Structure-based Molecular Dynamics Research Articles

Virtual structure-based docking, WaterMap, and molecular dynamics guided identification of the potential natural compounds as inhibitors of protein-tyrosine phosphatase 1B

Neuroinflammation is considered as the pathological hallmark of neurodegenerative diseases, including Alzheimer's disease (AD). Under inflammatory conditions, activation of microglial cells results in the increased expression of Protein tyrosine phosphatase 1B (PTP1B) levels, enhancing pro-inflammatory response. Computation based in silico docking studies were done using maestro interface to identify the inhibitors of PTP1B. A library of 1941 phytomolecules from Zinc database was screened for evaluation of their binding potential with PTP1B. Phytomolecules with better activity and binding were shortlisted after HTVS, SP, and XP mode of docking. The refining of the hit molecules was done by the analysis of the pharmacokinetic properties and toxicity prediction using QikProp tool. The molecules with better binding and pharmacokinetic properties were selected for WaterMap analysis and Molecular dynamics simulation study. The top three compounds were selected for further studies, including QikProp analysis, water map analysis, and molecular dynamics study. Compounds ZINC000001785780, ZINC000013543704, ZINC000040874044 were found to be potent inhibitors against PTP1B based on the docking score and binding interactions. Among the selected molecules, ZINC000013543704 showed better stability in the molecular dynamics simulation study and WaterMap study. The identified hit could be a potent inhibitor of PTP1B that further requires experimental validation using in vitro and in vivo experimental models.

Inchworm stepping of Myc-Max heterodimer protein diffusion along DNA

Oncogenic protein Myc serves as a transcription factor to control cell metabolisms. Myc dimerizes via leucine zipper with its associated partner protein Max to form a heterodimer structure, which then binds target DNA sequences to regulate gene transcription. The regulation depends on Myc-Max binding to DNA and searching for target sequences via diffusional motions along DNA. Here, we conduct structure-based molecular dynamics (MD) simulations to investigate the diffusion dynamics of the Myc-Max heterodimer along DNA. We found that the heterodimer protein slides on the DNA in a rotation-uncoupled manner in coarse-grained simulations, as its two helical DNA binding basic regions (BRs) alternate between open and closed conformations via inchworm stepping motions. In such motions, the two BRs of the heterodimer step across the DNA strand one by one, with step sizes reaching about half of a DNA helical pitch length. Atomic MD simulations of the Myc-Max heterodimer in complex with DNA have also been conducted. Hydrogen bond interactions are revealed between the two BRs and two complementary DNA strands, respectively. In the non-specific DNA binding, the BR from Myc shows an onset of stepping on one association DNA strand and starts detaching from the other strand. Overall, our simulation studies suggest that the inchworm stepping motions of the Myc-Max heterodimer can be achieved during the protein diffusion along DNA.

Structure-based virtual screening and molecular dynamics of phytochemicals derived from Saudi medicinal plants to identify potential COVID-19 therapeutics

Coronavirus disease 2019 (COVID-19) has affected almost every country in the world by causing a global pandemic with a high mortality rate. Lack of an effective vaccine and/or antiviral drugs against SARS-CoV-2, the causative agent, has severely hampered the response to this novel coronavirus. Natural products have long been used in traditional medicines to treat various diseases, and purified phytochemicals from medicinal plants provide a valuable scaffold for the discovery of new drug leads. In the present study, we performed a computational screening of an in-house database composed of ~1000 phytochemicals derived from traditional Saudi medicinal plants with recognised antiviral activity. Structure-based virtual screening was carried out against three druggable SARS-CoV-2 targets, viral RNA-dependent RNA polymerase (RdRp), 3-chymotrypsin-like cysteine protease (3CLpro) and papain like protease (PLpro) to identify putative inhibitors that could facilitate the development of potential anti-COVID-19 drug candidates. Computational analyses identified three compounds inhibiting each target, with binding affinity scores ranging from −9.9 to −6.5 kcal/mol. Among these, luteolin 7-rutinoside, chrysophanol 8-(6-galloylglucoside) and kaempferol 7-(6″-galloylglucoside) bound efficiently to RdRp, while chrysophanol 8-(6-galloylglucoside), 3,4,5-tri-O-galloylquinic acid and mulberrofuran G interacted strongly with 3CLpro, and withanolide A, isocodonocarpine and calonysterone bound tightly to PLpro. These potential drug candidates will be subjected to further in vitro and in vivo studies and may assist the development of effective anti-COVID-19 drugs.

