COMPUTATIONAL
Structural Biology

Computational approaches to generate, analyse, and interpret structural models in scientific context.

From structural hypotheses to project-relevant insight.

Computational structural biology helps generate and interpret molecular insight when experimental structures are not available, incomplete, or need additional context. AI structure prediction, virtual screening, molecular dynamics simulations, and model validation can support research, drug discovery, protein engineering, and structural interpretation at different stages of a project.

At BIMOVIS, we see the strongest value in combining computational and experimental structural biology. AI-generated models, docking results, or simulation data become more useful when they are interpreted together with sequence information, biochemical data, cryo-EM, X-ray crystallography, public structures, and the scientific question behind the project.

Our computational structural biology services can be used as standalone analyses or as part of an integrated workflow. In drug discovery projects, they also support computer-aided drug design by helping define structural hypotheses, prioritize chemical space, assess binding-site behavior, and guide experimental follow-up.

AI Structure Prediction & Model Analysis

From predicted structures to useful molecular insight.

AI structure prediction has opened new possibilities for structural biology. It can provide rapid access to structural hypotheses and help explore protein architecture, domains, complexes, interfaces, and functional regions much earlier in a project.

At BIMOVIS, we actively offer AI-supported structure prediction and model analysis. We generate, assess, and interpret AI-generated models in the context of the biological question, available data, and project strategy. The goal is not only to obtain a model, but to understand what it supports, where confidence is strong and where further analysis or validation is needed.

AI / COMP

Virtual Screening

Computational screening to prioritize promising compounds and chemical starting points.

Virtual screening helps explore chemical space before committing to larger experimental screening campaigns. It supports hit identification by prioritizing compounds with plausible binding behavior, structural fit, or similarity to known active molecules.

At BIMOVIS, virtual screening is connected to structural biology and computer-aided drug design. We use structure-based and ligand-informed approaches, including molecular docking and computational scoring, to generate compound priorities and binding hypotheses for experimental follow-up.

VSCREEN

Molecular Dynamics Simulations

Physical modelling of molecular motion, interactions and binding-site behavior.

Molecular dynamics simulations add a time dimension to structural biology, helping explore how proteins, complexes, ligands or binding sites move, respond, and interact under defined conditions.

At BIMOVIS, we use molecular simulations to investigate questions where flexibility, stability, or interaction dynamics matter. This may support the interpretation of binding mechanisms, residue interactions, conformational changes, or model stability. Where available, simulation setups are informed by experimental structures, AI-generated models, and biochemical context.

MD · SIM

Computational Epitope Mapping

Structural modelling to identify and characterize antibody–antigen binding interfaces.

Computational epitope mapping helps identify where and how an antibody is likely to bind its antigen, providing residue-level hypotheses of the binding interface even when an experimental complex structure is not yet available.

At BIMOVIS, we combine structural modelling with antibody–antigen interface analysis to predict binding regions, key interacting residues and overall binding geometry. The resulting structural hypotheses can support antibody selection, candidate differentiation, affinity maturation and experimental follow-up.

STRUCT-ANAL

Structure Analysis & Model Validation

Expert assessment of structures, models and structural data in scientific context.

Structural models are most valuable when their quality, limitations and biological meaning are understood. This applies to experimental structures, AI-generated models, protein-ligand complexes, molecular assemblies and models used for simulation, docking or visualization.

At BIMOVIS, we analyse structures in relation to the scientific question. We assess model quality, confidence, uncertainty, and structural features such as binding sites, interfaces, conformational states, or residue-level interactions. The goal is to define what a structure can support, where interpretation needs caution, and which next step is most appropriate.

MD · SIM

Connect molecular visualization with structural biology.

Experimental Structural Biology

Cryo-EM, X-ray crystallography and related methods to generate experimental structures and validate computational hypotheses.

Molecular Visualization

Scientific images, animations and visual formats that make structural models, mechanisms and computational findings clear.

Structural Biology Consulting

Method-independent expert input to define suitable computational or experimental strategies and interpret structural biology results.

Go deeper in our Knowledge Hub.

Guides, protocols, and reference materials to support your structural biology projects — free to access.

COMPUTATIONAL Structural Biology