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

Quantitative Structure Activity Relationships in Computer Aided Drug Design: A Review

The process of processing a drug and reaching to the market consists of various steps. In the early times of Drug Discovery, researchers faced with little or no Structure Activity Relationships information regarding any chemical moiety. Computer Aided Drug Designing (CADD) is a discipline allowing various aspects of research to merge together and stimulate each other. CADD acts as a tunnel in Drug Discovery and accelerates finding new lead compounds. The theoretical basis of CADD involves quantum mechanics and molecular modelling studies like Structure-based design, Ligand-based design, database searching and binding affinity. QSAR is structural descriptors of chemical compound to its biological activity. It is very important to find out relationships between molecular structure and useful properties and so Drug Discovery and Development get more complex. But automation of chemical synthesis and pharmacological screening provides a vast amount of experimental data. Keywords: QSAR, Drug Design, CADD, Descriptor

A Computer-Aided Drug Design Approach to Predict Marine Drug-Like Leads for SARS-CoV-2 Main Protease Inhibition

UIDB/50006/2020 UIDB/04378/2020 Norma transitória DL 57/2016The investigation of marine natural products (MNPs) as key resources for the discovery of drugs to mitigate the COVID-19 pandemic is a developing field. In this work, computer-aided drug design (CADD) approaches comprising ligand- and structure-based methods were explored for predicting SARS-CoV-2 main protease (Mpro) inhibitors. The CADD ligand-based method used a quantitative structure–activity relationship (QSAR) classification model that was built using 5276 organic molecules extracted from the ChEMBL database with SARS-CoV-2 screening data. The best model achieved an overall predictive accuracy of up to 67% for an external and internal validation using test and training sets. Moreover, based on the best QSAR model, a virtual screening campaign was carried out using 11,162 MNPs retrieved from the Reaxys® database, 7 in-house MNPs obtained from marine-derived actinomycetes by the team, and 14 MNPs that are currently in the clinical pipeline. All the MNPs from the virtual screening libraries that were predicted as belonging to class A were selected for the CADD structure-based method. In the CADD structure-based approach, the 494 MNPs selected by the QSAR approach were screened by molecular docking against Mpro enzyme. A list of virtual screening hits comprising fifteen MNPs was assented by establishing several limits in this CADD approach, and five MNPs were proposed as the most promising marine drug-like leads as SARS-CoV-2 Mpro inhibitors, a benzo[f]pyrano[4,3-b]chromene, notoamide I, emindole SB beta-mannoside, and two bromoindole derivatives.publishersversionpublishe

TCM Database@Taiwan: The World's Largest Traditional Chinese Medicine Database for Drug Screening In Silico

Rapid advancing computational technologies have greatly speeded up the development of computer-aided drug design (CADD). Recently, pharmaceutical companies have increasingly shifted their attentions toward traditional Chinese medicine (TCM) for novel lead compounds. Despite the growing number of studies on TCM, there is no free 3D small molecular structure database of TCM available for virtual screening or molecular simulation. To address this shortcoming, we have constructed TCM Database@Taiwan (http://tcm.cmu.edu.tw/) based on information collected from Chinese medical texts and scientific publications. TCM Database@Taiwan is currently the world's largest non-commercial TCM database. This web-based database contains more than 20,000 pure compounds isolated from 453 TCM ingredients. Both cdx (2D) and Tripos mol2 (3D) formats of each pure compound in the database are available for download and virtual screening. The TCM database includes both simple and advanced web-based query options that can specify search clauses, such as molecular properties, substructures, TCM ingredients, and TCM classification, based on intended drug actions. The TCM database can be easily accessed by all researchers conducting CADD. Over the last eight years, numerous volunteers have devoted their time to analyze TCM ingredients from Chinese medical texts as well as to construct structure files for each isolated compound. We believe that TCM Database@Taiwan will be a milestone on the path towards modernizing traditional Chinese medicine.National Science Council of Taiwan (NSC 99-2221-E-039-013-)China Medical UniversityAsia UniversityAsia University (CMU98-ASIA-09)Taiwan. Dept. of Health (Clinical Trial and Research Center of Excellence (DOH99-TD-B-111-004))Taiwan. Dept. of Health (Cancer Research Center of Excellence (DOH99-TD-C-111-005)

