Structure-Based Function Prediction Service

Structure-Based Function Prediction utilizes the three-dimensional (3D) structure of macromolecules, primarily proteins, to deduce their biological role, binding partners, and mechanism of action. By analyzing features such as active site geometry, surface topology, ligand-binding pockets, and conformational dynamics, we can predict functional characteristics with high fidelity, often surpassing predictions based solely on sequence homology. This service is critical for novel drug target identification, understanding disease mechanisms, and guiding protein engineering efforts.

CD Biosynsis offers a cutting-edge Structure-Based Function Prediction CRO service, integrating high-resolution structural data (from X-ray crystallography, NMR, or Cryo-EM) with sophisticated computational tools, including molecular docking, molecular dynamics (MD) simulations, and proprietary machine learning algorithms. We provide deep insights into protein-ligand, protein-protein, and protein-nucleic acid interactions. Our end-to-end service transforms raw structural models into comprehensive functional profiles, significantly accelerating the validation and optimization phases in therapeutic and biotechnology development.

Highlights

Our platform delivers unparalleled functional insights by directly interrogating the physical architecture of biological molecules.

• Deep Mechanistic Insight: Directly visualize and quantify interaction forces within the active site, explaining functional differences among variants.
• High-Fidelity Binding Prediction: Utilize advanced molecular docking and scoring functions to predict binding affinity (Kd) for novel ligands.
• Dynamic Analysis: Employ Molecular Dynamics (MD) simulations to predict conformational changes critical for function, allosteric regulation, and stability.
• Prediction for Orphan Proteins: Successfully predict functions for proteins lacking significant sequence homology to known proteins, provided a structure is available.

Applications

Structure-based function prediction is a foundational tool for rational design and discovery across multiple disciplines:

Drug Design and Repurposing

Identifying new allosteric sites and screening compound libraries against a target protein's 3D pocket for lead discovery.

Protein-Protein Interaction (PPI) Analysis

Mapping and characterizing the interface residues involved in key signaling and assembly processes for therapeutic intervention.

Enzyme Engineering

Rational design of mutations to enhance activity, alter substrate specificity, or improve thermal stability based on active site geometry.

Variant Interpretation

Predicting the functional consequence (gain or loss of function) of single nucleotide polymorphisms (SNPs) and other structural variants.

Platform

Our Structure-Based Function Prediction platform combines advanced computational chemistry and bioinformatics tools for accurate functional assignment.

Structure Quality Assessment

Rigorous validation and refinement of input structures (PDB, AlphaFold models) to ensure geometric accuracy for downstream simulations.

Pocket Identification and Classification

Automated algorithms to identify and characterize potential ligand-binding sites, classifying them by druggability score and shape.

Homology and Fold Analysis

Structural comparisons against known functional domains to infer function even when sequence similarity is low (structure-based homology).

Molecular Docking and Virtual Screening

Advanced docking protocols to accurately predict the binding mode and affinity of small molecules or peptides to the target structure.

Conformational Dynamics (MD)

Simulation of protein movement in an aqueous environment to capture critical functional states, such as loop opening/closing and domain motion.

Workflow

Our Structure-Based Function Prediction service follows a methodical, multi-step computational pipeline to deliver reliable functional annotations:

• Structure Acquisition and Preparation: We start with the client-provided 3D structure (or a predicted model). The structure is cleaned, optimized (e.g., protonation states), and validated for quality.
• Ligand and Cofactor Identification: Computational tools identify potential binding sites (pockets) and predict possible physiological ligands or cofactors based on pocket shape and residue composition.
• Functional Domain Annotation: The structure is compared against databases of known functional domains (e.g., CATH, SCOP) and active site templates to assign an initial functional family.
• Mechanistic Modeling: Techniques like molecular docking, simulation, and pharmacophore modeling are employed to predict the specific molecular mechanism (e.g., catalysis, inhibition) and key residues involved.
• Functional Profiling and Reporting: All structural and simulation data are integrated to build a comprehensive functional profile of the protein, which is summarized in a detailed, actionable report with high-resolution visualizations.

CD Biosynsis guarantees a high standard of computational rigor, ensuring that the predicted functional data is directly translatable to your experimental research. Every project includes:

• Quantitative Interaction Data: Predicted binding affinities (e.g., pKd) and detailed residue interaction maps for all identified partners.
• High-Resolution Visualizations: Delivery of structural files and images suitable for scientific publication and presentation.
• Methodological Transparency: A comprehensive description of the computational methods, parameters, and simulation timeframes used for reproducibility.
• Expert Consultation: Access to our structural biology experts for interpreting complex dynamics and integrating results into experimental plans.