AlaScan: A Graphical User Interface for Alanine Scanning Free

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AlaScan: A graphical user interface for alanine scanning free-energy calculations Vijayaraj Ramadoss, Francois Dehez, and Christophe Chipot J. Chem. Inf. Model., Just Accepted Manuscript • DOI: 10.1021/acs.jcim.6b00162 • Publication Date (Web): 23 May 2016 Downloaded from http://pubs.acs.org on May 24, 2016

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Journal of Chemical Information and Modeling

AlaScan: A graphical user interface for alanine scanning free-energy calculations Vijayaraj Ramadoss,† François Dehez,† and Christophe Chipot∗,†,‡ Laboratoire International Associé Centre National de la Recherche Scientifique et University of Illinois at Urbana-Champaign, Unité Mixte de Recherche n◦ 7565, Université de Lorraine, B.P. 70239, 54506 Vandœuvre-lès-Nancy cedex, France, and Department of Physics, University of Illinois at Urbana-Champaign, 1110 West Green Street, Urbana, Illinois 61801 E-mail: [email protected]

Abstract

Computation of the free–energy changes that underlie molecular recognition and association has gained significant importance due to its considerable potential in drug discovery. The massive increase of computational power in recent years substantiates the application of more accurate theoretical methods for the calculation of binding free energies. The impact of such advances is the application of parent approaches, like computational alanine scanning, to investigate in silico the effect of amino–acid replacement in protein–ligand and protein–protein complexes, or probe the thermostability of individual proteins. Because human effort represents a significant cost that precludes the routine use of this form of free–energy calculations, minimizing manual intervention constitutes a stringent prerequisite for any such systematic ∗

To whom correspondence should be addressed Laboratoire International Associé CNRS/UIUC ‡ Department of Physics, University of Illinois at Urbana-Champaign, 1110 West Green Street, Urbana, Illinois 61801 †

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computation. With this objective in mind, we propose a new plug–in, referred to as AlaScan, developed within the popular visualization program VMD to automate the major steps in alanine–scanning calculations, employing free–energy perturbation as implemented in the widely–used molecular dynamics code NAMD. The AlaScan plug–in can be utilized upstream, to prepare input files for selected alanine mutations. It can also be utilized downstream to perform the analysis of different alanine–scanning calculations and to report the free–energy estimates in a user–friendly graphical user interface, allowing favorable mutations to be identified at a glance. The plug–in also assists the end–user in assessing the reliability of the calculation through rapid visual inspection.

Introduction Alanine scanning mutagenesis (ASM) is a method often used to investigate the role of specific amino acids in protein folding and stability, 1,2 as well as in protein–protein 3,4 and protein–ligand 5 interactions. Substituting an amino acid into alanine does not modify the main chain conformation and merely reduces the side chain beyond the β–carbon — this statement should certainly hold for host–guest complexes, but may not be necessarily true for isolated proteins. In experimental ASM, alanine–substituted proteins are separately cloned and expressed. 6 Then, the activity or thermostability of the protein is assessed in in–vitro assays. Experimental use of ASM to perform systematic scanning of large proteins is, however, anticipated to be time consuming owing to the unwieldy protocols implied. It still remains that ASM of isolated proteins and protein–protein interfacial residues has contributed to improve our understanding of protein structure and of their binding properties. 3,7 Recently, ASM has received much attention in the field of membrane protein engineering. 2,8 Structural and biophysical characterization of integral membrane proteins is hampered by their flexibility and instability when they are extracted from their natural environment. 9 Among the different avenues explored to circumvent this difficulty, ASM has proven useful to identify alanine mutations that improve the stability and expression levels of membrane proteins. 1,2,6,9–11 2 ACS Paragon Plus Environment

