This distinguished event was expertly hosted by Pritha Das, whose seamless coordination and confident presence set a strong and professional tone for the day. Her ability to engage the audience, guide insightful discussions, and ensure a smooth progression between sessions was highly commendable. From the opening address to the closing remarks, Pritha das demonstrated exceptional professionalism, clarity, and a consistent focus on fostering meaningful and productive dialogue.

Beyond overseeing the event flow, she made a concerted effort to ensure that every participant felt acknowledged and valued. Through thoughtful moderation, interactive engagement, and a welcoming approach, she created an inclusive environment that encouraged active participation and knowledge exchange. Her dedication to excellence and passion for collaboration played a significant role in the overall success of the event, leaving a lasting and positive impression on all attendees.

Advent –  Surojit Sadhu, Founder and CEO, Advent Informatics Pvt. Ltd.

Surojit started the session with a brief presentation about Advent. He focussed on its history and how he always tries to bring the best of global solutions to Indian users and enable cost-effective research. He shared the mission of Advent was to be an end-to-end high-quality software solution provider for Pharma, Biotech , Chemical companies and empower academics with  state-of-the-art softwares for Chemoinformatics, Molecular Modelling, Medicinal Chemistry, and Chemical data management. He also shares a brief overview of the Solutions we offer from various companies like Chemaxon, Molsoft, Certara, Chempass, KeyModule, and Transgene IT.

He also shared how Advent’s clients appreciate the timely support Advent provides and rate Advent very high in terms of its support and responsiveness.

ICM as a Comprehensive Environment for Drug Discovery – Prof. Ruben Abagyan, Founder – Molsoft LLC

Dr. Ruben Abagyan presented ICM as a unified, physics-based platform for structure-based drug discovery, combining molecular modeling, docking, screening, and AI/ML. He highlighted ICM’s foundation in internal coordinate mechanics, enabling efficient conformational sampling and accurate flexible docking. Comparisons with deep-learning pose predictors show that physics-driven ICM achieves superior pose recovery and enrichment, underscoring the value of rigorous physical modeling.
ICM employs a multi-layer architecture consisting of a cross platform graphical front end, scalable CPU/GPU back-end engines, and a unified internal file format to support reproducibility and seamless data exchange. Dr. Abagyan highlighted hybrid scoring strategies that combine physics-based energy functions with neural-network models such as RTCNN, together with curated structural resources (e.g., Pocketome), ultra-large chemical libraries, and LigBend-based advanced docking workflows for efficient exploration of complex binding sites.
Case studies demonstrated rapid translation from virtual screening to the clinic, including Lonitoclax, now in Phase II after overcoming Venetoclax-resistant BCL-2 mutations.
Lomonitinib, an ICM-enabled FLT3 inhibitor active against resistant mutants, has completed Phase I and is advancing to Phase II.
The presentation emphasized how integrating accurate physics, advanced AI, and cross-disciplinary collaboration accelerates modern drug discovery.

Inside MolSoft ICM: Combining Artificial Intelligence and Physics for Next-Generation Molecular Discovery – Dr. Andrew Orry – Senior Scientist – Molsoft LLC

Dr. Andrew Orry, Senior Scientist at MolSoft LLC, delivered his first presentation in India on the integration of artificial intelligence and physics within MolSoft ICM for next-generation molecular discovery. He highlighted recent advancements in ICM (beta version 3.9.4A), emphasizing new AI-driven tools for drug design and development. Key features include GroupGen, a neural network for site-specific R-group generation, which uses a 3D graph convolutional encoder to capture receptor context and a decoder to propose chemically feasible 2D modifications. These designs are scored using combined physics-based and RTCNN neural network scoring, balancing binding accuracy, strain, and synthesizability.
Dr. Orry demonstrated Ligand AIDE, enabling fully interactive de novo ligand design within the binding pocket, and showcased tools for peptide modeling, including residue modification, terminal group addition, and peptide stapling with integrated energy minimization. He also introduced GigaSearch, a high speed substructure and fingerprint search across online chemical databases such as Enamine REAL, Chemspace, and ZINC.
Finally, he presented CombiRidge, a GPU-accelerated workflow combining fragment-based docking, conformer generation via GINGER, and iterative generative design to efficiently explore ultra-large chemical spaces (billions of compounds), identifying novel hits beyond conventional libraries. Additional highlights included a new AI assistant for automated script generation and workflow support, reinforcing ICM’s role as a unified platform for physics- and AI-driven drug discovery.

