Comparative protein modelling by satisfaction of spatial restraints

Recent Progress of Protein Tertiary Structure Prediction

The prediction of three-dimensional (3D) protein structure from amino acid sequences has stood as a significant challenge in computational and structural bioinformatics for decades. Recently, the widespread integration of artificial intelligence (AI) algorithms has substantially expedited advancements in protein structure prediction, yielding numerous significant milestones. In particular, the end-to-end deep learning method AlphaFold2 has facilitated the rise of structure prediction performance to new heights, regularly competitive with experimental structures in the 14th Critical Assessment of Protein Structure Prediction (CASP14). To provide a comprehensive understanding and guide future research in the field of protein structure prediction for researchers, this review describes various methodologies, assessments, and databases in protein structure prediction, including traditionally used protein structure prediction methods, such as template-based modeling (TBM) and template-free modeling (FM) approaches; recently developed deep learning-based methods, such as contact/distance-guided methods, end-to-end folding methods, and protein language model (PLM)-based methods; multi-domain protein structure prediction methods; the CASP experiments and related assessments; and the recently released AlphaFold Protein Structure Database (AlphaFold DB). We discuss their advantages, disadvantages, and application scopes, aiming to provide researchers with insights through which to understand the limitations, contexts, and effective selections of protein structure prediction methods in protein-related fields.

Human GST P1-1 Redesigned for Enhanced Catalytic Activity with the Anticancer Prodrug Telcyta and Improved Thermostability

Protein engineering can be used to tailor enzymes for medical purposes, including antibody-directed enzyme prodrug therapy (ADEPT), which can act as a tumor-targeted alternative to conventional chemotherapy for cancer. In ADEPT, the antibody serves as a vector, delivering a drug-activating enzyme selectively to the tumor site. Glutathione transferases (GSTs) are a family of naturally occurring detoxication enzymes, and the finding that some of them are overexpressed in tumors has been exploited to develop GST-activated prodrugs. The prodrug Telcyta is activated by GST P1-1, which is the GST most commonly elevated in cancer cells, implying that tumors overexpressing GST P1-1 should be particularly vulnerable to Telcyta. Promising antitumor activity has been noted in clinical trials, but the wildtype enzyme has modest activity with Telcyta, and further functional improvement would enhance its usefulness for ADEPT. We utilized protein engineering to construct human GST P1-1 gene variants in the search for enzymes with enhanced activity with Telcyta. The variant Y109H displayed a 2.9-fold higher enzyme activity compared to the wild-type GST P1-1. However, increased catalytic potency was accompanied by decreased thermal stability of the Y109H enzyme, losing 99% of its activity in 8 min at 50 °C. Thermal stability was restored by four additional mutations simultaneously introduced without loss of the enhanced activity with Telcyta. The mutation Q85R was identified as an important contributor to the regained thermostability. These results represent a first step towards a functional ADEPT application for Telcyta.

PLAS-20k: Extended Dataset of Protein-Ligand Affinities from MD Simulations for Machine Learning Applications

Computing binding affinities is of great importance in drug discovery pipeline and its prediction using advanced machine learning methods still remains a major challenge as the existing datasets and models do not consider the dynamic features of protein-ligand interactions. To this end, we have developed PLAS-20k dataset, an extension of previously developed PLAS-5k, with 97,500 independent simulations on a total of 19,500 different protein-ligand complexes. Our results show good correlation with the available experimental values, performing better than docking scores. This holds true even for a subset of ligands that follows Lipinski's rule, and for diverse clusters of complex structures, thereby highlighting the importance of PLAS-20k dataset in developing new ML models. Along with this, our dataset is also beneficial in classifying strong and weak binders compared to docking. Further, OnionNet model has been retrained on PLAS-20k dataset and is provided as a baseline for the prediction of binding affinities. We believe that large-scale MD-based datasets along with trajectories will form new synergy, paving the way for accelerating drug discovery.

Bacterial cytochrome P450s: a bioinformatics odyssey of substrate discovery

Bacterial P450 cytochromes (BacCYPs) are versatile heme-containing proteins responsible for oxidation reactions on a wide range of substrates, contributing to the production of valuable natural products with limitless biotechnological potential. While the sequencing of microbial genomes has provided a wealth of BacCYP sequences, functional characterization lags behind, hindering our understanding of their roles. This study employs a comprehensive approach to predict BacCYP substrate specificity, bridging the gap between sequence and function. We employed an integrated approach combining sequence and functional data analysis, genomic context exploration, 3D structural modeling with molecular docking, and phylogenetic clustering. The research begins with an in-depth analysis of BacCYP sequence diversity and structural characteristics, revealing conserved motifs and recurrent residues in the active site. Phylogenetic analysis identifies distinct groups within the BacCYP family based on sequence similarity. However, our study reveals that sequence alone does not consistently predict substrate specificity, necessitating additional perspectives. The study delves into the genetic context of BacCYPs, utilizing neighboring gene information to infer potential substrates, a method proven very effective in many cases. Molecular docking is employed to assess BacCYP-substrate interactions, confirming potential substrates and providing insights into selectivity. Finally, a comprehensive strategy is proposed for predicting BacCYP substrates, involving all the evaluated approaches. The effectiveness of this strategy is demonstrated with two case studies, highlighting its potential for substrate discovery.

