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Saifi I, Bhat BA, Hamdani SS, Bhat UY, Lobato-Tapia CA, Mir MA, Dar TUH, Ganie SA. Artificial intelligence and cheminformatics tools: a contribution to the drug development and chemical science. J Biomol Struct Dyn 2024; 42:6523-6541. [PMID: 37434311 DOI: 10.1080/07391102.2023.2234039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Accepted: 07/03/2023] [Indexed: 07/13/2023]
Abstract
In the ever-evolving field of drug discovery, the integration of Artificial Intelligence (AI) and Machine Learning (ML) with cheminformatics has proven to be a powerful combination. Cheminformatics, which combines the principles of computer science and chemistry, is used to extract chemical information and search compound databases, while the application of AI and ML allows for the identification of potential hit compounds, optimization of synthesis routes, and prediction of drug efficacy and toxicity. This collaborative approach has led to the discovery, preclinical evaluations and approval of over 70 drugs in recent years. To aid researchers in the pursuit of new drugs, this article presents a comprehensive list of databases, datasets, predictive and generative models, scoring functions and web platforms that have been launched between 2021 and 2022. These resources provide a wealth of information and tools for computer-assisted drug development, and are a valuable asset for those working in the field of cheminformatics. Overall, the integration of AI, ML and cheminformatics has greatly advanced the drug discovery process and continues to hold great potential for the future. As new resources and technologies become available, we can expect to see even more groundbreaking discoveries and advancements in these fields.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Ifra Saifi
- Chaudhary Charan Singh University, Meerut, Uttar Pradesh, India
| | - Basharat Ahmad Bhat
- Department of Bioresources, School of Biological Sciences, University of Kashmir, Srinagar, J&K, India
| | - Syed Suhail Hamdani
- Department of Bioresources, School of Biological Sciences, University of Kashmir, Srinagar, J&K, India
| | - Umar Yousuf Bhat
- Department of Zoology, School of Biological Sciences, University of Kashmir, Srinagar, J&K, India
| | | | - Mushtaq Ahmad Mir
- Department of Clinical Laboratory Sciences, College of Applied Medical Science, King Khalid University, KSA, Saudi Arabia
| | - Tanvir Ul Hasan Dar
- Department of Biotechnology, School of Biosciences and Biotechnology, BGSB University, Rajouri, India
| | - Showkat Ahmad Ganie
- Department of Clinical Biochemistry, School of Biological Sciences, University of Kashmir, Srinagar, J&K, India
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2
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de Azevedo DQ, Campioni BM, Pedroz Lima FA, L Medina-Franco J, Castilho RO, Maltarollo VG. A critical assessment of bioactive compounds databases. Future Med Chem 2024; 16:1029-1051. [PMID: 38910575 PMCID: PMC11221550 DOI: 10.1080/17568919.2024.2342203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 04/03/2024] [Indexed: 06/25/2024] Open
Abstract
Compound databases (DBs) are essential tools for drug discovery. The number of DBs in public domain is increasing, so it is important to analyze these DBs. In this article, the main characteristics of 64 DBs will be presented. The methodological strategy used was a literature search. To analyze the characteristics obtained in the review, the DBs were categorized into two subsections: Open Access and Commercial DBs. Open access includes generalist DBs (containing compounds of diverse origins), DBs with specific applicability, DBs exclusive to natural products and those containing compounds with specific pharmacological action. The literature review showed that there are challenges to making these repositories available, such as standardizing information curation practices and funding to maintain and sustain them.
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Affiliation(s)
- Daniela Quadros de Azevedo
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais, Campus Pampulha, Belo Horizonte, Minas Gerais, 31270-900, Brazil
| | - Beatriz Mattos Campioni
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais, Campus Pampulha, Belo Horizonte, Minas Gerais, 31270-900, Brazil
| | - Felipe Augusto Pedroz Lima
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais, Campus Pampulha, Belo Horizonte, Minas Gerais, 31270-900, Brazil
| | - José L Medina-Franco
- DIFACQUIM Research Group, Department of Pharmacy, School of Chemistry, National Autonomous University of Mexico, Mexico City, 04510, Mexico
| | - Rachel Oliveira Castilho
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais, Campus Pampulha, Belo Horizonte, Minas Gerais, 31270-900, Brazil
| | - Vinícius Gonçalves Maltarollo
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais, Campus Pampulha, Belo Horizonte, Minas Gerais, 31270-900, Brazil
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Otarigho B, Falade MO. Natural Perylenequinone Compounds as Potent Inhibitors of Schistosoma mansoni Glutathione S-Transferase. Life (Basel) 2023; 13:1957. [PMID: 37895339 PMCID: PMC10608284 DOI: 10.3390/life13101957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 09/19/2023] [Accepted: 09/21/2023] [Indexed: 10/29/2023] Open
Abstract
The existing treatment strategy for Schistosomiasis centers on praziquantel, a single drug, but its effectiveness is limited due to resistance and lack of preventive benefits. Thus, there is an urgent need for novel antischistosomal agents. Schistosoma glutathione S-transferase (GST) is an essential parasite enzyme, with a high potential for targeted drug discovery. In this study, we conducted a screening of compounds possessing antihelminth properties, focusing on their interaction with the Schistosoma mansoni glutathione S-transferase (SmGST) protein. We demonstrated the unique nature of SmGST in comparison to human GST. Evolutionary analysis indicated its close relationship with other parasitic worms, setting it apart from free-living worms such as C. elegans. Through an assessment of binding pockets and subsequent protein-ligand docking, we identified Scutiaquinone A and Scutiaquinone B, both naturally derived Perylenequinones, as robust binders to SmGST. These compounds have exhibited effectiveness against similar parasites and offer promising potential as antischistosomal agents.