Using ICM in diverse modalities – Dr. Ramesh Sistla, Founder and MD, Think Molecular Technologies Pvt Ltd

Dr. Ramesh Sistla, Founder and Managing Director of Think Molecular Technologies Pvt. Ltd., and Dr. Kuzhanthaivelan S, Research Investigator, presented Think Molecular’s integrated AI- and physics-based molecular modeling platform at the ICM User Meeting, emphasizing the extensive application of ICM-MolSoft technologies for structure-guided small-molecule drug discovery. The presentation outlined Think Molecular’s positioning as a technologies-driven organization providing end-to-end computational support from target identification and assessment through hit discovery, lead optimization, and candidate design.

The platform integrates structure-based virtual screening, Atomic Property Field (APF) pharmacophore modeling, fragment-based drug discovery, ensemble (4D) docking, molecular dynamics simulations, 3D ligand editing, exit-vector prediction, homology modeling, and machine-learning–augmented scoring within the ICM framework. Representative case studies demonstrated successful application across covalent inhibitor discovery, metalloprotein targeting, peptide and macrocyclic ligand design, PROTAC ternary complex modeling, radioligand development, and RNA- targeted small molecules, including clinically relevant programs.
Collectively, the work illustrates how ICM-MolSoft, proprietary algorithms, and high-performance computing enable accurate molecular recognition and accelerated generation of high-quality chemical matter for modern computational drug discovery.

Predictions of hard and soft spots with MolSoft: Drug metabolism and covalent binding applications – Dr. Vaibhav A. Dixit, NIPER-Guwahati.

Dr. Vaibhav A. Dixit, Assistant Professor at NIPER, presented a computational framework for predicting metabolic hard/soft spots and guiding covalent inhibitor design using MolSoft tools, DFT, and molecular modeling. The approach integrates reactivity (DFT-derived activation barriers, pathways, and electrophilicity) with accessibility (ICM docking and molecular dynamics) to rationalize metabolite formation and toxicity.

Using PARP1 inhibitors such as Olaparib, cytochrome P450-mediated hydroxylation and amide hydrolysis pathways were characterized. Gaussian-based DFT calculations identified M12 as a highly electrophilic, potentially toxic metabolite, while the major metabolite M11 was predicted to be non-toxic. Docking of metabolites into CYP3A4 using MolSoft ICM showed that some energetically feasible pathways are limited by poor accessibility. MD simulations further supported pose stability and explained inter-individual variability in metabolite formation.

Extending these principles to covalent inhibitor discovery, particularly for EGFR, Dr. Dixit, presented a case study on covalent docking in which reversible pre-binding, warhead positioning, and covalent bond formation with catalytic cysteine residues were modeled using MolSoft. A 3D-QSAR model for reversible binding achieved an R² of ~0.83, and further evaluation using a novel Unbiased R² (UR²) metric that incorporates experimental uncertainty indicated that model performance is already within experimental error, minimizing the risk of overfitting.

Overall, the study demonstrates how physics-based calculations and structure-based modeling can guide safer drug design and selective covalent inhibitor development.

Computational Repurposing of Approved Drugs using ICM Suite: Exploring New Therapeutic Avenues for Liver Disorders – Dr. Asha Thomas & Ms. Pranali Jadhav, DPU Pharmacy, Pune.

Dr Asha Thomas (Professor and HOD) gynan prasad global university, and Pranali Jadhav assistant prof at gynan prasad global university
Liver disorders, particularly MASH and NASH, are increasing globally and are strongly associated with metabolic abnormalities, sedentary lifestyles, and epigenetic regulation. Although drugs such as resmetirom, semaglutide, and pioglitazone demonstrate clinical benefit, concerns regarding long-term safety and limited accessibility underscore the need for alternative and natural hepatoprotective therapeutic strategies.
This study employed an integrated Molsoft-based computational and experimental approach to identify novel hepatoprotective agents. A curated library of phytoconstituents from medicinal herbs was screened using Molsoft cheminformatics and drug-likeness evaluation, followed by in vitro validation in HepG2 cells, resulting in the selection of 40 bioactive compounds. Network pharmacology and STRING-based protein–protein interaction analysis identified key molecular targets, including PPARβ/δ, TNF-α, AKT1, mTOR, and interferon signaling pathways.

