Comparative protein structure modeling using Modeller

Computation-guided transcription factor biosensor specificity engineering for adipic acid detection

Transcription factor (TF)-based biosensors that connect small-molecule sensing with readouts such as fluorescence have proven to be useful synthetic biology tools for applications in biotechnology. However, the development of specific TF-based biosensors is hindered by the limited repertoire of TFs specific for molecules of interest since current construction methods rely on a limited set of characterized TFs. In this study, we present an approach for engineering the specificity of TFs through a computation-based workflow using molecular docking that enables targeted alteration of TF ligand specificity. Using this method, we engineer the LysR family BenM TF to alter its specificity from its cognate ligand cis,cis-muconic acid to adipic acid through a single amino acid substitution identified by our computational workflow. When implemented in a cell-free system, the engineered biosensor shows higher ligand sensitivity, expanding the potential applications of this circuit. We further investigate ligand binding through molecular dynamics to analyze the substitution, elucidating the impact of modulating a single amino acid position on the mechanism of BenM ligand binding. This study represents the first application of biomolecular modeling methods for altering BenM specificity and for gaining insights into how mutations influence the structural dynamics of BenM. Such methods can potentially be applied to other TFs to alter specificity and analyze the dynamics responsible for these changes, highlighting the applicability of computational tools for informing experiments. In addition, our developed adipic acid biosensor can be applied for the identification and engineering of enzymes to produce adipic acid.

Apprehensions and emerging solutions in ML-based protein structure prediction

The three-dimensional structure of proteins determines their function in vital biological processes. Thus, when the structure is known, the molecular mechanism of protein function can be understood in more detail and obtained information utilized in biotechnological, diagnostics, and therapeutic applications. Over the past five years, machine learning (ML)-based modeling has pushed protein structure prediction to the next level with AlphaFold in the front line, predicting the structure for hundreds of millions of proteins. Further advances recently report promising ML-based approaches for solving remaining challenges by incorporating functionally important metals, co-factors, post-translational modifications, structural dynamics, and interdomain and multimer interactions in the structure prediction process.

Identification of lead compound screened from the natural products atlas to treat renal inflammasomes using molecular docking and dynamics simulation

One of the most prevalent ailments is kidney disease. Effective therapies for chronic renal disease are hard to come by. As a result, there is significant clinical and social interest to predict and develop novel compounds to treat renal disorders. So, specific natural products have been employed in this study because they have protective effects against kidney diseases. When taken orally, natural products can help protect against or lessen the severity of the kidney damage caused by high fructose intake, a high-fat diet, and both Type I and Type 2 diabetes. Reduced podocyte injury, a contributor to albuminuria in diabetic nephropathy, reduces renal endothelial barrier function disruption due to hyperglycemia, as well as urinary microalbumin excretion and glomerular hyperfiltration. Multiple natural products have been shown to protect the kidneys from nephrotoxic chemicals such as LPS, gentamycin, alcohol, nicotine, lead, and cadmium, all of which can persuade acute kidney injury (AKI) or chronic kidney disease (CKD). Natural compounds inhibit regulatory enzymes for controlling inflammation-related diseases. For this, use computational methods such as drug design to identify novel flavonoid compounds against kidney diseases. Drug design via computational methods gaining admiration as a swift and effective technique to identify lead compounds in a shorter time at a low cost. In this in-silico study, we screened The Natural Product Atlas based on a structure-based pharmacophore query. Top hits were analyzed for ADMET analysis followed by molecular docking and docking validation. Finally, the lead compound was simulated for a period of 200 ns and trajectories were studied for stability. We found that NPA024823 showed promising binding and stability with the AIM2. This research work aims to predict novel anti-inflammatory compounds against kidney diseases to inhibit kidney inflammasome by targeting the AIM2 protein. So, in initial preclinical research, there will be lower failure rates that demonstrate safety profiles against predicted compounds.Communicated by Ramaswamy H. Sarma.

Synthesis and biological evaluation of orally active anti-Trypanosoma agents

In previous studies, we developed anti-trypanosome tubulin inhibitors with promising in vitro selectivity and activity against Human African Trypanosomiasis (HAT). However, for such agents, oral activity is crucial. This study focused on further optimizing these compounds to enhance their ligand efficiency, aiming to reduce bulkiness and hydrophobicity, which should improve solubility and, consequently, oral bioavailability. Using Trypanosoma brucei brucei cells as the parasite model and human normal kidney cells and mouse macrophage cells as the host model, we evaluated 30 new analogs synthesized through combinatorial chemistry. These analogs have fewer aromatic moieties and lower molecular weights than their predecessors. Several new analogs demonstrated IC50s in the low micromolar range, effectively inhibiting trypanosome cell growth without harming mammalian cells at the same concentration. We conducted a detailed structure-activity relationship (SAR) analysis and a docking study to assess the compounds' binding affinity to trypanosome tubulin homolog. The results revealed a correlation between binding energy and anti-Trypanosoma activity. Importantly, compound 7 displayed significant oral activity, effectively inhibiting trypanosome cell proliferation in mice.

ANCUT1, a novel thermoalkaline cutinase from Aspergillus nidulans and its application on hydroxycinnamic acids lipophilization

One of the four cutinases encoded in the Aspergillus nidulans genome, ANCUT1, is described here. Culture conditions were evaluated, and it was found that this enzyme is produced only when cutin is present in the culture medium, unlike the previously described ANCUT2, with which it shares 62% amino acid identity. The differences between them include the fact that ANCUT1 is a smaller enzyme, with experimental molecular weight and pI values of 22 kDa and 6, respectively. It shows maximum activity at pH 9 and 60 °C under assayed conditions and retains more than 60% of activity after incubation for 1 h at 60 °C in a wide range of pH values (6-10) after incubations of 1 or 3 h. It has a higher activity towards medium-chain esters and can modify long-chain length hydroxylated fatty acids constituting cutin. Its substrate specificity properties allow the lipophilization of alkyl coumarates, valuable antioxidants and its thermoalkaline behavior, which competes favorably with other fungal cutinases, suggests it may be useful in many more applications.

Protein Effects on the Excitation Energies and Exciton Dynamics of the CP24 Antenna Complex

In this study, the site energy fluctuations, energy transfer dynamics, and some spectroscopic properties of the minor light-harvesting complex CP24 in a membrane environment were determined. For this purpose, a 3 μs-long classical molecular dynamics simulation was performed for the CP24 complex. Furthermore, using the density functional tight binding/molecular mechanics molecular dynamics (DFTB/MM MD) approach, we performed excited state calculations for the chlorophyll a and chlorophyll b molecules in the complex starting from five different positions of the MD trajectory. During the extended simulations, we observed variations in the site energies of the different sets as a result of the fluctuating protein environment. In particular, a water coordination to Chl-b 608 occurred only after about 1 μs in the simulations, demonstrating dynamic changes in the environment of this pigment. From the classical and the DFTB/MM MD simulations, spectral densities and the (time-dependent) Hamiltonian of the complex were determined. Based on these results, three independent strongly coupled chlorophyll clusters were revealed within the complex. In addition, absorption and fluorescence spectra were determined together with the exciton relaxation dynamics, which reasonably well agrees with experimental time scales.

G protein-specific mechanisms in the serotonin 5-HT2A receptor regulate psychosis-related effects and memory deficits

G protein-coupled receptors (GPCRs) are sophisticated signaling machines able to simultaneously elicit multiple intracellular signaling pathways upon activation. Complete (in)activation of all pathways can be counterproductive for specific therapeutic applications. This is the case for the serotonin 2 A receptor (5-HT2AR), a prominent target for the treatment of schizophrenia. In this study, we elucidate the complex 5-HT2AR coupling signature in response to different signaling probes, and its physiological consequences by combining computational modeling, in vitro and in vivo experiments with human postmortem brain studies. We show how chemical modification of the endogenous agonist serotonin dramatically impacts the G protein coupling profile of the 5-HT2AR and the associated behavioral responses. Importantly, among these responses, we demonstrate that memory deficits are regulated by Gαq protein activation, whereas psychosis-related behavior is modulated through Gαi1 stimulation. These findings emphasize the complexity of GPCR pharmacology and physiology and open the path to designing improved therapeutics for the treatment of stchizophrenia.

Understanding the Interactions of Ubiquitin-Specific Protease 7 with Its Substrates through Molecular Dynamics Simulations: Insights into the Role of Its C-Terminal Domains in Substrate Recognition

Ubiquitin-specific protease 7 (USP7) is a deubiquitinase enzyme that plays a critical role in regulating various cellular processes by cleaving ubiquitin molecules from target proteins. The C-terminal loop (CTL) motif is a specific region at the C-terminal end of the USP7 enzyme. Recent experiments suggest that the CTL motif plays a role in USP7's catalytic activity by contributing to the enzyme's structural stability, substrate recognition, and catalytic efficiency. The objective of this work is to elucidate these roles through the utilization of computational methods for molecular simulations. For this, we conducted extensive molecular dynamics (MD) simulations to investigate the conformational dynamics and protein-protein interactions within the USP7 enzyme-substrate complex with the substrate consisting of the ubiquitin tagged with the fluorescent label rhodamine 110-gly (Ub-Rho). Our results demonstrate that the CTL motif plays a crucial role in stabilizing the Ubl domains' conformation and augmenting the stability of active conformations within the enzyme-substrate complex. Conversely, the absence of the CTL motif results in increased flexibility and variability in Ubl domains' motion, leading to a reduced percentage of active conformations. Furthermore, our analysis of protein-protein interactions highlights the significance of the CTL motif in anchoring the Ubl45 domains to the catalytic domain (CD), thereby facilitating stable interactions with the substrate. Overall, our findings provide valuable insights into the conformational dynamics and protein-protein interactions inherent in the USP7 enzyme-substrate complex. These insights shed light on some mechanistic details of USP7 concerning the substrate's recognition before its catalytic action.