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Affiliation(s)
- Benson Otarigho
- Department of Molecular Microbiology and Immunology, Oregon Health and Science University, Portland, OR 97239, USA
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Khan H, Waqas M, Khurshid B, Ullah N, Khalid A, Abdalla AN, Alamri MA, Wadood A. Investigating the role of Sterol C24-Methyl transferase mutation on drug resistance in leishmaniasis and identifying potential inhibitors. J Biomol Struct Dyn 2023:1-14. [PMID: 37723868 DOI: 10.1080/07391102.2023.2256879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 09/02/2023] [Indexed: 09/20/2023]
Abstract
Leishmaniasis is a fatal disease caused by the leishmania parasite. For the survival of the leishmania parasite, Sterol C24-Methyl Transferase (SMT) is essential which is an enzyme of the ergosterol pathway. SMT protein mutation is responsible for Amphotericin-B drug resistance in Leishmania, which is the main treatment for visceral leishmaniasis. Amphotericin-B resistance is caused by three mutated residues V131I, V321I and F72C. The underlying mechanisms and structural changes in SMT enzymes responsible for resistance due to mutation are still not well understood. In the current study, the potential mechanism of resistance due to these mutations and the structure variation of wild and mutant SMT proteins were investigated through molecular dynamics simulations and molecular docking analysis. The results showed that AmB established strong bonding interaction with wild SMT as compare to mutants SMT. The binding energy calculation showed that binding energy of AmB with mutants SMT increases as compare to the wild SMT. Further structural based virtual screening was carried out to design potential inhibitors for the mutant SMT. On the basis of structural-based virtual screening four inhibitors (SANC01057, SANC00882, SANC00414, SANC01047) were computationally identified as potential mutant SMT (F72C) inhibitors. This work provides valuable information for improved management of drug resistant Leishmaniasis.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Huma Khan
- Department of Biochemistry, Abdul Wali Khan University Mardan, Mardan, Pakistan
| | - Muhammad Waqas
- Natural and Medical Sciences Research Center, University of Nizwa, Birkat Al-Mouz Nizwa, Oman
| | - Beenish Khurshid
- Department of Biochemistry, Abdul Wali Khan University Mardan, Mardan, Pakistan
| | - Nazif Ullah
- Department of Biotechnology, Abdul Wali Khan University Mardan, Mardan, Pakistan
| | - Asaad Khalid
- Substance Abuse and Toxicology Research Center, Jazan University, Jazan, Saudi Arabia
| | - Ashraf N Abdalla
- Department of Pharmacology and Toxicology, College of Pharmacy, Umm Al-Qura University, Makkah, Saudi Arabia
| | - Mubarak A Alamri
- Department of Pharmaceutical Chemistry, College of Pharmacy, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
| | - Abdul Wadood
- Department of Biochemistry, Abdul Wali Khan University Mardan, Mardan, Pakistan
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Ali H, Samad A, Ajmal A, Ali A, Ali I, Danial M, Kamal M, Ullah M, Ullah R, Kalim M. Identification of Drug Targets and Their Inhibitors in Yersinia pestis Strain 91001 through Subtractive Genomics, Machine Learning, and MD Simulation Approaches. Pharmaceuticals (Basel) 2023; 16:1124. [PMID: 37631039 PMCID: PMC10459760 DOI: 10.3390/ph16081124] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 07/20/2023] [Accepted: 07/28/2023] [Indexed: 08/27/2023] Open
Abstract
Yersinia pestis, the causative agent of plague, is a Gram-negative bacterium. If the plague is not properly treated it can cause rapid death of the host. Bubonic, pneumonic, and septicemic are the three types of plague described. Bubonic plague can progress to septicemic plague, if not diagnosed and treated on time. The mortality rate of pneumonic and septicemic plague is quite high. The symptom-defining disease is the bubo, which is a painful lymph node swelling. Almost 50% of bubonic plague leads to sepsis and death if not treated immediately with antibiotics. The host immune response is slow as compared to other bacterial infections. Clinical isolates of Yersinia pestis revealed resistance to many antibiotics such as tetracycline, spectinomycin, kanamycin, streptomycin, minocycline, chloramphenicol, and sulfonamides. Drug discovery is a time-consuming process. It always takes ten to fifteen years to bring a single drug to the market. In this regard, in silico subtractive proteomics is an accurate, rapid, and cost-effective approach for the discovery of drug targets. An ideal drug target must be essential to the pathogen's survival and must be absent in the host. Machine learning approaches are more accurate as compared to traditional virtual screening. In this study, k-nearest neighbor (kNN) and support vector machine (SVM) were used to predict the active hits against the beta-ketoacyl-ACP synthase III drug target predicted by the subtractive genomics approach. Among the 1012 compounds of the South African Natural Products database, 11 hits were predicted as active. Further, the active hits were docked against the active site of beta-ketoacyl-ACP synthase III. Out of the total 11 active hits, the 3 lowest docking score hits that showed strong interaction with the drug target were shortlisted along with the standard drug and were simulated for 100 ns. The MD simulation revealed that all the shortlisted compounds display stable behavior and the compounds formed stable complexes with the drug target. These compounds may have the potential to inhibit the beta-ketoacyl-ACP synthase III drug target and can help to combat Yersinia pestis-related infections. The dataset and the source codes are freely available on GitHub.
