An in silico analysis of the binding modes and binding affinities of small molecule modulators of PDZ-peptide interactions

A novel peptide pair-based rapid fluorescent diagnostic system for malaria Plasmodium falciparum detection

Advanced diagnostic materials, such as aptamers, are required due to the scarcity of efficient diagnostic antibodies and the low sensitivity of rapid diagnostic kits at detecting the malaria parasite, Plasmodium falciparum.

METHODS

Two peptides M2.9 [(KPTAEQTESPELQSAPEN) and M2.17 (KILFNVYSPLGCTCECWV)] were designed using simple epitope prediction tools and modified against the merozoite surface antigen 2 of P. falciparum (Pf.MSP2) by 3-dimensional modeling based on binding affinity. Based on five prediction tools for hydropathy, M2.17 was selected as an appropriate capture peptide. A peptide-based fluorescence-linked immunosorbent assay (FLISA) and a peptide pair-based fluorescent immunochromatographic test strip (FICT) were developed to detect P. falciparum 3D7 (drug-sensitive) and P. falciparum K1 (multi drugs-resistant) strains.

RESULTS

Bioinformatic analysis of two peptides demonstrated the potential binding affinity with the merozoite surface protein 2 of P. falciparum (Pf.MSP2) with a positive hydropathy value. The limit of detection (LOD) of FLISA was 10 parasites/μL and of a peptide pair-linked rapid FICT system was 5 and 200 parasites/μL for P. falciparum 3D7 and K1, respectively. Compared to commercial rapid detection systems (RDTs), a peptide pair-linked FICT system exhibited a 20-fold greater efficiency in detecting P. falciparum 3D7 and specifically discriminated another protozoan spp.

CONCLUSION

A peptide pair-linked rapid diagnostic strip could be an alternative to conventional RDTs for monitoring wild-type and drug-resistant malaria parasites.

Molecular Design of Novel Inhibitor by Targeting IL-6Rα using Combined Pharmacophore and Experimentally Verified Plant Products with Scaffold-Hopping Techniques: A Dual Therapeutic Strategy for COVID-19 and Cancer

The IL-6/IL-6R/gp130 complex serves as a significant indicator of cytokine release syndrome in COVID-19 and chronic inflammation, increasing the risk of cancer. Therefore, we identified IL-6Rα as a potential target to block gp130 interaction. Notably, there has been no reception of approval for an orally available drug to serve this purpose, to date. In this study, we targeted IL-6Rα to inhibit IL-6Rα/gp130 interaction. The selection of the lead candidate L821 involved the amalgamation of three drug discovery approaches. This library was screened employing tertiary structure-based pharmacophore models followed by molecular docking models, scaffold-hopping, MM/PBSA as well as MM/GBSA analysis, and assessments of pKi and ADMET properties. After evaluating the binding interactions with key amino acids, 15 potential ligands were chosen, with the top ligand undergoing further investigation by means of molecular dynamics simulations. Considering the stability of the complexes, the strong interactions observed between ligand and residues of IL-6Rα/gp130, and the favorable binding free energy calculations, L821 emerged as the prime candidate for inhibiting IL-6Rα. Notably, L821 exhibited a docking-based binding affinity of -9.5 kcal/mol. Our study presents L821 as a promising inhibitor for future in vitro analysis, potentially combatting SARS-CoV-2-related cytokine storms and serving as an oncogenic drug therapy.

Profiling the Antidiabetic Potential of Compounds Identified from Fractionated Extracts of Entada africana toward Glucokinase Stimulation: Computational Insight

Glucokinase plays an important role in regulating the blood glucose level and serves as an essential therapeutic target in type 2 diabetes management. Entada africana is a medicinal plant and highly rich source of bioactive ligands with the potency to develop new target drugs for glucokinase such as diabetes and obesity. Therefore, the study explored a computational approach to predict identified compounds from Entada africana following its intermolecular interactions with the allosteric binding site of the enzymes. We retrieved the three-dimensional (3D) crystal structure of glucokinase (PDB ID: 4L3Q) from the online protein data bank and prepared it using the Maestro 13.5, Schrödinger Suite 2022-3. The compounds identified were subjected to ADME, docking analysis, pharmacophore modeling, and molecular simulation. The results show the binding potential of the identified ligands to the amino acid residues, thereby suggesting an interaction of the amino acids with the ligand at the binding site of the glucokinase activator through conventional chemical bonds such as hydrogen bonds and hydrophobic interactions. The compatibility of the molecules was highly observed when compared with the standard ligand, thereby leading to structural and functional changes. Therefore, the bioactive components from Entada africana could be a good driver of glucokinase, thereby paving the way for the discovery of therapeutic drugs for the treatment of diabetes and its related complications.