Utilization of the EpiMed Coronabank Chemical Collection to identify potential SARS-CoV-2 antivirals: in silico studies targeting the nsp14 ExoN domain and PLpro naphthalene binding site

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome encodes 29 proteins including four structural, 16 nonstructural (nsps), and nine accessory proteins (https://epimedlab.org/sars-cov-2-proteome/). Many of these proteins contain potential targetable sites for the development of antivirals. Despite the widespread use of vaccinations, the emergence of variants necessitates the investigation of new therapeutics and antivirals. Here, the EpiMed Coronabank Chemical Collection (https://epimedlab.org/crl/) was utilized to investigate potential antivirals against the nsp14 exoribonuclease (ExoN) domain. Molecular docking was performed to evaluate the binding characteristics of our chemical library against the nsp14 ExoN site. Based on the initial screen, trisjuglone, ararobinol, corilagin, and naphthofluorescein were identified as potential lead compounds. Molecular dynamics (MD) simulations were subsequently performed, with the results highlighting the stability of the lead compounds in the nsp14 ExoN site. Protein-RNA docking revealed the potential for the lead compounds to disrupt the interaction with RNA when bound to the ExoN site. Moreover, hypericin, cyanidin-3-O-glucoside, and rutin were previously identified as lead compounds targeting the papain-like protease (PLpro) naphthalene binding site. Through performing MD simulations, the stability and interactions of lead compounds with PLpro were further examined. Overall, given the critical role of the exonuclease activity of nsp14 in ensuring viral fidelity and the multifunctional role of PLpro in viral pathobiology and replication, these nsps represent important targets for antiviral drug development. Our databases can be utilized for in silico studies, such as the ones performed here, and this approach can be applied to other potentially druggable SARS-CoV-2 protein targets.

Identification of ligands binding to MB327-PAM-1, a binding pocket relevant for resensitization of nAChRs

Desensitization of nicotinic acetylcholine receptors (nAChRs) can be induced by overstimulation with acetylcholine (ACh) caused by an insufficient degradation of ACh after poisoning with organophosphorus compounds (OPCs). Currently, there is no generally applicable treatment for OPC poisoning that directly targets the desensitized nAChR. The bispyridinium compound MB327, an allosteric modulator of nAChR, has been shown to act as a resensitizer of nAChRs, indicating that drugs binding directly to nAChRs can have beneficial effects after OPC poisoning. However, MB327 also acts as an inhibitor of nAChRs at higher concentrations and can thus not be used for OPC poisoning treatment. Consequently, novel, more potent resensitizers are required. To successfully design novel ligands, the knowledge of the binding site is of utmost importance. Recently, we performed in silico studies to identify a new potential binding site of MB327, MB327-PAM-1, for which a more affine ligand, UNC0646, has been described. In this work, we performed ligand-based screening approaches to identify novel analogs of UNC0646 to help further understand the structure-affinity relationship of this compound class. Furthermore, we used structure-based screenings and identified compounds representing four new chemotypes binding to MB327-PAM-1. One of these compounds, cycloguanil, is the active metabolite of the antimalaria drug proguanil and shows a higher affinity towards MB327-PAM-1 than MB327. Furthermore, cycloguanil can reestablish the muscle force in soman-inhibited rat muscles. These results can act as a starting point to develop more potent resensitizers of nAChR and to close the gap in the treatment after OPC poisoning.

Investigation of cathinone analogs targeting human dopamine transporter using molecular modeling

In a step towards understanding the structure-property relationship among Synthetic Cathinones (SCs), a combined methodology based on Density Functional Theory (DFT), Administration, Distribution, Metabolism, Excretion, and Toxicity (ADMET) predictions, docking and molecular dynamics simulations have been applied to correlate physicochemical descriptors of various SCs to their biological activity. The results from DFT and molecular docking studies correlate well with each other explaining the biological activity trends of the studied SCs. Quantum mechanical descriptors viz. polarizability, electron affinity, ionization potential, chemical hardness, electronegativity, molecular electrostatic potential, and ion interaction studies unravel the distinguishingly reactive nature of Group D (pyrrolidine substituted) and Group E (methylenedioxy and pyrrolidine substituted) compounds. According to ADMET analysis, Group D and Group E molecules have a higher probability of permeating through the blood-brain barrier. Molecular docking results indicate that Phe76, Ala77, Asp79, Val152, Tyr156, Phe320, and Phe326 constitute the binding pocket residues of hDAT in which the most active ligands MDPV, MDPBP, and MDPPP are bound. Finally, to validate the derived quantum chemical descriptors and docking results, Molecular Dynamics (MD) simulations are performed with homology-modelled hDAT (human dopamine transporter). The MD simulation results revealed that the majority of SCs remain stable within the hDAT protein's active sites via non-bonded interactions after 100 ns long simulations. The findings from DFT, ADMET analysis, molecular docking, and molecular dynamics simulation studies complement each other suggesting that pyrrolidine-substituted SCs (Group D and E), specifically, MPBP and PVN are proven potent SCs along with MDPV, validating various experimental observations.Communicated by Ramaswamy H. Sarma.

Prediction of the essential intermolecular contacts for side-binding of VASP on F-actin

Vasodilator-stimulated phosphoprotein (VASP) family proteins play a crucial role in mediating the actin network architecture in the cytoskeleton. The Ena/VASP homology 2 (EVH2) domain in each of the four identical arms of the tetrameric VASP consists of a loading poly-Pro region, a G-actin-binding domain (GAB), and an F-actin-binding domain (FAB). Together, the poly-Pro, GAB, and FAB domains allow VASP to bind to sides of actin filaments in a bundle, and recruit profilin-G-actin to processively elongate the filaments. The atomic resolution structure of the ternary complex, consisting of the loading poly-Pro region and GAB domain of VASP with profilin-actin, has been solved over a decade ago; however, a detailed structure of the FAB-F-actin complex has not been resolved to date. Experimental insights, based on homology of the FAB domain with the C region of WASP, have been used to hypothesize that the FAB domain binds to the cleft between subdomains 1 and 3 of F-actin. Here, in order to develop our understanding of the VASP-actin complex, we first augment known structural information about the GAB domain binding to actin with the missing FAB domain-actin structure, which we predict using homology modeling and docking simulations. In earlier work, we used mutagenesis and kinetic modeling to study the role of domain-level binding-unbinding kinetics of Ena/VASP on actin filaments in a bundle, specifically on the side of actin filaments. We further look at the nature of the side-binding of the FAB domain of VASP at the atomistic level using our predicted structure, and tabulate effective mutation sites on the FAB domain that would disrupt the VASP-actin complex. We test the binding affinity of Ena with mutated FAB domain using total internal reflection fluorescence microscopy experiments. The binding affinity of VASP is affected significantly for the mutant, providing additional support for our predicted structure.

Staphylococcus aureus FtsZ and PBP4 bind to the conformationally dynamic N-terminal domain of GpsB

In the Firmicutes phylum, GpsB is a membrane associated protein that coordinates peptidoglycan synthesis with cell growth and division. Although GpsB has been studied in several bacteria, the structure, function, and interactome of Staphylococcus aureus GpsB is largely uncharacterized. To address this knowledge gap, we solved the crystal structure of the N-terminal domain of S. aureus GpsB, which adopts an atypical, asymmetric dimer, and demonstrates major conformational flexibility that can be mapped to a hinge region formed by a three-residue insertion exclusive to Staphylococci. When this three-residue insertion is excised, its thermal stability increases, and the mutant no longer produces a previously reported lethal phenotype when overexpressed in Bacillus subtilis. In S. aureus, we show that these hinge mutants are less functional and speculate that the conformational flexibility imparted by the hinge region may serve as a dynamic switch to fine-tune the function of the GpsB complex and/or to promote interaction with its various partners. Furthermore, we provide the first biochemical, biophysical, and crystallographic evidence that the N-terminal domain of GpsB binds not only PBP4, but also FtsZ, through a conserved recognition motif located on their C-termini, thus coupling peptidoglycan synthesis to cell division. Taken together, the unique structure of S. aureus GpsB and its direct interaction with FtsZ/PBP4 provide deeper insight into the central role of GpsB in S. aureus cell division.