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Affiliation(s)
- Hamid Ali
- Department of Biosciences, COMSATS University Islamabad, Park Road, Tarlai Kalan, Islamabad 44000, Pakistan
| | - Abdus Samad
- Department of Biochemistry, Abdul Wali Khan University, Mardan 23200, Pakistan; (A.S.); (A.A.); (M.D.); (M.K.)
| | - Amar Ajmal
- Department of Biochemistry, Abdul Wali Khan University, Mardan 23200, Pakistan; (A.S.); (A.A.); (M.D.); (M.K.)
| | - Amjad Ali
- Faculty of Biological Sciences, Department of Biochemistry, Quaid-i-Azam University, Islamabad 45320, Pakistan;
| | - Ijaz Ali
- Centre for Applied Mathematics and Bioinformatics (CAMB), Gulf University for Science and Technology, Hawally 32093, Kuwait;
| | - Muhammad Danial
- Department of Biochemistry, Abdul Wali Khan University, Mardan 23200, Pakistan; (A.S.); (A.A.); (M.D.); (M.K.)
| | - Masroor Kamal
- Department of Biochemistry, Abdul Wali Khan University, Mardan 23200, Pakistan; (A.S.); (A.A.); (M.D.); (M.K.)
| | - Midrar Ullah
- Department of Biotechnology, Shaheed Benazir Bhutto University Sheringal, Dir Upper 18050, Pakistan;
| | - Riaz Ullah
- Department of Pharmacognosy, College of Pharmacy King Saud University, Riyadh 11451, Saudi Arabia;
| | - Muhammad Kalim
- Department of Microbiology and Immunology, Wake Forest School of Medicine, Winston-Salem, NC 27101, USA;
- Houston Methodist Cancer Center/Weill Cornel Medicine, Houston, TX 77030, USA
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Issahaku AR, Mncube SM, Agoni C, Kwofie SK, Alahmdi MI, Abo-Dya NE, Sidhom PA, Tawfeek AM, Ibrahim MAA, Mukelabai N, Soremekun O, Soliman MES. Multi-dimensional structural footprint identification for the design of potential scaffolds targeting METTL3 in cancer treatment from natural compounds. J Mol Model 2023; 29:122. [PMID: 36995499 DOI: 10.1007/s00894-023-05516-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Accepted: 03/15/2023] [Indexed: 03/31/2023]
Abstract
CONTEXT [Formula: see text]-adenosine-methyltransferase (METTL3) is the catalytic domain of the 'writer' proteins which is involved in the post modifications of [Formula: see text]-methyladinosine ([Formula: see text]). Though its activities are essential in many biological processes, it has been implicated in several types of cancer. Thus, drug developers and researchers are relentlessly in search of small molecule inhibitors that can ameliorate the oncogenic activities of METTL3. Currently, STM2457 is a potent, highly selective inhibitor of METTL3 but is yet to be approved. METHODS In this study, we employed structure-based virtual screening through consensus docking by using AutoDock Vina in PyRx interface and Glide virtual screening workflow of Schrodinger Glide. Thermodynamics via MM-PBSA calculations was further used to rank the compounds based on their total free binding energies. All atom molecular dynamics simulations were performed using AMBER 18 package. FF14SB force fields and Antechamber were used to parameterize the protein and compounds respectively. Post analysis of generated trajectories was analyzed with CPPTRAJ and PTRAJ modules incorporated in the AMBER package while Discovery studio and UCSF Chimera were used for visualization, and origin data tool used to plot all graphs. RESULTS Three compounds with total free binding energies higher than STM2457 were selected for extended molecular dynamics simulations. The compounds, SANCDB0370, SANCDB0867, and SANCDB1033, exhibited stability and deeper penetration into the hydrophobic core of the protein. They engaged in relatively stronger intermolecular interactions involving hydrogen bonds with resultant increase in stability, reduced flexibility, and decrease in the surface area of the protein available for solvent interactions suggesting an induced folding of the catalytic domain. Furthermore, in silico pharmacokinetics and physicochemical analysis of the compounds revealed good properties suggesting these compounds could serve as promising MEETL3 entry inhibitors upon modifications and optimizations as presented by natural compounds. Further biochemical testing and experimentations would aid in the discovery of effective inhibitors against the berserk activities of METTL3.
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Diabate O, Cisse C, Sangare M, Soremekun O, Fatumo S, Shaffer JG, Doumbia S, Wele M. Identification of promising high-affinity inhibitors of SARS-CoV-2 main protease from African Natural Products Databases by Virtual Screening. RESEARCH SQUARE 2023:rs.3.rs-2673755. [PMID: 36993208 PMCID: PMC10055610 DOI: 10.21203/rs.3.rs-2673755/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/31/2023]
Abstract
With the rapid spread of the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen agent of COVID-19 pandemic created a serious threat to global public health, requiring the most urgent research for potential therapeutic agents. The availability of genomic data of SARS-CoV-2 and efforts to determine the protein structure of the virus facilitated the identification of potent inhibitors by using structure-based approach and bioinformatics tools. Many pharmaceuticals have been proposed for the treatment of COVID-19, although their effectiveness has not been assessed yet. However, it is important to find out new-targeted drugs to overcome the resistance concern. Several viral proteins such as proteases, polymerases or structural proteins have been considered as potential therapeutic targets. But the virus target must be essential for host invasion match some drugability criterion. In this Work, we selected the highly validated pharmacological target main protease Mpro and we performed high throughput virtual screening of African Natural Products Databases such as NANPDB, EANPDB, AfroDb, and SANCDB to identify the most potent inhibitors with the best pharmacological properties. In total, 8753 natural compounds were virtually screened by AutoDock vina against the main protease of SARS-CoV-2. Two hundred and five (205) compounds showed high-affinity scores (less than - 10.0 Kcal/mol), while fifty-eight (58) filtered through Lipinski's rules showed better affinity than known Mpro inhibitors (i.e., ABBV-744, Onalespib, Daunorubicin, Alpha-ketoamide, Perampanel, Carprefen, Celecoxib, Alprazolam, Trovafloxacin, Sarafloxacin, Ethyl biscoumacetate…). Those promising compounds could be considered for further investigations toward the developpement of SARS-CoV-2 drug development.
