Binding Site Of Target Protein Research Articles

Hybrid Caffeic Acid-Based DHFR Inhibitors as Novel Antimicrobial and Anticancer Agents

A novel series of 1,2,4-triazole analogues of caffeic acid was designed, synthesized, characterized, and assessed for their capacity to inhibit DHFR, as well as their anticancer and antimicrobial properties. A molecular docking analysis was conducted on DHFR, utilizing PDB IDs 1U72 and 2W9S, aiming to design anticancer and antimicrobial drugs, respectively. Among all the synthesized derivatives, compound CTh7 demonstrated the highest potency as a DHFR inhibitor, with an IC50 value of 0.15 μM. Additionally, it exhibited significant cytotoxic properties, with an IC50 value of 8.53 µM. The molecular docking analysis of the CTh7 compound revealed that it forms strong interactions with key residues of homo sapiens DHFR such as Glu30, Phe34, Tyr121, Ile16, Val115, and Phe31 within the target protein binding site and displayed excellent docking scores and binding energy (−9.9; −70.38 kcal/mol). Additionally, synthesized compounds were screened for antimicrobial properties, revealing significant antimicrobial potential against bacterial strains and moderate effects against fungal strains. Specifically, compound CTh3 exhibited notable antibacterial efficacy against Staphylococcus aureus (MIC = 5 µM). Similarly, compound CTh4 demonstrated significant antibacterial activity against both Escherichia coli and Pseudomonas aeruginosa, with MIC values of 5 µM for each. A docking analysis of the most active antimicrobial compound CTh3 revealed that it forms hydrogen bonds with Thr121 and Asn18, a π–cation bond with Phe92, and a salt bridge with the polar residue Asp27.

Computational insight into the spectroscopic and molecular docking analysis of estrogen receptor with ligand 2,3-dimethyl-N[2-(hydroxy)benzylidene] aniline

A comprehensive approach encompassing a blend of spectral techniques and Density Functional Theory (DFT) was employed to elucidate the electronic, vibrational, structural, and nonlinear optical properties of 2,3-dimethyl-N[2-(Hydroxy)benzylidene] aniline (DNHBA). The investigation of this chemical compound involved a meticulous examination using spectroscopic techniques (FTIR, FT-Raman). The DFT calculations utilized the B3LYP method in conjunction with 6-311G (d, p) basis sets. The findings were substantiated by comparing the estimated vibrational frequencies and molecule geometry with experimental data. Using the Time Dependent −Density Functional Theory (TD-DFT) method to calculate the energy band gap of the compound at different solvents. We looked into frontier molecular orbitals (FMO) Molecular electrostatic potential (MEP) and natural bond analysis (NBO) to determine the compound’s kinetic stability and chemical reactivity. Hirshfeld surface (HS) analysis calculated the O–H..O, H-H and intermolecular interaction energy of the compound. The electron density distribution, interactions, and excitation within the title molecule are illustrated by performing topological analyses (RDG, ELF and LOL) using the Multiwfn software. In addition to these assessments, molecular dynamics provides an understanding of the system's dynamic development over a predefined duration during which atoms and molecules are permitted to interact. Utilizing the molecular docking approach allows us to energize the atomic-level interplay between small molecules and proteins within the binding sites of target proteins. This approach enhances our comprehension of vital biochemical processes associated with the behavior of small molecule. The intricacy and hazards associated with drug discovery and development processes have increased dramatically, leading to higher drug research costs.

Evaluation of influence of Butea monosperma floral extract on inflammatory biomarkers

Abstract Butea monosperma is a deciduous tree, widely distributed throughout India, Burma, and Ceylon. The present study was intended to investigate the anti-inflammatory effects of Butea monosperma on the induced inflammatory model by evaluating pro-inflammatory biomarkers and their computational analysis. The anti-inflammatory activity may be attributed to the phyto-constituents for inhibitory effects on the two pro-inflammatory mediators (IL-8 and TNF-α). For this purpose, rats (n = 48) were equally divided in each group, i.e., 8 each in the negative and positive control and 32 in the experimental group with 8 rats for each dose, i.e., 50, 100, 200, and 400 mg/kg. TNF-α and IL-8 were tested by serum enzyme-linked immunosorbent assay (ELISA). The ELISA results showed 400 mg/kg dose as the potent anti-inflammatory. The binding sites of target proteins (TNF-α and IL-8) were docked with the active compounds (butrin and butein) of Butea monosperma. The butrin (target: TNF-α) and butein (target: IL-8) showed −8.4 and −6.0 kcal/mol binding energies, respectively, compared to the (diclofenac) standard drug with −6.8 kcal/mol binding energy. Hence, we concluded that Butea monosperma can be subjected to as a useful anti-inflammatory drug.

