In-silico Approach Research Articles

Identification of phytochemicals as potential inhibitors of Candida albicans SAP3: An in-silico approach

Background: Candida albicans is a major threat to human health, causing a variety of diseases. Candida albicans can overgrow and trigger infections like thrush, diaper rash, and vaginal yeast infections. Therefore, finding potential inhibitors of C. albicans from plant sources has become important, recently.Methods: This study investigated the interaction of natural compounds (N = 450) from the ZINC database with the C. albicans SAP3 protein. PyRx tools were used to conduct molecular docking analyses, which included ligand and target receptor preparation, data analysis, and visualization.Result: The binding energies between the natural compounds and SAP3 ranged from -8.8 to -7.8 kcal/mol, indicating that the interactions were predominantly strong. Among the compounds screened, ZINC000252509014, ZINC000252509722, ZINC000253389136, ZINC000251981944, and ZINC000252480871 were extensively explored in this study because they were found to be the best among others. Furthermore, these compounds showed favorable drug-like properties.Conclusion: These findings lay the groundwork for future research aimed at developing potent SAP3 inhibitors to treat C. albicans infections.Keywords: Candida albicans; SAP3 protein; Natural compounds; Virtual screening; Drug-likeness

Suspect and non-target screening of chemicals of emerging Arctic concern in biota, air and human serum

Contaminants of emerging concern receive increasing attention in the Arctic environment. The aim of this study was to screen for chemicals of emerging Arctic concern (CEACs) in different types of Arctic samples including biota, air and human serum. We used a combination of gas chromatography (GC) and liquid chromatography (LC) with high resolution mass spectrometry (HRMS) for suspect and non-target screening (NTS). Suspect screening of 25 CEACs was based on published in-silico approaches for the identification of CEACs and revealed tetrabromophthalic anhydride (TBPA) in pilot whale and air, albeit with low detection frequencies (17 and 33%, respectively). An NTS workflow detected 49, 42, 31 and 30 compounds in pilot whale, ringed seal, air, and human serum, respectively, at confidence level 2 and 3. Although legacy POPs still dominated the samples, 64 CEACs were tentatively identified and further assessed for persistence (P), bioaccumulation (B), mobility (M), toxicity (T), and long-range transport potential (LRTP). While four PBT compounds were identified, 37 PMT substances dominated among these 64 compounds. Our study indicated that many chemicals of potential risk might be present in Arctic samples and would benefit from confirmation and further studies of their transport to and accumulation in the Arctic environment.

CSSP-2.0: A refined consensus method for accurate protein secondary structure prediction

Studying the relationship between sequences and their corresponding three-dimensional structure assists structural biologists in solving the protein-folding problem. Despite several experimental and in-silico approaches, still understanding or decoding the three-dimensional structures from the sequence remains a mystery. In such cases, the accuracy of the structure prediction plays an indispensable role. To address this issue, an updated web server (CSSP-2.0) has been created to improve the accuracy of our previous version of CSSP by deploying the existing algorithms. It uses input as probabilities and predicts the consensus for the secondary structure as a highly accurate three-state Q3 (helix, strand, and coil). This prediction is achieved using six recent top-performing methods: MUFOLD-SS, RaptorX, PSSpred v4, PSIPRED, JPred v4, and Porter 5.0. CSSP-2.0 validation includes datasets involving various protein classes from the PDB, CullPDB, and AlphaFold databases. Our results indicate a significant improvement in the accuracy of the consensus Q3 prediction. Using CSSP-2.0, crystallographers can sort out the stable regular secondary structures from the entire complex structure, which would aid in inferring the functional annotation of hypothetical proteins. The web server is freely available at https://bioserver3.physics.iisc.ac.in/cgi-bin/cssp-2/

In-silico molecular docking, ADME study, and molecular dynamic simulation of new azetidin-2-one derivatives with antiproliferative activity