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Affiliation(s)
- Oudou Diabate
- University of Sciences, Technics and Technologies of Bamako (USTTB)
| | - Cheickna Cisse
- University of Sciences, Technics and Technologies of Bamako (USTTB)
| | | | | | - Segun Fatumo
- University of Sciences, Technics and Technologies of Bamako (USTTB)
| | | | - Seydou Doumbia
- University of Sciences, Technics and Technologies of Bamako (USTTB)
| | - Mamadou Wele
- University of Sciences, Technics and Technologies of Bamako (USTTB)
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Khan A, Heng W, Imran K, Zhu G, Ji J, Zhang Y, Guan X, Ge G, Wei DQ. Discovery of Isojacareubin as a covalent inhibitor of SARS-CoV-2 main protease using structural and experimental approaches. J Med Virol 2023; 95:e28542. [PMID: 36727647 DOI: 10.1002/jmv.28542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 01/25/2023] [Accepted: 01/30/2023] [Indexed: 02/03/2023]
Abstract
The ongoing pandemic with the emergence of immune evasion potential and, particularly, the current omicron subvariants intensified the situation further. Although vaccines are available, the immune evasion capabilities of the recent variants demand further efficient therapeutic choices to control the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Hence, considering the necessity of the small molecule inhibitor, we target the main protease (3CLpro), which is an appealing target for the development of antiviral drugs against SARS-CoV-2. High-throughput molecular in silico screening of South African natural compounds database reported Isojacareubin and Glabranin as the potential inhibitors for the main protease. The calculated docking scores were reported to be -8.47 and -8.03 kcal/mol, respectively. Moreover, the structural dynamic assessment reported that Isojacareubin in complex with 3CLpro exhibit a more stable dynamic behavior than Glabranin. Inhibition assay indicated that Isojacareubin could inhibit SARS-CoV-2 3CLpro in a time- and dose-dependent manner, with half maximal inhibitory concentration values of 16.00 ± 1.35 μM (60 min incubation). Next, the covalent binding sites of Isojacareubin on SARS-CoV-2 3CLpro was identified by biomass spectrometry, which reported that Isojacareubin can covalently bind to thiols or Cysteine through Michael addition. To evaluate the inactivation potency of Isojacareubin, the inactivation kinetics was further investigated. The inactivation kinetic curves were plotted according to various concentrations with gradient-ascending incubation times. The KI value of Isojacareubin was determined as 30.71 μM, whereas the Kinact value was calculated as 0.054 min-1 . These results suggest that Isojacareubin is a covalent inhibitor of SARS-CoV-2 3CLpro .
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Affiliation(s)
- Abbas Khan
- Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, P.R. China
- Zhongjing Research and Industrialization Institute of Chinese Medicine, Zhongguancun Scientific Park, Meixi, Nayang, Henan, P.R., China
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, P.R., China
| | - Wang Heng
- International School of Cosmetics, School of Perfume and Aroma Technology, Shanghai Institute of Technology, Shanghai, P.R., China
| | - Kashif Imran
- Services Institute of Medical Sciences, Lahore, Punjab, Pakistan
| | - Guanghao Zhu
- Shanghai Frontiers Science Center for Chinese Medicine Chemical Biology, Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jun Ji
- Henan Provincial Engineering and Technology Center of Health Products for Livestock and Poultry, Henan Provincial Engineering and Technology Center of Animal Disease Diagnosis and Integrated Control, Nanyang Normal University, Nanyang, P.R., China
| | - Yani Zhang
- Peng Cheng Laboratory, Vanke Cloud City, Nashan District, Shenzhen, Guangdong, P.R., China
| | - Xiaoqing Guan
- Shanghai Frontiers Science Center for Chinese Medicine Chemical Biology, Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Guangbo Ge
- Shanghai Frontiers Science Center for Chinese Medicine Chemical Biology, Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Dong-Qing Wei
- Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, P.R. China
- Zhongjing Research and Industrialization Institute of Chinese Medicine, Zhongguancun Scientific Park, Meixi, Nayang, Henan, P.R., China
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, P.R., China
- Peng Cheng Laboratory, Vanke Cloud City, Nashan District, Shenzhen, Guangdong, P.R., China
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Guo L, Zafar F, Moeen N, Alshabrmi FM, Lin J, Ali SS, Munir M, Khan A, Wei D. Ultra-Large-Scale Screening of Natural Compounds and Free Energy Calculations Revealed Potential Inhibitors for the Receptor-Binding Domain (RBD) of SARS-CoV-2. Molecules 2022; 27:7317. [PMID: 36364143 PMCID: PMC9656483 DOI: 10.3390/molecules27217317] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2022] [Revised: 10/06/2022] [Accepted: 10/10/2022] [Indexed: 11/19/2023] Open
Abstract
The emergence of immune-evading variants of SARS-CoV-2 further aggravated the ongoing pandemic. Despite the deployments of various vaccines, the acquired mutations are capable of escaping both natural and vaccine-induced immune responses. Therefore, further investigation is needed to design a decisive pharmacological treatment that could efficiently block the entry of this virus into cells. Hence, the current study used structure-based methods to target the RBD of the recombinant variant (Deltacron) of SARS-CoV-2, which was used as a model variant. From the virtual drug screenings of various databases, a total of four hits were identified as potential lead molecules. Key residues were blocked by these molecules with favorable structural dynamic features. The binding free energies further validated the potentials of these molecules. The TBE for MNP was calculated to be -32.86 ± 0.10 kcal/mol, for SANC00222 the TBE was -23.41 ± 0.15 kcal/mol, for Liriodenine the TBE was -34.29 ± 0.07 kcal/mol, while for Carviolin the TBE was calculated to be -27.67 ± 0.12 kcal/mol. Moreover, each complex demonstrated distinct internal motion and a free energy profile, indicating a different strategy for the interaction with and inhibition of the RBD. In conclusion, the current study demands further in vivo and in vitro validation for the possible usage of these compounds as potential drugs against SARS-CoV-2 and its variants.