Computer integrated manufacturing in the chemical industry: Theory & practice

This paper addresses the possibilities of implementing Computer Integrated Manufacturing in the process industry, and the chemical industry in particular. After presenting some distinct differences of the process industry in relation to discrete manufacturing, a number of focal points are discussed. They identify the adaptations to be made to a conventional CIM system, so that it will be applicable to the process industry. Interviews with managers of six chemical firms indicate that the process industry may benefit from a new CIM approach to management thinking.Chemical Industry;Manufacturing;CIM;production

feature Should medicinal chemists do molecular modelling?

In this article we discuss the pros and cons of medicinal chemists undertaking three-dimensional (3D) computer-aided Q2 drug design (CADD) activities for themselves, from the viewpoint of both medicinal chemists and computational chemists. We describe how best this can be implemented, the potential benefits that can be obtained and the pitfalls that are often encountered. It is not common practice for a computational chemist or molecular modeller to leave his or her workstation, don a white coat and perform organic chemistry experiments in a medicinal chemistry lab. Indeed many people would consider this to be rather reckless behaviour. Conversely there has always been a school of thought that medicinal chemists should carry out, to a greater or lesser extent, some elements of computer-aided drug design (CADD) for themselves, but is this suggestion just as reckless? In this article we discuss the reasoning behind this approach, how it could be implemented and the potential advantages and pitfalls that can accompany this endeavour. Medicinal chemists use computer programs on a daily basis during the course of their work, for example to generate experiments in an electronic laboratory notebook, perform database searches, retrieve biological test results, calculate physicochemical properties and generate plots to examine structure-activity relationships. When chemical structures are involved, they are usually considered in two dimensions. For the purposes of this article, the definition of CADD will not cover such activities, but rather focus on computational approaches using three-dimensional (3D) molecular structures, such as conformational analysis, molecular overlays, pharmacophore modelling and searching, ligand-protein docking, among others. A comprehensive review of CADDrelated software and resources has recently been publishe

Perceived importance of national occupational CADD skill standards among faculty of NAIT accredited institutions

This study presents a descriptive survey that examined the importance and relevance of National Occupational CARD Skills based on the perceptions of faculty teaching at National Association of Industrial Technology (NAIT) accredited institutions. The major goal of the study was to determine what National Occupational CADD Skill Standards are relevant and important to faculty teaching CARD courses. The study was also designed to determine ratings of the perceived importance and relevance of National Occupational CADD Skill Standards by faculty teaching CADD courses at NAIT accredited institutions based on their area of specialization, professional ranking, and teaching experience. This study provided NAIT accredited programs, professionals, and affiliated organizations a reflection of CADD standards developed, adopted, and practiced by faculty teaching CADD courses at NAIT accredited institutions in relation to National Occupational CADD Skill Standards. The population used for this study includes faculty teaching CADD courses in various Industrial Technology programs. For testing hypothesis I, a single sample was used for survey responses. Independent samples were used for survey responses in hypotheses II, III, and V. A single survey instrument was developed for this study. The survey instrument has five sections representing: demographics, fundamental drafting skills, fundamental computer skills, basic CADD skills, and advanced CADD skills. A research hypothesis (H1 : μ ≠ 3) was established for hypothesis I for each item. Research hypotheses (H1 At least one pair of the category means would be different) were established for hypotheses II, III, and IV. Hypothesis I was tested using a single sample t -test at the .O5 level of significance for each of the CADD skill standard item. The ANOVA was used to test hypotheses II, III, and IV. The results of the statistical analyses were used to arrive at inferences on the importance and relevance of National Occupational CADD Skill Standards developed by National Coalition for Advanced Manufacturing (NACFAM) by faculty teaching at NAIT accredited institutions. Statistical analyses also checked on the balance of opinions on importance and relevance of National Occupational CADD Skill Standards between industry and educators. Statistical analyses failed to establish significant mean differences on how faculty teaching CADD at NAIT accredited institutions perceive the importance and relevance of National Occupational CADD Skill Standards in the four hypotheses tested. The four hypotheses are stated in Chapter 1 of the study. Recommendations for further studies are provided in Chapter 5