AutoDock Koto: A Gradient Boosting Differential Evolution for Molecular Docking

Molecular docking plays a vital role in modern drug discovery, by supporting predictions of the binding modes and affinities of ligands at the binding site of target proteins. Several docking programs have been developed for both commercial and academic applications. Typically, a docking program’s performance depends on the sampling algorithm used to generate the ligand’s potential conformations and the scoring function applied to evaluate and rank these conformations. Evolutionary algorithms are widely used as sampling algorithms in docking programs. However, both the linkage problem and the dimensionality degenerate the search ability of evolutionary algorithms in the docking process. Therefore, a newly designed docking program named AutoDock Koto was developed in this study, which adopts a novel gradient boosting differential evolution algorithm to effectively address these issues. Experimental results show that compared with commonly used docking programs, AutoDock Koto yields dramatic improvements in docking performance based on an extensive dataset of 285 protein-ligand complexes. In addition, due to its strong docking ability, AutoDock Koto was used to identify potential drugs for COVID-19 based on a virtual screening of all approved drugs in our experiments. Sixteen drugs are found to possess low binding energy to the main target protease of SARS-CoV-2, and thus have the potential to treat COVID-19 as antiviral drugs. The source code of AutoDock Koto can be downloaded for free from. https://github.com/codezhouj/Molecular_Docking.

A Comparative Study of Binding Interactions of Natural Flavonoids and Conventional Drug Donepezil for Multiple Alzheimer's Disease Targets Using In silico Approach

Background: Alzheimer's disease (AD) is one of the major causes of morbidity, affecting more than 36 million population worldwide. Current anti-AD treatments result in limited therapeutic outcomes owing to the complexity of the disease. Some natural promising herbal drugs and phytoconstituents utilized as an alternative treatment for AD have been reported by several researchers for their neuroprotective action. Objective: This study aimed at carrying out molecular docking studies of selected promising flavonoids such as curcumin, quercetin, bilobalide, ferulic acid, reseveratrol for their molecular interactions with multiple AD target proteins and further compare the data with the standard acetylcholine esterase inhibitor drug donepezil. Methods: The molecular docking interactions were studied between the selected actives and the AD target proteins acetylcholine esterase, butyrylcholine esterase, and tau protein using the AutoDock Vina software. The Swiss ADME approach performed prediction of the ADME properties. Binding interactions of the ligands at the target protein binding sites were examined using the Discovery Studio Visualizer 2021. Results: The binding energy for quercetin in the active site of the selected target enzymes acetylcholine esterase, butyrylcholine esterase, and tau protein was -9.5 , -7.8 , and -8.2 kcal/mol, respectively which was much greater than other flavonoids and comparable to the standard drug donepezil binding energy - 10.3, -7.5,-7.9 kcal/mol respectively. Conclusion: This work focuses on recognizing structural features and comparing selected flavonoids and standard acetylcholine esterase (AChEs) inhibitors for molecular docking with three primary targets of AD, namely AChEs, Butyrylcholine esterase, and tau protein. This in silico study concluded that quercetin had significant docking interactions and good pharmacokinetic features, making it a potential therapeutic candidate for the treatment of AD.