High-efficiency removal of pyrethroids using a redesigned odorant binding protein

Pyrethroids are ubiquitously present in environmental media and threaten both the ecosystem and human health. To explore effective ways to remove pyrethroids from the environment, an odorant binding protein (OBP) with affinity for various pyrethroids was investigated. Initially, the target OBP, Spodoptera littoralis pheromone binding protein 1 (SlitPBP1), underwent redesign to enhance its affinity for pyrethroids. The modified SlitPBP1E97ND106E demonstrated a substantially increased affinity for deltamethrin (DeltaM), with a dissociation constant of 0.77 ± 0.17 μM. The affinity of SlitPBP1E97ND106E for other pyrethroids also increased to varying extents. Consequently, SlitPBP1E97ND106E displayed a markedly enhanced capability to adsorb and remove pyrethroids. When exposed to free SlitPBP1E97ND106E in solution, the reduction in DeltaM surged from 16.78 ± 0.32% to 97.51 ± 0.56%. SlitPBP1E97ND106E was immobilized by coupling the protein to Ni2+-NTA agarose resin. Liquid chromatography results attested to the superior efficacy of immobilized SlitPBP1E97ND106E in removing pyrethroids, especially DeltaM. No significant differences in pyrethroid removal were detected across various water samples. Our findings introduce a potent tool for pyrethroid removal. A wider range of OBPs can similarly be optimized and applied to remove organic pollutants, including but not limited to pesticides.

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.

Microsecond dynamics control the HIV-1 Envelope conformation

The HIV-1 Envelope (Env) glycoprotein facilitates host cell fusion through a complex series of receptor-induced structural changes. Although remarkable progress has been made in understanding the structures of various Env conformations, microsecond timescale dynamics have not been studied experimentally. Here, we used time-resolved, temperature-jump small-angle x-ray scattering to monitor structural rearrangements in an HIV-1 Env SOSIP ectodomain construct with microsecond precision. In two distinct Env variants, we detected a transition that correlated with known Env structure rearrangements with a time constant in the hundreds of microseconds range. A previously unknown structural transition was also observed, which occurred with a time constant below 10 μs, and involved an order-to-disorder transition in the trimer apex. Using this information, we engineered an Env SOSIP construct that locks the trimer in the prefusion closed state by connecting adjacent protomers via disulfides. Our findings show that the microsecond timescale structural dynamics play an essential role in controlling the Env conformation with impacts on vaccine design.

Dual mutations in the whitefly nicotinic acetylcholine receptor β1 subunit confer target-site resistance to multiple neonicotinoid insecticides

Neonicotinoid insecticides, which target insect nicotinic acetylcholine receptors (nAChRs), have been widely and intensively used to control the whitefly, Bemisia tabaci, a highly damaging, globally distributed, crop pest. This has inevitably led to the emergence of populations with resistance to neonicotinoids. However, to date, there have been no reports of target-site resistance involving mutation of B. tabaci nAChR genes. Here we characterize the nAChR subunit gene family of B. tabaci and identify dual mutations (A58T&R79E) in one of these genes (BTβ1) that confer resistance to multiple neonicotinoids. Transgenic D. melanogaster, where the native nAChR Dβ1 was replaced with BTβ1A58T&R79E, were significantly more resistant to neonicotinoids than flies where Dβ1 were replaced with the wildtype BTβ1 sequence, demonstrating the causal role of the mutations in resistance. The two mutations identified in this study replace two amino acids that are highly conserved in >200 insect species. Three-dimensional modelling suggests a molecular mechanism for this resistance, whereby A58T forms a hydrogen bond with the R79E side chain, which positions its negatively-charged carboxylate group to electrostatically repulse a neonicotinoid at the orthosteric site. Together these findings describe the first case of target-site resistance to neonicotinoids in B. tabaci and provide insight into the molecular determinants of neonicotinoid binding and selectivity.

