PL-PatchSurfer2: Improved Local Surface Matching-Based Virtual Screening Method That Is Tolerant to Target and Ligand Structure Variation

Shin, Woong‐Hee; Christoffer, Charles; Wang, Jibo; Kihara, Daisuke

doi:10.1021/acs.jcim.6b00163

Cited by 27 publications

(30 citation statements)

References 61 publications

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“…This gave rise to a new virtual screening methodology based on shape complementarity between binding pockets and ligands. PL-Patch-Surfer2 program evaluates the compatibility between ligand and binding pocket by measuring the complementarity between ligand surface and local surface patches in the binding pocket (Shin et al, 2016a , b ; Figure 4C ). The program utilizes 3DZD to represent molecular shape while physicochemical properties are also mapped onto the surface.…”

Section: Application Of Shape Similarity Methods In Drug Discoverymentioning

confidence: 99%

Advances in the Development of Shape Similarity Methods and Their Application in Drug Discovery

2018

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Molecular similarity is a key concept in drug discovery. It is based on the assumption that structurally similar molecules frequently have similar properties. Assessment of similarity between small molecules has been highly effective in the discovery and development of various drugs. Especially, two-dimensional (2D) similarity approaches have been quite popular due to their simplicity, accuracy and efficiency. Recently, the focus has been shifted toward the development of methods involving the representation and comparison of three-dimensional (3D) conformation of small molecules. Among the 3D similarity methods, evaluation of shape similarity is now gaining attention for its application not only in virtual screening but also in molecular target prediction, drug repurposing and scaffold hopping. A wide range of methods have been developed to describe molecular shape and to determine the shape similarity between small molecules. The most widely used methods include atom distance-based methods, surface-based approaches such as spherical harmonics and 3D Zernike descriptors, atom-centered Gaussian overlay based representations. Several of these methods demonstrated excellent virtual screening performance not only retrospectively but also prospectively. In addition to methods assessing the similarity between small molecules, shape similarity approaches have been developed to compare shapes of protein structures and binding pockets. Additionally, shape comparisons between atomic models and 3D density maps allowed the fitting of atomic models into cryo-electron microscopy maps. This review aims to summarize the methodological advances in shape similarity assessment highlighting advantages, disadvantages and their application in drug discovery.

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Section: Application Of Shape Similarity Methods In Drug Discoverymentioning

confidence: 99%

Advances in the Development of Shape Similarity Methods and Their Application in Drug Discovery

2018

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“…The human Sirtuin 1 crystal structure (PDBID: 4KXQ) was used as a receptor. From the prescreened compound library, PL-PatchSurfer2 18 was used to select the top 2,000 molecules. These molecule were docked to Sirtuin 1 by AutoDock Vina 19 .…”

Section: Methodsmentioning

confidence: 99%

A prospective compound screening contest identified broader inhibitors for Sirtuin 1

Chiba

Ohue

Gryniukova

et al. 2019

Sci Rep

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Potential inhibitors of a target biomolecule, NAD-dependent deacetylase Sirtuin 1, were identified by a contest-based approach, in which participants were asked to propose a prioritized list of 400 compounds from a designated compound library containing 2.5 million compounds using in silico methods and scoring. Our aim was to identify target enzyme inhibitors and to benchmark computer-aided drug discovery methods under the same experimental conditions. Collecting compound lists derived from various methods is advantageous for aggregating compounds with structurally diversified properties compared with the use of a single method. The inhibitory action on Sirtuin 1 of approximately half of the proposed compounds was experimentally accessed. Ultimately, seven structurally diverse compounds were identified.

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“…The new formulation has many advantages over many similar moment-based approaches, such as TRS invariants [21] and Zernike descriptors [22]: 1) Krawtchouk polynomials are defined on a discrete space, so the moments derived Local shape search methods have many applications also in structural biology, which deals with 3D structures of biomolecules. An important application is the identification of ligand molecules (i.e., small chemical compounds including drug molecules) that bind to local protein surface regions, which is important for predicting biological function of proteins [24,25,26] and for computational drug design [27,39,38]. Ligand molecules that bind to a local surface region in a protein can be predicted by finding similar local regions (binding pockets) of known ligand-binding proteins in the protein structure database.…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional Krawtchouk descriptors for protein local surface shape comparison

Sit

Shin

2019

Pattern Recognition

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Direct comparison of three-dimensional (3D) objects is computationally expensive due to the need for translation, rotation, and scaling of the objects to evaluate their similarity. In applications of 3D object comparison, often identifying specific local regions of objects is of particular interest. We have recently developed a set of 2D moment invariants based on discrete orthogonal Krawtchouk polynomials for comparison of local image patches. In this work, we extend them to 3D and construct 3D Krawtchouk descriptors (3DKD) that are invariant under translation, rotation, and scaling. The new descriptors have the ability to extract local features of a 3D surface from any region-of-interest. This property enables comparison of two arbitrary local surface regions from different 3D objects. We present the new formulation of 3DKD and apply it to the local shape comparison of protein surfaces in order to predict ligand molecules that bind to query proteins. from them do not carry any error due to discretization unlike many other moments related to continuous functions [23]. 2) These polynomials are orthogonal; each moment brings in a new feature of the image, where minimum redundancy is critical in their discriminative performance. Moreover, they are directly defined in the image coordinate space, and hence their orthogonality property is well retained in the computed moments. 3) They are complete with a finite number of functions (equal to the image size) while many other polynomial spaces have infinitely many members. 4) They have the ability to retrieve local image patches by only changing the resolution of reconstruction and using low order moments. 5) The location of the patch can also be controlled by changing three parameters and hence shifting the region-of-interest along each dimension. 6) We also prove that these moments can be transformed into local descriptors, which are invariant under translation, rotation, and scaling. Therefore, using only a small number of invariant descriptors per image will make it possible to develop an efficient method for quick local image retrieval.Moment-based approaches, particularly Krawtchouk moments, are very useful for representing biological and medical images as they are pixelized or voxelized data. In medical imaging, such as computerized tomography (CT) scan and magnetic resonance imaging (MRI), objects are observed at different viewpoints and local images need to be extracted and examined. In digital pathology, for instance, pathologists are interested in information about specific structures rather than the whole image [9]. Thus, it is necessary to construct moment invariants that do not change by translation, rotation, and scaling and can retrieve local image patches or subimages.

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PL-PatchSurfer2: Improved Local Surface Matching-Based Virtual Screening Method That Is Tolerant to Target and Ligand Structure Variation

Cited by 27 publications

References 61 publications

Advances in the Development of Shape Similarity Methods and Their Application in Drug Discovery

Advances in the Development of Shape Similarity Methods and Their Application in Drug Discovery

A prospective compound screening contest identified broader inhibitors for Sirtuin 1

Three-dimensional Krawtchouk descriptors for protein local surface shape comparison

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