RedOx regulation of LRRK2 kinase activity by active site cysteines

Mutations of the human leucine-rich repeat kinase 2 (LRRK2) have been associated with both, idiopathic and familial Parkinson's disease (PD). Most of these pathogenic mutations are located in the kinase domain (KD) or GTPase domain of LRRK2. In this study we describe a mechanism in which protein kinase activity can be modulated by reversible oxidation or reduction, involving a unique pair of adjacent cysteines, the "CC" motif. Among all human protein kinases, only LRRK2 contains this "CC" motif (C2024 and C2025) in the Activation Segment (AS) of the kinase domain. In an approach combining site-directed mutagenesis, biochemical analyses, cell-based assays, and Gaussian accelerated Molecular Dynamics (GaMD) simulations we could attribute a role for each of those cysteines. We employed reducing and oxidizing agents with potential clinical relevance to investigate effects on kinase activity and microtubule docking. We find that each cysteine gives a distinct contribution: the first cysteine, C2024, is essential for LRRK2 protein kinase activity, while the adjacent cysteine, C2025, contributes significantly to redox sensitivity. Implementing thiolates (R-S-) in GaMD simulations allowed us to analyse how each of the cysteines in the "CC" motif interacts with its surrounding residues depending on its oxidation state. From our studies we conclude that oxidizing agents can downregulate kinase activity of hyperactive LRRK2 PD mutations and may provide promising tools for therapeutic strategies.

Can Duvelisib and Eganelisib work for both cancer and COVID-19? Molecular-level insights from MD simulations and enhanced samplings

SARS-CoV-2 has caused severe illness and anxiety worldwide, evolving into more dreadful variants capable of evading the host's immunity. Cytokine storms, led by PI3Kγ, are common in cancer and SARS-CoV-2. Naturally, there is a yearning to see whether any drugs could alleviate cytokine storms for both. Upon investigation, we identified two anticancer drugs, Duvelisib and Eganelisib, that could also work against SARS-CoV-2. This report is the first to decipher their synergic therapeutic effectiveness against COVID-19 and cancer with molecular insights from atomistic simulations. In addition to PI3Kγ, these drugs exhibit specificity for the main protease among all SARS-CoV-2 targets, with significant negative binding free energies and small time-dependent conformational changes of the complexes. Complexation makes active sites and secondary structures highly mechanically stiff, with barely any deformation. Replica simulations estimated large pulling forces in enhanced sampling to dissociate the drugs from Mpro's active site. Furthermore, the radial distribution function (RDF) demonstrated that the therapeutic molecules were closest to the His41 and Cys145 catalytic dyad residues. Finally, analyses implied Duvelisib and Eganelisib as promising dual-purposed anti-COVID and anticancer drugs, potentially targeting Mpro and PI3Kγ to stop virus replication and cytokine storms concomitantly. We also distinguished hotspot residues imparting significant interactions.

Antimicrobial activity of Geranyl acetate against cell wall synthesis proteins of P. aeruginosa and S. aureus using molecular docking and simulation

Incidences of Methicillin-Resistant Staphylococcus aureus and Multi-Drug Resistant Pseudomonas aeruginosa causing skin and soft tissue infections are becoming more prevalent due to repeated mutations and changes in the environment. Coriandrum sativum, a well-known Indian herbal medicinal plant, is shown to have antioxidant, antibacterial, and anti-inflammatory activity. This comparative study focuses on the molecular docking (PyRx v0.9.8) of ligand binding domains of WbpE Aminotransferase involved in O-antigen assembly in Pseudomonas aeruginosa (3NU7) and Beta-Lactamase found in Staphylococcus aureus (1BLC) with selected phytocompounds of Coriandrum sativum along with a known binder and a clinical reference drug. This was followed by molecular dynamics simulation studies (GROMACS v2019.4) for the docked complexes (with Geranyl acetate) with the best binding affinities (-23.4304 kJ/mol with Beta-Lactamase and -28.4512 kJ/mol with WbpE Aminotransferase) and maximum hydrogen bonds. Molecular dynamics simulation studies for both the proteins demonstrated that the complex with Geranyl acetate showed stability comparable to the complex with reference drug observed via Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF) and H-bond analyses. Changes in the secondary structural elements indicated that Geranyl acetate could possibly cause improper functioning of WbpE Aminotransferase leading to disrupted cell wall formation. Further, MM/PBSA analyses showed significant binding affinity of Geranyl acetate with WbpE Aminotransferase and Beta-Lactamase. This study aims to provide rationale for further studies of Coriandrum sativum as an antimicrobial, and to contextualise the results in the current scenario of growing antimicrobial resistance. HIGHLIGHTSPhytoconstituents present in Coriandrum sativum show significant binding affinity to the proteins in Pseudomonas aeruginosa and Staphylococcus aureus.Geranyl acetate exhibited the highest binding affinity with WbpE Aminotransferase involved in O-antigen assembly in Pseudomonas aeruginosa (PDB ID:3NU7) and Beta-Lactamase found in Staphylococcus aureus (PDB ID: 1BLC)Molecular dynamics simulation analyses show that the phytoconstituent, Geranyl acetate has an effect similar to the clinical reference drug, thus exhibiting potential antibacterial activity.Communicated by Ramaswamy H. Sarma.

Haematological, biochemical, enzymological changes and mitochondrial dysfunction of liver in freshwater climbing perch Anabas testudineus during their acute and chronic exposure to sodium fluoride

Anthropogenic activities are increasing fluoride concentration in watercourses. The present study focuses on the sublethal toxicity of sodium fluoride during sub-chronic and chronic time periods in the freshwater fish Anabas testudineus. The 96-hour LC50 value for fluoride was found to be 616.50 mg/L. Excessive mucous production and hyper excitability, followed by loss of balance, were seen in fish under acute fluoride exposure. Significant reduction in yield and specific growth rate of fish were assessed at 15, 30 and 45-days exposure intervals. Different bio-indicators like Hepatosomatic-index, Gonadosomatic-index and fecundity were reduced significantly in fish exposed to 10% (61.6 mg/L) and 20% (123.2 mg/L) of 96 h of LC50 values of fluoride in comparison to control. Toxicant concentrations directly correlated with parameter lowering. Fluoride exposure increased plasma glucose, creatinine, AST, and ALT and reduced total RBC, haemoglobin content, Hct (%), plasma protein, and cholesterol. Moreover, fluoride exposure significantly reduces the mitochondrial membrane potential in liver. This may result in metabolic depression, haematological, biochemical, and enzymological stress. The in-silico structural analysis predicts that fluoride may impede cytochrome c oxidase of the electron transport system, hence inhibiting mitochondrial functionality. These findings collectively highlight the urgent need for stringent regulation and monitoring of fluoride levels in freshwater ecosystems, as the subchronic and chronic effects observed in A. testudineus may have broader implications for aquatic ecosystems.

Molecular Prediction and Correlation of the Structure and Function of Universal Stress Protein A (UspA) from Salmonella Typhimurium

Salmonella Typhimurium (ST) is a zoonotic pathogen that can cause gastroenteritis in humans when they consume contaminated food or water. When exposed to various stressors, both from living organisms (biotic) and the environment (abiotic), Salmonella Typhimurium produces Universal Stress Proteins (USPs). These proteins are gaining recognition for their crucial role in bacterial stress resistance and the ability to enter a prolonged state of growth arrest. Additionally, USPs exhibit diverse structures due to the fusion of the USP domain with different catalytic motifs, enabling them to participate in various reactions and cellular activities during stressful conditions. In this particular study, researchers cloned and analyzed the uspA gene obtained from poultry-derived strains of Salmonella Typhimurium. The gene comprises 435 base pairs, encoding a USP family protein consisting of 144 amino acids. Phylogenetic analysis demonstrated a close relationship between the uspA genes of Salmonella Typhimurium and those found in other bacterial species. We used molecular dynamics simulations and 3D structure prediction to ensure that the USPA protein was stable. Furthermore, we also carried out motif search and network analysis of protein-protein interactions. The findings from this study offer valuable insights for the development of inhibitors targeted against Salmonella Typhimurium.

Targeting RdRp of SARS-CoV-2 with De Novo Molecule Generation

Viruses are known for their extremely high mutation rates, allowing them to evade both the human immune system and many forms of standard medicine. Despite this, the RNA dependent RNA polymerase (RdRp) of the RNA viruses has been largely conserved, and any significant mutation of this protein is unlikely. The recent COVID-19 pandemic presents a need for therapeutics. We have designed a de novo drug design algorithm that generates strong binding ligands from scratch, based on only the structure of the target protein's receptor. In this paper, we applied our method to target SARS-CoV-2 RdRp and generated several de novo molecules. We then chose some drug molecules based on the structural similarity to some of our strongest binding de novo molecules. Subsequently, we showed, using rigorous all-atom explicit-water free energy calculations in near-microsecond time scales using state-of-the-art well-tempered metadynamics simulations, that some of our de novo generated ligands bind more strongly to RdRp than the recent FDA approved drug remdesivir in its active form, remdesivir triphosphate (RTP). We elucidated the binding mechanism for some of the top binders and compared it with RTP. We believe that this work will be useful both by presenting lead structures for RdRp inhibition and by delivering key insights into the residues of the protein potentially involved in the binding/unbinding of these small molecule drugs, leading to more targeted studies in the future.