Three chemosensory proteins enriched in antennae and tarsi of Rhaphuma horsfieldi differentially contribute to the binding of insecticides

Antennae and legs (primarily the tarsal segments) of insects are the foremost sensory organs that contact a diverse range of toxic chemicals including insecticides. Binding proteins expressed in the two tissues are potential molecular candidates serving as the binding and sequestering of insecticides, like chemosensory proteins (CSPs). Insect CSPs endowed with multiple roles have been suggested to participate in insecticide resistance, focusing mainly on moths, aphids and mosquitos. Yet, the molecular underpinnings underlying the interactions of cerambycid CSPs and insecticides remain unexplored. Here, we present binding properties of three antenna- and tarsus-enriched RhorCSPs (RhorCSP1, CSP2 and CSP3) in Rhaphuma horsfieldi to eight insecticide classes totaling 15 chemicals. From the transcriptome of this beetle, totally 16 CSP-coding genes were found, with seven full-length sequences. In phylogeny, these RhorCSPs were distributed dispersedly in different clades. Expression profiles revealed the abundant expression of RhorCSP1, CSP2 and CSP3 in antennae and tarsi, thus as representatives for studying the protein-insecticide interactions. Binding assays showed that the three RhorCSPs were tuned differentially to insecticides but exhibited the highest affinities with hexaflumuron, chlorpyrifos and rotenone (dissociation constants <13 μM). In particular, RhorCSP3 could interact strongly with 10 of tested insecticides, of which four residues (Tyr25, Phe42, Val65 and Phe68) contributed significantly to the binding of six, four, three and four ligands, respectively. Of these, the binding of four mutated RhorCSP3s to a botanical insecticide rotenone was significantly weakened compared to the wildtype protein. Furthermore, we also evidenced that RhorCSP3 was a broadly-tuned carrier protein in response to a wide variety of plant odorants outside insecticides. Altogether, our findings shed light on different binding mechanisms and odorant-tuning profiles of three RhorCSPs in R. horsfieldi and identify key residues of the RhorCSP3-insecticide interactions.

Adaptive Evolution of Nearctic Deepwater Fish Vision: Implications for Assessing Functional Variation for Conservation

Intraspecific functional variation is critical for adaptation to rapidly changing environments. For visual opsins, functional variation can be characterized in vitro and often reflects a species' ecological niche but is rarely considered in the context of intraspecific variation or the impact of recent environmental changes on species of cultural or commercial significance. Investigation of adaptation in postglacial lakes can provide key insight into how rapid environmental changes impact functional evolution. Here, we report evidence for molecular adaptation in vision in 2 lineages of Nearctic fishes that are deep lake specialists: ciscoes and deepwater sculpin. We found depth-related variation in the dim-light visual pigment rhodopsin that evolved convergently in these 2 lineages. In vitro characterization of spectral sensitivity of the convergent deepwater rhodopsin alleles revealed blue-shifts compared with other more widely distributed alleles. These blue-shifted rhodopsin alleles were only observed in deep clear postglacial lakes with underwater visual environments enriched in blue light. This provides evidence of remarkably rapid and convergent visual adaptation and intraspecific functional variation in rhodopsin. Intraspecific functional variation has important implications for conservation, and these fishes are of conservation concern and great cultural, commercial, and nutritional importance to Indigenous communities. We collaborated with the Saugeen Ojibway Nation to develop and test a metabarcoding approach that we show is efficient and accurate in recovering the ecological distribution of functionally relevant variation in rhodopsin. Our approach bridges experimental analyses of protein function and genetics-based tools used in large-scale surveys to better understand the ecological extent of adaptive functional variation.

AI-driven GPCR analysis, engineering, and targeting

This article investigates the role of recent advances in Artificial Intelligence (AI) to revolutionise the study of G protein-coupled receptors (GPCRs). AI has been applied to many areas of GPCR research, including the application of machine learning (ML) in GPCR classification, prediction of GPCR activation levels, modelling GPCR 3D structures and interactions, understanding G-protein selectivity, aiding elucidation of GPCRs structures, and drug design. Despite progress, challenges in predicting GPCR structures and addressing the complex nature of GPCRs remain, providing avenues for future research and development.

Clinical features, functional consequences, and rescue pharmacology of missense GRID1 and GRID2 human variants

GRID1 and GRID2 encode the enigmatic GluD1 and GluD2 proteins, which form tetrameric receptors that play important roles in synapse organization and development of the central nervous system. Variation in these genes has been implicated in neurodevelopmental phenotypes. We evaluated GRID1 and GRID2 human variants from the literature, ClinVar, and clinical laboratories and found that many of these variants reside in intolerant domains, including the amino terminal domain of both GRID1 and GRID2. Other conserved regions, such as the M3 transmembrane domain, show different intolerance between GRID1 and GRID2. We introduced these variants into GluD1 and GluD2 cDNA and performed electrophysiological and biochemical assays to investigate the mechanisms of dysfunction of GRID1/2 variants. One variant in the GRID1 distal amino terminal domain resides at a position predicted to interact with Cbln2/Cbln4, and the variant disrupts complex formation between GluD1 and Cbln2, which could perturb its role in synapse organization. We also discovered that, like the lurcher mutation (GluD2-A654T), other rare variants in the GRID2 M3 domain create constitutively active receptors that share similar pathogenic phenotypes. We also found that the SCHEMA schizophrenia M3 variant GluD1-A650T produced constitutively active receptors. We tested a variety of compounds for their ability to inhibit constitutive currents of GluD receptor variants and found that pentamidine potently inhibited GluD2-T649A constitutive channels (IC50 50 nM). These results identify regions of intolerance to variation in the GRID genes, illustrate the functional consequences of GRID1 and GRID2 variants, and suggest how these receptors function normally and in disease.