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One of the striking examples of ASM applications in protein engineering is the identification of thermostabilizing point mutations in G protein–coupled receptors (GPCRs). 1,6,11 In–silico ASM is an appealing alternative to in–vitro experiments. 12,13 It can be performed using a variety of methods ranging from approximate to very accurate levels of theory. 14 Knowledge– based approaches have recently emerged as a fast option to detect hotspots at protein interfaces. 15 Computationally affordable end–point methods include molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA), 16 molecular mechanics/generalized Born surface area (MM/GBSA) 16 and linear interaction energy (LIE). 17 Approaches such as free–energy perturbation (FEP) 18 and thermodynamic integration (TI) 19 offer a more rigorous framework, leading to estimates of relative binding affinity and solvation free energies in principle of greater accuracy. 20 These approaches can be applied to large molecular assemblies, harnessing continuously growing computational resources. However informative, the use of FEP remains tedious in the context of a large number of alanine mutations, requiring substantial human intervention, which often constitutes a limiting factor for the routine application of in–silico ASM. Automation of the various computing steps involved, i.e., preparation of the input structure for each alanine mutation, analysis of each transformation and display of the free–energy differences for quick visual inspection would provide a hassle–free solution towards well–organized computational alanine scanning. Design of an integrated tool would, therefore, significantly facilitate in–silico ASM and make it accessible to a greater audience, notably to non practitioners. Of particular interest, this tool should prove useful to experimentalists eager to assess rapidly the effect of alanine mutations, without necessarily having to overcome the learning curve of free–energy calculations. In the present contribution, we introduce a plug–in developed for the popular visualization program VMD, 21 entitled AlaScan and intended to automate the different steps involved for in–silico alanine scanning calculations within the framework of FEP as implemented in the widely used molecular dynamics program NAMD, 22 in a spirit similar to that of toolkits devised for MM/PBSA calculations. 23 Specifically, the AlaScan plug–in can be utilized to prepare the various input files



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required for FEP calculations. In addition, the plug–in offers a convenient environment for the analysis of the free–energy calculations and assessment of their convergence. For each in–silico ASM experiment, the estimated free–energy differences and associated errors are depicted in a user–friendly fashion. Although it has been developed within the programs VMD and NAMD, the proposed plug–in can be adapted seamlessly to alternate visualization and molecular dynamics packages. The usefulness of AlaScan is illustrated by carrying out a series of alanine mutations in the peptide–protein complex, PMI–MDM2 24 (see S.I.).

Methods Implementation. The integrated tool AlaScan is implemented as an external TCL plug–in for VMD. 21 The graphical user interface of AlaScan can be accessed from the “Extensions/Modeling” menu. The plug–in can be utilized to perform ASM computations on either protein–ligand — or protein–protein complexes, or isolated proteins. The former case pertains to host–guest assemblies, wherein point mutations are performed to estimate the role played by specific side chains in the reversible binding of the partners at play. Conversely, in the latter case, in–silico ASM is employed to identify thermostabilizing mutations. Here, the protein can be viewed as an isolated host. The thermodynamic cycle for the determination of the differential binding affinity in the host–guest complex is depicted in Figure 1a. Strictly speaking, host–guest absolute binding free energies are determined by performing the horizontal transformations highlighted in Figure 1a. The difference MT between the binding free energies for the wild type, ∆GWT binding , and the mutant, ∆Gbinding , yields

the free–energy change arising from the substitution of a native amino acid by an alanine. In practice, the relative binding affinity is estimated by carrying out the alchemical transformations, wherein a single amino acid is mutated in the bound and the unbound, free states. These transformations correspond to the vertical legs of the thermodynamic cycle of Figure 1a. The relative MT 0 1 binding free energy due to the ASM is ∆∆G = ∆GWT binding −∆Gbinding = ∆Gmutation −∆Gmutation .


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Figure 1: (a) Thermodynamic cycle for the estimation of the relative binding free energy in a host–guest model complex. WT and MT denote, respectively, the wild type and the mutant. The vertical alchemical transformations are performed in the unbound, free state (left) and in the bound state (right). (b) Thermodynamic cycle for thermostability analysis upon alanine mutation in an isolated host. WT and MT denote, respectively, the wild type and the mutant. The unfolded state is modeled by means of a capped single amino acid X, i.e., ACE—X—CT3. The thermodynamic cycle for the isolated host alone is depicted in Figure 1b. In the context of thermostability investigations, ASM calculations ought to be performed in principle on folded and unfolded states of the protein. The difference between the free–energy estimates for these alternate states yields the relative change in free energy due to the mutation of one residue into alanine. In practice, the folded state is described by native protein in its natural environment, whereas the unfolded state is modeled using a short peptide. Here, use will be made of a capped standard amino amino acid X, i.e., ACE—X—CT3. Using the CHARMM nomenclature, 25 ACE and CT3 are capping acetyl, –COCH3 , and –NHCH3 groups, respectively. The underlying assumption here is that in the unfolded state, residue X does not interact with other residues of the protein. 26 In previous studies, the reduction of the unfolded state to capped amino acids has produced reasonable results. 26–28 The relative free energy arising from alanine mutation is determined following the horizontal alchemical transformations of the thermodynamic cycle reported in Figure 1b, namely WT 0 1 ∆∆G = ∆GMT folding − ∆Gfolding = ∆Gmutation − ∆Gmutation . The main advantage of reducing the

unfolded state to a mere capped amino acid is that the relevant FEP calculations can be performed once and for all, and their results stored in a lookup table.



