Ligand information, CID number, and reference of 47 drugs with potential activity against the SARS-CoV-2 viral cycle.
\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:{caption:"Highly Cited",originalUrl:"/media/original/117"}},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\n'}],latestNews:[{slug:"intechopen-supports-asapbio-s-new-initiative-publish-your-reviews-20220729",title:"IntechOpen Supports ASAPbio’s New Initiative Publish Your Reviews"},{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"}]},book:{item:{type:"book",id:"482",leadTitle:null,fullTitle:"Biomedical Engineering, Trends, Research and Technologies",title:"Biomedical Engineering",subtitle:"Trends, Research and Technologies",reviewType:"peer-reviewed",abstract:"This book is addressed to scientists and professionals working in the wide area of biomedical engineering, from biochemistry and pharmacy to medicine and clinical engineering. The panorama of problems presented in this volume may be of special interest for young scientists, looking for innovative technologies and new trends in biomedical engineering.",isbn:null,printIsbn:"978-953-307-514-3",pdfIsbn:"978-953-51-4535-6",doi:"10.5772/993",price:159,priceEur:175,priceUsd:205,slug:"biomedical-engineering-trends-research-and-technologies",numberOfPages:658,isOpenForSubmission:!1,isInWos:1,isInBkci:!0,hash:"8ec55bcda429a187bb7ddb2920d2ddc0",bookSignature:"Malgorzata Anna Komorowska and Sylwia Olsztynska-Janus",publishedDate:"January 8th 2011",coverURL:"https://cdn.intechopen.com/books/images_new/482.jpg",numberOfDownloads:85361,numberOfWosCitations:164,numberOfCrossrefCitations:46,numberOfCrossrefCitationsByBook:10,numberOfDimensionsCitations:143,numberOfDimensionsCitationsByBook:12,hasAltmetrics:0,numberOfTotalCitations:353,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"April 7th 2010",dateEndSecondStepPublish:"May 5th 2010",dateEndThirdStepPublish:"September 9th 2010",dateEndFourthStepPublish:"October 9th 2010",dateEndFifthStepPublish:"December 8th 2010",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7,8",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"58190",title:"Dr.",name:"Sylwia",middleName:null,surname:"Olsztynska",slug:"sylwia-olsztynska",fullName:"Sylwia Olsztynska",profilePictureURL:"https://mts.intechopen.com/storage/users/58190/images/3614_n.jpg",biography:"Sylwia Olsztyńska-Janus is currently an assistant professor in the Institute of Biomedical Engineering and Instrumentation at the Wrocław University of Technology, Wrocław, Poland. Her main research interests are focused on the processes occurring in tissues under near infrared radiation and their monitoring using several spectroscopic methods. These processes, occurring at the molecular level, have great importance in medical diagnosis and therapy. She received a Ph.D. and Eng. in Physics from Wrocław University of Technology (2004; Małgorzata Komorowska, advisor). Her professional internships held mainly in Laboratoire de Spectrochiemie Infrarouge et Raman (LASIR), Institute of Chemistry, USTL, Lille, France (1999-2000), and in the Commissariat à l’énergie atomique (CEA), Grenoble, France (2006). Dr. Olsztyńska-Janus was a recipient of a grant at the Summer School in the International University Bremen, Germany (2006), a scholarship in the CEA, Grenoble, France (2006) and a DAAD scholarship, Germany (1997).",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"1",institution:null}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"15311",title:"Prof.",name:"Małgorzata",middleName:null,surname:"Komorowska",slug:"malgorzata-komorowska",fullName:"Małgorzata Komorowska",profilePictureURL:"https://mts.intechopen.com/storage/users/15311/images/system/15311.jpg",biography:"Małgorzata Anna Komorowska was born in Kraków-Poland and educated at the Jagiellonian University. She received a Ph.D. in Chemistry in Academy of Mining and Metalurgy, Kraków. Since that time she has been working at Wrocław University of Technology, where she is currently professor of chemistry at the Institute of Biomedical Engineering and Instrumentation. Since 1973, her research interests have concentrated on application of different spectroscopic techniques to study of biological and model membranes. She has authored numerous papers on application of EPR spectroscopy, spin labeling of membranes , for monitoring their structure and effects of different factors on them. Currently she has worked on the method of blood protection during extracorporeal circulation and on molecular mechanism of action of the Near Infrared Radiation on biological materials: blood cells, proteins, amino acids and DNA. She was visiting scientist at the university of Kentucky, Free University of Berlin and Technical University of Lille. 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This condition also needs to be carefully managed to prevent more complications [1]. One of the major complications is acute peripancreatic fluid collections (APPFC) and pseudocyst development [2, 3]. The clinical decision for pancreatic pseudocyst or necrotic infected cyst drainage procedure is very important with regard to the patient’s clinical condition and imaging evaluation. There are several well-known routes of drainage procedure of choice such as percutaneous, endoscopic, or surgical drainage [4].
\nRecently, development of therapeutic endoscopic ultrasound (EUS) procedure has become more popular in most of the highly experienced centers as a first-line management in pancreatic fluid collection drainage [5, 6, 7] (Figure 1). However, it would need a good comprehensive team work and facilities to perform this kind of procedure.
\nPatient with infected pancreatic pseudocyst and acute pancreatitis [
Acute pancreatitis is an acute clinical condition due to sudden inflammation of the pancreas, and it is mostly caused by gallstone disease or alcohol consumption. The other risks of acute pancreatitis are endoscopic retrograde cholangiopancreatography (ERCP) procedure, some medications, trauma of the abdomen, autoimmune disease, hypertriglyceridemia, hereditary factors, abnormalities of the pancreas anatomy, infection, surgical procedure, and pancreatic tumor. Acute pancreatitis consists of two phases of disease: (1) within 1 week, where the systemic inflammation plays an important role and it can be accompanied by organ failure; and (2) more than 1 week, where local complications happened, such as acute peripancreatic fluid collections (APPFC), acute necrotic fluid collection (ANC), pancreatic pseudocyst (PPC), and walled-off necrosis (WON), either can be sterile or infected. This has been classified based on the revised Atlanta criteria. This criteria has been mainly based on time after the onset (whether it is ≤4 weeks or >4 weeks from the onset of pain) and whether there is a necrosis condition through the imaging examination [7, 8]. Acute pancreatitis can be easily diagnosed based on three classic parameters, which are abdominal pain, serum amylase, and/or lipase more than three times upper limit normal, and abdominal imaging study. Abdominal ultrasound should be routinely performed in acute pancreatitis patients as gallstone disease is still the most common etiology. This issue is important to consider early cholecystectomy to prevent more complications in the pancreas [9].
\nOn the other hand, the development of PFC can also be subdivided into early complication (APPFC and ANC) and delayed complication (PPC and WON). APPFC, which contains sterile pancreatic juice, is usually developed within 48 h in almost 50% acute pancreatitis patients, where this condition might be resolved within 2–4 weeks. In the imaging study, homogeneous fluid attenuation conforms to the retroperitoneal structures without any wall which is the hallmark. Meanwhile, ANC can be located pancreatic, peripancreatic, or mixed. It is usually arising from the necrotic pancreas tissue or glandular and mostly it is connected to the pancreatic duct. Imaging study showed inhomogeneous without any liquefied components and wall. If the fluid collection persists, then usually it can further lead to the development of PPC. PPC is a pancreatic juice collection surrounded by the wall. The location of pseudocyst development usually is at the lesser sac. The cyst wall is formed from the fibrous or granulomatous tissue. Based on imaging studies, it is an oval-round cystic lesion with a thin-walled even though sometimes the wall can be thicker. More than 50% of PPC are usually either resolved or drained spontaneously into the stomach. The larger size of PPC can cause symptoms such as abdominal pain or rupture into the peritoneal cavity. Other related complications are secondary infection, internal bleeding, and bile duct or duodenal obstruction. WON is the transformation of pseudocyst and ANC; it is a thick cavity wall containing semi-liquid collection and necrotic debris. Based on the imaging study, there is an inhomogeneous nonliquefied component encapsulated with wall. Imaging studies are very important to differentiate each of PFC types, as it will have different management and prognosis [10, 11].