Identification of potential modulator of Anopheles gambiae odorant binding protein 1 by hierarchical virtual screening and molecular dynamics

Malaria is a protozoan infection transmitted by the bite of the infected female mosquito belonging to the genus Anopheles spp., which causes more than 445 million annual deaths worldwide. Available drugs have serious adverse effects (e.g. blurred vision, hypotension and headache) and species-dependent efficacy. An alternative to overcome these problems involve the use of molecules with affinity to the Anopheles gambiae mosquito odor receptors, minimizing the reinfection process as well as reducing the problems related to pharmacological therapy. The vector control can interrupt the epidemiological cycle and, therefore, control the malaria incidence. In the olfactory pathway, odorant binding protein 1 acts on the first level of odor recognition on malarial vector and thus can be used to modulate mosquito behavior and development of new attracts or repellents. Thus, this study applied ligand-based (2D-chemical similarity) and structure-based (docking and molecular dynamics) computational approaches to prioritize potential olfactory modulators on natural products catalogs at ZINC15 database (n = 98,379). Hierarchical virtual screening prioritized a potential olfactory modulator (Z8217) against Anopheles gambiae odorant binding protein 1 (AgOBP1). Next, it was submitted to molecular dynamics routine to identify structural requirements and the interactions profile required for binding-site affinity. This promising natural compound can interact like experimental ligand and will be used in repellency assay to confirm its sensorial behavior. Communicated by Ramaswamy H. Sarma

Computational investigation of potential inhibitors of novel coronavirus 2019 through structure-based virtual screening, molecular dynamics and density functional theory studies

Despite the intensive research efforts towards antiviral drug against COVID-19, no potential drug or vaccines has not yet discovered. Initially, the binding site of COVID-19 main protease was predicted which located between regions 2 and 3. Structure-based virtual screening was performed through a hierarchal mode of elimination technique after generating a grid box. This led to the identification of five top hit molecules that were selected on the basis of docking score and visualization of non-bonding interactions. The docking results revealed that the hydrogen bonding and hydrophobic interactions are the major contributing factors in the stabilization of complexes. The docking scores were found between −7.524 and −6.711 kcal/mol indicating strong ligand-protein interactions. Amino acid residues Phe140, Leu141, Gly143, Asn142, Thr26, Glu166 and Thr190 (hydrogen bonding interactions) and Phe140, Cys145, Cys44, Met49, Leu167, Pro168, Met165, Val42, Leu27 and Ala191 (hydrophobic interactions) formed the binding pocket of COVID-19 main protease. From identified hits, ZINC13144609 and ZINC01581128 were selected for atomistic MD simulation and density functional theory calculations. MD simulation results confirm that the protein interacting with both hit molecules is stabilized in the chosen POPC lipid bilayer membrane. The presence of lowest unoccupied molecular orbital (LUMO) and highest occupied molecular orbital (HOMO) in the hydrophobic region of the hit molecules leads to favorable ligand-protein contacts. The calculated pharmacokinetic descriptors were found to be in their acceptable range and therefore confirming their drug-like properties. Hence, the present investigation can serve as the basis for designing and developing COVID-19 inhibitors. Communicated by Ramaswamy H. Sarma

Structure-based virtual screening and molecular dynamics simulation of SARS-CoV-2 Guanine-N7 methyltransferase (nsp14) for identifying antiviral inhibitors against COVID-19

