RESUMO
AIMS: Huanglongbing (citrus greening) is a plant disease putatively caused by the unculturable Gram-negative bacterium Candidatus Liberibacter asiaticus (CLas), and it has caused severe damage to citrus plantations worldwide. There are no definitive treatments for this disease, and conventional disease control techniques have shown limited efficacy. This work presents an in silico evaluation of using specifically targeting anti-microbial peptides (STAMPs) consisting of a targeting segment and an antimicrobial segment to inhibit citrus greening by inhibiting the BamA protein of CLas, which is an outer membrane protein crucial for bacterial viability. METHODS AND RESULTS: Initially, a set of peptides with a high affinity toward BamA protein were screened and evaluated via molecular docking and molecular dynamics simulations and were verified in vitro via bio-layer interferometry (BLI). In silico studies and BLI experiments indicated that two peptides, HASP2 and HASP3, showed stable binding to BamA. Protein structures for STAMPs were created by fusing known anti-microbial peptides (AMPs) with the selected short peptides. The binding of STAMPs to BamA was assessed using molecular docking and binding energy calculations. The attachment of high-affinity short peptides significantly reduced the free energy of binding for AMPs, suggesting that it would make it easier for the STAMPs to bind to BamA. Efficacy testing in vitro using a closely related CLas surrogate bacterium showed that STAMPs had greater inhibitory activity than AMP alone. CONCLUSIONS: In silico and in vitro results indicate that the STAMPs can inhibit CLas surrogate Rhizobium grahamii more effectively compared to AMPs, suggesting that STAMPs can achieve better inhibition of CLas, potentially via enhancing the site specificity of AMPs.
Assuntos
Citrus , Hemípteros , Rhizobiaceae , Animais , Peptídeos Antimicrobianos , Simulação de Acoplamento Molecular , Liberibacter , Citrus/microbiologia , Doenças das Plantas/prevenção & controle , Doenças das Plantas/microbiologia , Hemípteros/microbiologiaRESUMO
Citrus greening, also known as Huanglongbing (HLB), is caused by the unculturable bacterium Candidatus Liberibacter spp. (e.g., CLas), and has caused a devastating decline in citrus production in many areas of the world. As of yet, there are no definitive treatments for controlling the disease. Antimicrobial peptides (AMPs) that have the potential to block secretion-dependent effector proteins at the outer-membrane domains were screened in silico. Predictions of drug-receptor interactions were built using multiple in silico techniques, including molecular docking analysis, molecular dynamics, molecular mechanics generalized Born surface area analysis, and principal component analysis. The efflux pump TolC of the Type 1 secretion system interacted with natural bacteriocin plantaricin JLA-9, blocking the ß barrel. The trajectory-based principal component analysis revealed the possible binding mechanism of the peptides. Furthermore, in vitro assays using two closely related culturable surrogates of CLas (Liberibacter crescens and Rhizobium spp.) showed that Plantaricin JLA-9 and two other screened AMPs inhibited bacterial growth and caused mortality. The findings contribute to designing effective therapies to manage plant diseases associated with Candidatus Liberibacter spp.
Assuntos
Citrus , Hemípteros , Rhizobiaceae , Animais , Liberibacter , Peptídeos Antimicrobianos , Simulação de Acoplamento Molecular , Claritromicina/farmacologia , Citrus/microbiologia , Doenças das Plantas/microbiologiaRESUMO
"Candidatus Liberibacter spp." are insect-vectored, fastidious, and vascular-limited phytopathogens. They are the presumptive causal agents of potato zebra chip, tomato vein clearing, and the devastating citrus greening disease worldwide. There is an urgent need to develop new strategies to control them. In this study, we characterized a dual-specificity serine/tyrosine phosphatase (STP) that is well conserved among thirty-three geographically diverse "Candidatus Liberibacter spp." and strains that infect multiple Solanaceaea and citrus spp. The STP is expressed in infected plant tissues, localized at the plant cytosol and plasma membrane, and interferes with plant cell death responses. We employed an in silico target-based molecular modeling and ligand screen to identify two small molecules with high binding affinity to STP. Efficacy studies demonstrated that the two molecules can inhibit "Candidatus Liberibacter spp." but not unrelated pathogens and confer plant disease tolerance. The inhibitors and strategies are promising means to control "Candidatus Liberibacter spp."
RESUMO
The rapid geographic expansion of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the infectious agent of Coronavirus Disease 2019 (COVID-19) pandemic, poses an immediate need for potent drugs. Enveloped viruses infect the host cell by cellular membrane fusion, a crucial mechanism required for virus replication. The SARS-CoV-2 spike glycoprotein, due to its primary interaction with the human angiotensin-converting enzyme 2 (ACE2) cell-surface receptor, is considered a potential target for drug development. In this study, around 5,800 molecules were virtually screened using molecular docking. Five molecules were selected for in vitro experiments from those that reported docking scores lower than -6 kcal/mol. Imatinib, a Bcr-Abl tyrosine kinase inhibitor, showed maximum antiviral activity in Vero cells. We further investigated the interaction of imatinib, a compound under clinical trials for the treatment of COVID-19, with SARS-CoV-2 RBD, using in silico methods. Molecular dynamics simulations verified that imatinib interacts with RBD residues that are critical for ACE2 binding. This study also provides significant molecular insights on potential repurposable small-molecule drugs and chemical scaffolds for the development of novel drugs targeting the SARS-CoV-2 spike RBD.Communicated by Ramaswamy H. Sarma.
