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What is PyMOL?

PyMOL is a molecular visualization software that operates as a user-supported open-source project, with its management and distribution handled by Schrödinger. The transition to the PyQt interface has replaced Tcl/Tk and MacPyMOL across all systems, which has greatly improved the overall user experience. This platform provides enhanced compatibility for third-party plugins and custom scripting, establishing it as a robust tool for visualizing and animating three-dimensional molecular structures. Additionally, a plug-in enables users to seamlessly integrate 3D images and animations into PowerPoint presentations, facilitating better communication of scientific concepts. While PyMOL is commercially licensed, a significant portion of its source code is available for free under a permissive license, supporting its open-source nature. This initiative is primarily funded by the sales of PyMOL licenses, with Schrödinger playing a key role in its sustainability. Users enjoy the advantages of open access to executables and a flexible evaluation system, allowing them to explore the software's capabilities thoroughly. Recent updates have introduced an improved fuse command that eliminates hypervalent bonds, substituting them with monovalent atoms, and a new properties inspector that allows settings to be unset using the “delete” key for greater user control. Moreover, the resolution issues that previously caused the workspace to disappear have been addressed, enhancing the overall user experience significantly. As a result, users can now work more effectively, enjoying a more polished and reliable interface.

What is MolPad?

MolPad integrates an interactive chemistry sketching tool into various online educational platforms, empowering educators to formulate open-ended inquiries related to molecular structures and organic chemistry that go beyond mere correct answer identification. Discover how MolPad enhances chemistry instruction online through a low-code framework that streamlines the creation of captivating content and intelligent assessments. Our platform provides several innovative solutions for the intuitive drawing of structural formulas, enabling students to interact with concepts like chemical nomenclature, functional groups, and Lewis structures in a digital environment. By delivering tailored feedback based on specific errors, students can gain a more profound understanding compared to traditional multiple-choice methods, ultimately enriching their chemistry learning experience. This interactive methodology not only promotes critical thinking but also stimulates creativity as students delve into complex chemical concepts. Therefore, the combination of technology and education in MolPad represents a significant advancement in the way chemistry can be taught and learned.

Media

Media

Integrations Supported

Laby
Microsoft PowerPoint
Python

Integrations Supported

Laby
Microsoft PowerPoint
Python

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

PyMOL

Company Location

Germany

Company Website

pymol.org/2/

Company Facts

Organization Name

MolPad

Company Website

molpad.com

Categories and Features

Categories and Features

Chemical

Certificates of Analysis
Chemical Process Simulation
Computer-Assisted Structure Elucidation (CASE)
ISO Management
Inventory Management
Particle Tracking
Reporting & Statistics
Samples Tracking
Traceability
Uncertainty Analysis

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