Phytocompounds as potential inhibitors of mycobacterial multidrug efflux pump Rv1258c: an in silico approach

The number of infections and deaths caused by multidrug resistant (MDR) tuberculosis is increasing globally. One of the efflux pumps, that makes Mycobacterium tuberculosis resistant to a number of antibiotics and results in unfavourable treatment results is Tap or Rv1258c. In our study, we tried to utilize a rational drug design technique using in silico approach to look for an efficient and secure efflux pump inhibitor (EPI) against Rv1258c. The structure of Rv1258c was built using the homology modeling tool MODELLER 9.24. 210 phytocompounds were used for blind and site-specific ligand docking against the modelled structure of Rv1258c using AutoDock Vina software. The best docked plant compounds were further analysed for druglikeness and toxicity. In addition to having excellent docking scores, two plant compounds-ellagic acid and baicalein-also exhibited highly desirable drug-like qualities. These substances outperform more well-known EPIs like piperine and verapamil in terms of effectiveness. This data shows that these two compounds might be further investigated for their potential as Rv1258c inhibitors.

Spectrum of genetic variants in bilateral sensorineural hearing loss

Background: Hearing loss (HL) is an impairment of auditory function with identified genetic forms that can be syndromic (30%) or non-syndromic (70%). HL is genetically heterogeneous, with more than 1,000 variants across 150 causative genes identified to date. The genetic diagnostic rate varies significantly depending on the population being tested. Countries with a considerably high rate of consanguinity provide a unique resource for studying rare forms of recessive HL. In this study, we identified genetic variants associated with bilateral sensorineural HL (SNHL) using whole-exome sequencing (WES) in 11 families residing in the United Arab Emirates (UAE). Results: We established the molecular diagnosis in six probands, with six different pathogenic or likely pathogenic variants in the genes MYO15A, SLC26A4, and GJB2. One novel nonsense variant, MYO15A:p.Tyr1962Ter*, was identified in a homozygous state in one family, which has not been reported in any public database. SLC26A4 and GJB2 were found to be the most frequently associated genes in this study. In addition, six variants of uncertain significance (VUS) were detected in five probands in the genes CDH23, COL11A1, ADGRV1, NLRP3, and GDF6. In total, 12 variants were observed in eight genes. Among these variants, eight missense variants (66.7%), three nonsense variants (25.0%), and one frameshift (8.3%) were identified. The overall diagnostic rate of this study was 54.5%. Approximately 45.5% of the patients in this study came from consanguineous families. Conclusion: Understanding the genetic basis of HL provides insight for the clinical diagnosis of hearing impairment cases through the utilization of next-generation sequencing (NGS). Our findings contribute to the knowledge of the heterogeneous genetic profile of HL, especially in a population with a high rate of consanguineous marriage in the Arab population.

Binding Position Dependent Modulation of Smoothened Activity by Cyclopamine

Cyclopamine is a natural alkaloid that is known to act as an agonist when it binds to the Cysteine Rich Domain (CRD) of the Smoothened receptor and as an antagonist when it binds to the Transmembrane Domain (TMD). To study the effect of cyclopamine binding to each binding site experimentally, mutations in the other site are required. Hence, simulations are critical for understanding the WT activity due to binding at different sites. Additionally, there is a possibility that cyclopamine could bind to both sites simultaneously especially at high concentration, the implications of which remain unknown. We performed three independent sets of simulations to observe the receptor activation with cyclopamine bound to each site independently (CRD, TMD) and bound to both sites simultaneously. Using multi-milliseconds long aggregate MD simulations combined with Markov state models and machine learning, we explored the dynamic behavior of cyclopamine's interactions with different domains of WT SMO. A higher population of the active state at equilibrium, a lower activation free energy barrier of ~ 2 kcal/mol, and expansion of the hydrophobic tunnel to facilitate cholesterol transport agrees with the cyclopamine's agonistic behavior when bound to the CRD of SMO. A higher population of the inactive state at equilibrium, a higher free energy barrier of ~ 4 kcal/mol and restricted the hydrophobic tunnel to impede cholesterol transport showed cyclopamine's antagonistic behavior when bound to TMD. With cyclopamine bound to both sites, there was a slightly larger inactive population at equilibrium and an increased free energy barrier (~ 3.5 kcal/mol). The tunnel was slightly larger than when solely bound to TMD, and showed a balance between agonism and antagonism with respect to residue movements exhibiting an overall weak antagonistic effect.

Molecular Dynamics Simulation of an Iron(III) Binding Site on the Fc Domain of IgG1 Relevant for Visible Light-Induced Protein Fragmentation

Molecular dynamics simulations were employed to investigate the interaction between Fe(III) and an iron-binding site composed of THR259, ASP252, and GLU261 on the Fc domain of an IgG1. The goal was to provide microscopic mechanistic information for the photochemical, iron-dependent site-specific oxidative fragmentation of IgG1 at THR259 reported in our previous paper. The distance between Fe(III) and residues of interest as well as the binding pocket size was examined for both protonated and deprotonated THR259. The Fe(III) binding free energy (ΔG) was estimated by using an umbrella sampling approach. The pKa shift of the THR259 hydroxyl group caused by the presence of nearby Fe(III) was estimated based on a thermodynamic cycle. The simulation results show that Fe(III) resides inside the proposed binding pocket and profoundly changes the pocket configuration. The ΔG values indicate that the pocket possesses a strong binding affinity for Fe(III). Furthermore, Fe(III) profoundly lowers the pKa value of the THR259 hydroxyl group by 5.4 pKa units.

Draft genome sequence of novel Candidatus Ornithobacterium hominis carrying antimicrobial resistance genes in Egypt

BACKGROUND

Candidatus Ornithobacterium hominis (O. hominis), which was identified in nasopharyngeal swabs from Egypt, has been associated with respiratory disorders in humans. O. hominis, a recently identified member of the Flavobacteriaceae family, belongs to the largest family within the Bacteroidetes phylum. This family includes hundreds of species and 90 genera, including major human pathogens such as Capnocytophaga canimorsus and Elizabethkingia meningoseptica. Herein, we presented two draft genome assemblies of O. hominis that were extracted from metagenomic data using the Illumina sequencing method. The alignment of reads against the O. hominis genome was accomplished using BLASTN, and the reads with significant hits were extracted using Seqtk and assembled using SPAdes. The primary goal of this study was to obtain a more profound understanding of the genomic landscape of O. hominis, with an emphasis on identifying the associated virulence, antimicrobial genes, and distinct defense mechanisms to shed light on the potential role of O. hominis in human respiratory infections.

RESULTS

The genome size was estimated to be 1.84 Mb, including 1,931,660 base pairs (bp), with 1,837 predicted coding regions and a G+C content of 35.62%. Genes encoding gliding motility, antibiotic resistance (20 genes), and the toxA gene were all included in the genome assembly. Gliding motility lipoproteins (GldD, GldJ, GldN, and GldH) and the gliding motility-associated ABC transporter substrate-binding protein, which acts as a crucial virulence mechanism in Flavobacterium species, were identified. The genome contained unique genes encoding proteins, such as the ParE1 toxin that defend against the actions of quinolone and other antibiotics. The cobalt-zinc-cadmium resistance gene encoding the protein CzcB, which is necessary for metal resistance, urease regulation, and colonization, was also detected. Several multidrug resistance genes encoding proteins were identified, such as MexB, MdtK, YheI, and VanC.

CONCLUSION

Our study focused on identifying virulence factors, and antimicrobial resistance genes present in the core genome of O. hominis. These findings provide valuable insights into the potential pathogenicity and antibiotic susceptibility of O. hominis.

Viper Venom Phospholipase A2 Database: The Structural and Functional Anatomy of a Primary Toxin in Envenomation

Viper venom phospholipase A2 enzymes (vvPLA2s) and phospholipase A2-like (PLA2-like) proteins are two of the principal toxins in viper venom that are responsible for the severe myotoxic and neurotoxic effects caused by snakebite envenoming, among other pathologies. As snakebite envenoming is the deadliest neglected tropical disease, a complete understanding of these proteins' properties and their mechanisms of action is urgently needed. Therefore, we created a database comprising information on the holo-form, cofactor-bound 3D structure of 217 vvPLA2 and PLA2-like proteins in their physiologic environment, as well as 79 membrane-bound viper species from 24 genera, which we have made available to the scientific community to accelerate the development of new anti-snakebite drugs. In addition, the analysis of the sequenced, 3D structure of the database proteins reveals essential aspects of the anatomy of the proteins, their toxicity mechanisms, and the conserved binding site areas that may anchor universal interspecific inhibitors. Moreover, it pinpoints hypotheses for the molecular origin of the myotoxicity of the PLA2-like proteins. Altogether, this study provides an understanding of the diversity of these toxins and how they are conserved, and it indicates how to develop broad, interspecies, efficient small-molecule inhibitors to target the toxin's many mechanisms of action.