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Affiliation(s)
- Lisha Guo
- Zhongjing Chinese Medicine College, Nanyang Institute of Technology, 80 Changjiang Road, Nanyang 473004, China
| | - Faryar Zafar
- Nishtar Medical University, Multan 59341, Pakistan
| | - Nawal Moeen
- Nawaz Sharif Medical College, Gujrat 50700, Pakistan
| | - Fahad M. Alshabrmi
- Department of Medical Laboratories, College of Applied Medical Sciences, Qassim University, Buraydah 51452, Saudi Arabia
| | - Junqi Lin
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China
| | - Syed Shujait Ali
- Center for Biotechnology and Microbiology, University of Swat, Swat 19120, Pakistan
| | - Muhammad Munir
- Division of Biomedical and Life Sciences, Lancaster University, Bailrigg, Lancaster LA1 4YW, UK
| | - Abbas Khan
- Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
- Zhongjing Research and Industrialization Institute of Chinese Medicine, Zhongguancun Scientific Park, Meixi, Nanyang 473006, China
| | - Dongqing Wei
- Division of Biomedical and Life Sciences, Lancaster University, Bailrigg, Lancaster LA1 4YW, UK
- Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
- Zhongjing Research and Industrialization Institute of Chinese Medicine, Zhongguancun Scientific Park, Meixi, Nanyang 473006, China
- Peng Cheng Laboratory, Vanke Cloud City Phase I Building 8, Xili Street, Nashan District, Shenzhen 518055, China
- State Key Laboratory of Microbial Metabolism, Joint Laboratory of International Laboratory of Metabolic and Developmental Sciences, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Ministry of Education and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200030, China
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10
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Mohammed Ali H. In-silico investigation of a novel inhibitors against the antibiotic-resistant Neisseria gonorrhoeae bacteria. Saudi J Biol Sci 2022; 29:103424. [PMID: 36091725 PMCID: PMC9460163 DOI: 10.1016/j.sjbs.2022.103424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 07/14/2022] [Accepted: 08/17/2022] [Indexed: 12/03/2022] Open
Abstract
Antibiotics are drugs that are used to treat or prevent bacterial infections. They work by either killing or stopping bacteria from spreading. Nevertheless, it appeared in the last decade, Antibiotic-resistant bacteria are bacteria resistant to antibiotics and cannot be controlled or killed by them. In the presence of an antibiotic, they can live and even reproduce. The Neisseria gonorrhoeae bacteria is appearing to be a multidrug-resistant pathogen. Many factors contribute to antibiotic resistance, including unfettered access to antimicrobials, incorrect drug selection, misuse, and low-quality antibiotics. Here, we investigated in-silico docking screening and analysis for ten natural marine fungus extracted compounds. The resulted data were examined for the best binding affinity, toxicity, and chemical interactions. The most superior compound was elipyrone A with six hydrogen bonds, −8.5 of binding affinity, and preferable results in the SWISS-ADME examination. It is well known that “Declining corporate investment and a lack of innovation in the development of new antibiotics are weakening efforts to battle drug-resistant illnesses,” according to the World Health Organization (WHO). So, we extended our effort to predict a new natural compound to overcome the resistance of this bacteria.
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11
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Panecka-Hofman J, Poehner I, Wade R. Anti-trypanosomatid structure-based drug design - lessons learned from targeting the folate pathway. Expert Opin Drug Discov 2022; 17:1029-1045. [PMID: 36073204 DOI: 10.1080/17460441.2022.2113776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Trypanosomatidic parasitic infections of humans and animals caused by Trypanosoma brucei, Trypanosoma cruzi, and Leishmania species pose a significant health and economic burden in developing countries. There are few effective and accessible treatments for these diseases, and the existing therapies suffer from problems such as parasite resistance and side effects. Structure-based drug design (SBDD) is one of the strategies that has been applied to discover new compounds targeting trypanosomatid-borne diseases. AREAS COVERED We review the current literature (mostly over the last 5 years, searched in PubMed database on Nov 11th 2021) on the application of structure-based drug design approaches to identify new anti-trypanosomatidic compounds that interfere with a validated target biochemical pathway, the trypanosomatid folate pathway. EXPERT OPINION The application of structure-based drug design approaches to perturb the trypanosomatid folate pathway has successfully provided many new inhibitors with good selectivity profiles, most of which are natural products or their derivatives or have scaffolds of known drugs. However, the inhibitory effect against the target protein(s) often does not translate to anti-parasitic activity. Further progress is hampered by our incomplete understanding of parasite biology and biochemistry, which is necessary to complement SBDD in a multiparameter optimization approach to discovering selective anti-parasitic drugs.
