Resources

Public computational workflows and resources connected to Kabir Lab research.

Resources

These resources are public research workflows or related contributions. Repository maturity labels are conservative until the PI confirms current maintenance status.

Workflows

Agent-Assisted QM/MM Platform

Purpose: Interactive flavoprotein study design with FMN/FAD detection, user-defined redox state, property-aware QM-region proposals, and portable GPU run planning.

Maturity: public study designer / Expanse submission gateway in development
Constraints: PDB structural input; QM-region and run-plan approval remain user decisions
Execution: browser planning with no public job submission

Open QM/MM Platform

Ab-Initio Interaction Map

Purpose: Automated protocol for generating three-dimensional interaction maps between molecular partners from structural inputs.

Maturity: research workflow / fork of Liu Group repository
Constraints: AMBER16 or newer, Packmol, Python 2.7-era dependencies, pyvdwsurface
License: MIT

Repository

Electrostatic Spectral Tuning Maps

Purpose: Workflow for computing van der Waals surface points and electrostatic spectral tuning maps from molecular coordinates.

Maturity: research workflow / legacy protocol
Constraints: Python 2.7, NumPy, Matplotlib, Cython, pyvdwsurface, Gaussian workflow scripts
License: MIT

Repository

Workflow For Umbrella Sampling

Purpose: Protocol for umbrella sampling simulations and PMF generation as a function of center-of-mass distance between molecules.

Maturity: research workflow / fork of Liu Group repository
Constraints: AMBER16 or newer, Packmol, WHAM
License: MIT

Repository

External Learning Resources

Public documentation, tutorials, lectures, and short books useful for computational chemistry onboarding. Software access can depend on licensing, platform, or institutional availability.

Molecular Simulation and Visualization

Quantum Chemistry Software

Programming and Foundations

Video Learning

Seminar and Lecture Archives

Short Books and Guides

Source list adapted from the public Acharya Lab resources page.

Student Onboarding Resources

Students joining computational projects typically begin with Linux command-line work, Python scripting, molecular visualization, version control, and careful research notebooks. Public training materials will be added here after they are approved for reuse.