Predicting Antifouling Activity and Acetylcholinesterase Inhibition of Marine-Derived Compounds Using a Computer-Aided Drug Design Approach

UIDB/50006/2020 Norma transit?ria DL 57/2016 UIDP/04378/2020 LA/P/0140/2020Biofouling is the undesirable growth of micro-and macro-organisms on artificial waterimmersed surfaces, which results in high costs for the prevention and maintenance of this process (billion €/year) for aquaculture, shipping and other industries that rely on coastal and off-shore infrastructure. To date, there are still no sustainable, economical and environmentally safe solutions to overcome this challenging phenomenon. A computer-aided drug design (CADD) approach comprising ligand-and structure-based methods was explored for predicting the antifouling activities of marine natural products (MNPs). In the CADD ligand-based method, 141 organic molecules extracted from the ChEMBL database and literature with antifouling screening data were used to build the quantitative structure–activity relationship (QSAR) classification model. An overall predictive accuracy score of up to 71% was achieved with the best QSAR model for external and internal validation using test and training sets. A virtual screening campaign of 14,492 MNPs from Encinar’s website and 14 MNPs that are currently in the clinical pipeline was also carried out using the best QSAR model developed. In the CADD structure-based approach, the 125 MNPs that were selected by the QSAR approach were used in molecular docking experiments against the acetylcholinesterase enzyme. Overall, 16 MNPs were proposed as the most promising marine drug-like leads as antifouling agents, e.g., macrocyclic lactam, macrocyclic alkaloids, indole and pyridine derivatives.publishersversionpublishe

Base RDT&E investment strategy

Issued as Statement of work, and Reports [nos. 1-5], Project D-48-628 (subproject E-20-616

A study to identify selected factors affecting the implementation of computer-aided design and drafting in industrial technology baccalaureate programs

The purpose of the study was to identify and analyze selected factors affecting the present status of Computer Aided Drafting and Design (CADD) and those factors which were needed to reach a desired level of CADD implementation in Industrial Technology Baccalaureate Programs (ITBPs) in the United States. The intent of this study was to identify and analyze selected factors which facilitate the implementation of CADD in ITBPs within the United States. One hundred and sixty-four ITBPs institutions from the 1992 National Association of Industrial Technology (NAIT) Directory were used for participation in this study. A questionnaire identifying both current and ideal status was constructed and validated through the pilot-test. The instruments were distributed, collected, and the data analyzed. Descriptive statistics were used to analyze the data. A frequency distribution was used for all variables. A mean rank was computed for the selected factors which inhibited the implementation or continuation of CADD in ITBPs. Selected Findings and Conclusions were: (1) A majority of respondents (91%) reported that they offered one or more CADD courses in their departments; (2) The majority of respondents (52%) indicated that for the current status, CADD was required of all majors in their departments. At the perceived ideal level, an overwhelming majority of respondents (92%) believe that CADD should be required for all majors in their departments; (3) a combination of separate CADD courses and CADD integrated into all design and drafting courses was recommended regarding CADD instruction by a majority of the respondents (67%); (4) Funding was the most inhibiting factor in the implementation or continuation of CADD in ITBPs, receiving the highest mean (4.34 on a 5-point scale). Based on the information collected in the survey, selected Recommendations were: (1) Industrial Technology Programs should hire more faculty who have expertise in the area of CADD in order to facilitate the implementation of CADD in their departments. (2) Vendor workshops and in-house training programs should be provided to faculty who need assistance to enhance their CADD knowledge so as to facilitate the implementation of CADD in their departments. (3) All industrial technology instructors should be encouraged to integrate CADD into their design and drafting programs. (4) Industrial technology instructors should be encouraged to develop their own instructional materials to suit their particular curriculum needs