\nTraditionally, percutaneous and surgical approaches are the old standard methods for PFC (PPC and WON) drainage, where the percutaneous approach can be performed easily for PPC drainage with transabdominal ultrasound-guided or computed tomography (CT) guide. Meanwhile, the surgical approach is the usually preferred method, especially for ANC or WON. It is an open approach and consists of cystogastrostomy, cystoduodenostomy, and cystojejunostomy. Laparoscopic method for PFC drainage was also increasingly reported afterward. However, looking at the high complication rate of surgery approach and possible ineffective drainage result with high recurrence rate in percutaneous approach, recently, endoscopic method has become a new alternative route and the most preference method nowadays [12].
\nThe first report was published by Sahel et al. in 19 patients with chronic pancreatitis [13]. The complications occurred in four patients (bleeding in two patients, and two perforations). Another pioneer study by Cremer et al. also showed high success rate for endoscopic cystoduodenostomy (ECD) and 100% for endoscopic cystogastrostomy (ECG) [14]. However, both studies were performed in small sample size. Study by Weckman et al. in larger study subjects within 6 years period showed 86.1% success rate for endoscopic management in PPC patients with around 13.9% needing surgical intervention due to unsuccessful therapeutic endoscopy [15].
\nMore studies have been conducted regarding endoscopic transpapillary stenting for pancreatic duct (PD) leak or disruption causing PPC or fistula, and also endoscopic management in WON. First, study by Catalano et al. performing endoscopic cystenterostomy in 8 of 21 PPC patients with duct strictures was successful in all cases [16]. In the recent study of transpapillary management route by Brennan et al., where it only included 30 patients with the indications of PD stenting were PPC, pancreatic ascites, pancreatic duct leak, and fistula, the follow-up success rate after PD stenting for pancreatic duct rupture was 88%, while for pseudocyst, it was 63% [17]. In the WON study, endoscopic treatment was performed in 101 patients. The therapeutic success rate was 98.02%; whereas, long-term follow-up success rate was 96.04% in patients with symptomatic WON [18].
\nThe clinical decision when to intervene the PFC is usually based on comprehensive clinical and imaging evaluation. Gastric outlet obstruction or biliary obstruction needs to be managed as soon as possible (Figure 2). It can be recognized early through the clinical symptoms such as abdominal pain, vomiting, weight loss, early satiety, or even jaundice. Infected PPC is one of the absolute indications for drainage procedure (Figure 3). Imaging evaluation as well as the fluoroscopy-guided or transabdominal-guided endoscopic management is considered as an important thing, especially in non-bulging PPC [19].
\nPatient with pancreatic pseudocyst and gastric outlet obstruction [
Patient with infected pancreatic pseudocyst and biliary obstruction (Courtesy: Dr. Cosmas Rinaldi A. Lesmana).
Nowadays, endoscopic ultrasound (EUS) has replaced the traditional way to do the drainage procedure. Through EUS examination, it is easy to evaluate non-bulging PFC as well as other factors, such as the puncture site with large vessels avoidance, accurate fluid aspiration with the wall evaluation, and pancreatic duct connection. Defining the characteristics of each PFC type can also be easily done through EUS examination as the location and the size of the PFC, including the solid material, the wall, and the border, can be scored. It can also evaluate the bile duct under direct visualization [20].
\nThe indication for endoscopic management is usually based on the patient’s symptoms, the resolution or severity of infections, and the size of the cyst. Another consideration involves the cyst wall maturity. Usually, the right time to perform endoscopic intervention is after 4 weeks as it allowed better encapsulation. Recent systematic review, comparing percutaneous, surgical, and endoscopic methods in managing PPC, shows that endoscopic management using EUS reduced the length of hospital admission time, cost, and improved patient’s quality of life [21, 22].
\nThere are two options of endoscopic drainage method, which are transmural, transpapillary, or even combining these two techniques. In the pseudocyst case, endoscopic ultrasound (EUS) has been widely used for transmural drainage with previous evaluation where direct visualization of cystic lesions through the gastrointestinal (GI) lumen can be easily performed. It has become the most important tool in the management for pancreatic cyst, especially to differentiate benign from malignant condition. However, other than anatomic factor, the presence of ductal communication is also an important factor to decide which route is better to perform. In the WON case, the principle is the same; however, the fluid collection resolution after 72 h is the main consideration for more aggressive endoscopic intervention, which is known as EUS-guided transmural necrosectomy procedure. The drainage procedure can be done either with transpapillary or transmural approach. The needle puncture is performed using 19-G FNA needle. After the tip of the needle entering the cyst cavity, the needle sheath can be left inside by pulling out the needle and the guide wire was inserted through the needle sheath until it is coiled up. Then, the sheath was pulled out with maintaining the wire inside the cyst cavity. The dilatation process will further be performed either with dilator or 5 or 6-fr cystotome to make a larger fistula. Finally, the stent is inserted through the fistula track (plastic or metallic stent) [23, 24, 25, 26].
\nThere are two types of stents that are usually used in the management of PPC: metal stent and double pigtail plastic stent. There have been some concerns about using the plastic stents, which are possible for re-intervention due to ineffective drainage, longer procedure time regarding the need of two plastic stents placement, or even the risk of leakage. However, some studies have shown that plastic stent success rate for PPC drainage ranges from 84 to 94%, but the success rate was found to be lower in few studies when managing WON cases [27, 28, 29]. One of the studies by Bang et al. showed that there was no difference for the treatment success between 7 and 10 Fr plastic stents, and even only one plastic stent placement when compared to more than one plastic stents. Another consideration need to be put in clinical practice is the cost, where it would be cheaper to use the plastic stent [30]. Recent meta-analysis study showed that there was a higher clinical success rate (OR 3.39, 95% CI 1.35–21.19) and lower adverse events (OR 0.37, 95% CI 0.21–0.66) in the metal stent studies. The concern is regarding adverse events, such as bleeding, perforation, and stent migration. Fully covered metallic stent (FCMS) might be considered better in bleeding prevention due to the tamponade direct effect from the stent. In the subgroup analysis, even though the success rate in the metal stent group was 98.3%, however, the success rate in the plastic stent group also more than 90%. The success rate in the plastic group was below than 90% only in the WON group, where the metal stent group has still more than 90% success rate [31]. Another development in the stent evolution, lumen apposing metal stent (LAMS) development where this stent is used not only for endoscopic drainage procedure, but also for endoscopic necrosectomy procedure. This stent has also advantage in migration prevention when compared to FCMS [32, 33, 34, 35].
\nUntil now, there are still debates and conflicting data with regard to the use of type of the stents. However, even though technically there is no significant difference between placing metal stent versus plastic stent, every type of case need to be decided individually as the cost issue, stent availability, PFC type, and possible complications are still important things for clinical consideration.
\nAcute pancreatitis with pancreatic fluid collection (PFC) is a challenging condition in the field of gastroenterology as it would need good comprehensive clinical assessment and good timing to decide when to intervene. Transmural approach through endoscopic procedure has replaced percutaneous or surgical approach to manage pancreatic pseudocyst. The use of metal stent seemed to be superior than the plastic stent for PFC drainage, however, it would be depending on the cost, availability, and the type of PFC.