Over the past two decades, protein kinase has been a heavily studied target in the development of new anti-proliferative medications. Heterocyclic systems have been identified as the preferred scaffold because of their wide range of biological properties. In this research, the objective was to design and develop fifteen novel azetidin-2-one derivatives and assess their cytotoxic potential as inhibitors of the epidermal growth factor receptor, which is considered one of the key factors influencing cell growth and proliferation. The crystal structure of inactive EGFR tyrosine kinase domain ligand erlotinib from protein data bank was retrieved in order to be docked with our proposed azetidine-2-one derivatives to evaluate their activity as anti-proliferative agents. In this article, an in-silico molecular docking approach proposes that these azetidine-2-one derivatives have satisfactory binding contact with the erlotinib binding site. Although, three compounds have been identified as the most powerful as they have PLP fitness scores of (77.79, 76.68 and 71.46), respectively, while the reference ligand’s fitness score was (71.94). Additionally, all of our derivatives have satisfied the Swiss-ADME parameters, indicating that they may be orally active compounds. In conclusion, two compounds (A-2 and A-8) have better PLP fitness, and one (A-14) has a comparable score in comparison to the reference ligand, at the active site of epidermal growth factor receptor. indicating that the novel azetidine-2-one derivatives have shown interesting results and could be used as model compounds to create novel anti-proliferative drugs. However, more pharmacological evaluation is needed.

Exploring the Binding Mechanism of 5-HT7 Specific Benzoxazolone alkyl Piperazinium Derivatives: A Comprehensive Analysis Using Spectroscopic and Computational Approaches.

Recently, the 5-HT7 receptor has achieved greater attention in research fraternity due to the involvement of neurotransmitter serotonin (5-hydroxytryptamine, 5-HT) in several neurological disorders. Targeting this neuroreceptor, we have synthesized six compounds named as butyl-benzoxazolone substituted piperazinium derivatives (BBOP) derivatives, abbreviated as L1-L6. These compounds have been evaluated for their binding interaction with BSA through photophysical and in-silico approaches. The UV absorption of these compounds with BSA at λmax = 280nm, showed an optical density (O.D.) in the range of 0.5-0.9, i.e., 21%-53% (L1max = 1.4, L5min = 0.7385) at varied concentrations (17μM-114μM). For fluorescence studies, the Ksv value varied inversely with temperature, which confirmed the static mechanism of quenching with L1 showing maximum quenching. The parameters (ΔH, ΔS) obtained from the thermodynamic study for interaction between BSA and L1-L6 were correlated with in-silico (molecular docking) data. The in-silico docking study showed hydrophobic and the Van der Waals forces were the most significant forces. Amino acid residues ARG 217 & TRP 213 (Sudlow Site I) and LYS 116 & GLU 125 (Sudlow Site II) of BSA were primarily involved in H-bonding.Furthermore, the catalytic activity of BSA for hydrolyzingdifferent chemical entities have monitored in the presence of L1-L6 through esterase-like assay with p-NPA as a substrate, to get more insight about the interaction with catalytic residues (LYS 414, LYS 413, and TYR 411) in BSA at site II. These findings showed the potential of these 5-HT7 markers as promising ligands with appropriate drug likeliness characteristics.

A Chronicle Review of In-Silico Approaches for Discovering Novel Antimicrobial Agents to Combat Antimicrobial Resistance.

The online version contains supplementary material available at 10.1007/s12088-024-01355-x.

Structure based functional identification of an uncharacterized protein from Coxiella burnetii involved in adipogenesis

Coxiella burnetii, the causative agent of Q fever, is an intracellular pathogen posing a significant global public health threat. There is a pressing need for dependable and effective treatments, alongside an urgency for further research into the molecular characterization of its genome. Within the genomic landscape of Coxiella burnetii, numerous hypothetical proteins remain unidentified, underscoring the necessity for in-depth study. In this study, we conducted comprehensive in silico analyses to identify and prioritize potential hypothetical protein of Coxiella burnetii, aiming to elucidate the structure and function of uncharacterized protein. Furthermore, we delved into the physicochemical properties, localization, and molecular dynamics and simulations, and assessed the primary, secondary, and tertiary structures employing a variety of bioinformatics tools. The in-silico analysis revealed that the uncharacterized protein contains a conserved Mth938-like domain, suggesting a role in preadipocyte differentiation and adipogenesis. Subcellular localization predictions indicated its presence in the cytoplasm, implicating a significant role in cellular processes. Virtual screening identified ligands with high binding affinities, suggesting the protein’s potential as a drug target against Q fever. Molecular dynamics simulations confirmed the stability of these complexes, indicating their therapeutic relevance. The findings provide a structural and functional overview of an uncharacterized protein from C. burnetii, implicating it in adipogenesis. This study underscores the power of in-silico approaches in uncovering the biological roles of uncharacterized proteins and facilitating the discovery of new therapeutic strategies. The findings provide valuable preliminary data for further investigation into the protein’s role in adipogenesis.