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Preparing the input files for FEP calculations.

A schematic workflow for the AlaScan plug–

in is represented in Figure S1 (see S.I.). AlaScan requires as inputs a PSF, a PDB and an XSC file for the protein of interest in order to prepare (i) the hybrid structure with the suitable dual– topology 14 and (ii) the FEP configuration files compliant with NAMD. 22 Figure S2a shows the graphical user interface (GUI) for the “Setup FEP input files” section of the tool. After loading the relevant input files, the AlaScan plug–in opens a secondary window, which displays the list of amino acids present in the different segments of the protein, as indicated in Figure S3. This list can be utilized to select the amino acids for in–silico ASM experiments. By default, the alanine residues are excluded from the clickable selection, and the non–protein segments are not displayed in the list. The secondary structure of each amino acid is highlighted with the same color codes used in VMD by STRIDE. 29 The display of segment name in the list allows amino acids that belong to a specific chain of the protein to be selected without any ambiguity. The secondary GUI, however, does not allow amino acids from multiple protein segments to be selected when the “Host-Guest System” option is chosen. In the case of a protein–ligand complex, the secondary GUI displays only the protein segment to select amino acids towards alanine replacement. By default, the AlaScan plug–in considers the segment wherein alanine mutations occur as the host. Conversely, a protein segment wherein no mutation is performed, or a ligand molecule bound to a protein is always considered as a guest. In other words, the protein is considered as a host when the in–silico ASM is performed on it, while the ligand bound to it is treated as a guest. After selecting the amino acids towards alanine mutation, the main plug–in window expands to reveal different options for loading the force–field–parameter and hybrid–topology 30 files (see Figure S4). The users can upload multiple force–field–parameter files. By default, the GUI displays the hybrid–topology files located in the VMD installation directory. Contrary to standard topology files, dual–topology files contain both the initial and the final state of the point mutation for the entire series of naturally occurring amino acids. 30 Moreover, users can upload their own customized versions of the topology files. Once the necessary parameters are set up, the plug–in performs a series of actions in the following order — (i) a directory is created within the 6 ACS Paragon Plus Environment

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current path by adding the “–FEP” suffix to the PDB file name, (ii) a subdirectory is created for each mutation with a unique syntax, starting with the residue id and the three–letter residue codes, e.g., “27–LEU2ALA”, (iii) in the case of a host–guest complex, two subdirectories, “Host” and “Host–Guest”, are created for each mutation in the host and host–guest systems (see Figure 1a), (iv) the hybrid PDB structure and corresponding topology files of the molecular assemblies are generated for each residue selected towards alanine mutation, and (v) a NAMD configuration file for preliminary equilibration, as well as FEP forward and backward transformations 31 is spawned in designated subdirectories for each residue. A tree view of the different directories and files generated by the “Setup FEP input files” section is provided in Figure S5. In the event of a host–guest setup, the hybrid structure and topology files for the host are prepared by considering the protein segment wherein alanine scanning is performed. The host protein segment is isolated from the rest of the complex, preceding solvation and charge neutralization. In order to launch the thermalization and FEP calculations using NAMD, a simple script can be written to access each directory in an organized fashion.

Analysis of the FEP calculations. The “Analyze FEP output” section of the AlaScan plug–in should prove useful for the automated analysis of the FEP calculations, i.e., to analyze globally multiple alanine mutations carried out on a biological object (see Figure 2). This section requires the native PDB and PSF files of the molecular assembly as an input. The physical location of the directory containing the output of the different in–silico ASM experiments ought to be provided to access sequentially each free–energy calculation. The tree structure for the different mutants should correspond to the overview of directories in Figure S5. For example, the root directory in that schematic view can be chosen as the input for “Path to read FEP outfiles” (see Figure S2b). The AlaScan plug–in invokes another plug–in of VMD, namely ParseFEP, 32 which has been designed for post–hoc analysis of FEP calculations performed with NAMD. 31 Within a user–friendly environment, ParseFEP offers the proper infrastructure to determine for bidirectional transformations the Bennett acceptance ratio 33 (BAR) estimator of the free energy and its associated uncertainty, 31 7 ACS Paragon Plus Environment


