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Description

Aurora utilizes principles of quantum mechanics and thermodynamics alongside a sophisticated continuous water model to assess the solvation effects on ligand binding affinities. This methodology is significantly different from the traditional scoring functions typically employed for predicting binding affinities. By integrating entropy and aqueous electrostatic contributions directly into the computations, Aurora's algorithms yield far more precise and reliable binding free energy values. The interaction between a ligand and a protein is fundamentally defined by the binding free energy value. This free energy (F) serves as a thermodynamic measure that correlates directly with the experimentally determined inhibition constant (IC50), influenced by factors such as electrostatic interactions, quantum effects, aqueous solvation forces, and the statistical characteristics of the molecules involved. Non-additivity in F arises primarily from two key components: the electrostatic and solvation energy, and the entropy, which together contribute to the complexity of ligand-protein interactions. Understanding these contributions is essential for the accurate prediction of binding affinities in drug design and molecular biology.

Description

ESMC represents the newest advancement in the ESM series of protein language models, pushing the boundaries of representation learning within the field of protein biology. With training on billions of evolutionary sequences, it adeptly captures representations that encapsulate a mechanistic understanding of protein structure and function. The model utilizes a transformer architecture, focusing on sequences as its primary modality, and is trained on a vast dataset comprising up to 6 billion proteins. ESMC is tailored for various protein science applications, such as predicting structures, annotating functions, designing proteins, and exploring evolutionary connections among proteins. Additionally, it possesses the capability to create novel proteins based on partial sequences, structures, or functional constraints, thereby enabling researchers to investigate innovative avenues in protein design and biological discovery. Accessible through the Biohub Platform, ESMC can be utilized via an API and the ESM Python package, which includes quickstart resources for installation, API key generation, and platform connectivity, ensuring a seamless experience for users. This comprehensive accessibility encourages a broader engagement with protein research and enhances collaborative efforts in the scientific community.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Biohub
Python

Integrations

Biohub
Python

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Aurora Fine Chemicals

Founded

1990

Country

United States

Website

aurorafinechemicals.com/drug-discovery-software.html

Vendor Details

Company Name

Biohub

Founded

2016

Country

United States

Website

biohub.ai/models/esmc

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Product Features

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