‘Synthesis, antiviral activity, molecular docking, and molecular dynamics studies of ethoxy phthalimide pyrazole derivatives against Cytomegalovirus and Varicella-Zoster virus: potential consequences and strategies for developing new antiviral treatments’

Substituted ethoxy phthalimide pyrazole derivatives (6a–e) have been produced using a one-pot synthesis technique. Spectral analysis was used to establish the molecular structure of the synthesized compounds, and they were examined in silico and in vitro for their ability to bind to and inhibit replication of the AD-169 strain, the Davis strain of CMV, the OKA strain and the 07/1 strain of Varicella-Zoster virus (VZV). Molecular Docking was used to estimate the binding mechanism and energy of compounds 4, 6a–e to their respective target proteins, thymidine kinase (TK), Varicella-Zoster protease (VZP) of VZV and tegument protein pp71 (TPpp71) of Cytomegalovirus (CMV). The MIC50 and EC50 were utilized to evaluate the antiviral and cytotoxic activities of test compounds in human embryonic lung (HEL) cells against the two reference medicines, Ganciclovir and Acyclovir. The chemicals studied showed a high affinity for binding sites and near binding sites of target proteins by generating H-bonds, carbon-hydrogen bonds, π-anion, π-sulfur, π-sigma, alkyl and π-alkyl interactions. All of the test compounds (6a–e) had higher binding energy than the standard medications. The ADME/T data suggests that these potential inhibitors are less toxic. Drug-protein complexes are structurally compact and demonstrate minimal conformational change in molecular dynamics (MDs) simulations, indicating stability and stiffness. MM-PBSA and post-simulation analysis can predict lead compound active cavity binding stability. By inhibiting multitargeted proteins, these synthetic compounds may improve antiviral therapy. Our research suggests that these unique synthesized chemicals may be useful and accessible adjuvant antiviral therapy for Varicella Zoster and CMV. Highlights Two components synthesis of substituted ethoxy phthalimide pyrazole derivatives (6a–e). Tested compounds (6a–e) have antiviral and cytotoxicity activity against CMV and Varicella-Zoster virus (VZV) in HEL cells. Compounds bind to TK, Varicella-Zoster protease (VZP) of VZV, and modeled TPpp71 of Cytomegalovirus (CMV). In comparison to reference drugs, compounds have strong binding free energy and interactions with VZV and CMV protein complexes. The RMSD, RMSF, Rg, residual correlative motion (RCM), No. of hydrogen bonds, protein secondary structure content, per-residue protein secondary structure and MM/PBSA energy calculated for the selected compound with thymidine kinase (TK), VZP of VZV, and modeled tegument protein pp71 (TPpp71) of CMV through MD simulation studies for 50 ns. In comparison to the two reference drugs, ligands/compounds were found to meet the Lipinski rule of five and to have strong biological activity. Communicated by Ramaswamy H. Sarma

Green Tea Catechins as Potential Drug Scaffolding Molecules in Structural Studies with Diverse Protein Targets

Abstract: Previous studies provide substantial evidence that catechins, polyphenol bioactive compounds, exhibit medicinal benefits. These polyphenols are found in abundance in green teas, including a combination of the four major types of catechins: (-)-Epicatechin (EC), (-)-Epicatechin-3-gallate (ECG), (-)- Epigallocatechin (EGC), and (-)- Epigallocatechin-3-gallate (EGCG). Although all four exhibit medicinal benefits, the catechin cited in the literature the most is EGCG, so derivatives of this catechin were selected for these studies. Literature searches identified catechins as biologically active compounds for a diverse set of diseases ranging from cancer, metabolism, neurological, and neuromuscular ailments. A diverse set of potential protein targets for docking with catechin derivatives was first identified as a list (n = 48). The targets were then selected based on the presence of 3D protein coordinates for these targets provided by the Rutgers Consortium for Structural Biology (RCSB) Protein Data Bank (PDB) (n = 10). The surfaces of the 3D protein targets were evaluated with computational methods to identify potential binding sites for the EGCG catechin derivatives. Static and flexible docking was done using target protein binding sites performed with the catechin derivatives followed by molecular dynamics (MD). MD protocols were run to confirm binding in the physiological range and environment. In summary, the results of computational protocols confirmed predicted binding by docking with MD of several catechin derivatives to be used as scaffolds once validated in lab-based assays. Possible changes to these scaffolding molecules that could result in tighter, more specific binding is discussed.

