Welcome to CD ComputaBio, your premier destination for cutting-edge computational modeling services in Enzyme De Novo Design. At CD ComputaBio, we specialize in leveraging advanced algorithms and techniques to design novel enzymes tailored to meet specific client needs. Our team of experienced scientists and analysts are dedicated to delivering high-quality, customized solutions to advance research and innovation in the field of enzyme design.
Enzymes play a crucial role in various biological processes and industrial applications. Enzyme engineering, particularly De Novo Enzyme Design, offers the opportunity to create enzymes with enhanced properties, such as improved catalytic activity, stability, and substrate specificity. At CD ComputaBio, we harness the power of computational modeling to facilitate the rational design of enzymes with desired functionalities, providing our clients with tailored solutions to their enzyme engineering challenges.
Figure 1. Enzyme De Novo Design. (Zanghellini A.2014)
Our Enzyme De Novo Design process is powered by a sophisticated algorithm that integrates multiple computational techniques:
| Services | Description |
| Enzyme De Novo Design | Our core service involves the design of novel enzymes from scratch using advanced computational tools and algorithms. |
| Enzyme Engineering | We offer customized enzyme engineering solutions to optimize enzyme properties for specific applications. |
| Virtual Screening | Using molecular docking and simulation techniques, we identify potential enzyme candidates for further evaluation. |
| Structural Analysis | Our experts conduct in-depth structural analysis of enzymes to understand their functions and improve their performance. |
Enzyme De Novo Design has a wide range of applications across various industries, including:
Using homology modeling, ab initio modeling, and molecular dynamics simulations to predict the 3D structure of the target enzyme.
Detecting the active site and key residues using site-directed mutagenesis and computational docking studies.
Generating and screening variants through computational methods to identify beneficial mutations.
Enzyme Design Tools
| Category | Name | Description | Features and limitations |
| ASR | Bali-phy | A standalone tool for the estimation of multiple sequence alignments and evolutionary trees | Features: Excellent performance on tested protein data sets |
| Limitations: Tends to systematically under-align on the biological sequence data | |||
| IQ-TREE | Standalone software and web tool for the inference of phylogenetic trees using the maximum-likelihood approach | Features: It is an integral component of many biomedical research open-source applications such as Galaxy, Nextstrain, and QIIME 2 | |
| Limitations: Both IQ-Tree- and RaxML-NG-inferred maximum-likelihood gene trees have been suggested to have reproducibility issues | |||
| Molecular Evolutionary Genetics Analysis (MEGA X) | User-friendly software for molecular evolution analysis and construction of phylogenetic trees | Features: Easy-to-use graphical user interface (GUI) with good documentation available; works across all platforms | |
| Limitations: Works like a black box for some parameters, with no user control | |||
| MrBayes | A program for Bayesian inference and model choice across a wide range of phylogenetic and evolutionary models | Features: GPU acceleration available | |
| Limitations: Requires quite complex input data, which can hinder non-experts from performing ASR successfully | |||
| Phylogenetic Analysis by Maximum Likelihood (PAML) | Standalone software and web tool to perform phylogenetic analysis using the maximum likelihood approach | Features: Has a GUI version; very customizable | |
| Limitations: Steep learning curve for novice users | |||
| Randomized Axelerated Maximum Likelihood (RAxML) | A standalone tool for ASR using the maximum-likelihood approach; a GUI is being developed | Features: Has a GUI (under development but already available for use) | |
| Limitations: Both IQ-Tree- and RaxML-NG-inferred maximum-likelihood gene trees have been suggested to have reproducibility issues | |||
| The FastML Server (FastML) | A web tool for ASR using the maximum-likelihood approach | Features: Easy-to-use web tool; can take unaligned sequences as input | |
| Limitations: Accepts only the FASTA file format as input | |||
| Allostery | DFI | A protocol developed to identify per-residue contributions to a protein's overall dynamical profile | Features: Code easily available and ready to use |
| Limitations: Requires atomic coordinates | |||
| Ohm | Web tool that predicts allosteric sites and inter-residue correlation and identifies the allosteric pathways between them | Features: Easy-to-use web tool requiring only the insertion of a 3D structure | |
| Limitations: Structure-based predictions do not take dynamics into account | |||