Molecular docking, pharmacophore modeling, and virtual screening of ZINC natural derivative subsets using Molsoft tools identified multitarget candidates, with rosmarinic acid and gossypetin emerging as lead compounds. These were further validated through 500-ns molecular dynamics simulations and subsequent in vitro and in vivo studies. In parallel, FDA-approved drug repurposing using Molsoft-based APF modeling, docking, molecular dynamics simulations, and HepG2 MTT assays confirmed additional hepatoprotective potential.

ICM chemist for Medicinal chemistry project in CRO: Challenges and Opportunities. – Dr. Muruganantham Rajendran, Syngene Intl.

Dr. Murugananthan R (Syngene) highlighted the practical utility of ICM-Chemist Pro in supporting medicinal chemistry programs within CRO environments, where rapid decision-making is essential despite limited data availability. He emphasized that major efforts in lead optimization are distributed across ADME/property prediction (≈30%), analysis of ligand–target interactions (≈25%), SAR interpretation (≈20%), synthetic feasibility (≈15%), and project management (≈10%). ICM-Chemist Pro enables efficient evaluation of hydrogen bonding, electrostatic, and van der Waals interactions, identification of growth vectors, and trend analysis, thereby facilitating informed scaffold prioritization and multiparameter optimization (including CNS-MPO scoring). The platform supports library enumeration, centralized data management, filtering, and synthesis planning, promoting seamless collaboration between CADD scientists and medicinal chemists. Its lightweight architecture, fast 2D–3D editing, real-time pocket visualization, and user-friendly interface make it accessible even to non-computational chemists. Key challenges noted include limited automation for report generation, lack of ELN integration, and performance constraints when handling very large datasets.

Structure guided design of Biologics using Molsoft tools – Dr. Achintya Das, Syngene Intl.

Dr. Achintya Das, Head of Computational and Data Sciences at Syngene International, presented structure-guided biologics and antibody design workflows using MolSoft tools. He highlighted the growing demand for biologics and the computational challenges associated with modeling large, flexible biomolecules. Increased availability of biologics data has improved predictive accuracy to ~95% for several tasks, while epitope prediction remains around ~70% due to limited data.
He described an integrated workflow where Rosetta RFdiffusion models generate initial structures, followed by fast protein–protein rigid-body docking in ICM-MolSoft and rapid scoring using trained MMGBSA and internal scoring functions. This hybrid physics- and ML-aligned approach achieved ~95% correlation with experimental data while reducing computational time by ~50%. Fast docking and scoring with ICM, embedded within Syngene’s DMTA framework, enables efficient ADC and antibody modeling.
A case study on humanization and optimization of a murine antibody against five CXCL targets demonstrated structure generation, ICM FFT docking, internal scoring, and development liability assessment to guide candidate selection, underscoring ICM-MolSoft as a key enabler for rapid protein–protein docking in biologics discovery.

Structure based studies of RNA-small molecule and RNA-Protein complexes with Molsoft tools – Dr. Shamshair Singh Sardar & Mr. Aditya Mishra, Advent Informatics Pvt. Ltd.

Dr. Shamshair Singh and Aditya Mishra showcased Structure-based studies of RNA–small molecule and RNA–protein complexes using Molsoft ICM tools. They highlighted RNA as a viable target while outlining the challenges of RNA docking, underscore the central role of electrostatics, and emphasized the importance of ions and solvent for accurate predictions. The presenters discussed ICM features for both protein-RNA docking and RNA-small molecule docking, focusing on flexible docking, scoring viable with RNAs, and an integrated workflow for preparation, docking, and analysis. Benchmarking results demonstrated that employing RNA complexes and proper electrostatics improves pose accuracy and enrichment. Overall, their work positions ICM as a user-friendly, workflow driven environment that enhances reliability and reproducibility in RNA-focused docking studies.