\nThe coronavirus disease-2019 (COVID-19) is the third documented viral outbreak caused by a member of the
The initial stage of the infection cycle starts with the recognition and anchoring of the SARS-CoV-2 spike protein complex into the host angiotensin-converting enzyme 2 (ACE2) through the receptor-binding domain (RBD) located at each one of the 3S proteins [13]. Then, the activation of the spike occurs at the surface or endosome level by transmembrane serine protease 2 (TMPRSS2) or cathepsin B/L proteases, respectively, to allow viral entry [14]. Once the virus membrane merges with the cell membrane, the genomic material enters the cell. The cell’s ribosomes then translate the viral RNA into pp1a/ab polyproteins, which will be later processed by cleavage through the enzymatic activity of the main protease (Mpro) and the papain-like protease (PLpro) [15]. This process will release 16 non-structural proteins (NSPs), including the RNA-dependent RNA polymerase (NSP12) and co-factors NSP7, and NSP8 of the RNA-replication machinery (Rdrp). After replication, expression of the structural proteins occurs, the genomic material is packaged, and the virion is assembled on a lipid membrane and matured for subsequent exocytosis. In addition, evidence suggests that the SARS-CoV-2 proteases and some of their cleavage products, besides their critical function for the proper infection process, interplay with the host’s innate immune response through different mechanisms [16]. In particular, PLpro-ISG15 interaction allows the virus to evade the innate immune response through deubiquitination and deISGylation activities of the protease [17, 18]. Interestingly, the process occurs at the same binding cavity as the PLpro known inhibitor, GRL0617 [19].
The code for the cavity-detection guided blind docking (CB-Dock) [20] stand-alone version is freely available at Yang Cao’s Lab webpage [http://clab.labshare.cn/cb-dock/php/manual.php#download].
The customized high-throughput virtual screening pipeline we developed can be accessed at GitHub [https://github.com/tripplab/HTVS].
We conducted an extensive scientific literature search for drugs reported as potentially able to prevent SARS-CoV-2 infection. The search included
We performed the molecular
ID | Drug | CIDa | References |
---|---|---|---|
RPA01 | Losartan | 3961 | [30, 31] |
RPA02 | Telmisartan | 65,999 | [30, 32] |
RPA03 | Arbidol | 131,411 | [33, 34] |
RPA04 | Camostat mesylate | 5,284,360 | [33, 35] |
RPA05 | Rimantadine | 5071 | [36] |
RPA06 | Chloroquine | 2719 | [33, 37] |
RPA07 | Hydroxychloroquine | 3652 | [33, 37] |
RPA08 | Baricitinib | 44,205,240 | [38, 39] |
RPA09 | Colchicine | 6167 | [40, 41] |
RPA10 | Disulfiram | 3117 | [42, 43] |
RPA11 | Ebselen | 3194 | [42, 43, 44] |
RPA12 | Hesperidin | 10,621 | [45, 46] |
RPA13 | Qingdainone | 3,035,728 | [47] |
RPA14 | Nafamostat | 4413 | [48, 49] |
RPA15 | Dipeptidyl nitrile-derivative | Compound 10 | [50] |
RPB01 | Lopinavir | 92,727 | [33, 51] |
RPB02 | Ritonavir | 392,622 | [33, 51] |
RPB03 | Darunavir | 213,039 | [36, 52] |
RPB04 | Cobicistat | 25,151,504 | [52] |
RPB05 | Isatin-derivative | Compound 26 | [53] |
RPB06 | Rupinatrivir | 6,440,352 | [54, 55] |
RPB07 | E-64 | 123,985 | [56] |
RPB08 | N3 inhibitor | 405,067,310 | [57] |
RPC01 | Ribavirin | 37,542 | [58, 59] |
RPC02 | Sofosbuvir | 45,375,808 | [58, 59] |
RPC03 | Molnupiravir | 145,996,610 | [58, 59] |
RPC04 | Nilotinib | 644,241 | [60, 61, 62] |
RPC05 | Saquinavir | 441,243 | [36, 58, 59, 62] |
RPC06 | Tipranavir | 54,682,461 | [58, 59, 62] |
RPC07 | Lonafarnib | 148,195 | [62] |
RPC08 | Tegobuvir | 23,649,154 | [58, 59, 62] |
RPC09 | Simeprevir | 24,873,435 | [58, 59] |
RPC10 | Filibuvir | 54,708,673 | [58, 59, 62] |
RPC11 | Cepharanthine | 10,206 | [62] |
RPC12 | Redemsivir | 121,304,016 | [33, 58, 59] |
RPC13 | Favipiravir | 492,405 | [33, 58, 59] |
RPD01 | rac5c | 76,853,649 | [18] |
EXT01 | Ascorbic Acid | 54,670,067 | [63] |
EXT02 | Ergocalciferol | 5,280,793 | [64, 65] |
EXT03 | Cholecalciferol | 5,280,795 | [64, 65] |
EXT04 | Ivermectin | 6,321,424 | [66] |
EXT05 | Azithromycin | 447,043 | [67] |
EXT06 | Heparin | 772 | [68] |
EXT07 | Methylprednisolone | 6741 | [69] |
EXT08 | Carvacrol | 10,364 | [70] |
EXT09 | Ursolic acid | 45,358,157 | [71] |
EXT10 | Oleanolic acid | 485,707 | [71] |
Ligand information, CID number, and reference of 47 drugs with potential activity against the SARS-CoV-2 viral cycle.
In the absence of the CID, the reference to the original investigation and the compound number are provided.
We included viral and cellular targets involved in the SARS-CoV-2 infection cycle, covering the entry, polyprotein processing, and replication. The targets’ three-dimensional structures were obtained from the Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB) in PDB format [23]. The complete structure of the spike homotrimer complex (PDB: 6VXX-1-1-1) was retrieved from the CHARMM-GUI Archive-COVID-19 proteins library [24]. We took special consideration to the spike complex given its large size and quaternary structure. We focused on four independent spike-based structures to extend the cavity sampling: the full-length spike’s homotrimer complex, the homotrimer head (S1), 1 S protein monomer, and one isolated receptor-binding domain (RBD).
Water, ions, glycosylations, and co-crystallized ligands were removed from all targets. Charges and hydrogens were fixed at neutral pH using chimera 1.15, their structure optimized, and the final configuration saved in PDB format [21]. In total, 16 structures of 10 targets were curated, as summarized in Table 2.
ID | Target | PDB IDa | SARS-CoV-2 infection step | References |
---|---|---|---|---|
H00 | ACE2 | 1R4L_A | Viral recognition | [72] |
H01 | ACE2 (B0AT1 closed complex) | 6M18_B | Viral recognition | [73] |
H02 | ACE2 (B0AT1 open complex) | 6M1D_B | Viral recognition | [73] |
H03 | TMPRSS2 | 7MEQ_A | Viral priming | [74] |
H04 | Cathepsin B | 3AI8_B | Viral priming | [75] |
H05 | Cathepsin L | 2NQD_B | Viral priming | [76] |
V01 | Spike homotrimer | 6VXX1-1-1 | Viral recognition | [77, 78] |
V01H | Spike homotrimer head | 6VXX1-1-1 | Viral recognition | [77, 78] |
V02 | S protein | 6VXX1-1-1 | Viral recognition | [77, 78] |
V02R | S protein’s RBD | 6VXX1-1-1 | Viral recognition | [77, 78] |
V03 | Mpro | 6LU7_A | Polyprotein processing | [79] |
V08 | PLpro | 7JRN_A | Polyprotein processing | [19] |
V04 | NSP12 | 7AAP_A | RNA replication | [80] |
V05 | NSP7 | 6M71_C | RNA replication | [81] |
V06 | NSP8 | 6NUR_B | RNA replication | [82] |
V07 | Rdrp-complex (NSP12-NSP7-NSP8) | 6M71_ABC | RNA replication | [81] |
Structural information and PDB entries of viral (V) and host (H) targets included.
