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  <front>
    <journal-meta>
      <journal-title-group>
        <journal-title>IWSG</journal-title>
      </journal-title-group>
    </journal-meta>
    <article-meta>
      <title-group>
        <article-title>A Pipeline Pilot based SOAP implementation of FlexScreen for High-Throughput Virtual Screening</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Horacio Pérez-Sánchez</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Ivan Kondov</string-name>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>José M. García</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Konstantin Klenin</string-name>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Wolfgang W</string-name>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Computer Engineering and Technology Department, University of Murcia.</institution>
          <addr-line>Murcia</addr-line>
          ,
          <country country="ES">Spain</country>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Institute of Nanotechnology, Karlsruhe Institute of Technology.</institution>
          <addr-line>Karlsruhe</addr-line>
          ,
          <country country="DE">Germany</country>
        </aff>
        <aff id="aff2">
          <label>2</label>
          <institution>Steinbuch Centre for Computing, Karlsruhe Institute of Technology.</institution>
          <addr-line>Karlsruhe</addr-line>
          ,
          <country country="DE">Germany</country>
        </aff>
      </contrib-group>
      <pub-date>
        <year>2011</year>
      </pub-date>
      <volume>8</volume>
      <fpage>8</fpage>
      <lpage>10</lpage>
      <abstract>
        <p>Methods for in-silico screening of large databases of molecules increasingly complement and replace experimental techniques to discover novel compounds to combat diseases. As these techniques become more complex and computationally costly we are faced with an increasing problem to provide a community of life-science researchers with a convenient way to run complex high-throughput virtual screening (HTVS) calculations on distributed computing resources. To this end, we recently integrated the biophysics based drug screening methodology FlexScreen into a service applicable for large-scale parallel screening and reusable in the context of scientific workflows. Our implementation, based on Pipeline Pilot and SOAP provides an easy-to-use graphical user interface to construct complex workflows which are executed on distributed computing resources, thus accelerating the throughput by several orders of magnitude.</p>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>INTRODUCTION</title>
      <p>
        The discovery of new drugs can be drastically accelerated with the
use of high-throughput virtual screening (HTVS) methods
        <xref ref-type="bibr" rid="ref10 ref11 ref16 ref4 ref4 ref6 ref6 ref8 ref9">(Friesner, et al., 2004; Halgren, et al., 2004; Meng, et al., 1992;
Merlitz, et al., 2003; Merlitz and Wenzel, 2002; Merlitz and
Wenzel, 2004)</xref>
        ongoing trend in medical research taking
advantage of recent advances introduced in the field. In order to identify
promising candidates for new drugs, chemical compound databases
with millions of ligands
        <xref ref-type="bibr" rid="ref7">(Irwin and Shoichet, 2005)</xref>
        need to be
screened using HTVS against structurally resolved receptors and
hence the access to computational resources becomes a serious
issue. Many research organizations have access to high
performance computing (HPC) resources distributed in computing grids
and clusters, which can tremendously help to overcome these
constraints
        <xref ref-type="bibr" rid="ref14">(Perez-Sanchez and Wenzel, 2011)</xref>
        .
      </p>
      <p>HPC resources consist in a wide range of hardware and software
resources for the research group members. They are usually
accessed through well-defined gateways, which are based on web
services or remote-access user interface machines (UIs). However,
both solutions still require in-depth knowledge in grid technologies
from the non-expert end users. The major drawback of this direct
*To whom correspondence should be addressed.
approach of doing scientific research is related to its complexity
and difficulty of use making the learning curve too steep. Many
efforts have then to be made to hide the complexity embedded in
“the Grid” and to provide high-level services that allow scientists
to take more effectively further advantage of the distributed
resources.</p>
      <p>
        Science gateways are the primary solutions dedicated to bridge
such knowledge gaps. A Science gateway is defined as “a
community developed set of tools, applications, and data that is integrated
via a portal or a suite of applications, usually in a graphical user
interface, that is further customized to meet the needs of a targeted
community”
        <xref ref-type="bibr" rid="ref1 ref2">(Catlett, 2002; Catlett, 2005)</xref>
        . With science gateways
non-grid-aware users can use grid infrastructure to run shared,
well-tested applications customized for their own research field.