High-throughput virtual screening approach and dynamic simulation of natural compounds as target inhibitors of BACE1 in Alzheimer's disease

Background Beta-site amyloid precursor protein cleaving enzyme 1 (BACE1) protein holds significance in the development of Alzheimer’s disease (AD). This protein is highly expressed in the central nervous system, playing a significant role in the conversion of amyloid precursor protein (APP) into amyloid-beta peptides. The primary objective of the current study was to perform in silico inhibition investigations on this protein, utilizing computational methodologies such as molecular docking and molecular dynamics, to identify novel inhibitors with potential against BACE1. Our focus was on targeting the active site of BACE1, aiming to discover optimal interactions between the ligands and key residues of the target protein. Methods The natural compounds inhibitors data was carefully reviewed from the literature review articles. Molecular docking was conducted using AutoDock Vina with an active site defined by CB-Dock2. We assessed drug-likeness and toxicity using Lipinski’s rule of fives via SwissADME and the ProTox-II web server. Interaction visualization was facilitated using Discovery Studio, while molecular dynamics simulations were performed for 100 nanoseconds with hinokiflavone and BACE1 using Schrodinger LLC Desmond software. Results The molecular docking results showed promising binding affinities and the best binding free energy values were selected, and after conducting Lipinski’s rule of five using SwissADME as well as predicting toxicity using ProTox-II, only one molecule, hinokiflavone was filtered and succeeded in all the analyses to be a potential candidate. Molecular docking results were supported by molecular dynamics simulation. These results demonstrate the stability of the compound in the target protein binding site. Conclusions Finally, these obtained outcomes represent a strong lead to developing promising new natural compound inhibitors against BACE1. For future works, it is essential to concentrate on further experimental validation to ensure the effectiveness of the proposed approach.

Radioprotective Effects of Carvacrol and/or Thymol against Gamma Irradiation-Induced Acute Nephropathy: In Silico and In Vivo Evidence of the Involvement of Insulin-like Growth Factor-1 (IGF-1) and Calcitonin Gene-Related Peptide.

Radiotherapy (RT) is an effective curative cancer treatment. However, RT can seriously damage kidney tissues resulting in radiotherapy nephropathy (RN) where oxidative stress, inflammation, and apoptosis are among the common pathomechanisms. Carvacrol and thymol are known for their antioxidative, anti-inflammatory, and radioprotective activities. Therefore, this study investigated the nephroprotective potentials of carvacrol and/or thymol against gamma (γ) irradiation-induced nephrotoxicity in rats along with the nephroprotection mechanisms, particularly the involvement of insulin-like growth factor-1 (IGF-1) and calcitonin gene-related peptide (CGRP). Methods: Male rats were injected with carvacrol and/or thymol (80 and 50 mg/kg BW in the vehicle, respectively) for five days and exposed to a single dose of irradiation (6 Gy). Then, nephrotoxicity indices, oxidative stress, inflammatory, apoptotic biomarkers, and the histopathological examination were assessed. Also, IGF-1 and CGRP renal expressions were measured. Results: Carvacrol and/or thymol protected kidneys against γ-irradiation-induced acute RN which might be attributed to their antioxidative, anti-inflammatory, and antiapoptotic activities. Moreover, both reserved the γ -irradiation-induced downregulation of CGRP- TNF-α loop in acute RN that might be involved in the pathomechanisms of acute RN. Additionally, in Silico molecular docking simulation of carvacrol and thymol demonstrated promising fitting and binding with CGRP, IGF-1, TNF-α and NF-κB through the formation of hydrogen, hydrophobic and alkyl bonds with binding sites of target proteins which supports the reno-protective properties of carvacrol and thymol. Collectively, our findings open a new avenue for using carvacrol and/or thymol to improve the therapeutic index of γ-irradiation.

μMap Photoproximity Labeling Enables Small Molecule Binding Site Mapping.

The characterization of ligand binding modes is a crucial step in the drug discovery process and is especially important in campaigns arising from phenotypic screening, where the protein target and binding mode are unknown at the outset. Elucidation of target binding regions is typically achieved by X-ray crystallography or photoaffinity labeling (PAL) approaches; yet, these methods present significant challenges. X-ray crystallography is a mainstay technique that has revolutionized drug discovery, but in many cases structural characterization is challenging or impossible. PAL has also enabled binding site mapping with peptide- and amino-acid-level resolution; however, the stoichiometric activation mode can lead to poor signal and coverage of the resident binding pocket. Additionally, each PAL probe can have its own fragmentation pattern, complicating the analysis by mass spectrometry. Here, we establish a robust and general photocatalytic approach toward the mapping of protein binding sites, which we define as identification of residues proximal to the ligand binding pocket. By utilizing a catalytic mode of activation, we obtain sets of labeled amino acids in the proximity of the target protein binding site. We use this methodology to map, in vitro, the binding sites of six protein targets, including several kinases and molecular glue targets, and furthermore to investigate the binding site of the STAT3 inhibitor MM-206, a ligand with no known crystal structure. Finally, we demonstrate the successful mapping of drug binding sites in live cells. These results establish μMap as a powerful method for the generation of amino-acid- and peptide-level target engagement data.