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together with free–energy components, i.e., enthaplies and entropies. 32 As a good practice, 31 all FEP calculations of alanine replacement are run bidirectionally and the free–energy change is the maximum–likelihood BAR estimator. 33 After analyzing the forward and backward transformations, a GUI displays the list of amino acids present in the native protein, excluding non-protein segments, alongside the secondary structural information of each residue (see Figure 2). The amino acids involved in the alanine–scanning computations are shown using a single–letter code, e.g., W2A to denote the mutation of tryptophan into alanine. The GUI also displays the estimated free–energy changes in the presence and in the absence of the host environment in thermostability investigations, i.e., with an isolated protein. In the case of host–guest complexes, the free–energy differences in the presence and in the absence of the guest are reported, together with the relative binding free energy calculated from each alanine substitution. The result of the alchemical transformations is also displayed as a color gamut ranging from the most favorable to the most unfavorable point mutations. Combined with the sequence viewer, the end–user can highlight hotspots in the molecular objects. While FEP produces accurate free–energy estimates, it is also burdened by slow convergence. 14 Convergence of the free–energy calculations is reflected in the hysteresis, i.e., the free–energy difference between the forward and backward transformations, provided by the GUI. Colored circles next to the free–energy estimates allow the end–user to assess at a glance whether or not the simulations are likely to be converged. The AlaScan plug–in arbitrarily categorizes the hysteresis into three groups, namely a value (i) less than kB T (green circle), (ii) greater than kB T , but less than 2kB T (orange circle), and (iii) greater than 2kB T (red circle) — see figures 2, S7. These “traffic lights” are intended to draw the attention of the end–user on the free–energy calculations that ought to be improved, for instance through a finer stratification, 31 or altogether rerun.


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(a)

(b)

Figure 2: AlaScan GUI showing the results of a systematic analysis of FEP calculations performed on the PMI–MDM2 host–guest complex (a) and isolated PMI host (b).

Conclusion and perspective In this contribution, we have described the development and features of a new toolkit, coined Ala-Scan, for performing in–silico ASM experiments. Although AlaScan has been designed as a plug–in for the popular visualization program VMD, 21 to run in the background FEP calculations as implemented in the molecular dynamics package NAMD, 22 there is no technical hurdle that would preclude porting the toolkit to any alternate visualization and molecular dynamics platform. At the conceptual level, AlaScan has been developed to be of practical use to a wide audience embracing non–experts in the field of statistical–mechanics simulations. In fact, combined with other tools for the rapid setup of molecular dynamics simulations, like QwikMD, 34 which, within five clicks, allows an MD simulation to be started seamlessly, AlaScan makes computational alanine scanning available to novices, in particular experimentalists eager to obtain in no time in–silico



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predictions for alanine replacements. In a broader context, the AlaScan plug–in can also be used for post–hoc analysis of FEP calculations, generating pictorial representations of the alchemical transformation at hand. A user–friendly GUI enables the display of the amino–acid sequence from the input protein structure and facilitates the selection of residues that will be mutated into alanine. The plug–in will prepare the hybrid structure with the relevant dual topology, as well as the NAMD configuration files required for the thermalization MD simulation and ensuing free–energy calculation. Post–treatment of the different FEP calculations is accompanied by a display of the relative free energies with a color gradient for rapid visual assessment of favorable and unfavorable alanine mutations. The applicability of the AlaScan plug–in to a variety of host–guest complexes for the determination of relative binding affinities upon alanine mutations, and of isolated proteins in the context of thermostability studies, is convincingly illustrated with the test protein–peptide complex PMI–MDM2 (see S.I.). The toolkit proposed herein allows in–silico ASM experiments to be performed at a minimal human cost by automating completely the preparation of the underlying free–energy calculations and reducing manual intervention. The modular design of the code facilitates the introduction of possible extensions, notably the connection with other plug– ins, or the incorporation of geometrical restraints, which might be required in delicate alchemical transformations.

Supporting Information Available Additional methodological details. Application of the plug–in to a series of alanine mutations in the peptide–protein complex, PMI–MDM2 24 (computational details and analysis of the results). This material is available free of charge via the Internet at http://pubs.acs.org/.


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Acknowledgement The authors would like to acknowledge the Grand Nancy and the Fonds Européen de Développement ´ Economique et Régional (FEDER) for the support of this research.

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AlaScan: A graphical user interface for alanine scanning free-energy calculations Vijayaraj Ramadoss, François Dehez, Christophe Chipot


AlaScan: A Graphical User Interface for Alanine Scanning Free

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