SANCDB: an update on South African natural compounds and their readily available analogs

Diallo, Bakary N'tji; Glenister, Michael; Musyoka, Thommas M.; Lobb, Kevin A.; Bishop, Özlem Tastan

doi:10.1186/s13321-021-00514-2

Cited by 27 publications

(9 citation statements)

References 79 publications

(74 reference statements)

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“…Prior to the structure-based molecular search for potent drugs, the whole SANCDB (https://sancdb.rubi.ru.ac.za/) (accessed on 10 January 2022) was filtered for drugs-like molecules that obey Lipinski's rule of five [27]. The whole database was filtered for toxicophores, drug-like molecules, and the removal of pan assay interference (PAINS) compounds, and Eli Lilly MedChem rules was used together with the FAF-Drugs4 server (https://fafdrugs4.rpbs.univ-paris-diderot.fr/) (accessed on 10 January 2022) to filter druglike molecules which are non-toxic, and non-PAINS compounds [28].…”

Section: Sancdb Screening For Drug-like Moleculesmentioning

confidence: 99%

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

Hakami

2022

Biology

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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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Section: Sancdb Screening For Drug-like Moleculesmentioning

confidence: 99%

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

Hakami

2022

Biology

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“…A total of 623 compounds were first obtained from the South African natural compound database (SANCDB) 13,14 . Partial charges were assigned to compounds and the protonated proteins using the Gasteiger-Hückel protocol in AutoDockTools (ADT) 38 .…”

Section: High-throughput Virtual Screening Of Sancdb Compounds Against M Pro Proteinsmentioning

confidence: 99%

“…These centrality hubs form a communication path between the allosteric ligand binding site to the active site going through the interface residues of Domain I and II (Figure 14A). In the case of Protomer A of M pro -SANC00468 reference proteinligand complex, some new centrality hubs are gained (9,11,13,14), and some lost (38,149) compared to that of M pro -SANC00302 system; totaling to 20 EC hub residues (7,9,10,11,13,14,17,28,29,113,115,116,117,122,124,125,146,147, 148, 150) (Figure 13). Next, we looked at how these averaged EC hubs of protomer A change in the presence of mutations.…”

Section: Identification Of Ligand Specific Allosteric Communication Paths and Changes In The Presence Of Mutationsmentioning

confidence: 99%

“…As a continuation of our previous SARS-CoV-2 M pro work 12 , here we aim to set up alternative innovative therapeutic concepts on identification of allosteric modulators in the presence of early evolutionary mutations of the virus. These concepts are explained under three subsequent sections: PART I: Here, we identified potential allosteric modulators for the dimeric SARS-CoV-2 M pro protein, at a protonation state corresponding to pH 7.0, by screening it against 625 South African natural compounds 13,14 . Parallel to this, we also docked the natural compounds against the M pro protein of one of the seven human coronaviruses, HCoV-OC43.…”

Section: Introductionmentioning

confidence: 99%

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Novel dynamic residue network analysis approaches to study homodimeric allosteric modulation in SARS-CoV-2 Mpro and in its evolutionary mutations

Sheik

Amamuddy

Afriyie

et al. 2021

Preprint

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The rational search for allosteric modulators and the allosteric mechanisms of these modulators in the presence of evolutionary mutations, including resistant ones, is a relatively unexplored field. Here, we established novel in silico approaches and applied to SARS-CoV-2 main protease (Mpro). First, we identified six potential allosteric modulators (SANC00302, SANC00303, SANC00467, SANC00468, SANC00469, SANC00630) from the South African Natural Compounds Database (SANCDB) bound to the allosteric pocket of Mpro that we determined in our previous work. We also checked the stability of these compounds against Mpro of laboratory strain HCoV-OC43 and identified differences due to residue changes between the two proteins. Next, we focused on understanding the allosteric effects of these modulators on each protomer of the reference Mpro protein, while incorporating the symmetry problem in the functional homodimer. In general, asymmetric behavior of multimeric proteins is not commonly considered in computational analysis. We introduced a novel 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 (betweenness centrality (BC), closeness centrality (CC), degree centrality (DC), eigencentrality (EC) and katz centrality (KC)). The relationships and effectiveness of each metric in characterizing allosteric behavior were also investigated. 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, and we called them persistent hubs (residues 17, 111, 112 and 128 for averaged BC; 6, 7, 113, 114, 115, 124, 125, 126, 127 and 128 for averaged CC; 36, 91, 146, 150 and 206 for averaged DC; 7, 115 and 125 for EC; 36, 125 and 146 for KC). We also detected ligand specific signal changes some of which were in or around functional residues (i.e. chameleon switch PHE140). Using EC persistent hubs and ligand introduced hubs we identified a residue communication path between allosteric binding site and 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. The hit compounds showed various levels of stability in the presence of SARS-CoV-2 Mpro mutations, being most stable in A173V, N274D and R279C, and least stable in R60C, N151D V157I, C160S and A255V. SANC00468 was the most stable compound in the 43 mutant protein systems. We further used DRN metric analysis to define cold spots as being those regions that are least impacted, or not impacted, by mutations. One crucial outcome of this study 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 Domain I and II; and this path was either weakened or lost in the presence of some of the mutations. Overall, the results of this study revealed crucial aspects that need to be considered in drug discovery in COVID-19 specifically and in general for rational computational drug design purposes.

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“…Herein we used computational modeling and simulation approaches to target the interface of the ORF8-IRF3 complex with high-affinity natural products [ 24 ]. South African Natural Compounds Database (SANCDB) ( (accessed on 10 October 2021) [ 25 ] containing compounds from plant sources and marine life was screened against the interface residues of IRF3. Computational molecular search and rescoring of the whole database followed by induced-fit docking (IFD) protocol were employed to identify the best scoring compounds.…”

Section: Introductionmentioning

confidence: 99%

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

Albutti

2021

IJERPH

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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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SANCDB: an update on South African natural compounds and their readily available analogs

Cited by 27 publications

References 79 publications

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

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

Novel dynamic residue network analysis approaches to study homodimeric allosteric modulation in SARS-CoV-2 Mpro and in its evolutionary mutations

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

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