      </p>
      <p>Generally these solutions contain a set of research-specific
applications developed by (and for) the community, and provide services
integrated in a unified user interface, usually a web portal or a
stand-alone graphical user interface. In the context of HTVS this
problem is paramount because the target user community consists
of pharmacists and biologists not trained or experienced in the use
of HPC/grid infrastructures.</p>
      <p>
        Very often, science gateways provide special higher-level
services for construction and execution of scientific workflows, i.e.,
means to automate processing of multiple steps in parallel or in a
sequence, including branching and loops. Thus, workflows are
abstract logical maps of the complex simulation protocols.
Scientific workflows require each step (often a different scientific
application) to provide common interfaces for execution and data
exchange. Currently, several systems for workflow management are
employed in different projects. For example, the UNICORE
workflow engine has been used in the area of QSAR/QSPR
        <xref ref-type="bibr" rid="ref15">(Sild et
al. 2005)</xref>
        , Gridbus for brain imaging
        <xref ref-type="bibr" rid="ref13">(Pandey et al. 2009)</xref>
        . Other
very widely used workflow systems are Kepler (kepler-project.org)
and Taverna (taverna.org.uk). For a review on scientific workflows
we refer to
        <xref ref-type="bibr" rid="ref19">(Yu et al. 2005)</xref>
        .
      </p>
      <p>In order to make HTVS methods accessible for the relevant
community, we must (a) integrate the screening method into an
easy-to-use graphical interface (b) the interface must be reusable in
different scientific workflows in combination with other
applications and (c) provide a seamless access to large-scale
computational resources to enable large screening campaigns. In this work we
present a solution for the HTVS application FlexScreen which
Copyright @ 2011 for the individual papers by the papers’ authors. Copying permitted only for private and academic purposes. This volume is published and copyrighted by its editors.
takes into account these three aspects. In Section 2 we introduce
the program FlexScreen as well as the methods we employed to
integrate FlexScreen into workflows for HTVS. In Section 3, we
will particularly describe how we adopted Pipeline Pilot and the
SOAP standard to implement our concept and present a case study
with use of the developed machinery. In Section 4 we will
conclude and give an outline of future work.
2
2.1</p>
    </sec>
    <sec id="sec-2">
      <title>METHODS</title>
      <sec id="sec-2-1">
        <title>FlexScreen</title>
        <p>
          HTVS calculations have been performed with the all-atom receptor−ligand
docking program FlexScreen
          <xref ref-type="bibr" rid="ref10 ref16 ref5 ref9">(Guerrero, et al., 2011; Merlitz, et al., 2003;
Merlitz and Wenzel, 2002)</xref>
          , which employs a force-field based scoring
function (similar to Autodock
          <xref ref-type="bibr" rid="ref12">(Morris, et al., 1996)</xref>
          ) and a Monte-Carlo
based search algorithm based on the stochastic tunneling method
          <xref ref-type="bibr" rid="ref17">(Wenzel
and Hamacher, 1999)</xref>
          , which has the advantage that it suffers only a
comparatively small loss of efficiency when an increasing number of receptor
degrees of freedom is considered.
        </p>
        <p>
          A physical model is implemented which takes implicitly into account the
influence of the solvent in the interaction between ligands and proteins. The
free energy of the system includes vacuum contribution that has been
previously available in FlexScreen as well as additional solvation terms for
the individual species and for the complex as a linear sum of atomic
parameters
          <xref ref-type="bibr" rid="ref3">(Eisenberg, et al., 1984)</xref>
          . This latter model has the advantage that it
is faster than other methods presently used and still has proven to be
reasonably accurate. The solvent accessible surface area of the molecules must
be determined, which is a computationally intensive task, and in this work
an exact and an approximated, but less time consuming approach are
presented. The other main contribution of this approach is the
determination of the weight parameters for very different atom and bond types, being
them derived from experimental partition coefficients data in the cases
octanol−water and gas−water.