Discovery of a Hidden Trypanosoma cruzi Spermidine Synthase Binding Site and Inhibitors through In Silico, In Vitro, and X-ray Crystallography.

In drug discovery research, the selection of promising binding sites and understanding the binding mode of compounds are crucial fundamental studies. The current understanding of the proteins-ligand binding model extends beyond the simple lock and key model to include the induced-fit model, which alters the conformation to match the shape of the ligand, and the pre-existing equilibrium model, selectively binding structures with high binding affinity from a diverse ensemble of proteins. Although methods for detecting target protein binding sites and virtual screening techniques using docking simulation are well-established, with numerous studies reported, they only consider a very limited number of structures in the diverse ensemble of proteins, as these methods are applied to a single structure. Molecular dynamics (MD) simulation is a method for predicting protein dynamics and can detect potential ensembles of protein binding sites and hidden sites unobservable in a single-point structure. In this study, to demonstrate the utility of virtual screening with protein dynamics, MD simulations were performed on Trypanosoma cruzi spermidine synthase to obtain an ensemble of dominant binding sites with a high probability of existence. The structure of the binding site obtained through MD simulation revealed pockets in addition to the active site that was present in the initial structure. Using the obtained binding site structures, virtual screening of 4.8 million compounds by docking simulation, in vitro assays, and X-ray analysis was conducted, successfully identifying two hit compounds.

Chromatin Immunoprecipitation to Identify Target Protein Binding Sites on Genomic DNA

Chromatin Immunoprecipitation to Identify Target Protein Binding Sites on Genomic DNA

Chromatin Immunoprecipitation to Identify Target Protein Binding Sites on Genomic DNA

Chromatin Immunoprecipitation to Identify Target Protein Binding Sites on Genomic DNA

System analysis of Huang-Lian-Jie-Du-Tang and their key active ingredients for overcoming CML resistance by suppression of leukemia stem cells

BackgroundBCR-ABL1-based resistance to imatinib, mainly resulting from BCR-ABL1 mutations, is largely solved after second- and third-generation tyrosine kinase inhibitors (TKIs) are discovered. Nonetheless, imatinib resistance without BCR-ABL1 mutations, including intrinsic resistance induced by stem cells within chronic myeloid leukemia (CML), remains the major clinical challenge for many patients. PurposeTo study the key active ingredients and corresponding target proteins in Huang-Lian-Jie-Du-Tang (HLJDT) against BCR-ABL1-independent CML resistance to therapeutics, and then explore its mechanism of against CML drug resistance. MethodsCytotoxicity of HLJDT and its active ingredients in BCR-ABL1-independent imatinib resistance cells was analyzed through MTT assay. The cloning ability was measured through soft agar assay. Monitoring therapeutic effect on Xenografted mice CML model by in vivo imaging technology and mice survival time. Predicting the potential target protein binding sites by the technology of photocrosslinking sensor chip, molecular space simulation docking, and use Surface Plasmon Resonance (SPR) technology . Flow cytometry to detect the ratio of stem progenitor cells (CD34+). Constructing bone marrow transplantation mice CML leukemia model, detect the effects on leukemia stem cells LSK (Lin-\\ Sca-1+ \\C-kit+) self-renewal. ResultsTreatment with HLJDT, berberine and baicalein inhibited cell viability and colony formation of BCR-ABL1-independent imatinib-resistant cells in vitro while prolonging survival in mouse with CML xenografts and transplatation CML-like mouse models in vivo. JAK2 and MCL1were identified as targets of berberine and baicalein. JAK2 and MCL1 are involved in multi-leukemia stem cell-related pathways. Moreover, the ratio of CD34+ cells in resistant CML cells is higher than in treatment-sensitive CML cells. Treatment with BBR or baicalein partially suppressed CML leukemic stem cells (LSCs) self-renewal in vitro and in vivo. ConclusionFrom the above, we concluded that HLJDT and its key active ingredients (BBR and baicalein) allowed to overcome imatinib resistance with BCR-ABL1 independent by eradication of LSCs by targeting the JAK2 and MCL1 protein levels. Our results lay the foundation for applying HLJDT in patients with TKI-resistant CML.