Underscore denotes the chain selected from PDB coordinates files.
Molecular docking is a computational method that allows to sample the conformational space and rank the ligand poses through an energy scoring function. It attempts to generate an optimized target-ligand complex conformation with the lowest binding free-energy change estimate, predicting the interaction of the two molecules in the energy minimum. This task is a cyclic process performed by systematic or stochastic search methods. However, the latter is the choice of preference since it increases the probability of finding an energetic global minimum conformation because the search initiates from different random points [27]. For this reason, the results of two or more molecular docking cycles are not necessarily the same due to the random nature of the conformational search method. Therefore, performing as many cycles as necessary to get as close as possible to the energetic global minimum conformation is essential.
Easy customization of this parameter in the developed high-throughput virtual screening code offers the user the possibility of an exhaustive sampling of the conformational space that maximizes the accuracy of target-ligand complex prediction.
We have developed in-house bash scripts that integrate the CB-Dock’s cavity-guided blind molecular docking method, which automatically identifies binding sites by calculating putative cavities through a curvature-based detection approach. Molecular docking analysis is conducted in these putative cavities to sample and rank ligand poses and estimate the best target-ligand complex binding energy scores per cycle.
The pipeline has three phases comprised of nested loops, schematized in Figure 1 as a flowchart. First, each target
Flowchart of the customized high-throughput virtual screening pipeline implemented in this work. Four phases are involved, i) target and ligand molecular modeling (blue), ii) target cavity detection (green), iii) docking box optimization (orange), and iv) target-ligand docking (red).
In our study, we found that the optimal number of independent rounds is
The method we used for automatizing the virtual high-throughput screening process is blind; that is, it does not require any information on the binding site. Hence, we validated its predictions by reproducing the enzymatic targets’ experimental binding complexes. We gathered a set of ligands with available complex co-crystallized data. Eight known enzymatic inhibitors were modeled, optimized, and evaluated under the same methodology conditions as the rest of the ligands included in this study. The ligands in the control set are listed in Table 3.
Target ID | Target name | Ligand | PDB ID | Reference |
---|---|---|---|---|
1. Co-crystallized reproducibility | ||||
INH01 | ACE2 | MLN-4760 | 1R4L | [72] |
INH02 | TMPRSS2 | 4-Guanidinobenzoic acid | 7MEQ | [74] |
INH03 | Cathepsin B | Nitroxoline | 3AI8 | [75] |
INH04 | Cathepsin L | 4-Bipheylacetyl-cys-(D)-ARG-TYR -N-(2-Phenylethyl) Amide | 2NQD | [76] |
INV01 | Mpro | Narlaprevir | 7JYC | [19] |
INV02 | NSP12 | Remdesivir | 7BV2 | [84] |
INV03 | NSP12 | Favipiravir | 7AAP | [80] |
INV04 | PLpro | GRL0617 | 7JRN | [19] |
2. Negative controla | ||||
INV05 | Spike | Amantadine | NA | [83] |
Modeled ligands to validate that the method is capable of reproducing the co-crystallized complex conformations and previous
Does not prevent ACE2-Spike interaction despite inhibiting
Furthermore, at this time, a small drug-like co-crystallized molecule in complex with the spike homotrimer does not yet exist. We included amantadine (INV05) in our set as a negative control since it inhibits the SARS-CoV-2 infection but does not prevent spike-ACE2 interaction [83].
We inspected the top 10 size-ranked putative cavity sites screened for each target. We selected those that either had the active site (targets ACE2, TMPRSS2, cathepsin B/L, Mpro, and NSP12), or were inside a quaternary interface (targets spike, PLpro, and Rdrp). We selected the
We found that the
Target-ligand complex superimposition of native co-crystallized inhibitors (yellow) and the best-predicted ligand conformation after
After doing all the blind docking calculations with an extended conformation sampling, we analyzed the most negative energy scores. We performed a Z-score transformation of the data for each independent column in the matrix (targets
Target (columns) and ligand (rows) complex docking results. Heatmap of binding free-energy change estimates, using a color-based code according to the Z-score value through column analysis. Targets are grouped as host proteins (blue) and virus proteins (pink). Ligands are grouped by control set (green), potential repurposing drugs (orange), and others (brown). IDs correspond to those defined in
Since each column gathers the results for a different target, it is thus possible to identify which ligands had the best scores for each target (in green). It is worth noting that cathepsin L (H05) and PLpro (V08) co-crystallized inhibitors give a good binding free-energy estimate. Most of the co-crystallized inhibitors remained near the mean (in black, with respect to the experimental drug set), except for amantadine (INV05), which presents a positive Z-score value for the spike’s RBD (in red). The latter is concomitant to previous works, where amantadine fails to prevent the spike-ACE2 quaternary interaction [83].
Out of the 47 drugs screened, nine showed potential inhibition against viral or host targets of the SARS-CoV-2 infection cycle. Saquinavir, simeprevir, nilotinib, an isatin-derivative, telmisartan, tegobuvir, qingdainone, rac5c, and nafamostat achieved the selection criteria. Interestingly, all but rac5c and nafamostat showed the best scores against more than one target. The schematic representation of these results is summarized in Table 4.
ID | Drug | Target | VINA score | Z-scorea |
---|---|---|---|---|
RPC05 | Saquinavir | ACE2 (H00) | −12.9 | −1.70 |
RPB05 | Isatin-derivative | ACE2 (H01) | −10.7 | −2.06 |
RPC04 | Nilotinib | −10.2 | −1.72 | |
RPD01 | rac5c | −9.9 | −1.51 | |
RPC04 | Nilotinib | ACE2 (H02) | −10.7 | −1.85 |
RPC09 | Simeprevir | −10.4 | −1.62 | |
RPC04 | Nilotinib | TMPRSS2 (H03) | −8.9 | −1.58 |
RPC05 | Saquinavir | −8.8 | −1.49 | |
RPC04 | Nilotinib | Cathepsin B (H04) | −9.6 | −1.64 |
RPC09 | Simeprevir | −10.3 | −2.20 | |
RPA02 | Telmisartan | Spike (V02) | −9.4 | −1.63 |
RPB05 | Isatin-derivative | Spike (V01H) | −10.9 | −1.67 |
RPA13 | Qingdainone | Mpro (V03) | −9.4 | −1.56 |
RPC04 | Nilotinib | −9.7 | −1.80 | |
RPC09 | Simeprevir | NSP12 (V04) | −9.1 | −1.60 |
RPA13 | Qingdainone | NSP7 (V05) | −7.4 | −1.69 |
RPC08 | Tegobuvir | −7.3 | −1.59 | |
RPC09 | Simeprevir | −7.6 | −1.89 | |
RPA02 | Telmisartan | NSP8 (V06) | −8.8 | −1.65 |
RPC04 | Nilotinib | −8.9 | −1.73 | |
RPC05 | Saquinavir | −9 | −1.80 | |
RPC09 | Simeprevir | Rdrp (V07) | −10 | −1.96 |
RPA13 | Qingdainone | PLpro (V08) | −9.9 | −1.72 |
RPA14 | Nafamostat | −10.1 | −1.88 | |
RPC04 | Nilotinib | −9.8 | −1.65 | |
RPC08 | Tegobuvir | −9.8 | −1.65 |
Potential drugs for repurposing with the most negative free-energy change score found and their corresponding Z-score value grouped by the target.
Z-scores were calculated by the target.
