GruLab webpage

The GruLab group

Led by Sergei Grudinin, CNRS Researcher at Jean Kunzmann Laboratory, Grenoble Alpes University.

Checkout out GitLab repositories!

Group

Group and collaborators

Sergei Grudinin

CNRS researcher (Research Director), HDR, group leader.

Khan-Chi Nguyen-Pham

PhD student. Development of language models for virtual drug screening. Co-supervised with Yung-Sing Wong. Funded by Département de Pharmacochimie Moléculaire.

Wang Jing

PhD student. Development of novel physics-based cell simulation techniques. Funded by ANR.

Jérémie Perrin

PostDoc. Development of novel cell simulation techniques. Funded by ANR.

Khan-Chi Nguyen-Pham

PhD student. Development of language models for virtual drug screening. Co-supervised with Yung-Sing Wong. Funded by Département de Pharmacochimie Moléculaire.

Kento Okado

PhD student. Multiscale geometric learning. Co-supervised with Boris Thibert.

Elodie Laine

Professor at Sorbonne University, Paris, France. Protein sequence to structures and functions. Co-advises V. Lombard and Julien Nguyen Van.

Julien Nguyen Van

PhD student. Deciphering the complexity of proteoform interactions with evolutionary- and physically-informed protein language models. Co-supervised with Elodie Laine. Funded by the ERC.

Emmanuel Jehanno

PhD student. Development of deep-learning methods for material science. Co-supervised with Julien Mairal. Funded by the ERC.

Roman Klypa

PhD student. Novel Generative Models with Equivariant Properties for 3D Biological Data. Co-supervised with Alberto Bietti. Funded by École Polytechnique.

Davy Darankoum

PhD student. Development of deep-learning methods for EEG signals. Co-supervised with Julien Volle. Funded by SynapCell.

Tomáš Černocký

PhD student. Novel Generative Models for proteins with space-group symmetries. Co-supervised with Jacques-Philippe Colletier. Funded by MIAI.

Pablo Chacon

Research Staff Scientist at Institute of Physical Chemistry (IQFR-CSIC), Group leader (IQF Madrid, Spain).

Nathalie Reuter

Professor at Bergen University (Norway), Group leader.

Mikael Lund

Professor at Lund University (Sweden), Group leader.

Eric Deeds

Professor at UCLA (USA), Group leader.

Julien Mairal

Researcher at Inria, Group leader.

Yung-Sing Wong

CNRS Researcher, Group leader.

Dina Schneidman

Professor at Hebrew University of Jerusalem, Group leader.

Interns

Andrei Kalinin

Lancelot Ravier

Emmanouil Tsagkarakis

Nayane Gräff

Gabriel Pelle

Carmen Lopez Michalowska

Alumni

Kliment Olechnovič

Senior Researcher at Vilnius University Life Sciences Center.

Florian Echelard

Dmitrii Zhemchuzhnikov

Valentin Lombard

Rémi Vuillemot

We are hiring!

We are looking for highly talented and motivated PhDs and Post-doctoral fellows, with backgrounds in applied mathematics and physics, algorithms and computer science, and structural bioinformatics.

Get in touch!

Software

Try them out

All
Scattering
Symmetries
Motions
Proteins
[R,D]NAs
Drugs
Design
Algorithms
ML
DL

NOLB Normal Modes[Video]

How does my favourite protein move?

S. Grudinin+, E. Laine+, and A. Hoffmann (2020) Biophys. J. A. Hoffmann and S. Grudinin (2017) J. Chem. Th. Comput.

RNA-BAnG

A new way to generate RNA sequences by starting at the point where the RNA binds to the protein and building outward

R. Klypa, A. Bietti, S. Grudinin (2025) ICLM

AFMFit

How to reconstruct molecular motions using low-res AFM data?

R. Vuillemot, J.L. Pellequer, and S. Grudinin* (2025) Communications Biology

DANCE

From sparse static structures to movies!