The genomic landscape of CYP2D6 variation in the Indian population

Aim: The CYP2D6 gene is highly polymorphic, causing large interindividual variability in the metabolism of several clinically important drugs. Materials & methods: The authors investigated the diversity and distribution of CYP2D6 alleles in Indians using whole genome sequences (N = 1518). Functional consequences were assessed using pathogenicity scores and molecular dynamics simulations. Results: The analysis revealed population-specific CYP2D6 alleles (*86, *7, *111, *112, *113, *99) and remarkable differences in variant and phenotype frequencies with global populations. The authors observed that one in three Indians could benefit from a dose alteration for psychiatric drugs with accurate CYP2D6 phenotyping. Molecular dynamics simulations revealed large conformational fluctuations, confirming the predicted reduced function of *86 and *113 alleles. Conclusion: The findings emphasize the utility of comprehensive CYP2D6 profiling for aiding precision public health.

Bonds and bytes: The odyssey of structural biology

Characterizing structural and dynamic properties of proteins and large macromolecular assemblies is crucial to understand the molecular mechanisms underlying biological functions. In the field of structural biology, no single method comprehensively reveals the behavior of biological systems across various spatiotemporal scales. Instead, we have a versatile toolkit of techniques, each contributing a piece to the overall puzzle. Integrative structural biology combines different techniques to create accurate and precise multi-scale models that expand our understanding of complex biological systems. This review outlines recent advancements in computational and experimental methods in structural biology, with special focus on recent Artificial Intelligence techniques, emphasizes integrative approaches that combine different types of data for precise spatiotemporal modeling, and provides an outlook into future directions of this field.

The structural and mechanistic bases for the viral resistance to allosteric HIV-1 integrase inhibitor pirmitegravir

Allosteric HIV-1 integrase (IN) inhibitors (ALLINIs) are investigational antiretroviral agents which potently impair virion maturation by inducing hyper-multimerization of IN and inhibiting its interaction with viral genomic RNA. The pyrrolopyridine-based ALLINI pirmitegravir (PIR) has recently advanced into Phase 2a clinical trials. Previous cell culture based viral breakthrough assays identified the HIV-1(Y99H/A128T IN) variant that confers substantial resistance to this inhibitor. Here, we have elucidated the unexpected mechanism of viral resistance to PIR. While both Tyr99 and Ala128 are positioned within the inhibitor binding V-shaped cavity at the IN catalytic core domain (CCD) dimer interface, the Y99H/A128T IN mutations did not substantially affect direct binding of PIR to the CCD dimer or functional oligomerization of full-length IN. Instead, the drug-resistant mutations introduced a steric hindrance at the inhibitor mediated interface between CCD and C-terminal domain (CTD) and compromised CTD binding to the CCDY99H/A128T + PIR complex. Consequently, full-length INY99H/A128T was substantially less susceptible to the PIR induced hyper-multimerization than the WT protein, and HIV-1(Y99H/A128T IN) conferred >150-fold resistance to the inhibitor compared to the WT virus. By rationally modifying PIR we have developed its analog EKC110, which readily induced hyper-multimerization of INY99H/A128T in vitro and was ~14-fold more potent against HIV-1(Y99H/A128T IN) than the parent inhibitor. These findings suggest a path for developing improved PIR chemotypes with a higher barrier to resistance for their potential clinical use.

Contribution of Signaling Partner Association to Strigolactone Receptor Selectivity

The parasitic plant witchweed, Striga hermonthica, results in agricultural losses of billions of dollars per year. It perceives its host via plant hormones called strigolactones, which act as germination stimulants for witchweed. Strigolactone signaling involves substrate binding to the strigolactone receptor, followed by substrate hydrolysis and a conformational change from an inactive, or open state, to an active, or closed state. In the active state, the receptor associates with a signaling partner, MAX2. Recently, it was shown that this MAX2 association process acts as a strong contributor to the uniquely high signaling activity observed in ShHTL7; however, it is unknown why ShHTL7 has enhanced MAX2 association affinity. Using an umbrella sampling molecular dynamics approach, we characterized the association processes of AtD14, ShHTL7, a mutant of ShHTL7, and ShHTL6 with MAX2 homologue OsD3. From these results, we show that ShHTL7 has an enhanced standard binding free energy of OsD3 compared to those of the other receptors. Additionally, our results suggest that the overall topology of the T2/T3 helix region is likely an important modulator of MAX2 binding. Thus, differences in MAX2 association, modulated by differences in the T2/T3 helix region, are a contributor to differences in signaling activity between different strigolactone receptors.