| SPM | Tool developed for the identification of distal mutations affecting function, based on the shortest-path-map algorithm | Features: Uses long dynamic simulations to predict allosteric sites | |
| Limitations: Poor availability of the code | |||
| Databases (assorted) | BRENDA | Electronic repository containing molecular and biochemical information on enzymes | Features: Several different queries are available as examples; integrates CATH and SCOPe |
| Limitations: Requires login and there is a 'professional' version | |||
| PDB | A protein databank containing more than 179 000 macromolecular structures | Features: General database for protein structures obtained through NMR, X-ray crystallography, and cryoelectron microscopy | |
| Limitations: Contains redundant data and the search function could be better | |||
| UniProt | A central repository of protein data created by combining the Swiss-Prot, TrEMBL, and PIR-PSD databases | Features: De facto go-to database for general protein information | |
| Limitations: Overwhelming amount of data for newcomers | |||
| Databases (family information) | CATH Protein Structure Classification database | A database containing information about the evolutionary relationships of protein domains | Features: Huge open-source database helps with automated implementation in one's own workflows |
| Limitations: Drug compound information is still being developed | |||
| Fuzzle | A database containing evolutionary information about protein fragments | Features: Evolutionary information on fragments as opposed to full proteins only | |
| Limitations: Hierarchical databases can lead to misclassification when slight differences are present in the sequences | |||
| Pfam | A database with information about protein families, represented by multiple sequence alignments generated using Hidden Markov models | Features: Constant development and integration with other European Bioinformatics Institute (EBI) tools | |
| Limitations: There is a high-quality database and a low-quality database that can lead to errors | |||
| SCOP | A database of proteins classified based on structural relatedness, such as superfamilies, families, and folds | Features: Uses data deposited in the PDB to group proteins; curated to be non-redundant | |
| Limitations: New version is not totally backwards compatible | |||
| Modeling | AlphaFold | Protein prediction tool using neural networks; achieved a score twice as good as the second-best protein predictor in CASP14 | Features: New gold standard for protein structure prediction; makes use of a newly developed neural network |
| Limitations: It is better where others were good, but still lacks good loop region predictions. | |||
| iTasser | Both a web tool and a standalone tool, it predicts protein structure using a hierarchical approach; runs iteratively until the lowest-energy structures are achieved and then uses publicly available function information to identify closely related templates with the same function | Features: Good and easy-to-use web tool and a powerful standalone tool | |
| Limitations: Lacks accuracy when few templates are available and is slower than similar options available | |||
| Modeller | Protein structure modeling tool that predicts structures by the satisfaction of spatial restraints obtained from a sequence alignment and shown as a probability-density function | Features: Can be installed on any platform and is very fast in creating a new model | |
| Limitations: Speed comes at the cost of accuracy for models where slower tools yield better results | |||
| Multiple sequence alignment (MSA) | Clustal Omega | Multiple sequence alignment web tool | Features: Has been constantly developed since the 1980s for MSA |
| Limitations: Does not yield good results when a large amount of sequences is provided as input | |||
| Multiple Alignment Using Fast Fourier Transform (MAFFT) | Multiple sequence alignment web tool; can also be used locally as a standalone tool | Features: Users can choose between various multiple alignment methods | |
| Limitations: It requires more memory to run | |||
| Multiple Sequence Comparison by Log-Expectation (MUSCLE) | Multiple sequence alignment web tool; as with Clustal Omega, it is integrated in the EBI ecosystem | Features: Can achieve better average accuracy and speed than ClustalW2 or T-Coffee | |
| Limitations: The Kimura distance used at the second stage, although fast, does not consider which changes of amino acids occur between sequences | |||
| Protein design | AbDesign | An algorithm for backbone design using structure- and sequence-based information | Features: Stepwise workflow for the design of antibodies that focuses on stability and binding affinity |
| Limitations: Requires sufficient sequence data on homologs as well as atomic coordinates | |||