Development of a peptide aptamer pair-linked rapid fluorescent diagnostic system for Zika virus detection

A rapid diagnostic system employing an antigen detection biosensing method is needed to discriminate between Zika virus (ZIKV) and Dengue virus (DENV) due to their close antigenic homology. We developed a novel peptide pair-based flow immunochromatographic test strip (FICT) assay to detect ZIKV. Peptide aptamers, P6.1 (KQERNNWPLTWT), P29.1 (KYTTSTLKSGV), and B2.33 (KRHVWVSLSYSCAEA) were designed by paratopes and modified against the ZIKV envelope protein based on the binding affinity. An antibody-free lateral FICT was developed using a pair of peptide aptamers. In the rapid diagnostic strip, the limit of detection (LOD) for the B2.33-P6.1 peptide pair for ZIKV was 2 × 10⁴ tissue culture infective dose TCID₅₀/mL. Significantly, FICT could discriminate ZIKV from DENV. The stability and performance of FICT were confirmed using human sera and urine, showing a comparable LOD value. Our study demonstrated that in silico modeling could be used to develop a novel peptide pair-based FICT assay for detecting ZIKV by a rapid diagnostic test.

Caseinolytic Proteins (Clp) in the Genus Klebsiella: Special Focus on ClpK

Caseinolytic proteins (Clp), which are present in both prokaryotes and eukaryotes, play a major role in cell protein quality control and survival of bacteria in harsh environmental conditions. Recently, a member of this protein family, ClpK was identified in a pathogenic strain of Klebsiella pneumoniae which was responsible for nosocomial infections. ClpK is linked to the thermal stress survival of this pathogen. The genome wide analysis of Clp proteins in Klebsiella spp. indicates that ClpK is present in only 34% of the investigated strains. This suggests that the uptake of the clpk gene is selective and may only be taken up by a pathogen that needs to survive harsh environmental conditions. In silico analyses and molecular dynamic simulations show that ClpK is mainly α-helical and is highly dynamic. ClpK was successfully expressed and purified to homogeneity using affinity and anion exchange chromatography. Biophysical characterization of ClpK showed that it is predominantly alpha-helical, and this is in agreement with in silico analysis of the protein structure. Furthermore, the purified protein is biologically active and hydrolyses ATP in a concentration- dependent manner.

Rapid Detection of Avian Influenza Virus by Fluorescent Diagnostic Assay using an Epitope-Derived Peptide

Currently, the point of care testing (POCT) is not fully developed for subtype-specific avian influenza virus detection. In this study, an H5N1 hemaglutinin 1 (HA1) epitope (P0: KPNDAINF) and three modified peptides (P1: KPNTAINF, P2: KPNGAINF, P3: KPNDAINDAINF) were evaluated as POCT elements for rapid detection of avian influenza virus. Based on modeling predictions by Autodock Vina, binding affinity varied depending on alteration of one amino acid in these peptides. The binding energy of P2 indicated its potential for a strong interaction with HA. Fluorescence-linked immunosorbent assay experimentally demonstrated the interaction between these peptides and virus. The four peptides interacted with HA1 of H5N3 with different binding affinities with P2 showing the strongest binding affinity. When P0 and P2 peptides were used in rapid fluorescent immunochromatographic test (FICT) as detection elements, the inter-assay coefficients of variation (CV) indicated that P2-linked FICT was more acceptable than the P0-linked FICT in the presence of human specimens. Antibody pair-linked FICT was influenced by clinical samples more than the P2-linked FICT assay, which showed a 4-fold improvement in the detection limit of H5N3 and maintained H5 subtype-specificity. Compared to the rapid diagnostic test (RDT) which is not specific for influenza subtypes, P2-linked FICT could increase virus detection. In conclusion, results of this study suggest that HA epitope-derived peptides can be used as alternatives to antibodies for a rapid fluorescent diagnostic assay to detect avian influenza virus.

Homology modeling, substrate docking, and molecular simulation studies of mycobacteriophage Che12 lysin A

Mycobacteriophages produce lysins that break down the host cell wall at the end of lytic cycle to release their progenies. The ability to lyse mycobacterial cells makes the lysins significant. Mycobacteriophage Che12 is the first reported temperate phage capable of infecting and lysogenising Mycobacterium tuberculosis. Gp11 of Che12 was found to have Chitinase domain that serves as endolysin (lysin A) for Che12. Structure of gp11 was modeled and evaluated using Ramachandran plot in which 98 % of the residues are in the favored and allowed regions. Che12 lysin A was predicted to act on NAG-NAM-NAG molecules in the peptidoglycan of cell wall. The tautomers of NAG-NAM-NAG molecule were generated and docked with lysin A. The stability and binding affinity of lysin A - NAG-NAM-NAG tautomers were studied using molecular dynamics simulations.