Molecular Dynamics and Machine Learning reveal distinguishing mechanisms of Competitive Ligands to perturb α,β-Tubulin

The mechanisms of action of ligands competing for the Colchicine Binding Site (CBS) of the α,β-Tubulin are non-standard compared to the commonly witnessed ligand-induced inhibition of proteins. This is because their potencies are not solely judged by the binding affinity itself, but also by their capacity to bias the conformational states of the dimer. Regarding the latter requirement, it is observed that ligands competing for the same pocket that binds colchicine exhibit divergence in potential clinical outcomes. Molecular dynamics-based ∼5.2 µs sampling of α,β-Tubulin complexed with four different ligands has revealed that each ligand has its customized way of influencing the complex. Primarily, it is the proportion of twisting and/or bending characteristic of modes of the intrinsic dynamics which is revealed to be 'fundamental' to tune this variation in the mechanism. The milder influence of 'bending' makes a ligand (TUB092), better classifiable under the group of vascular disrupting agents (VDAs), which are phenotypically effective on cytoskeletons; whereas a stronger impact of 'bending' makes the classical ligand Colchicine (COL) a better Anti-Mitotic agent (AMA). Two other ligands BAL27862 (2RR) and Nocodazole (NZO) fall in the intermediate zone as they fail to explicitly induce bending modes. Random Forest Classification method and K-means Clustering is applied to reveal the efficiency of Machine Learning methods in classifying the Tubulin conformations according to their ligand-specific perturbations and to highlight the significance of specific amino acid residues, mostly positioned in the α-β and β-β interfaces involved in the mechanism. These key residues responsible to yield discriminative actions of the ligands are likely to be highly useful in future endeavours to design more precise inhibitors.

Minor changes in electrostatics robustly increase VP40 membrane binding, assembly, and budding of Ebola virus matrix protein derived virus-like particles

Ebola virus (EBOV) is a filamentous negative-sense RNA virus which causes severe hemorrhagic fever. There are limited vaccines or therapeutics for prevention and treatment of EBOV, so it is important to get a detailed understanding of the virus lifecycle to illuminate new drug targets. EBOV encodes for the matrix protein, VP40, which regulates assembly and budding of new virions from the inner leaflet of the host cell plasma membrane (PM). In this work we determine the effects of VP40 mutations altering electrostatics on PM interactions and subsequent budding. VP40 mutations that modify surface electrostatics affect viral assembly and budding by altering VP40 membrane binding capabilities. Mutations that increase VP40 net positive charge by one (e.g., Gly to Arg or Asp to Ala) increase VP40 affinity for phosphatidylserine (PS) and PI(4,5)P2 in the host cell PM. This increased affinity enhances PM association and budding efficiency leading to more effective formation of virus-like particles (VLPs). In contrast, mutations that decrease net positive charge by one (e.g., Gly to Asp) lead to a decrease in assembly and budding because of decreased interactions with the anionic PM. Taken together our results highlight the sensitivity of slight electrostatic changes on the VP40 surface for assembly and budding. Understanding the effects of single amino acid substitutions on viral budding and assembly will be useful for explaining changes in the infectivity and virulence of different EBOV strains, VP40 variants that occur in nature, and for long-term drug discovery endeavors aimed at EBOV assembly and budding.

Explicit ion modeling predicts physicochemical interactions for chromatin organization

Molecular mechanisms that dictate chromatin organization in vivo are under active investigation, and the extent to which intrinsic interactions contribute to this process remains debatable. A central quantity for evaluating their contribution is the strength of nucleosome-nucleosome binding, which previous experiments have estimated to range from 2 to 14 kBT. We introduce an explicit ion model to dramatically enhance the accuracy of residue-level coarse-grained modeling approaches across a wide range of ionic concentrations. This model allows for de novo predictions of chromatin organization and remains computationally efficient, enabling large-scale conformational sampling for free energy calculations. It reproduces the energetics of protein-DNA binding and unwinding of single nucleosomal DNA, and resolves the differential impact of mono- and divalent ions on chromatin conformations. Moreover, we showed that the model can reconcile various experiments on quantifying nucleosomal interactions, providing an explanation for the large discrepancy between existing estimations. We predict the interaction strength at physiological conditions to be 9 kBT, a value that is nonetheless sensitive to DNA linker length and the presence of linker histones. Our study strongly supports the contribution of physicochemical interactions to the phase behavior of chromatin aggregates and chromatin organization inside the nucleus.

In silico screening of phytoconstituents as potential anti-inflammatory agents targeting NF-κB p65: an approach to promote burn wound healing

Chronic burn wounds are frequently characterised by a prolonged and dysregulated inflammatory phase that is mediated by over-activation of NF-κB p65. Synthetic wound healing drugs used for treatment of inflammation are primarily associated with several shortcomings which reduce their therapeutic index. In this scenario, phytoconstituents that exhibit multifaceted biological activities including anti-inflammatory effects have emerged as a promising therapeutic alternative. However, identification and isolation of phytoconstituents from medicinal herbs is a cumbersome method that is linked to profound uncertainty. Hence, present study aimed to identify prospective phytoconstituents as inhibitors of RHD of NF-κB p65 by utilizing in silico approach. Virtual screening of 2821 phytoconstituents was performed against protein model. Out of 2821 phytoconstituents, 162 phytoconstituents displayed a higher binding affinity (≤ -8.0 kcal/mol). These 162 phytoconstituents were subjected to ADMET predictions, and 15 of them were found to satisfy Lipinski's rule of five and showed favorable pharmacokinetic properties. Among these 15 phytoconstituents, 5 phytoconstituents with high docking scores i.e. silibinin, bismurrayaquinone A, withafastuosin B, yuccagenin, (+)-catechin 3-gallate were selected for molecular dynamics (MD) simulation analysis. Results of MD simulation indicated that withafastuosin B, (+)-catechin 3-gallate and yuccagenin produced a compact and stable complex with protein without significant variations in conformation. Relative binding energy analysis of best hit molecules indicate that withafastuosin B, and (+)-catechin 3-gallate exhibit high binding affinity with target protein among other lead molecules. Findings of study suggest that these phytoconstituents could serve as promising anti-inflammatory agents for treatment of burn wounds by inhibiting the RHD of NF-κB p65.Communicated by Ramaswamy H. Sarma.

Identification and characterization of GLYCEROLIPASE A1 for wound-triggered JA biosynthesis in Nicotiana benthamiana leaves

Although many important discoveries have been made regarding the jasmonate signaling pathway, how jasmonate biosynthesis is initiated is still a major unanswered question in the field. Previous evidences suggest that jasmonate biosynthesis is limited by the availability of fatty acid precursor, such as ⍺-linolenic acid (⍺-LA). This indicates that the lipase responsible for releasing α-LA in the chloroplast, where early steps of jasmonate biosynthesis take place, is the key initial step in the jasmonate biosynthetic pathway. Nicotiana benthamiana glycerol lipase A1 (NbGLA1) is homologous to N. attenuata GLA1 (NaGLA1) which has been reported to be a major lipase in leaves for jasmonate biosynthesis. NbGLA1 was studied for its potential usefulness in a species that is more common in laboratories. Virus-induced gene silencing of both NbGLA1 and NbGLA2, another homolog, resulted in more than 80% reduction in jasmonic acid (JA) biosynthesis in wounded leaves. Overexpression of NbGLA1 utilizing an inducible vector system failed to increase JA, indicating that transcriptional induction of NbGLA1 is insufficient to trigger JA biosynthesis. However, co-treatment with wounding in addition to NbGLA1 induction increased JA accumulation several fold higher than the gene expression or wounding alone, indicating an enhancement of the enzyme activity by wounding. Domain-deletion of a 126-bp C-terminal region hypothesized to have regulatory roles increased NbGLA1-induced JA level. Together, the data show NbGLA1 to be a major lipase for wound-induced JA biosynthesis in N. benthamiana leaves and demonstrate the use of inducible promoter-driven construct of NbGLA1 in conjunction with its transient expression in N. benthamiana as a useful system to study its protein function.

Early detection of liver injuries by the Serum enhanced binding test sensitive to albumin post-transcriptional modifications

Early and sensitive biomarkers of liver dysfunction and drug-induced liver injury (DILI) are still needed, both for patient care and drug development. We developed the Serum Enhanced Binding (SEB) test to reveal post-transcriptional modifications (PTMs) of human serum albumin resulting from hepatocyte dysfunctions and further evaluated its performance in an animal model. The SEB test consists in spiking serum ex-vivo with ligands having specific binding sites related to the most relevant albumin PTMs and measuring their unbound fraction. To explore the hypothesis that albumin PTMs occur early during liver injury and can also be detected by the SEB test, we induced hepatotoxicity in male albino Wistar rats by administering high daily doses of ethanol and CCl4 over several days. Blood was collected for characterization and quantification of albumin isoforms by high-resolution mass spectrometry, for classical biochemical analyses as well as to apply the SEB test. In the exposed rats, the appearance of albumin isoforms paralleled the positivity of the SEB test ligands and histological injuries. These were observed as early as D3 in the Ethanol and CCl4 groups, whereas the classical liver tests (ALT, AST, PAL) significantly increased only at D7. The behavior of several ligands was supported by structural and molecular simulation analysis. The SEB test and albumin isoforms revealed hepatocyte damage early, before the current biochemical biomarkers. The SEB test should be easier to implement in the clinics than albumin isoform profiling.

Guiding discovery of protein sequence-structure-function modeling

MOTIVATION

Protein engineering techniques are key in designing novel catalysts for a wide range of reactions. Although approaches vary in their exploration of the sequence-structure-function paradigm, they are often hampered by the labor-intensive steps of protein expression and screening. In this work, we describe the development and testing of a high-throughput in silico sequence-structure-function pipeline using AlphaFold2 and fast Fourier transform docking that is benchmarked with enantioselectivity and reactivity predictions for an ancestral sequence library of fungal flavin-dependent monooxygenases.