2.2
        </p>
      </sec>
      <sec id="sec-2-2">
        <title>Pipeline Pilot</title>
        <p>
          Pipeline Pilot (http://www.scitegic.com) provides services and a workflow
engine basing on Service Oriented Architecture (SOA)
          <xref ref-type="bibr" rid="ref18">(Yang, et al., 2010)</xref>
          allowing very effective workflow life-cycle management, i.e. it ensures
maximum reuse of already integrated modules. In addition, it supports
SOAP with Web Services Description Language (WSDL) extensions for
efficient decoupling of workflow management from services’ internal
implementation. In this way, in addition to its built-in functionality, the
architecture of Pipeline Pilot has been organized for integration and
extensibility and designed to interoperate with external software objects and
applications. A number of mechanisms are available to automate the
execution of a remote program. Additional options are available if the screening
code resides on the workflow server. In general, two mechanisms are used
for remote execution. Simple integrations use Telnet and File Transfer
Protocol (FTP). More complex integrations use Simple Object Access
Protocol (SOAP)
          <xref ref-type="bibr" rid="ref16">(Snell, et al., 2002)</xref>
          and web services. SOAP provides a
way for applications to communicate with each other over the HPC
resources. The SOAP framework is independent of any particular
programming model, environment, or language. It is a structured method for sharing
messages between server and client, and relies on XML to define the
format of the information and then adds the necessary HTTP headers to the
information. Most applications do not deal directly with the underlying
SOAP data structures. Instead, they use a toolkit specific to their
programming language and operating system. The toolkit simplifies the process of
making SOAP calls and processing the returned results.
        </p>
        <p>Pipeline Pilot provides several integration methods so that several
applications existing either in the workflow server, remote server or cluster can
be executed automatically in a workflow. Pipeline Pilot provides also data
integration tools that assist in the assembly of information from different
formats and pertaining to different databases. A convenient and intuitive
graphical user interface via a web browser is provided for constructing and
executing the workflows. The workflows are assembled using modules that
are represented as icons in the graphical user interface. The workflows are
actually stored in an XML format and can be easily exchanged between
users. The modules, called components, include a variety of data readers,
manipulators, calculators, data viewers, and data writers. For example,
there are convenient data reading modules for ISIS files, SD-files, and
SMILES, as well as delimited text and Excel spreadsheet files. Data
viewers and writers include standard applications, such as WebLabViewerPro
and Spotfire. An HTML molecular table viewer provides a convenient way
to view tabular results with chemical structures. Although the applicability
of the pipelining provided by this software is generic, the numerous (&gt;200)
specific components provided by SciTegic are heavily geared toward
chemoinformatics environments. For academic users there is a free version
of Pipeline Pilot available.
2.3</p>
      </sec>
      <sec id="sec-2-3">
        <title>Workflows and Data Pipelining</title>
        <p>A workflow in Pipeline Pilot refers to the way a protocol is defined, usually
in form of several disconnected pipelines, each of which is made of
components joined by pipes. A component refers to an individual operation to
be performed on a set of data records. The order of execution depends on
the order the components are joined since the protocols are executed from
left to right, top to bottom.</p>
        <p>In the specific form of a workflow called data pipelining, records are
passed individually down the pipes. Data pipelining allows the automation
of the HTVS process and the integration of several related modeling and
database packages. Thus, in addition to orchestration of multiple workflow
steps the data pipelining provides means for seamless data exchange
between the individual application modules. The end users’ work in HTVS
projects can be enormously facilitated by the exploitation of already
prepared sets of commonly used collections of tasks in the form of workflows.
These protocols can be later deployed on HPC resources in a simple and
automated fashion. An advantage of the pipelining approach is the ability to
capture and conveniently share workflows for better reuse.
3
3.1</p>
      </sec>
    </sec>
    <sec id="sec-3">
      <title>IMPLEMENTATION AND USE CASES</title>
      <sec id="sec-3-1">
        <title>Pipeline Pilot Modules for FlexScreen</title>
        <p>FlexScreen was initially designed as a standalone command line
application. In the first part of the work reported here we have
implemented a set of Pipeline Pilot modules that are required to
run FlexScreen within Pipeline Pilot. The required executables and
template configuration files are placed in the Pipeline Pilot server.
The FlexScreen integration in Pipeline Pilot is depicted in Fig. 1.
In pipelines 1 and 2 end users need to specify receptor and ligand
database files in the molecular standard PDB format. If the user
works with other molecular formats (smi, sdf, etc.), the protocol
can be easily modified using molecular format converters included
in the standard components collection of Pipeline Pilot. Afterwards
the initial receptor and ligand files can be parameterized depending
on the charge model used, hydrogen model, etc. and additional
components (pH, tautomers, etc.) can also be easily included in the
pipeline. Once the molecules are ready for the HTVS calculations,
the docking parameters (degree of flexibility, simulation length,
physical model, etc.) and parallel calculation parameters (batch
size, number of processors to use, etc.) are specified at the
beginning of the third pipeline. In any case the protocol provides default
parameters for all the components so that the user only needs to
select ligand, receptor and binding site parameters.</p>
        <p>One of the challenges in a virtual screening experiment is to
analyze and organize the returned results. Again, an expert modeler
will be familiar with tools available within a modeling
environment to examine and filter the results. For an end user, the analysis
and presentation must be automated so that they can correctly
generate the information that they need for further decision
making. Using a single PC as a server, a single user is thus able to
design and run application workflows that link all available
Pipeline Pilot modules with FlexScreen for HTVS.