The recent pandemic caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) calls the whole world into a medical emergency. For tackling Coronavirus Disease 2019 (COVID-19), researchers from around the world are swiftly working on designing and identifying inhibitors against all possible viral key protein targets. One of the attractive drug targets is guanine-N7 methyltransferase which plays the main role in capping the 5′-ends of viral genomic RNA and sub genomic RNAs, to escape the host’s innate immunity. We performed homology modeling and molecular dynamic (MD) simulation, in order to understand the molecular architecture of Guanosine-P3-Adenosine-5’,5’-Triphosphate (G3A) binding with C-terminal N7-MTase domain of nsp14 from SARS-CoV-2. The residue Asn388 is highly conserved in present both in N7-MTase from SARS-CoV and SARS-CoV-2 and displays a unique function in G3A binding. For an in-depth understanding of these substrate specificities, we tried to screen and identify inhibitors from the Traditional Chinese Medicine (TCM) database. The combination of several computational approaches, including screening, MM/GBSA, MD simulations, and PCA calculations, provides the screened compounds that readily interact with the G3A binding site of homology modeled N7-MTase domain. Compounds from this screening will have strong potency towards inhibiting the substrate-binding and efficiently hinder the viral 5’-end RNA capping mechanism. We strongly believe the final compounds can become COVID-19 therapeutics, with huge international support. The focus of this study is to screen for antiviral inhibitors blocking guanine-N7 methyltransferase (N7-MTase), one of the key drug targets involved in the first methylation step of the SARS-CoV-2 RNA capping mechanism. Compounds binding the substrate-binding site can interfere with enzyme catalysis and impede 5’-end cap formation, which is crucial to mimic host RNA and evade host cellular immune responses. Therefore, our study proposes the top hit compounds from the Traditional Chinese Medicine (TCM) database using a combination of several computational approaches. Communicated by Ramaswamy H. Sarma.

Structure-Based Design and Molecular Dynamics Simulations of Pentapeptide AEYTR as a Potential Acetylcholinesterase Inhibitor

Structure-based virtual screening protocol to identify potent acetylcholinesterase inhibitors was retrospectively validated. The protocol could be employed to examine the potential of designed compounds as novel acetylcholinesterase inhibitors. In a research project designing short peptides as acetylcholinesterase inhibitors, peptide AEYTR emerged as one of the potential inhibitors. This article presents the design of AEYTR assisted by the validated protocol and guided by literature reviews followed by molecular dynamics studies to examine the interactions of the pentapeptide in the binding pocket of the acetylcholinesterase enzyme. The molecular dynamics simulations were performed using YASARA Structure in Google Cloud Platform. The peptide AEYTR was identified in silico as a potent acetylcholinesterase inhibitor with the average free energy of binding (DG) of -19.138 kcal/mol.

Identification of novel potential PI3Kα inhibitors for cancer therapy

Phosphatidylinositol 3-kinase alpha (PI3Kα) is among the most important PI3K isoforms and has been associated with multiple human cancers. Therefore, PI3Kα has garnered considerable attention as a viable target for anticancer drug discovery, and thus the identification and development of highly potent inhibitors of this isoform has become an important line of research. Here, structure-based virtual screening, bioassays, and molecular dynamics simulations were performed to discover novel potential PI3Kα inhibitors. TCM-N1 (ZINC13382850) was identified as a possible PI3Kα inhibitor. Particularly, fluorescence quenching assays determined that the binding affinity of the aforementioned compound was superior to that of a reference ligand (BYL719; i.e. a known PI3Kα inhibitor). Moreover, enzymatic activity and cell proliferation inhibition assays indicated that TCM-N1 possessed a moderate inhibition activity against PI3Kα and a relatively high anti-tumor proliferation ability in gastric, colorectal, and cervical cancer cells. The binding model and related thermodynamic parameters further demonstrated that TCM-N1 was tightly embedded into the ATP-binding pocket via hydrogen bonds, van der Waals interactions, and hydrophobic interactions. Therefore, this study provides promising insights into the development and design of more potent PI3Kα-inhibiting analogs. Communicated by Ramaswamy H. Sarma

In silico search of triple mutant T790M/C797S allosteric inhibitors to conquer acquired resistance problem in non-small cell lung cancer (NSCLC): a combined approach of structure-based virtual screening and molecular dynamics simulation

Third generation EGFR inhibitor osimertinib was approved as the first-line treatment for EGFR T790M mutation-positive Non-Small Cell Lung Cancer (NSCLC) patients in 2017. However, EGFR tertiary Cys797 to Ser797 (C797S) point mutation emanate rapidly after treatment of osimertinib, which is undruggable mutation to the all existing drugs. Recently, EAI045 fourth-generation allosteric EGFR inhibitor has been reported, which binds away from the ATP-binding site and not rely on Cys 797 binding. Here, we are reporting compound ZINC20531199 by virtual based screening studies as allosteric inhibitor to overcome the EGFR T790M/C797S Tyrosine Kinase (TK) mutation problem. Molecular Dynamics simulation for 10 ns further suggested that docked compound ZINC20531199 was stable into the allosteric pocket of the C797S EGFR tyrosine kinase. In silico pharmacokinetic predictions of the virtually screened compounds are within the defined range described for human use. Results indicate that the virtual screened compounds could be potential leads for the further development of new allosteric EGFR T790M/C797S inhibitors to overcome the problem of drug resistance. Communicated by Ramaswamy H. Sarma