Molecular modeling study of pyrrolidine derivatives as novel myeloid cell leukemia-1 inhibitors through combined 3D-QSAR, molecular docking, ADME/Tox and MD simulation techniques

A series of pyrrolidine derivatives have been used to study the main structural requirements for designing novel Mcl-1 inhibitors. For this purpose, three models CoMSIA, CoMFA and HQSAR were generated using QSAR molecular modeling techniques. The statistical results of the CoMFA (Q2 = 0.689; R = 0.999; R2pred = 0.986), CoMSIA (Q2 = 0.614; R2 = 0.923; R2pred = 0.815) and HQSAR (Q2= 0.603; R2 = 0.662; R2pred = 0.743) models showed good stability and predictability. The results of the models were presented as contours and colored fragments indicating the favorable and unfavorable contribution to the inhibitory activity of Mcl-1. Based on the obtained results, four new compounds were designed with more potent predicted pIC50 inhibitory activity. The ADME/Tox results and the pharmacokinetic properties revealed that these four compounds are orally bioavailable and show good permeability. In addition the four compounds showing non-inhibitors of CYP3A4 and CYP2D6 with the exception of Pred03. At the level of toxicity profile, the compounds Pred01, Pred02 and Pred03 showed interesting results and showed no AMES toxicity, no hERG inhibition and no skin sensitization. Molecular docking results were used to uncover the mode of interaction between the ligand and key residues of protein binding site. Molecular docking results were supported by molecular simulation and binding free energy estimation (MMPBSA). These results demonstrate the stability of the analyzed compounds in the target protein binding site during a 100 ns trajectory. Finally, all these results create a strong lead to develop promising new Pyrrolidine-based inhibitors against Mcl-1.Communicated by Ramaswamy H. Sarma

De novo design of anti-tuberculosis agents using a structure-based deep learning method

Mycobacterium tuberculosis (Mtb) is a pathogen of major concern due to its ability to withstand both first- and second-line antibiotics, leading to drug resistance. Thus, there is a critical need for identification of novel anti-tuberculosis agents targeting Mtb-specific proteins. The ceaseless search for novel antimicrobial agents to combat drug-resistant bacteria can be accelerated by the development of advanced deep learning methods, to explore both existing and uncharted regions of the chemical space. The adaptation of deep learning methods to under-explored pathogens such as Mtb is a challenging aspect, as most of the existing methods rely on the availability of sufficient target-specific ligand data to design novel small molecules with optimized bioactivity. In this work, we report the design of novel anti-tuberculosis agents targeting the Mtb chorismate mutase protein using a structure-based drug design algorithm. The structure-based deep learning method relies on the knowledge of the target protein's binding site structure alone for conditional generation of novel small molecules. The method eliminates the need for curation of a high-quality target-specific small molecule dataset, which remains a challenge even for many druggable targets, including Mtb chorismate mutase. Novel molecules are proposed, that show high complementarity to the target binding site. The graph attention model could identify the probable key binding site residues, which influenced the conditional molecule generator to design new molecules with pharmacophoric features similar to the known inhibitors.

Investigation of anti-diabetic potential and molecular simulation studies of dihydropyrimidinone derivatives.