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Affiliation(s)
- Joanna Panecka-Hofman
- Division of Biophysics, Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Pasteura 5a, 02-097 Warsaw, Poland
| | - Ina Poehner
- School of Pharmacy, University of Eastern Finland, Kuopio, Yliopistonranta 1C, PO Box 1627, FI-70211 Kuopio, Finland
| | - Rebecca Wade
- Center for Molecular Biology (ZMBH), Heidelberg University, Im Neuenheimer Feld 282, Heidelberg 69120, Germany.,Heidelberg Institute for Theoretical Studies (HITS), Schloß-Wolfsbrunnenweg 35, Heidelberg 69118, Germany.,DKFZ-ZMBH Alliance and Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Im Neuenheimer Feld 205, Heidelberg 69120, Germany
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Wah Tan Z, Tee WV, Berezovsky IN. Learning about allosteric drugs and ways to design them. J Mol Biol 2022; 434:167692. [PMID: 35738428 DOI: 10.1016/j.jmb.2022.167692] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Revised: 05/23/2022] [Accepted: 06/15/2022] [Indexed: 11/16/2022]
Abstract
While the accelerating quest for precision medicine requires new individually targeting and selective drugs, and the ability to work with so-called undruggable targets, the realm of allosteric drugs meeting this need remains largely uncharted. Generalizing the observations on two major drug targets with widely observed inherent allostery, GPCRs and kinases, we describe and discuss basic allosteric modes of action that are universally applicable in all types of structures and functions. Using examples of Class A GPCRs and CMGC protein kinases, we show how Allosteric Signalling and Probing Fingerprints can be used to identify potential allosteric sites and reveal effector-leads that may serve as a starting point for the development of allosteric drugs targeting these regulatory sites. A set of distinct characteristics of allosteric ligands was established, which highlights the versatility of their design and make them advantageous before their orthosteric counterparts in personalized medicine. We argue that rational design of allosteric drugs should begin with the search for latent sites or design of non-natural binding sites followed by fragment-based design of allosteric ligands and by the mutual adjustment of the site-ligand pair in order to achieve required effects. On the basis of the perturbative nature and reversibility of allosteric communication, we propose a generic protocol for computational design of allosteric effectors, enabling also the allosteric tuning of biologics, in obtaining allosteric control over protein functions.
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Affiliation(s)
- Zhen Wah Tan
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671
| | - Wei-Ven Tee
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671
| | - Igor N Berezovsky
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671; Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, 117579, Singapore.
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Unveiling the reactivity of truxillic and truxinic acids (TXAs): deprotonation, anion…H–O, cation…O and cation…$${\varvec{\pi}}$$ interactions in TXA0…Y+ and TXA0…Z− complexes (Y = Li, Na, K; Z = F, Cl, Br). Struct Chem 2022. [DOI: 10.1007/s11224-022-01965-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Tastan Bishop Ö, Mutemi Musyoka T, Barozi V. Allostery and missense mutations as intermittently linked promising aspects of modern computational drug discovery. J Mol Biol 2022; 434:167610. [DOI: 10.1016/j.jmb.2022.167610] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2022] [Revised: 04/21/2022] [Accepted: 04/22/2022] [Indexed: 12/15/2022]
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Targeting the RBD of Omicron Variant (B.1.1.529) with Medicinal Phytocompounds to Abrogate the Binding of Spike Glycoprotein with the hACE2 Using Computational Molecular Search and Simulation Approach. BIOLOGY 2022; 11:biology11020258. [PMID: 35205124 PMCID: PMC8869371 DOI: 10.3390/biology11020258] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 01/29/2022] [Accepted: 01/31/2022] [Indexed: 01/23/2023]
Abstract
Simple Summary The current study based on virtual drugs screening and simulations identified novel drugs to target the RBD of the spike protein from Omicron variant of SARS-CoV-2. Using molecular modeling tools to search for a good binding drugs we identified SANC00944, SANC01032, SANC00992, and SANC00317 from South African natural compounds database as potential inhibitor of the Spike-ACE2 complex. In sum, this study will help in the design and discovery of novel drug therapeutics, which may be used against the emerging Omicron variant of SARS-CoV-2. Abstract The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus continues to inflict chaos globally. The emergence of a novel Omicron variant (B.1.1.529) in South Africa harbors 30 mutations in the spike protein. The variant is distinguished from other variants of concern (VOCs) with an increased (15) number of mutations in the receptor-binding domain (RBD) and suggests higher chances of causing reinfections. Initial reports also claimed that this variant escapes all the neutralizing antibodies, thus demanding a novel strategy against it. Thus, in this study, we performed a computational molecular screening against the RBD of the Omicron (B.1.1.529) variant and assessed the binding affinity of potent drugs against the RBD. The multi-steps screening of the South African Natural Compounds Database (SANCDB) revealed four medicinal compounds as excellent (potential) anti-viral agents against the Omicron variant, namely SANC00944, SANC01032, SANC00992, and SANC00317. The simulation analysis of these compounds in complex with the RBD demonstrated stable dynamics and structural compactness. Moreover, the residual flexibility analysis revealed that the flexibility of three loops required for interaction with hACE2 has been reduced by the binding of these drugs. The post-simulation validation of these compounds such as binding free energy, in silico bioactivity, and dissociation constant prediction validated the anti-viral potency of these compounds. The total binding free energy (TBFE) for the SANC01032–RBD complex was reported to be −46.54 kcal/mol; for the SANC01032–RBD complex, the TBFE was −41.88 kcal/mol; for the SANC00992–RBD complex the TBFE was −29.05 kcal/mol, while for the SANC00317–RBD complex the TBFE was −31.03 kcal/mol. The results showed the inhibition potential of these compounds by targeting the RBD. In conclusion, this study will help in the design and discovery of novel drug therapeutics, which may be used against the emerging Omicron variant of SARS-CoV-2.
