TeachOpenCADD: a teaching platform for computer-aided drug design using open source packages and data

Owing to the increase in freely available software and data for cheminformatics and structural bioinformatics, research for computer-aided drug design (CADD) is more and more built on modular, reproducible, and easy-to-share pipelines. While documentation for such tools is available, there are only a few freely accessible examples that teach the underlying concepts focused on CADD, especially addressing users new to the field. Here, we present TeachOpenCADD, a teaching platform developed by students for students, using open source compound and protein data as well as basic and CADD-related Python packages. We provide interactive Jupyter notebooks for central CADD topics, integrating theoretical background and practical code. TeachOpenCADD is freely available on GitHub: https://github.com/volkamerlab/TeachOpenCAD

IVSPlat 1.0: an integrated virtual screening platform with a molecular graphical interface

<p>Abstract</p> <p>Background</p> <p>The virtual screening (VS) of lead compounds using molecular docking and pharmacophore detection is now an important tool in drug discovery. VS tasks typically require a combination of several software tools and a molecular graphics system. Thus, the integration of all the requisite tools in a single operating environment could reduce the complexity of running VS experiments. However, only a few freely available integrated software platforms have been developed.</p> <p>Results</p> <p>A free open-source platform, IVSPlat 1.0, was developed in this study for the management and automation of VS tasks. We integrated several VS-related programs into a molecular graphics system to provide a comprehensive platform for the solution of VS tasks based on molecular docking, pharmacophore detection, and a combination of both methods. This tool can be used to visualize intermediate and final results of the VS execution, while also providing a clustering tool for the analysis of VS results. A case study was conducted to demonstrate the applicability of this platform.</p> <p>Conclusions</p> <p>IVSPlat 1.0 provides a plug-in-based solution for the management, automation, and visualization of VS tasks. IVSPlat 1.0 is an open framework that allows the integration of extra software to extend its functionality and modified versions can be freely distributed. The open source code and documentation are available at <url>http://kyc.nenu.edu.cn/IVSPlat/.</url></p

Molecular Docking with Open Access Software: Development of an Online Laboratory Handbook and Remote Workflow for Chemistry and Pharmacy Master's Students to Undertake Computer-Aided Drug Design

In response to the closure of many university laboratories due to the Covid-19 pandemic in 2020, a handbook and remote webinar approach designed to support students in the use of software tools for computer-aided drug design has been developed. Specifically, the course has been designed for chemistry and pharmacy students who have little or no experience of computational techniques and can use open-source software on their own machines. In this way a flexible and relevant course, giving a rigorous academic experience, could be delivered even in the most challenging of circumstances. We believe that this laboratory protocol will help to "democratize"the scientific process in this field

Boosting the full potential of PyMOL with structural biology plugins

Over the past few decades, the number of available structural bioinformatics pipelines, libraries, plugins, web resources and software has increased exponentially and become accessible to the broad realm of life scientists. This expansion has shaped the field as a tangled network of methods, algorithms and user interfaces. In recent years PyMOL, widely used software for biomolecules visualization and analysis, has started to play a key role in providing an open platform for the successful implementation of expert knowledge into an easy-to-use molecular graphics tool. This review outlines the plugins and features that make PyMOL an eligible environment for supporting structural bioinformatics analyses

Accessible High-Throughput Virtual Screening Molecular Docking Software for Students and Educators

We survey low cost high-throughput virtual screening (HTVS) computer programs for instructors who wish to demonstrate molecular docking in their courses. Since HTVS programs are a useful adjunct to the time consuming and expensive wet bench experiments necessary to discover new drug therapies, the topic of molecular docking is core to the instruction of biochemistry and molecular biology. The availability of HTVS programs coupled with decreasing costs and advances in computer hardware have made computational approaches to drug discovery possible at institutional and non-profit budgets. This paper focuses on HTVS programs with graphical user interfaces (GUIs) that use either DOCK or AutoDock for the prediction of DockoMatic, PyRx, DockingServer, and MOLA since their utility has been proven by the research community, they are free or affordable, and the programs operate on a range of computer platforms

Computer Assisted Drug Design of Tinosporide for treatment of Cancer: a Combined Density Functional and Molecular Docking Study

This article discusses theory behind the most important methods and recent successful applications of halogen‑directed tinosporide, ligand-based methods use only ligand information for predicting activity depending on its similarity/dissimilarity to previously known active ligands. We review widely used ligand-based methods such as ligand-based pharmacophores, molecular descriptors, and quantitative structure-activity relationships. In addition, important tools such as target/ligand data bases, homology modeling, ligand ADMET etc., and necessary for successful implementation of various computer-aided drug discovery/design methods in best analogue of tinosporides discovery are discussed. Finally, computational methods for toxicity prediction and optimization for favorable physiologic properties are discussed with successful lead for tinosporides from literature. The therapeutic potential of tinosporide has been studied extensively and the active compounds of tinosporide are shown to be involved in modulating multiple physiological responses. Moreover this article will review the structure of series of halogen-directed tinosporides before illustration on how the molecules exert their functions via interactions with various signal transducer and activator proteins of transcription which were designed by homology modeling. Strategies for CADD vary depending on the extent of structural and other information available regarding the target (enzyme/receptor) and the ligands. The process by which a new tinosporide product is brought to market stage is referred to by a number of names most commonly as the development chain and consists of a number of distinct stages. Keywords: CADD; ADMET; Molecular Modeling; Tinosporide