V. Lombard, S. Grudinin* and E. Laine* (2024) Scientific Data

PETIMOT

A new formulation of protein flexibility that learns protein motions from sparse experimental data

V. Lombard, S. Grudinin* and E. Laine* (2025) ICLR Workshop LMRL

SeaMoon

From protein sequence to protein movies!

V. Lombard, D. Timsit, S. Grudinin* and E. Laine* (2025) Structure

6DCNN

6D roto-translational convolution filters for volumetric data processing

D. Zhemchuzhnikov, I. Igashov, S Grudinin* (2022)

ILPONet

Invariance to rotations and translations of local patterns in volumetric data

D. Zhemchuzhnikov, S Grudinin (2024)

EquiLoPO

Roto-translational equivariance and activation in the Fourier space

D. Zhemchuzhnikov, S Grudinin (2024)

S-GCN

Spherical graph convolutional networks

I. Igashov, N. Pavlichenko, and S. Grudinin* (2021)

VoroCNN

Convolutional neural network trained on Voronoi tessellation of 3D protein structures

I. Igashov, K. Olechnovič, M. Kadukova, Česlovas Venclovas, and S. Grudinin* (2021)

HOPMA

More freedom to the proteins!

E. Laine* and S. Grudinin* (2021) J. Phys. Chem. B

KORP-PL

Virtual screening pipeline

M. Kadukova, K. dos Santos Machado, P. Chacón*, S. Grudinin* (2021)

Knodle

KNOwledge-Driven Ligand Extractor

M. Kadukova, S. Grudinin* (2016)

Convex-PL

Knowledge-based scoring function for protein-ligand interactions

M. Kadukova, S. Grudinin* (2011-2020)

AnAnaS

Analytical Analyzer of Symmetries

G. Pagès & S. Grudinin* (2018)

Sam

Ultra-fast FFT-based protein symmetry asembler

D. Ritchie & S. Grudinin (2015)

Pepsi Suite

Multipole-based SAXS and SANS profile computation method

S. Grudinin (2016-now)

DeepSymmetry

3DCNN to detect structural repetitions in proteins and their density maps

G. Pagès, and S. Grudinin* (2019)

Ornate

3DCNN built on oriented local protein frames

G. Pagès, B. Charmettant, and S. Grudinin* (2019)

Sbrod

Smooth orientation-dependent scoring function for coarse-grained protein quality assessment

M. Karasikov, and S. Grudinin* (2018)

RapidRMSD

Rapid computations of the root mean square deviations (RMSD) of flexible molecules

E. Neveu, P. Popov, A. Hoffmann, and S. Grudinin* (2018)

RigidRMSD

Constant-time calculation of the root mean square deviations (RMSD) for rigid molecules