Identification of potential inhibitors of human methionine aminopeptidase (type II) for cancer therapy: Structure-based virtual screening, ADMET prediction and molecular dynamics studies

Methionine Aminopeptidases MetAPs are divalent-cofactor dependent enzymes that are responsible for the cleavage of the initiator Methionine from the nascent polypeptides. MetAPs are classified into two isoforms: namely, MetAP1 and MetAP2. Several studies have revealed that MetAP2 is upregulated in various cancers, and its inhibition has shown to suppress abnormal or excessive blood vessel formation and tumor growth in model organisms. Clinical studies show that the natural product fumagillin, and its analogs are potential inhibitors of MetAP2. However, due to their poor pharmacokinetic properties and neurotoxicities in clinical studies, their further developments have received a great setback. Here, we apply structure-based virtual screening and molecular dynamics methods to identify a new class of potential inhibitors for MetAP2. We screened Otava’s Chemical Library, which consists of about 3 200 000 tangible-chemical compounds, and meticulously selected the top 10 of these compounds based on their inhibitory potentials against MetAP2. The top hit compounds subjected to ADMET predictor using 3 independent ADMET prediction programs, were found to be drug-like. To examine the stability of ligand binding mode, and efficacy, the unbound form of MetAP2, its complexes with fumagillin, spiroepoxytriazole, and the best promising compounds compound-3369841 and compound-3368818 were submitted to 100 ns molecular dynamics simulation. Like fumagillin, spiroepoxytriazole, and both compound-3369841 and compound-3368818 showed stable binding mode over time during the simulations. Taken together, these uninherited-fumagillin compounds may serve as new class of inhibitors or provide scaffolds for further optimization towards the design of more potent MetAP2 inhibitors -development of such inhibitors would be essential strategy against various cancer types.

Elongation Factor Tu Switch I Element is a Gate for Aminoacyl-tRNA Selection

Selection of correct aminoacyl (aa)-tRNA at the ribosomal A site is fundamental to maintaining translational fidelity. Aa-tRNA selection is a multistep process facilitated by the guanosine triphosphatase elongation factor (EF)-Tu. EF-Tu delivers aa-tRNA to the ribosomal A site and participates in tRNA selection. The structural mechanism of how EF-Tu is involved in proofreading remains to be fully resolved. Here, we provide evidence that switch I of EF-Tu facilitates EF-Tu's involvement during aa-tRNA selection. Using structure-based and explicit solvent molecular dynamics simulations based on recent cryo-electron microscopy reconstructions, we studied the conformational change of EF-Tu from the guanosine triphosphate to guanine diphosphate conformation during aa-tRNA accommodation. Switch I of EF-Tu rapidly converts from an α-helix into a β-hairpin and moves to interact with the acceptor stem of the aa-tRNA. In doing so, switch I gates the movement of the aa-tRNA during accommodation through steric interactions with the acceptor stem. Pharmacological inhibition of the aa-tRNA accommodation pathway prevents the proper positioning of switch I with the aa-tRNA acceptor stem, suggesting that the observed interactions are specific for cognate aa-tRNA substrates, and thus capable of contributing to the fidelity mechanism.

Structure-Based Virtual Screening, Molecular Dynamics and Binding Free Energy Calculations of Hit Candidates as ALK-5 Inhibitors.