Computational design of novel therapeutics targeting Schistosomiasis, a neglected tropical disease

Schistosomiasis, caused by flatworm parasites, is a widespread disease resulting in chronic illness and fatalities globally. Given the risk of drug resistance and limited treatment options, finding new therapeutic options are crucial for managing and controlling this neglected tropical disease. In this research, various in-silico methods including Density-Functional-Theory (DFT) computations, Molecular-docking, molecular dynamics simulations and Pharmacokinetic evaluation were employed to identify ten potential inhibitors of Schistosoma mansoni HDAC8 (SmHDAC8). The modeled activities (pIC50) of these newly designed compounds (ranging between 7.110 and 6.959) surpassed that of the hit compound 19 (pIC50 = 6.445) and the standard reference control, Praziquantel (pIC50 = 5.989). Moreover, the MolDock scores (ranging between −188.964 and −158.351 kcal/mol) for these proposed compounds in the SmHDAC8 binding cavity outperformed the hit template 19 (MolDock score: −122.516 kcal/mol) and the Praziquantel (−110.245 kcal/mol). Furthermore, the conformational stability of the top three designed compounds (19a, 19i, and 19j) in the SmHDAC8 binding cavity was examined through a 100 ns of Molecular Dynamics simulation. Additionally, the drug-likeness and ADMET predictions of these compounds indicated favorable oral bioavailability and pharmacokinetic profiles. This study offers a reliable in-silico approach for identifying potential agents against Schistosomiasis.

Revolutionizing the probiotic functionality, biochemical activity, antibiotic resistance and specialty genes of Pediococcus acidilactici BCB1H via in-vitro and in-silico approaches.

This study presents a comprehensive genomic exploration, biochemical characterization, and the identification of antibiotic resistance and specialty genes of Pediococcus acidilactici BCB1H strain. The functional characterization, genetic makeup, biological activities, and other considerable parameters have been investigated in this study with a prime focus on antibiotic resistance and specialty gene profiles. The results of this study revealed the unique susceptibility patterns for antibiotic resistance and specialty genes. BCB1H had good invitro probiotic properties, which survived well in simulated artificial gastrointestinal fluid, and exhibited acid and bile salt resistance. BCB1H didn't produce hemolysis and had certain antibiotic sensitivity, making it a relatively safe LAB strain. Simultaneously, it had good self-coagulation characteristics and antioxidant activity. The EPS produced by BCB1H also had certain antioxidant activity and hypoglycemic function. Moreover, the genome with a 42.4 % GC content and a size of roughly 1.92 million base pairs was analyzed in the genomic investigations. The genome annotation identified 192 subsystems and 1,895 genes, offering light on the metabolic pathways and functional categories found in BCB1H. The identification of specialty genes linked to the metabolism of carbohydrates, stress response, pathogenicity, and amino acids highlighted the strain's versatility and possible uses. This study establishes the groundwork for future investigations by highlighting the significance of using multiple strains to investigate genetic diversity and experimental validation of predicted genes. The results provide a roadmap for utilizing P.acidilactici BCB1H's genetic traits for industrial and medical applications, opening the door to real-world uses in industries including food technology and medicine.

An integrated bioinformatics approach for unravelling the molecular insights into psoriasis pathology and therapeutics

Psoriasis is a chronic relapsing inflammatory disease of the skin that affects almost 2–3 % population worldwide. The current treatment strategies include palliative therapeutics targeting the inflammatory pathways that do not completely cure the lesioned skin. The molecular cues in the hyper-proliferative and aberrantly differentiated keratinocytes of the psoriatic lesioned skin remain unknown. Through an integrative in-silico approach, we have analyzed human psoriatic skin samples from 3 RNA-Seq and 3 microarray datasets to identify 340 differentially expressed genes (DEGs). Further, these DEGs were analyzed using gene ontology enrichment, KEGG pathways, and protein-protein interaction networks for their role in disease pathology and the identification of hub genes. The expression of the hub genes was validated in a preclinical murine model of psoriasiform dermatitis. Finally, the ten hub genes were assessed for their drugability, which revealed 74 drugs targeting 7 hub genes (CCNA2, TOP2A, BIRC5, RRM2, CDK1, AURKA, and CCNB1) that can be repurposed for psoriasis treatment. This study provides an understanding of psoriasis pathophysiology and suggests key molecular biomarkers as therapeutic targets for effective mitigation of the disease.