| FuncLib | Web tool to design and rank multiple point mutations based on evolutionary information and protein-folding stability calculations | Features: Multipoint variant design tool with an easy-to-use web server | |
| Limitations: Works better with a pre-stabilized protein scaffold; poor knowledge of one's system may lead to poor results | |||
| Loop Grafter | A web tool with a workflow to compare loop dynamics between proteins and transplant loops from one protein to another | Features: Automated way to transfer loops from one protein to the other | |
| Limitations: Works only with the input of both the template and the scaffold proteins | |||
| PROSS | A user-friendly web tool to predict protein amino acid substitutions that yield higher-stability variants | Features: Automated way to stabilize proteins by inserting mutations in the original protein; the method is reliable enough that only a more limited number of designs as output is sufficient | |
| Limitations: Requires a structure (which may not always be available) for stability calculations | |||
| ProtLego | A Python library for chimera design and analysis | Features: Automatic construction and ranking of chimeras | |
| Limitations: The correlation between structural features and experimental success is not yet clear | |||
| Rosetta | A comprehensive software suite with several algorithms that can be used for the modeling and analysis of proteins | Features: Encompasses many modules under the same umbrella name | |
| Limitations: Not unified and developed by many people through the years; can be hard to implement and use different modules | |||
| SEWING | A protocol to design new tertiary protein structures by 'sewing' together secondary-structure building blocks | Features: Continuous and discontinuous SEWING can be merged to create additional diversity | |
| Limitations: At present, it appears to have been applied only to the construction of all-α-helix chimeras | |||
| Tunnels and cavities | CAVER | Software tool for the analysis and visualization of tunnels and channels in protein structure | Features: Integration with other CaverSuite tools allows deeper analysis |
| Limitations: Still lacks the possibility of calculating pores | |||
| POVME | Standalone tool for ligand-binding pocket calculations | Features: Calculates ligand-binding pockets using MD snapshots | |
| Limitations: The lack of a GUI makes it less accessible to non-bioinformaticians | |||
| Similarity search | BLAST | A tool to calculate statistical significance between biological sequences | Features: One of the most-used tools for local alignment search; fast and easy to use |
| Limitations: Developed in 1990 and has not changed substantially since then | |||
| FASTA | A web tool to provide a heuristic local search with a protein query | Features: First tool in the field; as with any other tool from the EBI, it is integrated with many other tools and analyses; newer tools exist that have evolved from this | |
| Limitations: As opposed to BLAST, it does not remove low-complexity regions | |||
| Structure and trajectory data | Bio3D | R package for the analysis of protein structure and trajectory data; provides a variety of approaches for conformational analysis of a protein | Features: Comprehensive tool with many tutorials and easy installation |
| Limitations: Lack of GUI and a webserver makes for a steep learning curve for non-bioinformaticians |
To initiate an Enzyme De Novo Design project with us, we typically require the following samples and information:
Upon completion of the Enzyme De Novo Design process, we provide our clients with:
Our team consists of experienced scientists and analysts with expertise in computational modeling and enzyme design.
Our algorithm-driven approach accelerates the enzyme design process, delivering results in a timely manner.
We uphold high standards of quality and accuracy in our computational predictions and analyses.
Enzyme De Novo Design holds immense potential for revolutionizing enzyme engineering and biocatalysis, opening new avenues for innovation and sustainability. At CD ComputaBio, we are committed to providing top-notch computational modeling services to support our clients' enzyme design endeavors. With our expertise, cutting-edge technology, and dedication to excellence, we are your trusted partner in shaping the future of enzyme engineering.
How does enzyme de novo design work?
The process of enzyme de novo design generally follows several key steps:
What computational methods are commonly used in enzyme de novo design?
Various computational methods are employed in enzyme de novo design, each serving distinct purposes:
What are the applications of enzyme de novo design?
Enzyme de novo design has a broad range of applications, including:
How is enzyme de novo design changing the field of biotechnology?
Enzyme de novo design is revolutionizing biotechnology by allowing for:
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