Also, we inspected the results by ligand, performing a Z-score analysis by row (ligands). Since the rows gather data from the
Target (columns) and ligand (rows) complex docking results. Heatmap of binding free-energy change estimates, using a color-based code according to the Z-score value through row analysis. Targets are grouped as host proteins (blue) and virus proteins (pink). Ligands are grouped by control set (green), potential repurposing drugs (orange), and others (brown). IDs correspond to those defined in
The ligands such as arbidol, colchicine, qingdainone, nafamostat, and carvacrol exhibit a binding preference to PLpro (V08). It is important to highlight the essential function of the protease PLpro for processing the viral proteome and evading the host’s innate immune system. In the latter case, PLpro cleaves off post-translational modifications, such as ubiquitin and ubiquitin-like proteins from cell proteins, disrupting the inflammatory signaling pathway necessary for an appropriate immune response [17, 100]. Noteworthy, the potential PLpro inhibitors we have identified in the present work as repurposed drugs form a
Saquinavir is a peptide-mimetic HIV inhibitor. However, some reports suggest potential inhibitory activity against SARS-CoV-2 proteases [85, 86, 87] and other targets involved in the viral infection, such as the Rdrp replication complex [62, 88] and the spike-ACE2 PPI [89]. In our study, saquinavir showed the best energy scores against TMPRSS2, ACE2, and the NSP8-NSP12 interface of the Rdrp complex, as shown in Figure 5. The transmembrane serine protease 2 (TMPRRS2) is essential in several viral infections. Previous reports have shown that the inhibition of this target significantly reduces SARS-CoV-2 entry in lung cells at nM concentrations and therefore the viral infection [90]. Saquinavir also presented the best energy scores against the ACE2 active site, a critical host target needed to initiate entry through the formation of the spike-ACE2 quaternary complex. In this scenario, conformational changes upon ligand binding into the catalytic cavity may shift the relative positions of the receptor’s interface residues that bind to the spike protein and prevent the anchoring of the spike on host cells [91]. However, because saquinavir targets the catalytic site of ACE2, the main activity of this enzyme in the renin-angiotensin system requires further investigation of its biological effect as a competitive inhibitor [92]. In addition, our results show that this drug targets the Rdrp replication complex, which is consistent with the previous results reported in the literature [62, 93]. Interestingly, saquinavir appears to target two essential steps, compromising the entry and viral replication of the SARS-CoV-2.
Target-ligand complex conformations of potential drugs for repurposing. Molecular docking against viral and host targets relevant in the SARS-CoV-2 infection cycle. A. Superposition of ACE2 target (H00, H01, and H02) docked with saquinavir (cyan), isatin-derivative (red), nilotinib (pink), rac5c (brown), and simeprevir (yellow). B. TMPRSS2 docked with saquinavir (cyan) and nilotinib (pink). C. Spike docked with telmisartan (purple) and isatin-derivative (red). D. Cathepsin B docked with nilotinib and simeprevir (yellow). E. Mpro docked with nilotinib (pink) and qingdainone (orange). F. PLpro docked with nafamostat (green), nilotinib (pink), qingdainone (orange), and tegobuvir (dark orange). G. Superposition of NSP12 and NSP7 and NSP8 cofactors docked with simeprevir (yellow), tegobuvir (dark orange), nilotinib (pink), telmisartan (purple), qingdainone (orange), and saquinavir (cyan), created with the visual molecular dynamics (VMD) [
On the other hand, simeprevir also showed the best energy scores on targets relevant to viral entry and replication, including the active cavities of ACE2, cathepsin B, NSP12, and the Rdrp complex interface. We show a molecular visualization of these results in panels A, C, and G of Figure 5. This drug is a protease inhibitor that has presented potent
Nilotinib is used to treat chronic myelogenous leukemia as a Bcr-Abl tyrosine kinase antagonist. Our results suggest the potential inhibition of six targets involved in the SARS-CoV-2 infection process, including the catalytic cavities of enzyme targets ACE2, TMPRSS2, cathepsin B, Mpro, and the PLpro-ISG15 and Rdrp’s NSP8-NSP12 interfaces. We show a molecular visualization of these results in Figure 5. Reports suggest that nilotinib can inhibit the SARS-CoV and SARS-CoV-2 infection processes, but not MERS-CoV. Interestingly, the latter does not use ACE2 as a cell receptor [97, 98]. This observation is particularly interesting since other reports suggest that nilotinib can destabilize the SARS-CoV-2 spike-ACE2 complex [63]. According to our results, nilotinib might prevent the spike priming and activation since it showed the best energy scores against TMPRSS2 and cathepsin B at the active site cavities. These findings represent a potential inhibition of two independent priming pathways. Moreover, nilotinib potentially inhibits the Mpro and Rdrp complex and is consistent with previous
Interestingly, nilotinib also had the best energy scores against PLpro. In addition to PLpro’s essential protease activity in the processing of pp1a polyprotein, it is also implicated in host immune innate response evasion mechanisms as described in Section 4.4. The inhibition of PLpro decreases the exacerbated immune response, as described by other members of the Bcr-Abl inhibitors family, for example, ponatinib, which protects against cytokine storm in mouse models [101, 102].
Isatin-derivatives have shown potential antiviral properties, some of them with promising results against HCV, SARS-CoV [103, 104], and SARS-CoV-2 [53]. In particular, the compound 1-(naphthalen-2-ylmethyl)-2,3-dioxoindoline-5-carboxamide inhibits Mpro from SARS-CoV-2. Therefore, we decided to evaluate it against our whole set of targets. It presented the best score against the ACE2 active site, which might disrupt the spike-ACE2 interaction as discussed previously (see Section 5.1). Moreover, it also showed the best energy scores against the spike protein, precisely in the quaternary interface region of the homotrimer complex, and thus a plausible termination of the viral cycle at an early stage in the replication process.
Telmisartan is an anti-antihypertensive. There is evidence of a morbidity and mortality reduction in hospitalized patients infected with SARS-CoV-2 treated with this drug [105]. Telmisartan showed the best energy scores against a spike’s cavity in the homotrimer quaternary interface. Therefore, the isatin-derivative could inhibit two targets involved in the viral entry (spike and ACE2), while telmisartan might prevent the spike homotrimer formation and the Rdrp complex. We show the molecular visualization of these results in panels A, C, and G of Figure 5.
Tegobuvir is a non-nucleoside inhibitor of the NS5B polymerase of HCV. Our results suggest that this drug may prevent the formation of the Rdrp quaternary complex. Previously,
In addition, qingdainone also showed the potential inhibitory activity on Mpro active site, suggesting that this drug might completely disrupt the polyprotein processing stage by targeting both proteases, Mpro and PLpro. We show a molecular visualization of these results in Figure 5.
We included nafamostat and rac5c in our ligand sets due to evidence suggesting their inhibitory capacity against TMPRSS2 [108] and PLpro [18], respectively. Neither ligand achieved the selection criteria for their expected targets despite being on the borderline with scores of −8.3 and − 9.3 kcal/mol, which indicates the selection criteria’s exhaustiveness. However, nafamostat does achieve the best scores against PLpro’s USP domain, while rac5c presented the best score on the ACE2 active site. We show these results in panels A and F of Figure 5.
We have theoretically identified nine drugs or compounds for potential drug repurposing against SARS-CoV-2 through a cavity-based blind molecular docking protocol (Figure 6). Interestingly, seven of them present potential inhibitory activity on multiple targets at different stages of the viral infection cycle, including innate immune evasion. We have implemented an in-house high-throughput virtual screening pipeline that successfully reproduces experimental data and findings from previous works. After the target’s cavity detection and ranking by surface area, we used the pipeline to perform the numerous independent blind molecular docking rounds to achieve a sufficiently extensive conformational target-ligand complex search.
Repurposing drugs (left) with corresponding potential inhibitory activity on multiple viral or host targets (right).