In-silico approaches for discrimination of Curcuma species and their closely related family using the novel technique of DNA Barcoding

In this study, we have discriminated and identified the Genus of Curcuma and related species Zingiberaceae using rbcL and trnL DNA barcode primers. Curcuma genus related to the family Zingiberaceae comprises a significant number of medicinal plants renowned for their use in ethnomedicine, playing a pivotal role in the medical, health, and pharmaceutical sectors. Traditionally, morphological methods alone have proven insufficient for accurately identifying species within this family. However, DNA barcoding technology provides a contemporary solution by utilizing plant DNA sequences for species identification, thus enabling effective conservation efforts. We used DNA barcoding techniques and for analysis used the Maximum Parsimony tree in MEGA 11 with the Kimura 2-parameter (KP model) to analyse the genetic relationships between species. Out of the 13 accessions that were studied, 12 accessions belonged to Curcuma caesia and 1 accession belonged to Curcuma aeruginosa. The genetic relationships observed were correlated with the geographical distributions of these species. It was determined that C. aeruginosa is a mutated species of C. caesia. Additionally, 1 specimen of Alpinia galanga, a plant species related to the Zingiberaceae. Barcode primer trnL primer demonstrated a 92% efficiency during the investigation. The rbcL and trnL loci are recommended as potential barcode markers for discriminating between different plant species. This study developed a comprehensive DNA barcoding database that can confidently differentiate between species by combining morphological and molecular data. This database has the potential to identify adulteration in herbal products, combat illegal trade and adulteration of plant species, and assist in germplasm conservation efforts.

Dissecting the interaction between Graphene Oxide and Human Transferrin via biophysical, biochemical and in-silico approaches: Implications for nanomaterial anti-fibrillation properties and protein structure

Human Transferrin (HTF) plays a pivotal role in numerous neurological therapies by carrying drugs and nanomaterials through the challenging blood-brain barrier. Nonetheless, the binding of HTF with highly relevant nanomaterials is not fully comprehended. Here, the nanomaterial graphene oxide (GO) has been obtained and their interaction with HTF in the native and fibrillar form has been investigated, by employing multi-spectroscopic, modeling, and microscopic techniques. The fluorescence results reveal that GO quenches the HTF intrinsic fluorescence by following a mix of static and dynamic mechanisms, and the GO-HTF complex formation has been confirmed by UV-Vis spectroscopy. Additionally, HTF attaches firmly to GO (KS≈ 106M−1) through mainly by hydrophobic and hydrogen bonds (according to determined ΔH=-23.77±1.03 kJ.mol−1 and ΔS= +39.53 ± 1.69 J.mol−1.K−1). Further, the in-silico investigation has evidenced the residues and chemical groups involved in HTF-GO interaction. Furthermore, SEM images reveal the formation and inhibition of HTF aggregates by GO, and spectroscopic methods reveal the related protein structural modification involved in the fibrillation process. In summary, all the results open questions concerning GO use for many neurological therapies.

Targeting CERS6-AS1/FGFR1 axis as synthetic vulnerability to constrain stromal cells supported proliferation in Mantle cell lymphoma.

The interaction between stromal and tumor cells in tumor microenvironment is a crucial factor in Mantle cell lymphoma (MCL) progression and therapy resistance. We have identified a long non-coding RNA, CERS6-AS1, upregulated in MCL and associated with poor overall survival. CERS6-AS1 expression was elevated in primary MCL within stromal microenvironment and in a subset of MCL cells adhered to stromal layer. These stromal-adhered MCL-subsets exhibited cancer stem cell signatures than suspension counterparts. Mechanistically, we found that downregulating CERS6-AS1 in MCL reduced Fibroblast Growth Factor Receptor-1 (FGFR1), expression attributed to loss of its interaction with RNA-binding protein nucleolin. In addition, using in-silico approach, we have discovered a direct interaction between nucleolin and 5'UTR of FGFR1, thereby regulating FGFR1 transcript stability. We discovered a positive association of CERS6-AS1 with cancer stem cell signatures, and Wnt signaling. Building on these, we explored potential therapeutic strategies where combining nucleolin-targeting agent with FGFR1 inhibition significantly contributed to reversing cancer stem cell signatures and abrogated primary MCL cell growth on stromal layer. These findings provide mechanistic insights into regulatory network involving CERS6-AS1, nucleolin, and FGFR1 axis-associated crosstalk between tumor cells and stromal cell interaction and highlights therapeutic potential of targeting a non-coding RNA in MCL.