RNAdvisor: a comprehensive benchmarking tool for the measure and prediction of RNA structural model quality

RNA is a complex macromolecule that plays central roles in the cell. While it is well known that its structure is directly related to its functions, understanding and predicting RNA structures is challenging. Assessing the real or predictive quality of a structure is also at stake with the complex 3D possible conformations of RNAs. Metrics have been developed to measure model quality while scoring functions aim at assigning quality to guide the discrimination of structures without a known and solved reference. Throughout the years, many metrics and scoring functions have been developed, and no unique assessment is used nowadays. Each developed assessment method has its specificity and might be complementary to understanding structure quality. Therefore, to evaluate RNA 3D structure predictions, it would be important to calculate different metrics and/or scoring functions. For this purpose, we developed RNAdvisor, a comprehensive automated software that integrates and enhances the accessibility of existing metrics and scoring functions. In this paper, we present our RNAdvisor tool, as well as state-of-the-art existing metrics, scoring functions and a set of benchmarks we conducted for evaluating them. Source code is freely available on the EvryRNA platform: https://evryrna.ibisc.univ-evry.fr.

Polarizable AMOEBA Model for Simulating Mg2+·Protein·Nucleotide Complexes

Molecular mechanics (MM) simulations have the potential to provide detailed insights into the mechanisms of enzymes that utilize nucleotides as cofactors. In most cases, the activities of these enzymes also require the binding of divalent cations to catalytic sites. However, modeling divalent cations in MM simulations has been challenging. The inclusion of explicit polarization was considered promising, but despite improvements over nonpolarizable force fields and despite the inclusion of "Nonbonded-fix (NB-fix)" corrections, errors in interaction energies of divalent cations with proteins remain large. Importantly, the application of these models fails to reproduce the experimental structural data on Mg2+·Protein·ATP complexes. Focusing on these complexes, here we provide a systematic assessment of the polarizable AMOEBA model and recommend critical changes that substantially improve its predictive performance. Our key results are as follows. We first show that our recent revision of the AMOEBA protein model (AMOEBABIO18-HFC), which contains high field corrections (HFCs) to induced dipoles, dramatically improves Mg2+-protein interaction energies, reducing the mean absolute error (MAE) from 17 to 10 kcal/mol. This further supports the general applicability of AMOEBABIO18-HFC. The inclusion of many-body NB-fix corrections further reduces MAE to 6 kcal/mol, which amounts to less than 2% error. The errors are estimated with respect to vdW-inclusive density functional theory that we benchmark against CCSD(T) calculations and experiments. We also present a new model of ATP with revised polarization parameters to better capture its high field response, as well as new vdW and dihedral parameters. The ATP model accurately predicts experimental Mg2+-ATP binding free energy in the aqueous phase and provides new insights into how Mg2+ associates with ATP. Finally, we show that molecular dynamics (MD) simulations of Mg2+·Kinase·ATP complexes carried out with these improvements lead to a better agreement in global and local catalytic site structures between MD and X-ray crystallography.

Discovery of plant chemical defence mediated by a two-component system involving β-glucosidase in Panax species

Plants usually produce defence metabolites in non-active forms to minimize the risk of harm to themselves and spatiotemporally activate these defence metabolites upon pathogen attack. This so-called two-component system plays a decisive role in the chemical defence of various plants. Here, we discovered that Panax notoginseng, a valuable medicinal plant, has evolved a two-component chemical defence system composed of a chloroplast-localized β-glucosidase, denominated PnGH1, and its substrates 20(S)-protopanaxadiol ginsenosides. The β-glucosidase and its substrates are spatially separated in cells under physiological conditions, and ginsenoside hydrolysis is therefore activated only upon chloroplast disruption, which is caused by the induced exoenzymes of pathogenic fungi upon exposure to plant leaves. This activation of PnGH1-mediated hydrolysis results in the production of a series of less-polar ginsenosides by selective hydrolysis of an outer glucose at the C-3 site, with a broader spectrum and more potent antifungal activity in vitro and in vivo than the precursor molecules. Furthermore, such β-glucosidase-mediated hydrolysis upon fungal infection was also found in the congeneric species P. quinquefolium and P. ginseng. Our findings reveal a two-component chemical defence system in Panax species and offer insights for developing botanical pesticides for disease management in Panax species.

Structural basis of respiratory complexes adaptation to cold temperatures

In response to cold, mammals activate brown fat for respiratory-dependent thermogenesis reliant on the electron transport chain (1, 2). Yet, the structural basis of respiratory complex adaptation to cold remains elusive. Herein we combined thermoregulatory physiology and cryo-EM to study endogenous respiratory supercomplexes exposed to different temperatures. A cold-induced conformation of CI:III 2 (termed type 2) was identified with a ∼25° rotation of CIII 2 around its inter-dimer axis, shortening inter-complex Q exchange space, and exhibiting different catalytic states which favor electron transfer. Large-scale supercomplex simulations in lipid membrane reveal how unique lipid-protein arrangements stabilize type 2 complexes to enhance catalytic activity. Together, our cryo-EM studies, multiscale simulations and biochemical analyses unveil the mechanisms and dynamics of respiratory adaptation at the structural and energetic level.