Experimental design is a critical step in every scientific study, for example, method validation by including a control group. Nonetheless, one has to be wary of the limitations of the methodology employed. In this case, molecular docking can be a good estimator for the most energetically favorable
We analyzed the molecular binding predictions through rigorous visualization and Z-score-based statistical algorithms to identify the potential drugs for repurposing. In this context, our findings suggest that:
Saquinavir and simeprevir could target viral entry and Rdrp complex quaternary formation,
Nilotinib could target viral entry, polyprotein processing, and Rdrp quaternary complex formation,
An isatin-derivative and telmisartan could target SARS-CoV-2 entry into the host,
Tegobuvir, qingdainone, and nafamostat could target quaternary interface Rdrp regions, and
Nafamostat and rac5c could be potential inhibitors of PLpro and ACE2.
These results are relevant in understanding the SARS-CoV-2 drug’s molecular mechanisms and further clinical treatment development, either at a single or multi-target activity.
The authors acknowledge funding from the Consejo Nacional de Ciencia y Tecnología México [grant number 132376] and Fondo Sectorial de Investigación para la Educación [grant number A1-S-17041] to MCT. All computations and analyses reported here were performed at the bmdhpc computing resources of the Biomolecular Diversity Lab (tripplab.com) at CINVESTAV Unidad Monterrey, México.
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
Li-Ta | H00 | H01 | H02 | H03 | H04 | H05 | V01 | V01H | V02 | V02R | V03 | V04 | V05 | V06 | V07 | V08 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
INH01 | −9.5 | −7.3 | −7.7 | |||||||||||||
INH02 | −6 | |||||||||||||||
INH03 | −6.2 | |||||||||||||||
INH04 | −9 | |||||||||||||||
INV01 | −7.2 | |||||||||||||||
INV02 | −7.5 | −5.5 | −6.7 | −7.8 | ||||||||||||
INV03 | −7.6 | −5.7 | −6.6 | −8.6 | ||||||||||||
INV04 | −9.8 | |||||||||||||||
INV05 | −6 | −6 | −4.1 | −3.4 |
VINA scores of the conformation with the lowest scores after 30 independent cycles of each target–ligand pair for the enzymatic known inhibitors included.
Li-Ta | H00 | H01 | H02 | H03 | H04 | H05 | V01 | V01H | V02 | V02R | V03 | V04 | V05 | V06 | V07 | V08 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
RPA01 | −9.8 | −8.5 | −7.9 | −6.8 | −8 | −6.6 | −9.7 | −9.6 | −8.9 | −6.8 | −7.7 | −7.5 | −5.6 | −6.5 | −7.1 | −8.8 |
RPA02 | −11.4 | −8.8 | −10.3 | −8.2 | −8.1 | −7.5 | −9.3 | −10 | −9.4 | −7.7 | −8.7 | −8.2 | −6.9 | −8.8 | −9.2 | −9.2 |
RPA03 | −8.6 | −6.5 | −6.9 | −5.9 | −6.3 | −5.9 | −7.6 | −7.3 | −5.9 | −5.7 | −6.6 | −5.9 | −4.7 | −5.9 | −5.9 | −7.5 |
RPA04 | −9.8 | −8.7 | −8.7 | −7.6 | −7.6 | −7.8 | −9.5 | −9.4 | −7.8 | −6.6 | −7.4 | −7.3 | −6 | −7 | −7.6 | −8.4 |
RPA05 | −6.1 | −5 | −6.6 | −4.8 | −5.3 | −4.9 | −6.8 | −6.7 | −4.6 | −4.2 | −4.6 | −4.2 | −4.3 | −4.5 | −4.3 | −6 |
RPA06 | −7.3 | −7 | −7.6 | −5.7 | −5.8 | −5.9 | −7.8 | −7.8 | −6.4 | −5.2 | −6.1 | −5 | −4.5 | −5.8 | −5.3 | −7.3 |
RPA07 | −7.3 | −6.4 | −7.7 | −5.9 | −6 | −5.9 | −7.9 | −7.9 | −6.4 | −5.3 | −6.3 | −5.6 | −4.7 | −5.9 | −5.7 | −7.2 |
RPA08 | −9.5 | −8 | −7.9 | −7.3 | −7.9 | −6.7 | −8.9 | −8.9 | −8.3 | −5.9 | −8.2 | −6.9 | −5.3 | −6.2 | −6.9 | −8.1 |
RPA09 | −8.9 | −6.3 | −7.1 | −5.9 | −7 | −6.8 | −7.4 | −7.2 | −6.3 | −5.7 | −7 | −6.2 | −5.7 | −5.9 | −6.9 | −7.7 |
RPA10 | −4.7 | −5 | −5.1 | −3.9 | −4.3 | −4 | −5.2 | −5.2 | −4.1 | −3.4 | −4.5 | −3.6 | −3 | −3.6 | −3.7 | −4.7 |
RPA11 | −7.8 | −6.6 | −7.5 | −5.6 | −6.7 | −6 | −7.8 | −7.8 | −6.2 | −5.3 | −6.6 | −5.1 | −5.1 | −5.4 | −5.6 | −7.3 |
RPA12 | −11.6 | −9.1 | −8.9 | −8.7 | −8.8 | −8 | −9.2 | −9 | −7.8 | −7.5 | −8.9 | −8.9 | −6.5 | −7.1 | −8.8 | −8.3 |
RPA13 | −12 | −7.7 | −9.5 | −8 | −8.5 | −7.7 | −8.8 | −9.1 | −7.9 | −7 | −9.4 | −8 | −7.4 | −7.3 | −8.6 | −9.9 |
RPA14 | −10.5 | −9.2 | −9.5 | −8.3 | −8.3 | −7.8 | −9.8 | −9.9 | −8.2 | −7 | −8.5 | −8.4 | −6.8 | −7.7 | −8.9 | −10.1 |
RPA15 | −10.9 | −9.4 | −9.3 | −7.8 | −7.8 | −8.2 | −10.1 | −9.9 | −8.7 | −7.2 | −8.7 | −8 | −6 | −8 | −7.9 | −9 |
RPB01 | −11.1 | −8.7 | −9.3 | −7.6 | −8.3 | −7.7 | −9.1 | −9.8 | −8.8 | −7.5 | −8.9 | −7.3 | −5.8 | −7.8 | −8.3 | −8 |
RPB02 | −11.3 | −7.8 | −8.8 | −7.5 | −7.7 | −7.1 | −8.4 | −9.3 | −8.2 | −6.8 | −7.7 | −7.4 | −5.7 | −7.4 | −7.9 | −7.5 |
RPB03 | −10.6 | −7.8 | −8.5 | −7.5 | −8.6 | −7.6 | −9.7 | −9.6 | −8.6 | −6.9 | −8 | −7.3 | −5.9 | −6.8 | −7.6 | −7.8 |