Andrographolide: A potent antituberculosis compound that targets Aminoglycoside 2'-N-acetyltransferase in Mycobacterium tuberculosis

Tuberculosis (TB) still remains a major challenging infectious disease. The increased rate of emergence of multi-drug resistant and extensively-drug resistant strains of the organism has further complicated the situation, resulting in an urgent need for new anti-TB drugs. Antimycobacterial activity of Andrographis paniculata was evaluated using a rapid LRP assay and the probable targets were identified by docking analysis. The methanolic extract of A. paniculata showed maximum antimycobacterial activity at 250μg/ml against all the tested strains of M. tuberculosis (H37Rv, MDR, and drug sensitive). Based on bioassay guided fractionation, andrographolide was identified as the potent molecule. With the docking analysis, both ICDH (Isocitrate Dehydrogenase) and AAC (Aminoglycoside 2'-N-acetyltransferase) were predicted as targets of andrographolide in M. tuberculosis. Molecular simulation revealed that, ICDH showed low binding affinity to andrographolide. However, for AAC, the andrographolide was observed to be well within the active site after 10ns of molecular simulation. This suggests that ACC (PDB ID 1M4I) could be the probable target for andrographolide.

Mathematical and computational modeling in biology at multiple scales

A variety of topics are reviewed in the area of mathematical and computational modeling in biology, covering the range of scales from populations of organisms to electrons in atoms. The use of maximum entropy as an inference tool in the fields of biology and drug discovery is discussed. Mathematical and computational methods and models in the areas of epidemiology, cell physiology and cancer are surveyed. The technique of molecular dynamics is covered, with special attention to force fields for protein simulations and methods for the calculation of solvation free energies. The utility of quantum mechanical methods in biophysical and biochemical modeling is explored. The field of computational enzymology is examined.

Insights into the binding modes of CC chemokine receptor 4 (CCR4) inhibitors: a combined approach involving homology modelling, docking, and molecular dynamics simulation studies

CC chemokine receptor 4 (CCR4), a G protein-coupled receptor (GPCR), plays a vital role in the progression of asthma, T-cell lymphoma, inflammation, and Alzheimer's disease. To date, the structure of CCR4 has not been determined. Therefore, the nature of the interactions between inhibitors and CCR4 is not well known. In this study, we used CCR5 as a template to model the structure of CCR4. Docking studies were performed for four naphthalene-sulphonamide derivatives and crucial ligand-protein interactions were analysed. Molecular dynamics (MD) simulations of these complexes (100 ns each) were carried out to gain insights into the interactions between ligands and CCR4. MD simulations revealed that the residues identified by the docking were displaced and new residues were inserted near the ligands. Results of a principal component analysis (PCA) suggested that CCR4 unfolds at the extracellular site surrounding the ligands. Our simulations identified crucial residues involved in CCR4 antagonism, which were supported by previous mutational studies. Additionally, we identified Ser3.29, Leu3.33, Ser5.39, Phe6.47, Ile7.35, Thr7.38, Thr7.40, and Ala7.42 as residues that play crucial roles in CCR4 antagonism. Mutational studies will help elucidate the significance of these residues in CCR4 antagonism. An understanding of ligand-CCR4 interactions might aid in the design of novel CCR4 inhibitors.

PubChem applications in drug discovery: a bibliometric analysis

A bibliometric analysis of PubChem applications is presented by reviewing 1132 research articles. The massive volume of chemical structure and bioactivity data in PubChem and its online services have been used globally in various fields including chemical biology, medicinal chemistry and informatics research. PubChem supports drug discovery in many aspects such as lead identification and optimization, compound-target profiling, polypharmacology studies and unknown chemical identity elucidation. PubChem has also become a valuable resource for developing secondary databases, informatics tools and web services. The growing PubChem resource with its public availability offers support and great opportunities for the interrogation of pharmacological mechanisms and the genetic basis of diseases, which are vital for drug innovation and repurposing.

Structure-based multiscale approach for identification of interaction partners of PDZ domains

PDZ domains are peptide recognition modules which mediate specific protein-protein interactions and are known to have a complex specificity landscape. We have developed a novel structure-based multiscale approach which identifies crucial specificity determining residues (SDRs) of PDZ domains from explicit solvent molecular dynamics (MD) simulations on PDZ-peptide complexes and uses these SDRs in combination with knowledge-based scoring functions for proteomewide identification of their interaction partners. Multiple explicit solvent simulations ranging from 5 to 50 ns duration have been carried out on 28 PDZ-peptide complexes with known binding affinities. MM/PBSA binding energy values calculated from these simulations show a correlation coefficient of 0.755 with the experimental binding affinities. On the basis of the SDRs of PDZ domains identified by MD simulations, we have developed a simple scoring scheme for evaluating binding energies for PDZ-peptide complexes using residue based statistical pair potentials. This multiscale approach has been benchmarked on a mouse PDZ proteome array data set by calculating the binding energies for 217 different substrate peptides in binding pockets of 64 different mouse PDZ domains. Receiver operating characteristic (ROC) curve analysis indicates that, the area under curve (AUC) values for binder vs nonbinder classification by our structure based method is 0.780. Our structure based method does not require experimental PDZ-peptide binding data for training.