Membrane platform protein PulF of the Klebsiella type II secretion system forms a trimeric ion channel essential for endopilus assembly and protein secretion

IMPORTANCE

Type IV pili and type II secretion systems are members of the widespread type IV filament (T4F) superfamily of nanomachines that assemble dynamic and versatile surface fibers in archaea and bacteria. The assembly and retraction of T4 filaments with diverse surface properties and functions require the plasma membrane platform proteins of the GspF/PilC superfamily. Generally considered dimeric, platform proteins are thought to function as passive transmitters of the mechanical energy generated by the ATPase motor, to somehow promote insertion of pilin subunits into the nascent pilus fibers. Here, we generate and experimentally validate structural predictions that support the trimeric state of a platform protein PulF from a type II secretion system. The PulF trimers form selective proton or sodium channels which might energize pilus assembly using the membrane potential. The conservation of the channel sequence and structural features implies a common mechanism for all T4F assembly systems. We propose a model of the oligomeric PulF-PulE ATPase complex that provides an essential framework to investigate and understand the pilus assembly mechanism.

Experimental and Computational Analysis of Newly Identified Pathogenic Mutations in the Creatine Transporter SLC6A8

Creatine is an essential metabolite for the storage and rapid supply of energy in muscle and nerve cells. In humans, impaired metabolism, transport, and distribution of creatine throughout tissues can cause varying forms of mental disability, also known as creatine deficiency syndrome (CDS). So far, 80 mutations in the creatine transporter (SLC6A8) have been associated to CDS. To better understand the effect of human genetic variants on the physiology of SLC6A8 and their possible impact on CDS, we studied 30 missense variants including 15 variants of unknown significance, two of which are reported here for the first time. We expressed these variants in HEK293 cells and explored their subcellular localization and transport activity. We also applied computational methods to predict variant effect and estimate site-specific changes in thermodynamic stability. To explore variants that might have a differential effect on the transporter's conformers along the transport cycle, we constructed homology models of the inward facing, and outward facing conformations. In addition, we used mass-spectrometry to study proteins that interact with wild type SLC6A8 and five selected variants in HEK293 cells. In silico models of the protein complexes revealed how two variants impact the interaction interface of SLC6A8 with other proteins and how pathogenic variants lead to an enrichment of ER protein partners. Overall, our integrated analysis disambiguates the pathogenicity of 15 variants of unknown significance revealing diverse mechanisms of pathogenicity, including two previously unreported variants obtained from patients suffering from the creatine deficiency syndrome.

Disease-associated nonsense and frame-shift variants resulting in the truncation of the GluN2A or GluN2B C-terminal domain decrease NMDAR surface expression and reduce potentiating effects of neurosteroids

N-methyl-D-aspartate receptors (NMDARs) play a critical role in normal brain function, and variants in genes encoding NMDAR subunits have been described in individuals with various neuropsychiatric disorders. We have used whole-cell patch-clamp electrophysiology, fluorescence microscopy and in-silico modeling to explore the functional consequences of disease-associated nonsense and frame-shift variants resulting in the truncation of GluN2A or GluN2B C-terminal domain (CTD). This study characterizes variant NMDARs and shows their reduced surface expression and synaptic localization, altered agonist affinity, increased desensitization, and reduced probability of channel opening. We also show that naturally occurring and synthetic steroids pregnenolone sulfate and epipregnanolone butanoic acid, respectively, enhance NMDAR function in a way that is dependent on the length of the truncated CTD and, further, is steroid-specific, GluN2A/B subunit-specific, and GluN1 splice variant-specific. Adding to the previously described effects of disease-associated NMDAR variants on the receptor biogenesis and function, our results improve the understanding of the molecular consequences of NMDAR CTD truncations and provide an opportunity for the development of new therapeutic neurosteroid-based ligands.

Design, Synthesis, and Evaluation of Cephamycin-Based Antisporulation Agents targeting Clostridioides difficile

With the aim of discovering small molecule inhibitors of the sporulation process in Clostridioides difficile, we prepared a series of C-7 α-(4-substituted-1H-1,2,3-triazol-1-yl)acetamide analogues of cefotetan, a known inhibitor of the C. difficile sporulation-specific protein target CdSpoVD. These analogues were evaluated using both in vitro binding assays with CdSpoVD and antisporulation assays against C. difficile. Further design concepts were aided utilizing the predicted docking scores (DS) using both AlphaFold (AF) models, and a crystal structure of the CdSpoVD protein (PDB 7RCZ). Despite being 1 order of magnitude more potent as a sporulation inhibitor than cefotetan, in vivo studies on compound 6a in a murine-model of C. difficile infection demonstrated comparable spore shedding capabilities as cefotetan. Importantly, compound 6a had no concerning broad spectrum antibacterial activities, toxicity, or hemolytic activity and thus has potential for further drug development.