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Albutti A. Rescuing the Host Immune System by Targeting the Immune Evasion Complex ORF8-IRF3 in SARS-CoV-2 Infection with Natural Products Using Molecular Modeling Approaches. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 19:112. [PMID: 35010372 PMCID: PMC8750414 DOI: 10.3390/ijerph19010112] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 12/20/2021] [Accepted: 12/20/2021] [Indexed: 12/31/2022]
Abstract
The perennial emergence of SARS-CoV-2 and its new variants causing upper respiratory complexities since December 2019 has aggravated the pandemic situation around the world. SARS-CoV-2 encodes several proteins among which ORF8 is a novel factor that is unique to SARS-CoV-2 only and is reported to help the virus in disease severity and immune evasion. ORF8-IRF3 complex induces endoplasmic reticulum stress, thus helps in the evasion of immune response. Consequently, targeting the ORF8-IRF3 complex is considered as a prime target for the discovery of novel drugs against SARS-CoV-2. In this regard, computational methods are of great interest to fast track the identification and development of novel drugs. Virtual screening of South African Natural Compounds Database (SANCDB), followed by docking and molecular dynamics (MD) simulation analysis, were performed to determine novel natural compounds. Computational molecular search and rescoring of the SANCDB database followed by induced-fit docking (IFD) protocol identified Quercetin 3-O-(6″-galloyl)-beta-D-galactopyranoside (SANC00850), Tribuloside (SANC01050), and Rutin (SANC00867) are the best scoring compounds. Structural-dynamic properties assessment revealed that these three compounds have stable dynamics, compactness, and a higher number of hydrogen bonds. For validation, we used MM/GBSA, in silico bioactivity estimation and dissociation constant (KD) approaches, which revealed that these compounds are the more potent inhibitors of the ORF8-IRF3 complex and would rescue the host immune system potentially. These compounds need further in vitro and in vivo validations to be used as therapeutics against SARS-CoV-2 to rescue the host immune system during COVID-19 infection.
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Affiliation(s)
- Aqel Albutti
- Department of Medical Biotechnology, College of Applied Medical Sciences, Qassim University, Buraydah 52571, Saudi Arabia
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Sheik Amamuddy O, Afriyie Boateng R, Barozi V, Wavinya Nyamai D, Tastan Bishop Ö. Novel dynamic residue network analysis approaches to study allosteric modulation: SARS-CoV-2 M pro and its evolutionary mutations as a case study. Comput Struct Biotechnol J 2021; 19:6431-6455. [PMID: 34849191 PMCID: PMC8613987 DOI: 10.1016/j.csbj.2021.11.016] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 11/09/2021] [Accepted: 11/13/2021] [Indexed: 01/15/2023] Open
Abstract
The rational search for allosteric modulators and the allosteric mechanisms of these modulators in the presence of mutations is a relatively unexplored field. Here, we established novel in silico approaches and applied them to SARS-CoV-2 main protease (Mpro) as a case study. First, we identified six potential allosteric modulators. Then, we focused on understanding the allosteric effects of these modulators on each of its protomers. We introduced a new combinatorial approach and dynamic residue network (DRN) analysis algorithms to examine patterns of change and conservation of critical nodes, according to five independent criteria of network centrality. We observed highly conserved network hubs for each averaged DRN metric on the basis of their existence in both protomers in the absence and presence of all ligands (persistent hubs). We also detected ligand specific signal changes. Using eigencentrality (EC) persistent hubs and ligand introduced hubs we identified a residue communication path connecting the allosteric binding site to the catalytic site. Finally, we examined the effects of the mutations on the behavior of the protein in the presence of selected potential allosteric modulators and investigated the ligand stability. One crucial outcome was to show that EC centrality hubs form an allosteric communication path between the allosteric ligand binding site to the active site going through the interface residues of domains I and II; and this path was either weakened or lost in the presence of some of the mutations. Overall, the results revealed crucial aspects that need to be considered in rational computational drug discovery.
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Affiliation(s)
| | | | - Victor Barozi
- Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Makhanda, South Africa
| | - Dorothy Wavinya Nyamai
- Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Makhanda, South Africa
| | - Özlem Tastan Bishop
- Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Makhanda, South Africa
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Ntie-Kang F, Telukunta KK, Fobofou SAT, Chukwudi Osamor V, Egieyeh SA, Valli M, Djoumbou-Feunang Y, Sorokina M, Stork C, Mathai N, Zierep P, Chávez-Hernández AL, Duran-Frigola M, Babiaka SB, Tematio Fouedjou R, Eni DB, Akame S, Arreyetta-Bawak AB, Ebob OT, Metuge JA, Bekono BD, Isa MA, Onuku R, Shadrack DM, Musyoka TM, Patil VM, van der Hooft JJJ, da Silva Bolzani V, Medina-Franco JL, Kirchmair J, Weber T, Tastan Bishop Ö, Medema MH, Wessjohann LA, Ludwig-Müller J. Computational Applications in Secondary Metabolite Discovery (CAiSMD): an online workshop. J Cheminform 2021; 13:64. [PMID: 34488889 PMCID: PMC8419829 DOI: 10.1186/s13321-021-00546-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 08/23/2021] [Indexed: 11/12/2022] Open
Abstract
We report the major conclusions of the online open-access workshop "Computational Applications in Secondary Metabolite Discovery (CAiSMD)" that took place from 08 to 10 March 2021. Invited speakers from academia and industry and about 200 registered participants from five continents (Africa, Asia, Europe, South America, and North America) took part in the workshop. The workshop highlighted the potential applications of computational methodologies in the search for secondary metabolites (SMs) or natural products (NPs) as potential drugs and drug leads. During 3 days, the participants of this online workshop received an overview of modern computer-based approaches for exploring NP discovery in the "omics" age. The invited experts gave keynote lectures, trained participants in hands-on sessions, and held round table discussions. This was followed by oral presentations with much interaction between the speakers and the audience. Selected applicants (early-career scientists) were offered the opportunity to give oral presentations (15 min) and present posters in the form of flash presentations (5 min) upon submission of an abstract. The final program available on the workshop website ( https://caismd.indiayouth.info/ ) comprised of 4 keynote lectures (KLs), 12 oral presentations (OPs), 2 round table discussions (RTDs), and 5 hands-on sessions (HSs). This meeting report also references internet resources for computational biology in the area of secondary metabolites that are of use outside of the workshop areas and will constitute a long-term valuable source for the community. The workshop concluded with an online survey form to be completed by speakers and participants for the goal of improving any subsequent editions.