RESULTS

The predicted enantioselectivities and reactivities correlate well with previously described screens of an experimentally available subset of these proteins and capture known changes in enantioselectivity across the phylogenetic tree representing ancestorial proteins from this family. With this pipeline established as our functional screen, we apply ensemble decision tree models and explainable AI techniques to build sequence-function models and extract critical residues within the binding site and the second-sphere residues around this site. We demonstrate that the top-identified key residues in the control of enantioselectivity and reactivity correspond to experimentally verified residues. The in silico sequence-to-function pipeline serves as an accelerated framework to inform protein engineering efforts from vast informative sequence landscapes contained in protein families, ancestral resurrects, and directed evolution campaigns.

AVAILABILITY

Jupyter notebooks detailing the sequence-structure-function pipeline are available at https://github.com/BrooksResearchGroup-UM/seq_struct_func.

Amalgamated Pharmacoinformatics Study to Investigate the Mechanism of Xiao Jianzhong Tang against Chronic Atrophic Gastritis

BACKGROUND

Traditional Chinese medicine (TCM) Xiao Jianzhong Tang (XJZ) has a favorable efficacy in the treatment of chronic atrophic gastritis (CAG). However, its pharmacological mechanism has not been fully explained.

OBJECTIVE

The purpose of this study was to find the potential mechanism of XJZ in the treatment of CAG using pharmacocoinformatics approaches.

METHODS

Network pharmacology was used to screen out the key compounds and key targets, MODELLER and GNNRefine were used to repair and refine proteins, Autodock vina was employed to perform molecular docking, Δ Lin_F9XGB was used to score the docking results, and Gromacs was used to perform molecular dynamics simulations (MD).

RESULTS

Kaempferol, licochalcone A, and naringenin, were obtained as key compounds, while AKT1, MAPK1, MAPK14, RELA, STAT1, and STAT3 were acquired as key targets. Among docking results, 12 complexes scored greater than five. They were run for 50ns MD. The free binding energy of AKT1-licochalcone A and MAPK1-licochalcone A was less than -15 kcal/mol and AKT1-naringenin and STAT3-licochalcone A was less than -9 kcal/mol. These complexes were crucial in XJZ treating CAG.

CONCLUSION

Our findings suggest that licochalcone A could act on AKT1, MAPK1, and STAT3, and naringenin could act on AKT1 to play the potential therapeutic effect on CAG. The work also provides a powerful approach to interpreting the complex mechanism of TCM through the amalgamation of network pharmacology, deep learning-based protein refinement, molecular docking, machine learning-based binding affinity estimation, MD simulations, and MM-PBSA-based estimation of binding free energy.

A repository of COVID-19 related molecular dynamics simulations and utilisation in the context of nsp10-nsp16 antivirals

The coronavirus disease 2019 (COVID-19) pandemic highlighted the importance of establishing systems and infrastructure to develop vaccines, antiviral drugs, and therapeutic antibodies against emerging pathogens. Typical drug discovery processes involve targeting suitable proteins to effect pathogen replication or to attenuate host responses, by examining either large chemical databases or protein-protein interactions. Following initial screens, molecular dynamics (MD) simulations are critical for gaining further insight into molecular interactions. During the COVID-19 pandemic, many research groups made their simulations widely available, as highlighted by the comprehensive D.E. Shaw Research trajectory database. To investigate protein target sites and evaluate potential lead compounds, we performed over 300 MD simulations relating to COVID-19. We organised our simulations into a repository, which is publicly available at https://epimedlab.org/trajectories/. The trajectories cover a large part of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteome, and the majority of our MD simulations focused on the identification of potential antivirals. For example, we focused on the S-adenosyl-l-methionine binding site of the nsp10-nsp16 complex, a critical component of viral replication, revealing verbascoside as a potential lead. Moreover, we utilised MD trajectories to explore the interface between the spike protein receptor binding domain and human angiotensin-converting enzyme 2 receptor, with the ultimate aim being investigation of new variants in real-time. Overall, MD simulations are a critical component of the in silico drug discovery process and as highlighted throughout the pandemic, data sharing enables accelerated progress. We have organised our extensive collection of COVID-19 related MD trajectories into an easily accessible repository.

Trapping Charge Mechanism in Hv1 Channels (CiHv1)

The majority of voltage-gated ion channels contain a defined voltage-sensing domain and a pore domain composed of highly conserved amino acid residues that confer electrical excitability via electromechanical coupling. In this sense, the voltage-gated proton channel (Hv1) is a unique protein in that voltage-sensing, proton permeation and pH-dependent modulation involve the same structural region. In fact, these processes synergistically work in concert, and it is difficult to separate them. To investigate the process of Hv1 voltage sensor trapping, we follow voltage-sensor movements directly by leveraging mutations that enable the measurement of Hv1 channel gating currents. We uncover that the process of voltage sensor displacement is due to two driving forces. The first reveals that mutations in the selectivity filter (D160) located in the S1 transmembrane interact with the voltage sensor. More hydrophobic amino acids increase the energy barrier for voltage sensor activation. On the other hand, the effect of positive charges near position 264 promotes the formation of salt bridges between the arginines of the voltage sensor domain, achieving a stable conformation over time. Our results suggest that the activation of the Hv1 voltage sensor is governed by electrostatic-hydrophobic interactions, and S4 arginines, N264 and selectivity filter (D160) are essential in the Ciona-Hv1 to understand the trapping of the voltage sensor.

In silico evaluation of S-adenosyl-L-homocysteine analogs as inhibitors of nsp14-viral cap N7 methyltranferase and PLpro of SARS-CoV-2: synthesis, molecular docking, physicochemical data, ADMET and molecular dynamics simulations studies

A series of S-adenosyl-L-homosysteine (SAH) analogs, with modification in the base and sugar moiety, have been designed, synthesized and screened as nsp14 and PLpro inhibitors of severe acute respiratory syndrome corona virus (SARS-CoV-2). The outcomes of ADMET (Adsorption, Distribution, Metabolism, Excretion, and Toxicity) studies demonstrated that the physicochemical properties of all analogs were permissible for development of these SAH analogs as antiviral agents. All molecules were screened against different SARS-CoV-2 targets using molecular docking. The docking results revealed that the SAH analogs interacted well in the active site of nsp14 protein having H-bond interactions with the amino acid residues Arg289, Val290, Asn388, Arg400, Phe401 and π-alkyl interactions with Arg289, Val290 and Phe426 of Nsp14-MTase site. These analogs also formed stable H-bonds with Leu163, Asp165, Arg167, Ser246, Gln270, Tyr274 and Asp303 residues of PLpro proteins and found to be quite stable complexes therefore behaved as probable nsp14 and PLpro inhibitors. Interestingly, analog 3 showed significant in silico activity against the nsp14 N7 methyltransferase of SARS-CoV-2. The molecular dynamics (MD) and post-MD results of analog 3 unambiguously established the higher stability of the nsp14 (N7 MTase):3 complex and also indicated its behavior as probable nsp14 inhibitor like the reference sinefungin. The docking and MD simulations studies also suggested that sinefungin did act as SARS-CoV-2 PLpro inhibitor as well. This study's findings not only underscore the efficacy of the designed SAH analogs as potent inhibitors against crucial SARS-CoV-2 proteins but also pinpoint analog 3 as a particularly promising candidate. All the study provides valuable insights, paving the way for potential advancements in antiviral drug development against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Computational drug discovery of an inhibitor of APOBEC3B as a treatment for epithelial cancers

Cancer is one of the leading causes of death in the U.S., and tumorous cancers such as cervical, lung, breast, and ovarian cancers are the most common types. APOBEC3B is a nonessential cytidine deaminase found in humans and theorized to defend against viral infection. However, overexpression of APOBEC3B is linked to cancer in humans, which makes APOBEC3B a potential cancer treatment target through competitive inhibition for several tumorous cancers. Computational studies can help reveal a small molecule inhibitor using high-throughput virtual screening of millions of candidates with relatively little cost. This study aims to narrow the field of potential APOBEC3B inhibition candidates for future in vitro assays and provide an effective scaffold for drug design studies. Another goal of this project is to provide critical amino acid targets in the active site for future drug design studies. This study simulated 7.8 million drug candidates using high-throughput virtual screening and further processed the top scoring 241 molecules from AutoDock Vina, DOCK 6, and de novo design. Using virtual screening, de novo design, and molecular dynamics simulations, a competitive inhibitor candidate was discovered with an average binding free energy score of -46.03 kcal/mol, more than 10 kcal/mol better than the substrate control (dCMP). These results indicate that this molecule (or a structural derivative) may be an effective inhibitor of APOBEC3B and prevent host genome mutagenesis resulting from protein overexpression. Another important finding is the confirmation of essential amino acid targets, such as Tyr250 and Gln213 within the active site of APOBEC3B. Therefore, study used novel computational methods to provide a theoretical scaffold for future drug design studies that may prove useful as a treatment for epithelial cancers.Communicated by Ramaswamy H. Sarma.