In an attempt to find new targets for α-amylase and α-glucosidase for the treatment of type 2 diabetes mellitus, the present study aims in determining the anti-diabetic potential of synthesized dihydropyrimidinone derivatives. The in vitro α-glucosidase and α-amylase inhibitory activity was performed and the molecular docking analysis of the ligand in the active binding site of target protein was determined. The results revealed significant percent inhibition of α-glucosidase by the compound 6-benzyl-4-(4-hydroxyphenyl)-3,4,6,7-tetrahydro-1H-pyrrolo[3,4-d]pyrimidine-2,5-dione (compound A). The active compound showed 81.99% inhibition when compared to standard ascorbic acid having percent inhibition 81.18%. The IC50 of active compound (A) showed to be 1.02 µg/ml. The molecular docking analysis revealed that the ligand bound to the active binding site of protein with the lowest binding energy of -7.9 kcal/mol that was also significantly similar to standard having -7.8 kcal/mol binding energy. The molecular dynamic simulation studies also revealed stable binding of ligand in the active binding site of protein with low RMSD of 1.7 Å similar to the protein RMSD 1.6Å In conclusion, the study revealed a potential new target against α-glucosidase to treat type 2 diabetes mellitus.

Quantitative Frameworks for Multivalent Macromolecular Interactions in Biological Linear Lattice Systems.

Multivalent macromolecular interactions underlie dynamic regulation of diverse biological processes in ever-changing cellular states. These interactions often involve binding of multiple proteins to a linear lattice including intrinsically disordered proteins and the chromosomal DNA with many repeating recognition motifs. Quantitative understanding of such multivalent interactions on a linear lattice is crucial for exploring their unique regulatory potentials in the cellular processes. In this review, the distinctive molecular features of the linear lattice system are first discussed with a particular focus on the overlapping nature of potential protein binding sites within a lattice. Then, we introduce two general quantitative frameworks, combinatorial and conditional probability models, dealing with the overlap problem and relating the binding parameters to the experimentally measurable properties of the linear lattice-protein interactions. To this end, we present two specific examples where the quantitative models have been applied and further extended to provide biological insights into specific cellular processes. In the first case, the conditional probability model was extended to highlight the significant impact of nonspecific binding of transcription factors to the chromosomal DNA on gene-specific transcriptional activities. The second case presents the recently developed combinatorial models to unravel the complex organization of target protein binding sites within an intrinsically disordered region (IDR) of a nucleoporin. In particular, these models have suggested a unique function of IDRs as a molecular switch coupling distinct cellular processes. The quantitative models reviewed here are envisioned to further advance for dissection and functional studies of more complex systems including phase-separated biomolecular condensates.

DiMeLo-seq: a long-read, single-molecule method for mapping protein-DNA interactions genome wide.

Studies of genome regulation routinely use high-throughput DNA sequencing approaches to determine where specific proteins interact with DNA, and they rely on DNA amplification and short-read sequencing, limiting their quantitative application in complex genomic regions. To address these limitations, we developed Directed Methylation with Long-read sequencing (DiMeLo-seq), which uses antibody-tethered enzymes to methylate DNA near a target protein’s binding sites in situ. These exogenous methylation marks are then detected simultaneously with endogenous CpG methylation on unamplified DNA using long-read, single-molecule sequencing technologies. We optimized and benchmarked DiMeLo-seq by mapping chromatin-binding proteins and histone modifications across the human genome. Furthermore, we identified where centromere protein A (CENP-A) localizes within highly repetitive regions that we re unmappable with short sequencing reads, and we estimated the density of CENP-A molecules along single chromatin fibers. DiMeLo-seq is a versatile method that provides multimodal, genome-wide information for investigating protein-DNA interactions.

Secondary-structure switch regulates the substrate binding of a YopJ family acetyltransferase

The Yersinia outer protein J (YopJ) family effectors are widely deployed through the type III secretion system by both plant and animal pathogens. As non-canonical acetyltransferases, the enzymatic activities of YopJ family effectors are allosterically activated by the eukaryote-specific ligand inositol hexaphosphate (InsP6). However, the underpinning molecular mechanism remains undefined. Here we present the crystal structure of apo-PopP2, a YopJ family member secreted by the plant pathogen Ralstonia solanacearum. Structural comparison of apo-PopP2 with the InsP6-bound PopP2 reveals a substantial conformational readjustment centered in the substrate-binding site. Combining biochemical and computational analyses, we further identify a mechanism by which the association of InsP6 with PopP2 induces an α-helix-to-β-strand transition in the catalytic core, resulting in stabilization of the substrate recognition helix in the target protein binding site. Together, our study uncovers the molecular basis governing InsP6-mediated allosteric regulation of YopJ family acetyltransferases and further expands the paradigm of fold-switching proteins.