RPB04 | −11.8 | −8 | −9 | −7.6 | −8.1 | −7.6 | −8 | −8.6 | −8.2 | −7.5 | −7.9 | −7.2 | −6.2 | −7.4 | −8.2 | −8 |
RPB05 | −10.4 | −10.7 | −9 | −8.2 | −8.9 | −8.4 | −11 | −10.9 | −8 | −6.9 | −8.3 | −7.6 | −6.2 | −8.1 | −7.6 | −9.7 |
RPB06 | −10.7 | −7.7 | −9.4 | −7.5 | −8.8 | −7.4 | −9.1 | −9.7 | −7.9 | −6.7 | −7.8 | −7.3 | −6.1 | −7.6 | −8.2 | −8 |
RPB07 | −8 | −6.3 | −7.3 | −6.3 | −7.6 | −6.4 | −8.3 | −8.1 | −6.8 | −5.8 | −7 | −6.6 | −5 | −5.5 | −6.8 | −7.6 |
RPB08 | −11.6 | −8.6 | −9 | −7.6 | −8.2 | −7.6 | −8.6 | −8.5 | −8.4 | −7.4 | −7.6 | −7.2 | −6.1 | −7.1 | −7.9 | −8.2 |
RPC01 | −7.6 | −6.1 | −7.2 | −7 | −6.7 | −5.9 | −7.7 | −7.7 | −6.5 | −5.4 | −6.6 | −5.9 | −4.5 | −5.1 | −6.4 | −6.4 |
RPC02 | −10.3 | −7.7 | −8.3 | −7.7 | −8.2 | −7.3 | −9.9 | −9.8 | −7.4 | −7.2 | −8.1 | −7.2 | −6.1 | −7 | −7.3 | −8 |
RPC03 | −8.1 | −6.7 | −7.8 | −7 | −7.2 | −5.9 | −8.6 | −8.6 | −7.1 | −5.8 | −7.4 | −6.8 | −5.1 | −5.8 | −6.6 | −6.9 |
RPC04 | −12.3 | −10.2 | −10.7 | −8.9 | −9.6 | −8.3 | −10 | −10.7 | −8.8 | −7.9 | −9.7 | −8.6 | −7.2 | −8.9 | −9.1 | −9.8 |
RPC05 | −12.9 | −8.7 | −9.3 | −8.8 | −8.2 | −8.4 | −10 | −10.4 | −8.6 | −7.7 | −9.1 | −8 | −6.5 | −9 | −8.6 | −8.4 |
RPC06 | −11 | −9.8 | −9.8 | −7.7 | −8.6 | −7.6 | −9.9 | −9.6 | −7.6 | −7.7 | −8.1 | −7.6 | −6.2 | −8 | −8.1 | −8.1 |
RPC07 | −12.5 | −8.9 | −9.8 | −8.6 | −9 | −7.8 | −8.9 | −9.5 | −8.4 | −7.2 | −9.1 | −8.7 | −6.9 | −8.1 | −8.8 | −8.9 |
RPC08 | −11.5 | −9.5 | −10.2 | −7.9 | −9 | −8.1 | −9.7 | −9.7 | −8.6 | −8.1 | −8.6 | −8.8 | −7.3 | −8.1 | −8.7 | −9.8 |
RPC09 | −10.9 | −9.3 | −10.4 | −8.6 | −10.3 | −8.6 | −4.9 | −8.7 | −9.1 | −8.1 | −8.4 | −9.1 | −7.6 | −8.3 | −10 | −9.3 |
RPC10 | −11.2 | −8.7 | −9 | −7.7 | −8.4 | −7.9 | −9.2 | −9.2 | −8.6 | −7.7 | −8.6 | −7.8 | −6.4 | −7.9 | −8.1 | −8.7 |
RPC11 | −8.5 | −7.4 | −9.1 | −7.7 | −8.8 | −7.4 | −8 | −7.9 | −8.7 | −6.5 | −7.7 | −8.8 | −6.8 | −6.6 | −8.9 | −7.2 |
RPC12 | −10.3 | −8.3 | −8.9 | −7.7 | −8.1 | −7.3 | −8.9 | −8.7 | −8.1 | −6.7 | −8.2 | −7.4 | −5.8 | −7.6 | −7.5 | −7.6 |
RPC13 | −6.3 | −5.5 | −5.9 | −6.2 | −5.7 | −5.4 | −6.2 | −6.2 | −6.5 | −4.4 | −5.3 | −4.7 | −4.1 | −4.5 | −5.5 | −5.5 |
RPC14 | −6.4 | −5.5 | −6 | −6.3 | −5.8 | −5.4 | −6.2 | −6.1 | −6.6 | −4.3 | −5.1 | −4.6 | −3.9 | −4.4 | −5.4 | −5.7 |
RPD01 | −11 | −9.9 | −9 | −8.1 | −7.9 | −8.3 | −8.8 | −8.6 | −8.1 | −7 | −7.7 | −7.4 | −6.4 | −7.8 | −7.7 | −9.1 |
EXT01 | −6.3 | −5.1 | −5.5 | −5.9 | −5.8 | −5.3 | −6.2 | −6.2 | −6.2 | −4.4 | −5.1 | −4.9 | −3.9 | −4.3 | −5.3 | −5.6 |
EXT02 | −10 | −8.4 | −8.5 | −6.5 | −7.1 | −7.2 | −9.8 | −9.6 | −7.6 | −6.3 | −7.3 | −6.6 | −6 | −7 | −7.1 | −7.2 |
EXT03 | −9 | −7.8 | −8.3 | −6.5 | −6.9 | −6.8 | −10.1 | −10 | −7.1 | −5.7 | −6.8 | −6.1 | −5.7 | −6.4 | −6.8 | −6.9 |
EXT04 | −8 | −9 | −9.6 | −8.4 | −8.2 | −7.9 | 0.9 | −3.1 | −8.2 | −7.5 | −8.2 | −8.7 | −7.2 | −7.2 | −9.3 | −8.2 |
EXT05 | −6.2 | −6.1 | −7.2 | −6.5 | −6.9 | −5.6 | −6.9 | −6.7 | −6.1 | −5.4 | −7.4 | −7 | −5.3 | −5.7 | −7.4 | −5.2 |
EXT06 | −9.6 | −6.9 | −7.4 | −6.9 | −7.6 | −7.5 | −5.1 | −5.5 | −6.5 | −6 | −7.7 | −7.6 | −5.4 | −6 | −8 | −6.9 |
EXT07 | −9.9 | −7.3 | −8.1 | −6.7 | −7.5 | −6.3 | −7.2 | −7.8 | −6.7 | −6.3 | −7.2 | −6.6 | −5.9 | −6.5 | −6.5 | −7.1 |
EXT08 | −6 | −6.8 | −6.1 | −4.9 | −5 | −5 | −6 | −6 | −5.3 | −4.4 | −4.8 | −4 | −4.4 | −5 | −4.5 | −6.5 |
EXT09 | −11.2 | −7 | −9.2 | −6.7 | −8.6 | −6.6 | −7.8 | −7.8 | −7.6 | −6.4 | −7 | −7.4 | −6.4 | −7.2 | −7 | −6.1 |
EXT10 | −9.7 | −7.7 | −9 | −7.3 | −8.3 | −6.1 | −7.1 | −7.8 | −6.8 | −6.7 | −7.7 | −7.4 | −6.3 | −6.9 | −7.6 | −6 |
VINA scores of the conformation with the lowest scores after 30 independent cycles of each target–ligand pair for the set of ligands evaluated.
ACE2 | |
COVID-19 | Coronavirus disease 19 |
HCV | |
HTVS | |
ISG15 | |
MERS-CoV | Middle East respiratory syndrome coronavirus |
Mpro | |
PLpro | |
PPI | |
RBD | |
Rdrp complex | RNA-dependent RNA polymerase complex |
SARS-CoV | Severe acute respiratory syndrome coronavirus |
SARS-CoV-2 | Severe acute respiratory syndrome coronavirus 2 |
ssRNA | |
TMPRSS2 | Transmembrane serine protease 2 |
In our mission to support the dissemination of knowledge, we travel throughout the world to present our publications and support our Authors and Academic Editors. We attend international symposia, conferences, workshops and book fairs as well as business meetings with science, academic and publishing professionals. Take a look at the current events.