K-Means Clustering Coarse-Graining (KMC-CG): A Next Generation Methodology for Determining Optimal Coarse-Grained Mappings of Large Biomolecules

Coarse-grained (CG) molecular dynamics (MD) has become a method of choice for simulating various large scale biomolecular processes; therefore, the systematic definition of the CG mappings for biomolecules remains an important topic. Appropriate CG mappings can significantly enhance the representability of a CG model and improve its ability to capture critical features of large biomolecules. In this work, we present a systematic and more generalized method called K-means clustering coarse-graining (KMC-CG), which builds on the earlier approach of essential dynamics coarse-graining (ED-CG). KMC-CG removes the sequence-dependent constraints of ED-CG, allowing it to explore a more extensive space and thus enabling the discovery of more physically optimal CG mappings. Furthermore, the implementation of the K-means clustering algorithm can variationally optimize the CG mapping with efficiency and stability. This new method is tested in three cases: ATP-bound G-actin, the HIV-1 CA pentamer, and the Arp2/3 complex. In these examples, the CG models generated by KMC-CG are seen to better capture the structural, dynamic, and functional domains. KMC-CG therefore provides a robust and consistent approach to generating CG models of large biomolecules that can then be more accurately parametrized by either bottom-up or top-down CG force fields.

Structural and thermodynamic insights into antibody light chain tetramer formation through 3D domain swapping

Overexpression of antibody light chains in small plasma cell clones can lead to misfolding and aggregation. On the other hand, the formation of amyloid fibrils from antibody light chains is related to amyloidosis. Although aggregation of antibody light chain is an important issue, atomic-level structural examinations of antibody light chain aggregates are sparse. In this study, we present an antibody light chain that maintains an equilibrium between its monomeric and tetrameric states. According to data from X-ray crystallography, thermodynamic and kinetic measurements, as well as theoretical studies, this antibody light chain engages in 3D domain swapping within its variable region. Here, a pair of domain-swapped dimers creates a tetramer through hydrophobic interactions, facilitating the revelation of the domain-swapped structure. The negative cotton effect linked to the β-sheet structure, observed around 215 nm in the circular dichroism (CD) spectrum of the tetrameric variable region, is more pronounced than that of the monomer. This suggests that the monomer contains less β-sheet structures and exhibits greater flexibility than the tetramer in solution. These findings not only clarify the domain-swapped structure of the antibody light chain but also contribute to controlling antibody quality and advancing the development of future molecular recognition agents and drugs.

Revolutionizing Biological Science: The Synergy of Genomics in Health, Bioinformatics, Agriculture, and Artificial Intelligence

With climate emergency, COVID-19, and the rise of planetary health scholarship, the binary of human and ecosystem health has been deeply challenged. The interdependence of human and nonhuman animal health is increasingly acknowledged and paving the way for new frontiers in integrative biology. The convergence of genomics in health, bioinformatics, agriculture, and artificial intelligence (AI) has ushered in a new era of possibilities and applications. However, the sheer volume of genomic/multiomics big data generated also presents formidable sociotechnical challenges in extracting meaningful biological, planetary health and ecological insights. Over the past few years, AI-guided bioinformatics has emerged as a powerful tool for managing, analyzing, and interpreting complex biological datasets. The advances in AI, particularly in machine learning and deep learning, have been transforming the fields of genomics, planetary health, and agriculture. This article aims to unpack and explore the formidable range of possibilities and challenges that result from such transdisciplinary integration, and emphasizes its radically transformative potential for human and ecosystem health. The integration of these disciplines is also driving significant advancements in precision medicine and personalized health care. This presents an unprecedented opportunity to deepen our understanding of complex biological systems and advance the well-being of all life in planetary ecosystems. Notwithstanding in mind its sociotechnical, ethical, and critical policy challenges, the integration of genomics, multiomics, planetary health, and agriculture with AI-guided bioinformatics opens up vast opportunities for transnational collaborative efforts, data sharing, analysis, valorization, and interdisciplinary innovations in life sciences and integrative biology.

Molecular Modeling and Optimization of Type II E.coli l-Asparginase Activity by in silico Design and in vitro Site-directed Mutagenesis

INTRODUCTION

L-asparaginase (also known as L-ASNase) is a crucial therapeutic enzyme that is widely used in treatment of ALL (acute lymphoblastic leukemia) as a chemotherapeutic drug. Besides, this enzyme is used in the food industry as a food processing reagent to reduce the content of acrylamide in addition to the clinical industry. The improvement of activity and kinetic parameters of the L-ASNase enzyme may lead to higher efficiency resulting in practical achievement. In order to achieve this goal, we chosen glycine residue in position 88 as a potential mutation with advantageous outcomes.

METHOD

In this study, firstly to find the appropriate mutation on glycine 88, various in silico analyses, such as MD simulation and molecular docking, were carried out. Then, the rational design was adopted as the best strategy for molecular modifications of the enzyme to improve its enzymatic properties.

RESULT

Our in silico findings show that the four mutations G88Q, G88L, G88K, and G88A may be able to increase L-ASNase's asparaginase activity. The catalytic efficiency of each enzyme (kcat/Km) is the most important feature for comparing the catalytic activity of the mutants with the wild type form. The laboratory experiments showed that the kcat/Km for the G88Q mutant is 36.32% higher than the Escherichia coli K12 ASNase II (wild type), which suggests that L-ASNase activity is improved at lower concentration of L-ASN. Kinetic characterization of the mutants L-ASNase activity confirmed the high turnover rate (kcat) with ASN as substrate relative to the wild type enzyme.

CONCLUSION

In silico analyses and laboratory experiments demonstrated that the G88Q mutation rather than other mutation (G88L, G88K, and G88A) could improve the kinetics of L-ASNase.

Protective effects of niacin following high fat rich diet: an in-vivo and in-silico study

Niacin had long been understood as an antioxidant. There were reports that high fat diet (HFD) may cause psychological and physical impairments. The present study was aimed to experience the effect of Niacin on % growth rate, cumulative food intake, motor activity and anxiety profile, redox status, 5-HT metabolism and brain histopathology in rats. Rats were administered with Niacin at a dose of 50 mg/ml/kg body weight for 4 weeks following normal diet (ND) and HFD. Behavioral tests were performed after 4 weeks. Animals were sacrificed to collect brain samples. Biochemical, neurochemical and histopathological studies were performed. HFD increased food intake and body weight. The exploratory activity was reduced and anxiety like behavior was observed in HFD treated animals. Activity of antioxidant enzymes was decreased while oxidative stress marker and serotonin metabolism in the brain of rat were increased in HFD treated animals than ND fed rats. Morphology of the brain was also altered by HFD administration. Conversely, Niacin treated animals decreased food intake and % growth rate, increased exploratory activity, produced anxiolytic effects, decreased oxidative stress and increased antioxidant enzyme and 5-HT levels following HFD. Morphology of brain is also normalized by the treatment of Niacin following HFD. In-silico studies showed that Niacin has a potential binding affinity with degradative enzyme of 5-HT i.e. monoamine oxidase (MAO) A and B with an energy of ~ - 4.5 and - 5.0 kcal/mol respectively. In conclusion, the present study showed that Niacin enhanced motor activity, produced anxiolytic effect, and reduced oxidative stress, appetite, growth rate, increased antioxidant enzymes and normalized serotonin system and brain morphology following HFD intake. In-silico studies suggested that increase 5-HT was associated with the binding of MAO with Niacin subsequentially an inhibition of the degradation of monoamine. It is suggested that Niacin has a great antioxidant potential and could be a good therapy for the treatment of HFD induced obesity.

Equivariant Flexible Modeling of the Protein-Ligand Binding Pose with Geometric Deep Learning

Flexible modeling of the protein-ligand complex structure is a fundamental challenge for in silico drug development. Recent studies have improved commonly used docking tools by incorporating extra-deep learning-based steps. However, such strategies limit their accuracy and efficiency because they retain massive sampling pressure and lack consideration for flexible biomolecular changes. In this study, we propose FlexPose, a geometric graph network capable of direct flexible modeling of complex structures in Euclidean space without the following conventional sampling and scoring strategies. Our model adopts two key designs: scalar-vector dual feature representation and SE(3)-equivariant network, to manage dynamic structural changes, as well as two strategies: conformation-aware pretraining and weakly supervised learning, to boost model generalizability in unseen chemical space. Benefiting from these paradigms, our model dramatically outperforms all tested popular docking tools and recently advanced deep learning methods, especially in tasks involving protein conformation changes. We further investigate the impact of protein and ligand similarity on the model performance with two conformation-aware strategies. Moreover, FlexPose provides an affinity estimation and model confidence for postanalysis.