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Affiliation(s)
- Fidele Ntie-Kang
- Department of Chemistry, University of Buea, P. O. Box 63, Buea, Cameroon
- Institute of Pharmacy, Martin-Luther University of Halle-Wittenberg, Kurt-Mothes-Str. 3, 06120 Halle, Germany
- Institute of Botany, Technische Universität Dresden, Zellescher Weg 20b, 01062 Dresden, Germany
| | - Kiran K. Telukunta
- Tarunavadaanenasaha Muktbharatonnayana Samstha Foundation, Hyderabad, India
| | - Serge A. T. Fobofou
- Institute of Pharmaceutical Biology, Technische Universität Braunschweig, Mendelssohnstrasse 1, 38106 Braunschweig, Germany
| | - Victor Chukwudi Osamor
- Department of Computer and Information Sciences, Colege of Science and Technology, Covenant University, Km. 10 Idiroko Rd, Ogun Ota, Nigeria
| | - Samuel A. Egieyeh
- School of Pharmacy, University of the Western Cape, Cape Town, 7535 South Africa
- South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Cape Town, 7535 South Africa
| | - Marilia Valli
- Nuclei of Bioassays, Biosynthesis and Ecophysiology of Natural Products (NuBBE), Department of Organic Chemistry, Institute of Chemistry, Sao Paulo State University–UNESP, Araraquara, Brazil
| | | | - Maria Sorokina
- Institute for Inorganic and Analytical Chemistry, Friedrich Schiller University, Jena, Germany
| | - Conrad Stork
- Center for Bioinformatics, Universität Hamburg, 20146 Hamburg, Germany
| | - Neann Mathai
- Department of Chemistry and Computational Biology Unit (CBU), University of Bergen, 5020 Bergen, Norway
| | - Paul Zierep
- Pharmaceutical Bioinformatics, Albert-Ludwigs-University, Freiburg, Germany
| | - Ana L. Chávez-Hernández
- DIFACQUIM Research Group, Department of Pharmacy, School of Chemistry, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Miquel Duran-Frigola
- Ersilia Open Source Initiative, Cambridge, UK
- Joint IRB-BSC-CRG Programme in Computational Biology, Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Catalonia Spain
| | - Smith B. Babiaka
- Department of Chemistry, University of Buea, P. O. Box 63, Buea, Cameroon
| | | | - Donatus B. Eni
- Department of Chemistry, University of Buea, P. O. Box 63, Buea, Cameroon
| | - Simeon Akame
- Department of Immunology, School of Health Sciences, Catholic University of Central Africa, BP 7871, Yaoundé, Cameroon
| | | | - Oyere T. Ebob
- Department of Chemistry, University of Buea, P. O. Box 63, Buea, Cameroon
| | - Jonathan A. Metuge
- Department of Biochemistry and Molecular Biology, University of Buea, P. O. Box 63, Buea, Cameroon
| | - Boris D. Bekono
- Department of Physics, Ecole Normale Supérieure, University of Yaoundé I, BP. 47, Yaoundé, Cameroon
| | - Mustafa A. Isa
- Bioinformatics and Computational Biology Lab, Department of Microbiology, Faculty of Sciences, University of Maiduguri, P.M.B. 1069, Maiduguri, Borno State Nigeria
| | - Raphael Onuku
- Department of Pharmaceutical and Medicinal Chemistry, Faculty of Pharmaceutical Sciences, University of Nigeria Nsukka, Nsukka, Nigeria
| | - Daniel M. Shadrack
- Department of Chemistry, St. John’s University of Tanzania, P. O. Box 47, Dodoma, Tanzania
| | - Thommas M. Musyoka
- Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Makhanda, 6140 South Africa
| | - Vaishali M. Patil
- Computer Aided Drug Design Lab, KIET Group of Institutions, Delhi-NCR, Ghaziabad, 201206 India
| | | | - Vanderlan da Silva Bolzani
- Nuclei of Bioassays, Biosynthesis and Ecophysiology of Natural Products (NuBBE), Department of Organic Chemistry, Institute of Chemistry, Sao Paulo State University–UNESP, Araraquara, Brazil
| | - José L. Medina-Franco
- DIFACQUIM Research Group, Department of Pharmacy, School of Chemistry, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Johannes Kirchmair
- Department of Pharmaceutical Sciences, Division of Pharmaceutical Chemistry, University of Vienna, 1090 Vienna, Austria
| | - Tilmann Weber
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby, Denmark
| | - Özlem Tastan Bishop
- Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Makhanda, 6140 South Africa
| | - Marnix H. Medema
- Bioinformatics Group, Wageningen University, Wageningen, The Netherlands
| | - Ludger A. Wessjohann
- Department of Bioorganic Chemistry, Leibniz Institute of Plant Biochemistry (IPB), Weinberg 3, 06120 Halle (Saale), Germany
- German Centre for Integrative Biodiversity Research (iDiv), Puschstraße 4, 04103 Leipzig, Germany
| | - Jutta Ludwig-Müller
- Institute of Botany, Technische Universität Dresden, Zellescher Weg 20b, 01062 Dresden, Germany
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