Activin-like kinase 5 (ALK-5) is involved in the physiopathology of several conditions, such as pancreatic carcinoma, cervical cancer and liver hepatoma. Cellular events that are landmarks of tumorigenesis, such as loss of cell polarity and acquisition of motile properties and mesenchymal phenotype, are associated to deregulated ALK-5 signaling. ALK-5 inhibitors, such as SB505154, GW6604, SD208, and LY2157299, have recently been reported to inhibit ALK-5 autophosphorylation and induce the transcription of matrix genes. Due to their ability to impair cell migration, invasion and metastasis, ALK-5 inhibitors have been explored as worthwhile hits as anticancer agents. This work reports the development of a structure-based virtual screening (SBVS) protocol aimed to prospect promising hits for further studies as novel ALK-5 inhibitors. From a lead-like subset of purchasable compounds, five molecules were identified as putative ALK-5 inhibitors. In addition, molecular dynamics and binding free energy calculations combined with pharmacokinetics and toxicity profiling demonstrated the suitability of these compounds to be further investigated as novel ALK-5 inhibitors.

Suramin could block the activity of Arabinono-1, 4-lactone oxidase enzyme from Leishmania donovani: structure-based screening and molecular dynamics analyses.

Leishmania donovani, a parasitic protozoan causing visceral leishmaniasis, can lead to a dangerous and often fatal disease in humans. Current treatment for leishmaniasis may have severe side effects, low efficacy and high cost, hence an immediate need for new efficient drugs is essential. Arabinono-1, 4-lactone oxidase enzyme from Leishmania donovani (LdALO), which catalyzes the last step of the ascorbate biosynthesis pathway, has been considered as a potential target for antileishmanial drugs design. The current study was performed with an in silico approach to predict novel inhibitory molecules against the LdALO enzyme. Various modeling and refinement processes were employed to obtain a reliable 3D structure. The best LdALO model with the highest qualitative model energy analysis score was predicted by the Robetta server and subsequently refined by 3D refine and ModLoop servers. The high quality of the final LdALO model was confirmed using model assessment software. Based on docking analysis results, we predicted 10 inhibitory molecules of a US Food and Drug Administration-approved library, with appropriate criteria regarding energy binding and interaction with the main functionally active sites of LdALO, indicating that they could be significant targets for further drug design investigations against L. donovani. Suramin is used to treat the first stage of African sleeping sickness and its mechanism of action is unknown. Our results showed that suramin was the best-predicted inhibitor compound for LdALO enzyme activity.

Regulation of adenylyl cyclase 5 in striatal neurons confers the ability to detect coincident neuromodulatory signals.

Long-term potentiation and depression of synaptic activity in response to stimuli is a key factor in reinforcement learning. Strengthening of the corticostriatal synapses depends on the second messenger cAMP, whose synthesis is catalysed by the enzyme adenylyl cyclase 5 (AC5), which is itself regulated by the stimulatory Gαolf and inhibitory Gαi proteins. AC isoforms have been suggested to act as coincidence detectors, promoting cellular responses only when convergent regulatory signals occur close in time. However, the mechanism for this is currently unclear, and seems to lie in their diverse regulation patterns. Despite attempts to isolate the ternary complex, it is not known if Gαolf and Gαi can bind to AC5 simultaneously, nor what activity the complex would have. Using protein structure-based molecular dynamics simulations, we show that this complex is stable and inactive. These simulations, along with Brownian dynamics simulations to estimate protein association rates constants, constrain a kinetic model that shows that the presence of this ternary inactive complex is crucial for AC5’s ability to detect coincident signals, producing a synergistic increase in cAMP. These results reveal some of the prerequisites for corticostriatal synaptic plasticity, and explain recent experimental data on cAMP concentrations following receptor activation. Moreover, they provide insights into the regulatory mechanisms that control signal processing by different AC isoforms.

A Common Tag Nucleotide Variant in MMP7 Promoter Increases Risk for Hypertension via Enhanced Interactions With CREB (Cyclic AMP Response Element-Binding Protein) Transcription Factor.

