neuralgap.io

Update: Our Paper on our Multi-Unimodal Model architecture has been published in ISBI!
https://ieeexplore.ieee.org/document/10981182

Bioforager

Assisted Intelligent Drug Design

Early Alpha Coming Soon

Genesys Model Family

Built-In Transparency by Design

Multimodal by Architecture

Native integration of proteins, peptides, small molecules, ligand analogs
MUM framework enables incremental learning across modalities
Self-organizing protein class selection

Efficient by Design

10x less training data than benchmarks
Up to > 20x lower compute budgets
Superior out-of-distribution generalization

Interpretable by Default

Built-in transparency layers
Native hooks for attention mapping, layer archaeology, conformational analysis
Seamless integration with Circe’s confidence cartography

Learn About Genesys

Circe

Agentic Intelligence that Delivers Insight to How AI 'Thinks'

Early Alpha Coming Soon

Implement at Every Part of Your Work Flow

Neuralgap supports custom deep learning builds for Pharma clients.

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Structure Evaluation

Target protein selection & validation
Mutation-aware binding site analysis
Conformational dynamics assessment

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Hit Discovery & Optimization

Binding affinity prediction (sub-1.0 MSE)
Pose generation with uncertainty maps
SAR-guided analog prioritization

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Lead Optimization & Candidate Selection

Structure-based screening with interpretability
Ligand analog testing & ranking
Atomic-level modification assessment
False positive risk navigation

Our Articles

Follow our article series to keep track of the latest advances in AI in bio and cheminformatics

All Posts
Biotech

Unsupervised ML in Drug Discovery (I): Intro

Unsupervised ML in Drug Discovery (I): Intro Drug discovery is a challenging process, primarily due to the vast combinatorial chemical...

QSAR of Small Molecule Drugs: The Use of Neural Networks

QSAR of Small Molecule Drugs: The Use of Neural Networks Quantitative Structure-Activity Relationships (QSAR), the cornerstone of modern drug discovery,...

HMMs vs MSMs: Divergent Applications in Bioinformatics and Cheminformatics

HMMs vs MSMs: Divergent Applications in Bioinformatics and Cheminformatics From decoding the hidden messages in DNA to predicting the fluid...

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Pioneering Interpretability for AI Drug Discovery.

Bioforager

Assisted Intelligent Drug Design

Genesys Model Family

Built-In Transparency by Design

Circe

Agentic Intelligence that Delivers Insight to How AI 'Thinks'

Implement at Every Part of Your Work Flow

Neuralgap supports custom deep learning builds for Pharma clients.

Our Articles

Follow our article series to keep track of the latest advances in AI in bio and cheminformatics

Get in Touch!