MutAIverse detects known and novel DNA adducts and their precursor genotoxins using an AI-driven platform with mechanistic modeling and spectral mapping.

DOAJ (DOAJ: Directory of Open Access Journals) · Jun 1, 2026Peer-reviewedBioinformatics

Deep Learning Reveals Endogenous Sterols as Allosteric Modulators of the GPCR-Gα Interface

Sanjay Kumar Mohanty, Aayushi Mittal, Namra, Aakash Gaur, Subhadeep Duari, Saveena Solanki, Anmol Kumar Sharma, Sakshi Arora, Suvendu Kumar, Vishakha Gautam, Nilesh Kumar Dixit, Karthika Subramanian, Tarini Shankar Ghosh, Debarka Sengupta, Shashi Kumar Gupta, , Gaurav Ahuja

The paper identifies endogenous sterols as intracellular allosteric modulators of the GPCR-Gα interface using a deep learning toolkit and experimental validation.

eLife · Dec 8, 2025Peer-reviewedBioinformatics

Chemical Dice Integrator (CDI): A Scalable Framework for Multimodal Molecular Representation Learning

Suvendu Kumar, Saveena Solanki, Mudit Gupta, Sanjay Kumar Mohanty, Shiva Satija, Sonam Chauhan, Subhadeep Duari, Arushi Sharma, Vishakha Gautam, Sakshi Arora, Raidhani Shome, Sourav Sinha, Abhinav Kumar Sharma, Aayushi Mittal, Debarka Sengupta, , Gaurav Ahuja

The paper introduces CDI, a framework that unifies multiple molecular representations into a single embedding, achieving better predictive performance than individual methods.

bioRxiv · Nov 11, 2025 · PreprintBioinformatics

SynGlue: AI-Driven Designer for Clinically Actionable Multi-Target Therapeutics

Saveena Solanki, Sanjay Kumar Mohanty, Shiva Satija, Sonam Chauhan, N.V.M. Rao Bandaru, Sandeep Dukare, Nirbhay Kumar Tiwari, R. Naveen Kumar, A B Aravind, Subhendu Mukherjee, Dinesh Chikkanna, Wesley Roy Balasubramanian, Srinivasa Raju Sammeta, Vishakha Gautam, Sakshi Arora, , Gaurav Ahuja

SynGlue is an AI framework that designs multi-target therapeutics by combining data-driven and structure-guided methods, producing potent degraders for BRD4 and GSPT1.

bioRxiv · Aug 28, 2025 · PreprintBioinformatics

Artificial Intelligence uncovers carcinogenic human metabolites

Aayushi Mittal, Sanjay Kumar Mohanty, Vishakha Gautam, Sakshi Arora, Sheetanshu Saproo, Ria Gupta, Roshan Sivakumar, Prakriti Garg, Anmol Aggarwal, Padmasini Raghavachary, Nilesh Kumar Dixit, Vijay Pal Singh, Anurag Mehta, Juhi Tayal, Srivatsava Naidu, , Gaurav Ahuja

The paper develops Metabokiller, an AI model that predicts carcinogenic human metabolites by analyzing their biochemical properties and validates predictions through experimental assays.

Nature Chemical Biology · Aug 11, 2022Peer-reviewedBioinformatics