Assuntos
COVID-19 , SARS-CoV-2 , Animais , Chlorocebus aethiops , Humanos , Simulação de Acoplamento Molecular , Enzima de Conversão de Angiotensina 2 , Mesilato de Imatinib , Células VeroRESUMO
Fungal diseases, including downy mildew (caused by Plasmopara viticola) and gray mold (caused by Botrytis cinerea), significantly impact the marketable yield of grapes produced worldwide. Cytochrome b of the mitochondrial respiratory chain of these two fungi is a key target for Quinone outside inhibitor (QoI)-based fungicide development. Since the mode of action (MOA) of QoI fungicides is restricted to a single site, the extensive usage of these fungicides has resulted in fungicide resistance. The use of fungicide combinations with multiple targets is an effective way to counter and slow down the development of fungicide resistance. Due to the high cost of in planta trials, in silico techniques can be used for the rapid screening of potential fungicides. In this study, a combination of in silico simulations that include Schrödinger Glide docking, molecular dynamics, and Molecular Mechanism-Generalized Born Surface Area calculation were used to screen the most potent QoI and non-QoI-based fungicide combinations to wild-type, G143A-mutated, F129L-mutated, and double-mutated versions that had both G143A and F129L mutations of fungal cytochrome b. In silico docking studies indicated that mandestrobin, famoxadone, captan, and thiram have a high affinity toward WT cytochrome b of Botrytis cinerea. Although the QoIs mandestrobin and famoxadone were effective for WT based on in vitro results, they were not broadly effective against G143A-mutated isolates. Famoxadone was only effective against one isolate with G143A-mutated cytochrome b. The non-QoI fungicides thiram and captan were effective against both WT and isolates with G143A-mutated cytochrome b. Follow-up in silico docking and molecular dynamics studies suggested that fungicide combinations consisting of famoxadone, mandestrobin, fenamidone, and thiram should be considered in field testing targeting Plasmopara viticola and Botrytis cinerea fungicide resistance.
RESUMO
Earlier studies with montelukast (M) and telmisartan (T) have revealed their potential antiviral properties against SARS-CoV-2 wild-type (WT) but have not assessed their efficacy against emerging Variants of Concern (VOCs) such as Omicron. Our research fills this gap by investigating these drugs' impact on VOCs, a topic that current scientific literature has largely overlooked. We employed computational methodologies, including molecular mechanics and machine learning tools, to identify drugs that could potentially disrupt the SARS-CoV-2 spike RBD-ACE2 protein interaction. This led to the identification of two FDA-approved small molecule drugs, M and T, conventionally used for treating asthma and hypertension, respectively. Our study presents an additional potential use for these drugs as antivirals. Our results show that both M and T can inhibit not only the WT SARS-CoV-2 but also, in the case of M, the Omicron variant, without reaching cytotoxic concentrations. This novel finding fills an existing gap in the literature and introduces the possibility of repurposing these drugs for SARS-CoV-2 VOCs, an essential step in responding to the evolving global pandemic.
RESUMO
Pharmacophore modeling is an important step in computer-aided drug design for identifying interaction points between the receptor and ligand complex. Pharmacophore-based models can be used for de novo drug design, lead identification, and optimization in virtual screening as well as for multi-target drug design. There is a need to develop a user-friendly interface to filter the pharmacophore points resulting from multiple ligand conformations. Here, we present ELIXIR-A, a Python-based pharmacophore refinement tool, to help refine the pharmacophores between multiple ligands from multiple receptors. Furthermore, the output can be easily used in virtual pharmacophore-based screening platforms, thereby contributing to the development of drug discovery.
RESUMO
The Zika virus (ZIKV), a significant zoonotic flavivirus, was neglected as a human pathogen until the recent epidemic. The rapid geographic spread of the virus and association with neurological disorders has created a global public health concern pressing the need for anti-ZIKV drugs. Previous ZIKV drug discovery research has focused on three primary targets, RNA-dependent RNA polymerase, envelope protein, and viral proteases, and none has yet resulted in a commercially viable inhibitor. In the quest for finding effective inhibitors, it is important to expand the number of targets available for drug discovery research. To this end, the ZIKV precursor membrane protein (prM) comes to the forefront as a potential target due to its critical role in virus infectivity and pathogenicity. prM acts as a chaperone for envelope protein folding and prevents premature fusion of virions to the host membrane and has not been attempted as a drug target before. One critical requirement for a protein to be an effective target is the ability of the protein to be druggable, i.e. having active sites that can bind to specific ligands. In this work, the druggability of prM was assessed via molecular docking combined molecular dynamics simulations followed binding affinity kinetics studies. Compounds that had a high affinity to the prM protein were screened in silico and ligand-binding free energies were computed using molecular mechanics with generalized Born and surface area continuum solvation (MM-GBSA) method. In vitro binding kinetics via biolayer interferometry (BLI) and interaction analysis confirmed that prM could be targeted for drug discovery to combat ZIKV infection.Communicated by Ramaswamy H. Sarma.