cores.
Employs a sophisticated optimization algorithm that improves the probability of finding the global minimum of the scoring function.
Allows specified amino acid side chains in the receptor to be treated as flexible during the docking process.
Includes explicit water molecules in the docking process to account for water-mediated interactions.
Calculates binding affinity based on van der Waals, hydrogen bonding, electrostatic, and desolvation terms.
Models the formation of covalent bonds between the ligand and the receptor using specific grid potential adjustments.
Identifying potential hits against a viral protease from a library of 10,000 compounds.
Registry Updated:2/7/2026
Rank results by binding energy.
Refining the structure of a known binder to improve potency.
Accounting for protein movement upon ligand binding.