A Combined Ligand- and Structure-Based Virtual Screening To Identify Novel NaV1.2 Blockers: In Vitro Patch Clamp Validation and In Vivo Anticonvulsant Activity

Epilepsy is a neurological disorder characterized by recurrent seizures that arise from abnormal electrical activity in the brain. Voltage-gated sodium channels (NaVs), responsible for the initiation and propagation of action potentials in neurons, play a critical role in the pathogenesis of epilepsy. This study sought to discover potential anticonvulsant compounds that interact with NaVs, specifically, the brain subtype hNaV1.2. A ligand-based QSAR model and a docking model were constructed, validated, and applied in a parallel virtual screening over the DrugBank database. Montelukast, Novobiocin, and Cinnarizine were selected for in vitro testing, using the patch-clamp technique, and all of them proved to inhibit hNaV1.2 channels heterologously expressed in HEK293 cells. Two hits were evaluated in the GASH/Sal model of audiogenic seizures and demonstrated promising activity, reducing the severity of sound-induced seizures at the doses tested. The combination of ligand- and structure-based models presents a valuable approach for identifying potential NaV inhibitors. These findings may provide a basis for further research into the development of new antiseizure drugs for the treatment of epilepsy.

Promotion of ABCG2 gene expression by neolignans from Piper longum L

We focused on Piper longum L., a herbal drug produced in Myanmar, which has a renoprotective effect. Thus, we attempted to isolate and identify compounds that enhance the expression of the ABCG2 gene from the aerial parts of the plant except for the fruit. Among the various P. longum extracts, we isolated and identified the components. Using Caco-2 cells, the hABCG2 mRNA expression-enhancing effects of the isolated compounds were compared with the positive reference compound (3-methylcholanthrene [3MC]) using real-time polymerase chain reaction. Six compounds were isolated and identified from the methanol extract of P. longum. Among the isolated compounds, licarin A and neopomatene had lower toxicity and higher hABCG2 mRNA expression-enhancing effects in Caco-2 cells. Suppression of hAhR expression by siRNA reduced the activity of licarin A and neopomatene, as well as the hAhR agonist 3MC, suggesting that these 2 compounds may act as hAhR agonists to promote hABCG2 expression.

Simulation-guided engineering of split GFPs with efficient β-strand photodissociation

Green fluorescent proteins (GFPs) are ubiquitous for protein tagging and live-cell imaging. Split-GFPs are widely used to study protein-protein interactions by fusing proteins of interest to split GFP fragments that create a fluorophore upon typically irreversible complementation. Thus, controlled dissociation of the fragments is desirable. Although we have found that split strands can be photodissociated, the quantum efficiency of light-induced photodissociation of split GFPs is low. Traditional protein engineering approaches to increase efficiency, including extensive mutagenesis and screening, have proved difficult to implement. To reduce the search space, key states in the dissociation process are modeled by combining classical and enhanced sampling molecular dynamics with QM/MM calculations, enabling the rational design and engineering of split GFPs with up to 20-fold faster photodissociation rates using non-intuitive amino acid changes. This demonstrates the feasibility of modeling complex molecular processes using state-of-the-art computational methods, and the potential of integrating computational methods to increase the success rate in protein engineering projects.

Structure prediction, docking studies and molecular cloning of novel Pichia kudriavzevii YK46 metalloprotease (MetPr) for improvement of feather waste biodegradation

This study addresses the environmental risks associated with the accumulation of keratin waste from poultry, which is resistant to conventional protein degradation methods. To tackle this issue, microbial keratinases have emerged as promising tools for transforming resilient keratin materials into valuable products. We focus on the Metalloprotease (MetPr) gene isolated from novel Pichia kudriavzevii YK46, sequenced, and deposited in the NCBI GenBank database with the accession number OQ511281. The MetPr gene encodes a protein consisting of 557 amino acids and demonstrates a keratinase activity of 164.04 U/ml. The 3D structure of the protein was validated using Ramachandran's plot, revealing that 93% and 97.26% of the 557 residues were situated within the most favoured region for the MetPr proteins of template Pichia kudriavzevii strain 129 and Pichia kudriavzevii YK46, respectively. Computational analyses were employed to determine the binding affinities between the deduced protein and beta keratin. Molecular docking studies elucidated the optimal binding affinities between the metalloprotease (MetPr) and beta-keratin, yielding values of - 260.75 kcal/mol and - 257.02 kcal/mol for the template strains Pichia kudriavzevii strain 129 and Pichia kudriavzevii YK46, respectively. Subsequent molecular cloning and expression of the MetPr gene in E. coli DH5α led to a significantly higher keratinase activity of 281 ± 12.34 U/ml. These findings provide valuable insights into the potential of the MetPr gene and its encoded protein for keratin waste biotransformation, with implications for addressing environmental concerns related to keratinous waste accumulation.

Neutralizing Antibody Response to Genotypically Diverse Measles Viruses in Clinically Suspected Measles Cases

The neutralizing antibody (Nt-Ab) response to vaccine and wild-type measles viruses (MeV) was studied in suspected measles cases reported during the years 2012-2016. The neutralization activity against MeV A, D4 and D8 genotypes was studied on sera (Panel A; n = 68 (measles-immunized) and Panel B; n = 50 (unvaccinated)) that were either laboratory confirmed or not confirmed by the presence of IgM antibodies. Additionally, the Nt-Ab response in Panel A was measured against the MeV vaccine and four wild-type viruses. Neutralization results were compared using homology modeling and molecular dynamics simulation (MDS) of MeV-hemagglutinin (H) and fusion (F) proteins. Overall, the Nt-Ab titres for MeV-A were found to be significantly lower than MeV-D4 and MeV-D8 viruses for Panel A. No major difference was noted in Nt-Ab titres between MeV-D8 viruses (Jamnagar and New Delhi), whereas MeV-D4 (Sindhudurg and Bagalkot (BGK) viruses) showed significant differences between Nt-Ab titres for Panel B. Interestingly, the substitutions observed in epitopes of H-protein, L249P and G316A are observed to be unique to MeV-BGK. MDS of H-protein revealed significant fluctuations in neutralizing epitopes due to L249P substitution. The majority of the clinically suspected cases showed Nt-Abs to MeV wild-types. Higher IgG antibody avidity and Nt-Ab titres were noted in IgM-negatives than in IgM-positives cases, indicating reinfection or breakthrough. MDS revealed reduced neutralization due to decreased conformational flexibility in the H-epitope.

Complex Conformational Space of the RNA Polymerase II C-Terminal Domain upon Phosphorylation

Intrinsically disordered proteins (IDPs) have been closely studied during the past decade due to their importance in many biological processes. The disordered nature of this group of proteins makes it difficult to observe its full span of the conformational space using either experimental or computational studies. In this article, we explored the conformational space of the C-terminal domain (CTD) of RNA polymerase II (Pol II), which is also an intrinsically disordered low complexity domain, using enhanced sampling methods. We provided a detailed conformational analysis of model systems of CTD with different lengths; first with the last 44 residues of the human CTD sequence and finally the CTD model with 2-heptapeptide repeating units. We then investigated the effects of phosphorylation on CTD conformations by performing simulations at different phosphorylated states. We obtained broad conformational spaces in nonphosphorylated CTD models, and phosphorylation has complex effects on the conformations of the CTD. These complex effects depend on the length of the CTD, spacing between the multiple phosphorylation sites, ion coordination, and interactions with the nearby residues.

A novel missense compound heterozygous variant in TLR1 gene is associated with susceptibility to rheumatoid arthritis - structural perspective and functional annotations

INTRODUCTION

Besides human leukocyte antigen (HLA-DRB1) locus, more than 100 loci across the genome have been identified and linked with the onset, expression and/or progression of rheumatoid arthritis (RA). However, there are still grey areas in our understanding of the key genetic contributors of the disease, particularly in familial cases.

METHODS

In the present study, we have performed the whole exome sequencing (WES) of RA patients from two consanguineous families of Pakistan in a quest to identify novel, high-impact, RA-susceptibility genetic variants.

RESULTS

Through stepwise filtering, around 17,000 variants (common in the affected members) were recognized, out of which 2651 were predicted to be deleterious. Of these, 196 had direct relevance to RA. When selected for homozygous recessive mode of inheritance, two novel pathogenic variants (c.1324T>C, p.Cys442→Arg442; c.2036T>C, p.Ile679→Thr679) in the TLR1 gene displayed the role of compound heterozygosity in modulating the phenotypic expression and penetrance of RA. The structural and functional consequences of the TLR1 missense single nucleotide mutations (Cys442→Arg442; Ile679→Thr679) were evaluated through molecular dynamic simulation (MDS) studies. Analysis showed domain's rigidification, conferring stability to mutant TLR1-TIR/TIRAP-TIR complex with concomitant increase in molecular interactions with pro-inflammatory cytokines, compared to the wild-type conformation. Gene co-expression network analysis highlighted interlinked partnering genes along with interleukin-6 production of TLR1 (corrected p-value 2.98e-4) and acetylcholine receptor activity of CHRNG (corrected p-value 6.12e-2) as highly enriched associated functions.

CONCLUSION

The results, validated through case-control study subjects, suggested that the variants identified through WES and confirmed through Sanger sequencing and MDS are the novel disease variants and are likely to confer RA-susceptibility, independently and/or in a family-specific context. Key Points • Exploration of population based/ethno-specific big data is imperative to identify novel causal variants of RA. • Two new deleterious missense mutations in mutational hotspot exon 4 of TLR1 gene have been identified in Pakistani RA patients. • MD simulation data provides evidence for domain's rigidification, conferring stability to mutant TLR1-TIR/TIRAP-TIR complex, with concomitant increase in production of pro-inflammatory cytokines, thus adding to the onset/erosive outcome of RA.