Classification of MLH1 Missense VUS Using Protein Structure-Based Deep Learning-Ramachandran Plot-Molecular Dynamics Simulations Method

Pathogenic variation in DNA mismatch repair (MMR) gene MLH1 is associated with Lynch syndrome (LS), an autosomal dominant hereditary cancer. Of the 3798 MLH1 germline variants collected in the ClinVar database, 38.7% (1469) were missense variants, of which 81.6% (1199) were classified as Variants of Uncertain Significance (VUS) due to the lack of functional evidence. Further determination of the impact of VUS on MLH1 function is important for the VUS carriers to take preventive action. We recently developed a protein structure-based method named "Deep Learning-Ramachandran Plot-Molecular Dynamics Simulation (DL-RP-MDS)" to evaluate the deleteriousness of MLH1 missense VUS. The method extracts protein structural information by using the Ramachandran plot-molecular dynamics simulation (RP-MDS) method, then combines the variation data with an unsupervised learning model composed of auto-encoder and neural network classifier to identify the variants causing significant change in protein structure. In this report, we applied the method to classify 447 MLH1 missense VUS. We predicted 126/447 (28.2%) MLH1 missense VUS were deleterious. Our study demonstrates that DL-RP-MDS is able to classify the missense VUS based solely on their impact on protein structure.

Redocking the PDB

Molecular docking is a standard technique in structure-based drug design (SBDD). It aims to predict the 3D structure of a small molecule in the binding site of a receptor (often a protein). Despite being a common technique, it often necessitates multiple tools and involves manual steps. Here, we present the JAMDA preprocessing and docking workflow that is easy to use and allows fully automated docking. We evaluate the JAMDA docking workflow on binding sites extracted from the complete PDB and derive key factors determining JAMDA's docking performance. With that, we try to remove most of the bias due to manual intervention and provide a realistic estimate of the redocking performance of our JAMDA preprocessing and docking workflow for any PDB structure. On this large PDBScan22 data set, our JAMDA workflow finds a pose with an RMSD of at most 2 Å to the crystal ligand on the top rank for 30.1% of the structures. When applying objective structure quality filters to the PDBScan22 data set, the success rate increases to 61.8%. Given the prepared structures from the JAMDA preprocessing pipeline, both JAMDA and the widely used AutoDock Vina perform comparably on this filtered data set (the PDBScan22-HQ data set).

Bitter taste receptors establish a stable binding affinity with the SARS-CoV-2-spike 1 protein akin to ACE2

COVID-19 is caused by the highly contagious SARS-CoV-2 virus, which originated in Wuhan, China, resulting in the highest worldwide mortality rate. Gustatory dysfunction is common among individuals infected with the Wild-type Wuhan strain. However, there are no reported cases of gustatory dysfunction among patients infected with the mutant delta variant. The reason behind this remains elusive to date. This in-silico-based study aims to unravel this clinical factor by evaluating the overall binding affinity of predominant bitter taste receptors associated with gustatory function (T2R-4, 10, 14, 19, 31, 38, 43, and 46) with the Receptor Binding Domain (RBD) of spike 1 (S1) protein of Wuhan (Wild)/delta-SARS-CoV-2 (mut1-T478K; mut2-E484K) variants. Based on docking and MM/PBSA free binding energy scores, the Wild RBD showed a stronger interaction with T2R-46 compared to the ACE2 protein. However, both delta variant mutants (mut1 and mut2) could not establish a stronger binding affinity with bitter taste receptor proteins, except for T2R-43 against mut1. In conclusion, the delta variants could not establish a better binding affinity with bitter taste receptors, contradicting the Wild variant that determines the severity of gustatory dysfunction among patients exposed to the delta and Wild SARS-CoV-2 variants. The study's inference also proposes T2R-46 as an alternate binding receptor target for RBD-S1 of Wild SARS-CoV-2, augmenting its virulence in all functional organs with compromised α-gustducin interaction and bitter sensitization. This in-silico-based study needs further wet-lab-based validation for a better understanding of the role of T2R-46-based viral entry in the human host.Communicated by Ramaswamy H. Sarma.

Design, Synthesis, and Structure-Activity Relationship Studies of Novel GPR88 Agonists (4-Substituted-phenyl)acetamides Based on the Reversed Amide Scaffold

The development of synthetic agonists for the orphan receptor GPR88 has recently attracted significant interest, given the promise of GPR88 as a novel drug target for psychiatric and neurodegenerative disorders. Examination of structure-activity relationships of two known agonist scaffolds 2-PCCA and 2-AMPP, as well as the recently resolved cryo-EM structure of 2-PCCA-bound GPR88, led to the design of a new scaffold based on the "reversed amide" strategy of 2-AMPP. A series of novel (4-substituted-phenyl)acetamides were synthesized and assessed in cAMP accumulation assays as GPR88 agonists, which led to the discovery of several compounds with better or comparable potencies to 2-AMPP. Computational docking studies suggest that these novel GPR88 agonists bind to the same allosteric site of GPR88 that 2-PCCA occupies. Collectively, our findings provide structural insight and SAR requirement at the allosteric site of GPR88 and a new scaffold for further development of GPR88 allosteric agonists.