",metaTitle:"IntechOpen events",metaDescription:"In our mission to support the dissemination of knowledge, we travel worldwide to present our publications, authors and editors at international symposia, conferences, and workshops, as well as attend business meetings with science, academia and publishing professionals. We are always happy to host our scientists in our office to discuss further collaborations. Take a look at where we’ve been, who we’ve met and where we’re going.",metaKeywords:null,canonicalURL:"/page/events",contentRaw:'[{"type":"htmlEditorComponent","content":"May 18, 2022 | 1:00 PM - 2:00 PM CEST
\\n\\n\\n\\n\\n\\n
03 - 12 June 2022
\\n\\nPutra World Trade Centre, Kuala Lumpur, Malaysia
\\n\\nIntechOpen Represented by BOOKS INTERNATIONAL (M) SDN BHD
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24 - 27 August 2022, Beijing, China
\\n\\nIntechOpen Represented by China Publishers Services (CPS)
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19 - 23 October 2022, Frankfurt, Germany
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Guadalajara International Book Fair
\\n\\n26 November - 04 December 2022, Guadalajara, Mexico
\\n\\nIntechOpen Represented by LSR Libros Servicios y Representaciones SA de CV
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May 18, 2022 | 1:00 PM - 2:00 PM CEST
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03 - 12 June 2022
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\n\nIntechOpen Represented by BOOKS INTERNATIONAL (M) SDN BHD
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24 - 27 August 2022, Beijing, China
\n\nIntechOpen Represented by China Publishers Services (CPS)
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19 - 23 October 2022, Frankfurt, Germany
\n\n\n\n
Guadalajara International Book Fair
\n\n26 November - 04 December 2022, Guadalajara, Mexico
\n\nIntechOpen Represented by LSR Libros Servicios y Representaciones SA de CV
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I am also a member of the team in charge for the supervision of Ph.D. students in the fields of development of silicon based planar waveguide sensor devices, study of inelastic electron tunnelling in planar tunnelling nanostructures for sensing applications and development of organotellurium(IV) compounds for semiconductor applications. I am a specialist in data analysis techniques and nanosurface structure. 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He is an expert in structural, absorptive, catalytic and photocatalytic properties, in structural organization and dynamic features of ionic liquids, in magnetic interactions between paramagnetic centers. The author or co-author of 3 books, over 200 articles and reviews in scientific journals and books. He is an actual member of the International EPR/ESR Society, European Society on Quantum Solar Energy Conversion, Moscow House of Scientists, of the Board of Moscow Physical Society.",institutionString:null,institution:{name:"Semenov Institute of Chemical Physics",country:{name:"Russia"}}},{id:"62389",title:"PhD.",name:"Ali Demir",middleName:null,surname:"Sezer",slug:"ali-demir-sezer",fullName:"Ali Demir Sezer",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/62389/images/3413_n.jpg",biography:"Dr. Ali Demir Sezer has a Ph.D. from Pharmaceutical Biotechnology at the Faculty of Pharmacy, University of Marmara (Turkey). 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The comprehensive e-services system was developed and implemented in one of the higher educational institutions. The upcoming generations of students are increasingly likely to have prominent previous experience with the major use of digital technologies as a part of their elementary and secondary level education. Higher education institutions should expand the portfolio of their e-services, given that the demands of students are expected to increase in the future.",book:{id:"11914",title:"E-service Digital Innovation",coverURL:"https://cdn.intechopen.com/books/images_new/11914.jpg"},signatures:"Adam Malešević"},{id:"82995",title:"A Hybrid Genetic, Differential Evolution Optimization Algorithm",slug:"a-hybrid-genetic-differential-evolution-optimization-algorithm",totalDownloads:3,totalDimensionsCites:0,doi:"10.5772/intechopen.106204",abstract:"This chapter presents a heuristic evolutionary optimization algorithm that is loosely based on the principles of evolution and natural genetics. In particular, this chapter describes an evolutionary algorithm that is a hybrid of a genetic algorithm and a differential evolution algorithm. This algorithm uses an elitist, ranking, random selection method, several mutation methods and both two level and three level Taguchi crossover. This algorithm is applied to 13 commonly used global numerical optimization test functions, including a spherical, three hyper-ellipsoid, the sum of different powers, Rastrigin’s, Schwefel’s, Griewank’s, Rosenbrock’s valley, Styblinski-Tang, Ackley’s Path, Price-Rosenbrock, and Eggholder’s functions. This algorithm is applied 1000 times to each of the 13 test functions, and the results shows that this algorithm always converges to each of the 13 test function’s global minimum.",book:{id:"11555",title:"Ubiquitous and Pervasive Computing - New Trends and Opportunities",coverURL:"https://cdn.intechopen.com/books/images_new/11555.jpg"},signatures:"Peter Stubberud"},{id:"82921",title:"A Survey of Lightweight Image Encryption for IoT",slug:"a-survey-of-lightweight-image-encryption-for-iot",totalDownloads:4,totalDimensionsCites:0,doi:"10.5772/intechopen.104431",abstract:"IoT networks serve as a way for various devices interconnected over the internet to exchange data with each other and with other services. Most smartphones, laptops, and other communication devices are connected to the cloud today, making data accessible to everyone. There are many applications for IoT, from smart IoT applications to industrial products. Encryption is one of the best ways to make IoT networks secure since so much data is being transferred. A lightweight block cipher is one of the most sophisticated means for overcoming the security problems inherent to IoT networks. Because of the limited resources available to nodes, classical cryptography methods are costly and inefficient. In this paper, we have compared the systems, we have found that these modifications were made to the original AES algorithm, while the original algorithm security remains robust, the modified AES algorithm remains lightweight and faster, providing more satisfaction for embedding in IoT devices and sensors that consume little power. Furthermore, this algorithm enhanced the AES-ECC hybrid encryption system, which has good flexibility and versatility, and optimized the design of the ECC function according to the characteristics of wireless sensor networks. Using Salsa20/12 stream cipher, the texture images can be encrypted using bit masking and permutation procedures and as part of a new scheme for encrypting 3D objects, which complements the existing methods for 3D object encryption. With PLIE implemented in Python, the encryption time was approximately 50% faster than that of AES using the throughput increase, faster encryption time, and minimal complexity.",book:{id:"11190",title:"Lightweight Cryptographic Techniques and Cybersecurity Approaches",coverURL:"https://cdn.intechopen.com/books/images_new/11190.jpg"},signatures:"Haneen Dweik and Mohammad Abutaha"},{id:"82098",title:"Perspective chapter: Internet of Things in Healthcare - New Trends, Challenges and Hurdles",slug:"perspective-chapter-internet-of-things-in-healthcare-new-trends-challenges-and-hurdles",totalDownloads:5,totalDimensionsCites:0,doi:"10.5772/intechopen.104946",abstract:"Applied to health field, Internet of Things (IoT) systems provides continuous and ubiquitous monitoring and assistance, allowing the creation of valuable tools for diagnosis, health empowerment, and personalized treatment, among others. Advances in these systems follow different approaches, such as the integration of new protocols and standards, combination with artificial intelligence algorithms, application of big data processing methodologies, among others. These new systems and applications also should face different challenges when applying this kind of technology into health areas, such as the management of personal data sensed, integration with electronic health records, make sensing devices comfortable to wear, and achieve an accurate acquisition of the sensed data. The objective of this chapter is to present the state of the art, indicating the most current IoT trends applied to the health field, their contributions, technologies applied, and challenges faced.",book:{id:"11197",title:"Internet of Things - New Trends, Challenges and Hurdles",coverURL:"https://cdn.intechopen.com/books/images_new/11197.jpg"},signatures:"Luis Muñoz-Saavedra, Francisco Luna-Perejón, Javier Civit-Masot and Elena Escobar-Linero"},{id:"82742",title:"Activity Based Learning (ABL) Using Gamification (GBL) in Mechanical Engineering Design Education: A Studio-Based Case Study",slug:"activity-based-learning-abl-using-gamification-gbl-in-mechanical-engineering-design-education-a-stud",totalDownloads:9,totalDimensionsCites:0,doi:"10.5772/intechopen.104773",abstract:"In our research, we aim to introduce Game-based learning (GBL) activity as part of a holistic approach to supporting knowledge acquisition within a Mechanical Design module. 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