Repurposing Quercetin In Treating Parkinson’s Disease With Network Based Protein-Protein Interactions And Molecular Docking Studies

Quercetin a flavonoid found in fruits and vegetables is well known for its antioxidant, anti-inflammatory, antimicrobial, and neuroprotective properties. An insilico approach has been adapted in this study for repurposing Quercetin as a potential drug candidate for the treatment of Parkinson’s disease (PD) and other neurodegenerative disorders.

The Functional Role of microRNAs and mRNAs in Diabetic Kidney Disease: A Review.

Diabetes is a group of diseases marked by poor control of blood glucose levels. Diabetes mellitus (DM) occurs when pancreatic cells fail to make insulin, which is required to keep blood glucose levels stable, disorders, and so on. High glucose levels in the blood induce diabetic effects, which can cause catastrophic damage to bodily organs such as the eyes and lower extremities. Diabetes is classified into many forms, one of which is controlled by hyperglycemia or Diabetic Kidney Disease (DKD), and another that is not controlled by hyperglycemia (nondiabetic kidney disease or NDKD) and is caused by other factors such as hypertension, hereditary. DKD is associated with diabetic nephropathy (DN), a leading cause of chronic kidney disease (CKD) and end-stage renal failure. The disease is characterized by glomerular basement membrane thickening, glomerular sclerosis, and mesangial expansion, resulting in a progressive decrease in glomerular filtration rate, glomerular hypertension, and renal failure or nephrotic syndrome. It is also represented by some microvascular complications such as nerve ischemia produced by intracellular metabolic changes, microvascular illness, and the direct impact of excessive blood glucose on neuronal activity. Therefore, DKD-induced nephrotic failure is worse than NDKD. MicroRNAs (miRNAs) are important in the development and progression of several diseases, including diabetic kidney disease (DKD). These dysregulated miRNAs can impact various cellular processes, including inflammation, fibrosis, oxidative stress, and apoptosis, all of which are implicated during DKD. MiRNAs can alter the course of DKD by targeting several essential mechanisms. Understanding the miRNAs implicated in DKD and their involvement in disease development might lead to identifying possible therapeutic targets for DKD prevention and therapy. Therefore, this review focuses specifically on DKD-associated DN, as well as how in-silico approaches may aid in improving the management of the disease.

An in-silico approach towards multivariate acceptable ranges in biopharmaceutical manufacturing

Multivariate interactions between process parameters can heavily impact product quality and process performance in biopharmaceutical manufacturing processes. Thus, multivariate interactions should be identified and appropriately controlled. This article describes an in-silico approach to establish multivariate acceptable ranges; these ranges help to illustrate the combined impact of multiple input variables on product quality and process performance. Additionally, this article includes a case study for a monoclonal antibody polishing application.Proven acceptable ranges are set by changing only one input parameter at a time while keeping all others constant to understand the impact of process variability on product quality or process performance, but the impact of synergistic variables are not evaluated. Within multivariate acceptable ranges, any combination of input parameters of a unit operation yields the desired product quality and process performance. The layered approach applied in this article is based on risk assessment and statistical models to leverage prior knowledge and existing data. The risk assessment is specific for a manufacturing facility but is applicable to multiple products manufactured in the same facility. No additional wet-lab experiments are required for building the statistical models when development and process characterization are executed using a design of experiments approach, compared to a univariate evaluation of data. The established multivariate acceptable range justifies revised normal operating ranges to ensure process control. Further, the determination of multivariate acceptable ranges adds to overall process knowledge, ultimately supporting the implementation of a more effective control strategy.

Exploring the Molecular Mechanisms of Huaier on Modulating Metabolic Reprogramming of Hepatocellular Carcinoma: A Study based on Network Pharmacology, Molecular Docking and Bioinformatics.