PocketPicker: analysis of ligand binding-sites with shape descriptors

Background Identification and evaluation of surface binding-pockets and occluded cavities are initial steps in protein structure-based drug design. Characterizing the active site's shape as well as the distribution of surrounding residues plays an important role for a variety of applications such as automated ligand docking or in situ modeling. Comparing the shape similarity of binding site geometries of related proteins provides further insights into the mechanisms of ligand binding. Results We present PocketPicker, an automated grid-based technique for the prediction of protein binding pockets that specifies the shape of a potential binding-site with regard to its buriedness. The method was applied to a representative set of protein-ligand complexes and their corresponding apo-protein structures to evaluate the quality of binding-site predictions. The performance of the pocket detection routine was compared to results achieved with the existing methods CAST, LIGSITE, LIGSITEcs, PASS and SURFNET. Success rates PocketPicker were comparable to those of LIGSITEcs and outperformed the other tools. We introduce a descriptor that translates the arrangement of grid points delineating a detected binding-site into a correlation vector. We show that this shape descriptor is suited for comparative analyses of similar binding-site geometry by examining induced-fit phenomena in aldose reductase. This new method uses information derived from calculations of the buriedness of potential binding-sites. Conclusions The pocket prediction routine of PocketPicker is a useful tool for identification of potential protein binding-pockets. It produces a convenient representation of binding-site shapes including an intuitive description of their accessibility. The shape-descriptor for automated classification of binding-site geometries can be used as an additional tool complementing elaborate manual inspections

Interactivity:the missing link between virtual reality technology and drug discovery pipelines

The potential of virtual reality (VR) to contribute to drug design and development has been recognised for many years. Hardware and software developments now mean that this potential is beginning to be realised, and VR methods are being actively used in this sphere. A recent advance is to use VR not only to visualise and interact with molecular structures, but also to interact with molecular dynamics simulations of 'on the fly' (interactive molecular dynamics in VR, IMD-VR), which is useful not only for flexible docking but also to examine binding processes and conformational changes. iMD-VR has been shown to be useful for creating complexes of ligands bound to target proteins, e.g., recently applied to peptide inhibitors of the SARS-CoV-2 main protease. In this review, we use the term 'interactive VR' to refer to software where interactivity is an inherent part of the user VR experience e.g., in making structural modifications or interacting with a physically rigorous molecular dynamics (MD) simulation, as opposed to simply using VR controllers to rotate and translate the molecule for enhanced visualisation. Here, we describe these methods and their application to problems relevant to drug discovery, highlighting the possibilities that they offer in this arena. We suggest that the ease of viewing and manipulating molecular structures and dynamics, and the ability to modify structures on the fly (e.g., adding or deleting atoms) makes modern interactive VR a valuable tool to add to the armoury of drug development methods.Comment: 19 pages, 3 figure

Identification of Benzoxazolinone Derivatives Based Inhibitors for Depression and Pain Related Disorders Using Human Serotonin and Norepinephrine Transporter as Dual Therapeutic Target: A Computational Approach

Pain is commonly associated with depression. Both pain and depression share common biological pathways and neurotransmitters, which has implications for the treatment of both disorders. A drug that could ameliorate both pain and depression could be beneficial in the development of new therapeutics in the management of disorders associated with pain/depression dyad. Alterations in the neurotransmitters namely, serotonin and norepinephrine in the central nervous system (CNS) have been implicated in the pathophysiology of pain and depression. Serotonin and norepinephrine reuptake inhibitors (SNRIs) have been implicated as a novel therapeutic target for a wide range of biological functions, including pain, anxiety and depression. 2-benzoxazolinone (2-BOA) from the mangrove Acanthus ilicifolius and its derivatives have been reported for its analgesic and antidepressant activities. In the present work, docking studies were done on the crystal structure of human transporters of serotonin (hSERT) and on homology modeled human transporters of norepinephrine (hNET) as therapeutic targets of depression and pain related disorders using 2-BOA and its derivatives as potential candidates. A homology model for hNET was constructed using MODELLER and validated. Further docking studies were done on hSERT and hNET using 2-BOA and its structural analogs. The result of the study proposes the possible potential candidate among 2-BOA derivatives that may be further developed as a therapeutic lead compound for use in disorders associated with depression and pain