3.2</p>
      </sec>
      <sec id="sec-3-2">
        <title>SOAP Implementation of FlexScreen</title>
        <p>
          The integration in Pipeline Pilot alone is, however, insufficient for
really large in-silico screening campaigns. The improved accuracy
of FlexScreen comes at the price of the computation cost of the
underlying biophysical model. Therefore, we have implemented
the FlexScreen Pipeline Pilot modules as a SOAP-based
          <xref ref-type="bibr" rid="ref16">(Snell, et
al., 2002)</xref>
          service capable to run on large distributed architectures,
such as computing grids and clouds. We have developed
SOAPbased web services for the remote FlexScreen application using
software such as Apache / Tomcat (http://tomcat.apache.org) or the
Perl SOAP::Lite module (http://soaplite.com). The SOAP wrapper
contains sufficient processing functionality to perform the
following tasks:
1.
        </p>
        <sec id="sec-3-2-1">
          <title>Receive a batch of ligands and receptor file as a SOAP</title>
          <p>message and save them to a file. One of the advantages
of using SOAP is that it allows a batch size to be
specified, allowing the collation a series of individual
docking requests in a single request for efficiency.</p>
          <p>Receive complementary information as SOAP messages
and save it to files, e.g., protein active site, configuration
files related to simulation parameters, etc.</p>
          <p>Execute FlexScreen on the server and HPC resources
using the files previously created.</p>
        </sec>
        <sec id="sec-3-2-2">
          <title>Read the resulting files and pass them back as a SOAP message to the calling component. A report on the results will be automatically prepared as an interactive HTML report, a PDF document, or a spreadsheet.</title>
          <p>3.3</p>
        </sec>
      </sec>
      <sec id="sec-3-3">
        <title>Examples of Use</title>
        <p>Results from a HTVS calculation performed by an end user are
shown in Figs. 2 and 3. As seen in Fig. 2 the resulting data is
clearly organized in tables which are directly opened in the web
browser after the screening calculations. The user can control the degree
of detail in the final report interacting with the “table parameters”
component as well as reorganize easily and sort the final data with
a few mouse clicks in the web browser. There is also the
possibility of exporting the results to other standard formats, i.e., PDF,
Word, Excel spreadsheets, CSV text files, etc.</p>
        <p>From the perspective of users’ experience, we found that the
access to well-developed and validated workflows using
FlexScreen encourages the user to test and explore new ideas.
Informal discussions with users who have performed HTVS
calculations with FlexScreen in this way confirms that the deployment
of HTVS methods does not just get the same answers faster, but
that scientists end up asking many more “what-if” questions and
running many more experiments than they would have done when
a modeler had to be involved in each case.
4</p>
      </sec>
    </sec>
    <sec id="sec-4">
      <title>CONCLUSIONS AND FUTURE WORK</title>
      <p>In this paper, we have described the implementation of a HTVS
methodology in a science gateway environment making use of the
workflow environment provided by Pipeline Pilot. The solution
basing on SOAP and web services enables the exploitation of
distributed HPC resources (grid computing). The only drawback of
Pipeline Pilot is its commercial license for non-academic users.
Now we are exploring several open source alternatives.</p>
    </sec>
    <sec id="sec-5">
      <title>ACKNOWLEDGEMENTS</title>
      <p>This research was supported by a Marie Curie Intra European
Fellowship within the 7th European Community Framework
Programme (FP7 IEF INSILICODRUGDISCOVER), the
FundaciónSéneca (Agencia Regional de Ciencia y Tecnología, Región de
Murcia) under grants 00001/CS/2007 and 15290/PI/2010 and a
postdoctoral contract from the University of Murcia (30th
December 2010 resolution). I. K. acknowledges gratefully continuous
support and funding by Programme “Supercomputing” of the
Helmholtz Association.</p>
    </sec>
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