MMP (matrix metalloproteinase)-7-a potent extracellular matrix degrading enzyme-is emerging as a new regulator of cardiovascular diseases. However, potential contributions of MMP7 genetic variations to hypertension remain unknown. In this study, we probed for the association of a tag single-nucleotide polymorphism in the MMP7 promoter (-181A/G; rs11568818) with hypertension in an urban South Indian population (n=1501). The heterozygous AG genotype significantly increased risk for hypertension as compared with the wild-type AA genotype (odds ratio, 1.60 [95% CI, 1.25-2.06]; P=2.4×10-4); AG genotype carriers also displayed significantly higher diastolic blood pressure and mean arterial pressure than wild-type AA individuals. The study was replicated in a North Indian population (n=949) (odds ratio, 1.52 [95% CI, 1.11-2.09]; P=0.01). Transient transfection experiments using MMP7 promoter-luciferase reporter constructs revealed that the variant -181G allele conferred greater promoter activity than the -181A allele. Computational prediction and structure-based conformational and molecular dynamics simulation studies suggested higher binding affinity for the CREB (cyclic AMP response element-binding protein) to the -181G promoter. In corroboration, overexpression/downregulation of CREB and chromatin immunoprecipitation experiments provided convincing evidence for stronger binding of CREB with the -181G promoter. The -181G promoter also displayed enhanced responses to hypoxia and epinephrine treatment. The higher promoter activity of -181G allele translated to increased MMP7 protein level, and MMP7-181AG heterozygous individuals displayed elevated plasma MMP7 levels, which positively correlated with blood pressure. In conclusion, the MMP7 A-181G promoter polymorphism increased MMP7 expression under pathophysiological conditions (hypoxic stress and catecholamine excess) via increased interactions with CREB and enhanced the risk for hypertension in its carriers.

Structure-based screening and molecular dynamics simulation studies for the identification of potential acetylcholinesterase inhibitors

ABSTRACTAlzheimer’s disease (AD) is an irreversible, progressive neurodegenerative disease characterised by the appearance of amyloid β plaques and neurofibrillary tangles in the brain. The loss of cholinergic neurons is considered to be one of the contributing factors for cognitive and memory deficits in the disease. Donepezil, the most successful and prescribed drug to treat the symptoms of AD, is acetylcholinesterase (AChE) inhibitor that improves the memory and brain’s cognitive functions. In this study, the pharmacophoric features of donepezil were mapped from its cocrystal with AChE and were used to screen the Zinc15 database. The obtained hits were subjected to molecular properties and PAINS filter. The homology modelling and molecular dynamics (MD) were performed to prepare selected AChE protein model (PDB id 4EY7) for advanced studies. The virtual screening and precision docking led to the identification of five compounds. The ADMET property prediction and free energy calculations were carried out to obtain three final compounds. The Alanine scanning and MD study of the compounds viz. ZINC000013719534, ZINC000035551243 and ZINC000035596918 produced stable complexes of the ligands. The identified virtual leads have the potential for better AChE inhibition.HighlightsPharmacophore mapping of donepezil was developed from PDB id 4EY7.Pharmacophore-based screening yielded 601 compounds with RMSD < 0.5 Å.PAINS and Drug likeliness filtration resulted in 199 compounds for further virtual screening and precision docking studies.Free binding energy and ADMET studies provided three active compounds.The molecular dynamics study indicated that the compounds ZINC000013719534, ZINC000035551243 and ZINC000035596918 formed stable interactions with the protein.

Enhancement of the thermostability of Aspergillus niger α-l-rhamnosidase based on PoPMuSiC algorithm.

α-l-Rhamnosidase is a biotechnologically important enzyme in food industry and in the preparation of drugs and drug precursors. To expand the functionality of our previously cloned α-l-rhamnosidase from Aspergillus niger JMU-TS528, 14 mutants were constructed based on the changes of the folding free energy (ΔΔG), predicted by the PoPMuSiC algorithm. Among them, six single-site mutants displayed higher thermal stability than wild type (WT). The combinational mutant K573V-E631F displayed even higher thermostability than six single-site mutants. The spectra analyses displayed that the WT and K573V-E631F had almost similar secondary and tertiary structure profiles. The simulated protein structure-based interaction analysis and molecular dynamics calculation were further implemented to assess the conformational preferences of the K573V-E631F. The improved thermostability of mutant K573V-E631F may be attributed to the introduction of new cation-π and hydrophobic interactions, and the overall improvement of the enzyme conformation. PRACTICAL APPLICATIONS: The stability of enzymes, particularly with regards to thermal stability remains a critical issue in industrial biotechnology and industrial processing generally tends to higher ambient temperature to inhibit microbial growth. Most of the α-l-rhamnosidases are usually active at temperature from 30 to 60°C, which are apt to denature at temperatures over 60°C. To expand the functionality of our previously cloned α-l-rhamnosidase from Aspergillus niger JMU-TS528, we used protein engineering methods to increase the thermal stability of the α-l-rhamnosidase. Practically, conducting reactions at high temperatures enhances the solubility of substrates and products, increases the reaction rate thus reducing the reaction time, and inhibits the growth of contaminating microorganisms. Thus, the improvement on the thermostability of α-l-rhamnosidase on the one hand can increase enzyme efficacy; on the other hand, the high ambient temperature would enhance the solubility of natural substrates of α-l-rhamnosidase, such as naringin, rutin, and hesperidin, which are poorly dissolved in water at room temperature. Protein thermal resistance is an important issue beyond its obvious industrial importance. The current study also helps in the structure-function relationship study of α-l-rhamnosidase.

