"Topological Polar Surface Area" (TPSA)
Molecular polar surface area (PSA) is a descriptor showing the
correlation with passive molecular transport through membranes, which
allows prediction of the human intestinal absorption, Caco-2 monolayers
permeability, and blood-brain barrier penetration.
The calculation of PSA in a classical way requires special software to
generate the 3D structures that makes the prediction process is time
consuming. The "Topological Polar Surface Area" (TPSA)
approach (published by J Med Chem. 2000 Oct 5;43(20):3714-7., Ertl P,
Rohde B, Selzer P.) allowed the high-throughput calculation of the PSA
values and the quick estimation of related transport properties.
The TPSA module of Pallas frame system provides a quick
high-throughput tool for PSA calculation of compound libraries, and the
early identification of drug candidates with inappropriate absorption.
Web-based, network version of the EMIL software
For lead optimization purposes, CompuDrug launched the web-based
version of the EMIL (Example-Mediated Innovation for Lead evolution)
software. EMIL Net can be used from any terminal of your company without
the need of multiple installations. The lead evolution and lead
optimization databases of EMIL can be accessed via an Intranet/Internet
network; all you need is to open a web-browser and login to the central
EMIL server of your company. Every features of the Windows version are
available in the new release, but in a renewed style satisfying the
special needs of the web environment.
EMIL Net belongs to the next generation software family of CompuDrug,
which provides platform-independent, integrated use of drug design
tools.
MetabolExpert, HazardExpert and Rule of 5 are implemented in
Pallas SDK
The Pallas Software Development Kit (SDK) has been extended with the
HazardExpert, the MetabolExpert, and the Rule of 5 modules.
Pallas SDK is developed for use of system administrators and software
developers. It is based on the widely-used prediction engines of Pallas,
which are available in the form of shared libraries (DLL/DSO), and can
be embedded into your in-house database or chemical management system.
Pallas SDK 2.0 contains multithreaded DLLs and a Java Native Interface
for all of the available modules, so you can also access Pallas from the
Java and the C/C++ environment.
Pallas SDK allows a flexible usage of ADME/Tox prediction programs for
advanced computational scientists.
MetabolExpert and RetroMEX - Colored Highlights of Fragment
Reaction
The new features of MetabolExpert help the users to understand the
metabolic pathway of the MetabolExpert knowledge base. The active and
replacing substructures and the positive conditions are highlighted via
color drawing, and the highlighting emphasizes the essence of metabolic
reactions that occurred.
Newly Improved, User-Friendly Pallas:
- Easy Access toolbars for the Pallas modules and frequently-used
functions.
- Simple prediction button and menu for large database predictions.
- Additional modifications in Pallas applications to make them more
comfortable.
- Improved appearance of Pallas background pictures.
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CompuDrug offers a range of
predictive software tools to improve performance in the fields of
pharmaceutical and medicinal chemistry research.
CompuDrug´s Software Solutions are providing you help in:
ADME and evaluation and prediction by
Pallas
- Rule of Five evaluation
- Predicting metabolism pathways
in humans, animals, and plants
- Estimating toxic symptoms of
organic compounds in humans and animals
In silico calculation of
physico-chemical properties by Pallas
- LogP, pKa, logD calculation
Finding hits by structural
modeling, QSAR and other rational drug design approaches
- Prodrug design by RetroMex of
Pallas
- Emil serendipity enhancer and
knowledge base management
Lead Optimization
- Emil serendipity enhancer and
knowledge base management
- Lost the in vitro activity in
vivo? MexAlert of Pallas identifies first pass effect.
High Througput Screening
- Identifying potential false
positive compounds at cell based high, medium and low throughput
screening assays by ToxAlert of Pallas
For the analytical lab
- Method development and
optimization for HPLC techniques by Eluex
For agrochemical research:
- Light stability prediction of
agrochemical candidates by the Agro version of Pallas
Metabolexpert.
For detailed information
about each product, please go to
www.compudrug.com.
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New Artificial Intelligence - powered accurate
logP prediction: PrologP 7.0.
ANNlogP is the new prediction method used in our PrologP 7.0 software.
It is based on the atomic fragment collection of Ghose and Crippen.
Instead of the more common linear approaches, the new ANNlogP method
uses a neural network model. Since the neural network is able to
recognize the hidden and non-linear relationships between the chemical
structure and the logP value, the new software provides much more
accurate predicted values, and makes our PrologP 7.0 software one of the
most accurate logP predictors on the market today.
The program still uses the original fragmental methods, but combines
them with the new neural network algorithm, giving an optimal prediction
result. The balancing between the different calculation methods was
fine-tuned based on a large set of experimental logP values
(approx. 13,000 compounds). EMIL 2.3 - Expanded
knowledge
The Example Mediated Innovation for Lead evolution (EMIL) software takes
your screening hit and suggests chemical modifications to turn it into a
bona fide lead. EMIL searches through its extensive Knowledge Base
looking for similar chemistry and how it was optimized for potency and
bioavailability.
The software’s Knowledge Base has been expanded remarkably. The inserted
collection of data includes the results of drug discovery research of
the recent years, and provides large numbers of suggested structures for
the lead optimization or lead evolution process. EMIL 2.3 allows you to
extend your virtual libraries with the suggested structures.
Rule of 5 - new HTS module in Pallas for Windows
Since the majority of drug candidates fail because of bioavailability
problems, the early identification of poor absorption can save a huge
amount of time and money. The most common screening method is based on
Rule of 5.
This new Pallas module calculates the molecular weight, the logP
value, and the number of the H-bond acceptor and H-bond donor groups,
which characterize the drug-likeness of organic compounds. The
Pallas-Rule of 5 module is developed to choose which compounds are
acceptable for high-throughput screening: it is able to take an SDFile
of any size as input, and presents the result in a simple tabular form
that can easily be transferred to Excel. Speed up
your calculation with Pallas Cluster
Our latest product is a uniquely distributed system that is able to
predict the physico-chemical parameters of huge compound databases used
in high-throughput screening and combinatorial chemistry very quickly.
The Pallas Cluster allows the usage of free resources of office
computers for the physico-chemical property prediction of large chemical
databases. The Pallas Cluster predicts the logP, logD and
pKa values with the well known and widely-used Pallas
prediction engines, which is embedded into a web-service based
distributed system, and the power of clustered computers improves the
speed of the prediction even by orders of magnitudes.
Pallas for UNIX/Linux has been upgraded
The Unix/Linux version of Pallas prediction modules has been upgraded
and extended with the MetabolExpert, HazardExpert and Rule of 5 modules.
In the Unix/Linux environment the Pallas prediction modules are
available as command-line software. It allows to make batch prediction
for huge compound libraries, and avoids the need of the time-consuming
import/export procedures. The new release accepts SMILES structure
format as input, and able to export the results in SDFile format, so the
predicted values can be stored together with the corresponding compound
structures. This latter new feature made possible the implementation of
MetabolExpert, where the predicted metabolite structures are stored in
SDFile sets. An additional new function is the smiles input format. |