P. Popov, and S. Grudinin* (2014)

Publications

Full list here


Title	Cited by	Year
Single-and Multi-bead Coarse-grained Form Factors for SAXS Calculations I Vinterbladh, R Vuillemot, S Grudinin, M Lund		2026
Anisotropic coarse-grain Monte Carlo simulations of lysozyme, lactoferrin, and NISTmAb by precomputing atomistic models (vol 161, 094113, 2024) HW Hatch, C Bergonzo, MA Blanco, G Yuan, S Grudinin, M Lund, ... JOURNAL OF CHEMICAL PHYSICS 164 (23), 2026		2026
CryoARC: Atomic-resolution conformational landscapes of protein assemblies from cryo-EM single particles with evolutionary priors R Vuillemot, S Grudinin bioRxiv, 2026.05. 25.727696, 2026		2026
Multimodal Alignment and Preference Optimization for Zero-Shot Conditional RNA Generation R Klypa, A Bietti, S Grudinin arXiv preprint arXiv:2605.23961, 2026		2026
Effects of Mutations on Tandem-Repeat Proteins Conformation Mechanisms. Application to the Phosphatase PP2A M Chiappinelli, TE Saldaño, SCE Tosatto, S Grudinin, G Parisi, ... Journal of Chemical Information and Modeling 66 (7), 3976-3986, 2026		2026
SpecMoE: Spectral Mixture-of-Experts Foundation Model for Cross-Species EEG Decoding D Darankoum, C Habermacher, J Volle, S Grudinin arXiv preprint arXiv:2603.16739, 2026	2	2026
SimHS-AFMfit-MD: An Integrative Approach for Inferring Alpha-Actinin Atomic Conformational Dynamics KX Ngo, T Sumikama, R Vuillemot, HG Nguyen, NTP Le, S Grudinin Nano Letters 26 (9), 3298-3307, 2026	1	2026
DynamicGT: A dynamic-aware geometric transformer model to predict protein-binding interfaces in flexible and disordered regions O Mokhtari, S Grudinin, Y Karami, H Khakzad Cell Systems 17 (1), 2026	5	2026
Systematic analyses of lipid mobilization by human lipid transfer proteins K Titeca, A Chiapparino, ML Hennrich, D Türei, M Moqadam, ... Nature, 1-3, 2026	7	2026
From Intermolecular Poses to Thermodynamics using Subdivided Spheres I Vinterbladh, J Bye, R Curtis, H W. Hatch, S Grudinin, M Lund ChemRxiv 2025 (1217), 2025	2	2025
Navigating protein–nucleic acid sequence-structure landscapes with deep learning E Laine, S Grudinin, R Klypa, IC De Beauchêne Current opinion in structural biology 95, 103162, 2025	4	2025
Conformational dynamics of actin filaments crosslinked with alpha-actinin and their roles in suppressing cofilin-induced helical shortening and cluster formation KX Ngo, T Sumikama, R Vuillemot, HG Nguyen, NTP Le, S Grudinin, ... bioRxiv, 2025.11. 16.688667, 2025	1	2025
Intermolecular Pose Exploration using Subdivided Spheres I Vinterbladh, J Bye, R Curtis, HW Hatch, S Grudinin, M Lund		2025
Deciphering Protein-Ligand Interaction Using Protein Language Models NP Khanh-Chi, YS Wong, S Grudinin ChemBioParis2025, 2025		2025
Deciphering conformational dynamics in AFM data using fast nonlinear NMA and FFT-based search with AFMFit R Vuillemot, JL Pellequer, S Grudinin Communications Biology 8 (1), 1381, 2025	7	2025
CoSupFormer: A Contrastive Supervised learning approach for EEG signal Classification D Darankoum, C Habermacher, J Volle, S Grudinin arXiv preprint arXiv:2509.20489, 2025	1	2025
SeaMoon: From protein language models to continuous structural heterogeneity V Lombard, D Timsit, S Grudinin, E Laine Structure 33 (9), 1577-1590. e8, 2025	9*	2025
Challenges in Non-Polymeric Crystal Structure Prediction: Why a Geometric, Permutation-Invariant Loss is Needed E Jehanno, R Menegaux, J Mairal, S Grudinin arXiv preprint arXiv:2509.00832, 2025		2025
Crystal Structure Prediction with a Geometric Permutation-Invariant Loss Function E Jehanno, R Menegaux, J Mairal, S Grudinin arXiv e-prints, arXiv: 2509.00832, 2025		2025
PETIMOT: A Novel Framework for Inferring Protein Motions from Sparse Data Using SE (3)-Equivariant Graph Neural Networks V Lombard, S Grudinin, E Laine Learning Meaningful Representations of Life (LMRL) Workshop at ICLR 2025, 2025	5	2025

Conferences

Upcoming Scientific Events

Contact

Location:

LJK, UMR 5224
CNRS - Grenoble Alpes University
Bâtiment IMAG - first floor
150 place du Torrent
38401 Saint Martin d'Hères, FRANCE

Email:

sergei.grudinin@univ-grenoble-alpes.fr