Combined Computational-Experimental Approach to Explore the Molecular Mechanism of SaCas9 with a Broadened DNA Targeting Range.

Despite accelerating development of CRISPR technology, there remains high demand for further interrogation of its fundamental biology. This is particularly fascinating as new improved CRISPR tools were artificially engineered to harbor beneficial features but often lack mechanistic explanation. SaCas9, a minimal Cas9 ideal for in vivo applications, suffers from long protospacer adjacent motif (PAM), which prompted effort on mutant KKH SaCas9 with relaxed PAM requirement. Leveraging structure-based molecular dynamics simulation, free-energy perturbation, and targeted experimentation, we developed a workflow for probing SaCas9 and a series of its variants, revealing intriguing dynamics of PAM recognition and the molecular mechanism of KKH mutations. Furthermore, we deployed this approach to design and validate new mutant SaCas9, SaCas9-NR and SaCas9-RL, with enhanced targeting range distinctive from the KKH mutant and improved activity in mammalian cells. Overall, our approach provides a dynamic understanding of SaCas9 PAM recognition and a new gateway to enlighten rationally designed Cas9 variants harboring novel properties.

Identification of new DNA gyrase inhibitors based on bioactive compounds from streptomyces: structure-based virtual screening and molecular dynamics simulations approaches

DNA gyrase enzyme has vital role in bacterial survival and can be considered as a potential drug target. Owing to the appearance of resistance to gyrase-targeted drugs, especially fluoroquinolone, screening new compounds which bind more efficiently to the mutant binding pocket is essential. Hence, in this work, using Smina Autodock and through structure-based virtual screening of StreptomeDB, several natural products were discovered based on the SimocyclinoneD8 (SD8) binding pocket of GyrA subunit of DNA gyrase. After evaluation of binding affinity, binding modes, critical interactions and physicochemical and pharmaceutical properties, three lead compounds were selected for further analysis. Afterward 60 ns molecular dynamics simulations were performed and binding free energies were calculated by the molecular mechanics/Poisson–Boltzmann surface area method. Also, interaction of the selected lead compounds with the mutated GyrA protein was evaluated. Results indicated that all of the selected compounds could bind to the both wild-type and mutated GyrA with the binding affinities remarkably higher than SimocyclinoneD8. Interestingly, we noticed that the selected compounds comprised angucycline moiety in their structure which could sufficiently interact with GyrA and block the DNA binding pocket of DNA gyrase, in silico. In conclusion, three DNA gyrase inhibitors were identified successfully which were highly capable of impeding DNA gyrase and can be considered as potential drug candidates for treatment of fluoroquinolone-resistant strains.Communicated by Ramaswamy H. Sarma

A combinatorial approach of structure-based virtual screening and molecular dynamics simulation towards the discovery of a highly selective inhibitor for VP9 coat protein of Banna virus

Structure based virtual screening of two libraries containing 27,628 numbers of antiviral compounds was used to discover a few of the potent inhibitor molecules against Banna virus (BAV). Cross-docking studies with many common interfering proteins provided five of the highly selective inhibitor for BAV. Analyses of the leading molecules with ADME-Tox filtering tool and atomistic molecular dynamics simulation studies finally discovered a benzoxazolone derivative as one of the most promising molecules towards the highly selective inhibition of BAV. The theoretical calculations are also supported by the experimental evidences where the interactions between the hit ligand and a model peptide sequence, mimicking the VP9 protein of BAV, were studied. Overall the development of a personalized therapeutic towards the highly selective inhibition of BAV is discussed herein for the first time in literature.