Huaier (Trametes robiniophila Murr), a traditional Chinese medicine, is widely used in China as a complementary and alternative therapy to treat hepatocellular carcinoma (HCC). Past studies have shown that Huaier can arrest the cell cycle, promote apoptosis and inhibit the proliferation of cancer cells. However, how it regulates the metabolism of HCC is still unclear. This study explores the metabolic-related function of Huaier in treating HCC with an in-silico approach. A network pharmacology and bioinformatics-based approach was employed to investigate the molecular pathogenesis of metabolic reprogramming in HCC with Huaier. The compounds of Huaier were obtained from public databases. Oral bioavailability and drug likeness were screened using the TCMSP platform. The differential gene expressions between HCC and non-tumor tissue were calculated and used to find the overlap from the targets of Huaier. The enrichment analysis of the overlapped targets by Metascape helped filter out the metabolism-related targets of Huaier in treating HCC. Protein-protein interaction (PPI) network construction and topological screening revealed the hub nodes. The prognosis and clinical correlation of these targets were validated from the cancer genome atlas (TCGA) database, and the interactions between the hub nodes and active ingredients were validated by molecular docking. The results showed that Peroxyergosterol, Daucosterol, and Kaempferol were the primary active compounds of Huaier involved in the metabolic reprogramming of HCC. The top 6 metabolic targets included AKR1C3, CYP1A1, CYP3A4, CYP1A2, CYP17A1, and HSD11B1. The decreased expression of CYP3A4 and increased expression of AKR1C3 were related to the poor overall survival of HCC patients. The molecular docking validated that Peroxyergosterol and Kaempferol exhibited the potential to modulate CYP3A4 and AKR1C3 from a computational perspective. This study provided a workflow for understanding the mechanism of Huaier in regulating the metabolic reprogramming of HCC.

Pantothenate kinase: A promising therapeutic target against pathogenic Clostridium species

Current treatment of clostridial infections includes broad-spectrum antibiotics and antitoxins, yet antitoxins are ineffective against all Clostridium species. Moreover, rising antimicrobial resistance (AMR) threatens treatment effectiveness and public health. This study therefore aimed to discover a common drug target for four pathogenic clostridial species, Clostridium botulinum, C. difficile, C. tetani, and C. perfringens through an in-silico core genomic approach. Using four reference genomes of C. botulinum, C. difficile, C. tetani, and C. perfringens, we identified 1484 core genomic proteins (371/genome) and screened them for potential drug targets. Through a subtractive approach, four core proteins were finally identified as drug targets, represented by type III pantothenate kinase (CoaX) and, selected for further analyses. Interestingly, the CoaX is involved in the phosphorylation of pantothenate (vitamin B5), which is a critical precursor for coenzyme A (CoA) biosynthesis. Investigation of druggability analysis on the identified drug target reinforces CoaX as a promising novel drug target for the selected Clostridium species. During the molecular screening of 1201 compounds, a known agonist drug compound (Vibegron) showed strong inhibitory activity against targeted clostridial CoaX. Additionally, we identified tazobactam, a beta-lactamase inhibitor, as effective against the newly proposed target, CoaX. Therefore, identifying CoaX as a single drug target effective against all four clostridial pathogens presents a valuable opportunity to develop a cost-effective treatment for multispecies clostridial infections.

Novel derivatives of Costus igneus towards potentiality against diabetes mellitus receptors: ADME/Tox profiling, Computational Docking, and Molecular Dynamics Simulation study

Costus igneus has been practiced to alleviate a range of human ailments and the substantial vision was to explore potential bio-active compounds of Costus igneus to better comprehend the underlying mechanism in the management of diabetes. In-silico approach using AutoDock and Desmond, the anti-diabetic efficacy of discovered phytochemicals was evaluated. The best-docked were chosen for simulation studies. The molecular dynamic modelling showed that the complexes of ligands with receptors were stable during a time of 100 ns, which further confirmed and enhanced their significant binding affinity. According to docking scores and simulation studies, these phytocompounds could be targeted to garner efficient preventive medications for diabetes from a biological source using contemporary technology, and further in vivo and in vitro research of these compounds may be encouraged in the search for a potent treatment for the disease.

Virtual Screening of a Series of Phytocompounds from Polygonum cuspidatum for Identification of Potential Antibacterial Drug Candidates: an In-silico and Drug Design Approaches

Virtual Screening of a Series of Phytocompounds from Polygonum cuspidatum for Identification of Potential Antibacterial Drug Candidates: an In-silico and Drug Design Approaches