Agonistic effect of peptides derived from a truncated HMGB1 acidic tail sequence in TLR5 from Salmo salar

Based on the structural knowledge of TLR5 surface and using blind docking platforms, peptides derived from a truncated HMGB1 acidic tail from Salmo salar was designed as TLR5 agonistic. Additionally, a template peptide with the native N-terminal of the acidic tail sequence as a reference was included (SsOri). Peptide binding poses complexed on TLR5 ectodomain model from each algorithm were filtrated based on docking scoring functions and predicted theoretical binding affinity of the complex. The best peptides, termed 6WK and 5LWK, were selected for chemical synthesis and experimental functional assay. The agonist activity by immunoblotting and immunocytochemistry was determined following the NF-κBp65 phosphorylation (p-NF-κBp65) and the nuclear translocation of the NF-κBp65 subunit from the cytosol, respectively. HeLa cells stably expressing a S. salar TLR5 chimeric form (TLR5c7) showed increased p-NF-κBp65 levels regarding extracts from flagellin-treated cells. No statistically significant differences (p > 0.05) were found in the detected p-NF-κBp65 levels between cellular extracts treated with peptides or flagellin by one-way ANOVA. The image analysis of NF-κBp65 immunolabeled cells obtained by confocal microscopy showed increased nuclear NF-κBp65 co-localization in cells both 5LWK and flagellin stimulated, while 6WK and SsOri showed less effect on p65 nuclear translocation (p < 0.05). Also, an increased transcript expression profile of proinflammatory cytokines such as TNFα, IL-1β, and IL-8 in HKL cells isolated from Salmo salar was evidenced in 5LWK - stimulated by RT-PCR analysis. Overall, the result indicates the usefulness of novel peptides as a potential immunostimulant in S. salar.

Variations of the Mycobacterium abscessus F-ATP synthase subunit a-c interface alter binding and potency of the anti-TB drug bedaquiline

The anti-tuberculosis therapeutic bedaquiline (BDQ) is used against Mycobacterium abscessus. In M. abscessus BDQ is only bacteriostatic and less potent compared to M. tuberculosis or M. smegmatis. Here we demonstrate its reduced ATP synthesis inhibition against M. abscessus inside-out vesicles, including the F1FO-ATP synthase. Molecular dynamics simulations and binding free energy calculations highlight the differences in drug-binding of the M. abscessus and M. smegmatis FO-domain at the lagging site, where the drug deploys its mechanistic action, inhibiting ATP synthesis. These data pave the way for improved anti-M. abscessus BDQ analogs.

Molecular Docking of Intrinsically Disordered Proteins: Challenges and Strategies

Intrinsically disordered proteins (IDPs) are a novel class of proteins that have established a significant importance and attention within a very short period of time. These proteins are essentially characterized by their inherent structural disorder, encoded mainly by their amino acid sequences. The profound abundance of IDPs and intrinsically disordered regions (IDRs) in the biological world delineates their deep-rooted functionality. IDPs and IDRs convey such extensive functionality through their unique dynamic nature, which enables them to carry out huge number of multifaceted biomolecular interactions and make them "interaction hub" of the cellular systems. Additionally, with such widespread functions, their misfunctioning is also intimately associated with multiple diseases. Thus, understanding the dynamic heterogeneity of various IDPs along with their interactions with respective binding partners is an important field with immense potentials in biomolecular research. In this context, molecular docking-based computational approaches have proven to be remarkable in case of ordered proteins. Molecular docking methods essentially model the biomolecular interactions in both structural and energetic terms and use this information to characterize the putative interactions between the two participant molecules. However, direct applications of the conventional docking methods to study IDPs are largely limited by their structural heterogeneity and demands for unique IDP-centric strategies. Thus, in this chapter, we have presented an overview of current methodologies for successful docking operations involving IDPs and IDRs. These specialized methods majorly include the ensemble-based and fragment-based approaches with their own benefits and limitations. More recently, artificial intelligence and machine learning-assisted approaches are also used to significantly reduce the complexity and computational burden associated with various docking applications. Thus, this chapter aims to provide a comprehensive summary of major challenges and recent advancements of molecular docking approaches in the IDP field for their better utilization and greater applicability.Asp (D).

CMT2A-linked MFN2 mutation, T206I promotes mitochondrial hyperfusion and predisposes cells towards mitophagy

Mutations in Mitofusin2 (MFN2) associated with the pathology of the debilitating neuropathy Charcot-Marie-Tooth type 2A (CMT2A) are known to alter mitochondrial morphology. Previously, such mutations have been shown to elicit two diametrically opposite phenotypes - while some mutations have been causally linked to enhanced mitochondrial fragmentation, others have been shown to induce hyperfusion. Our study identifies one such MFN2 mutant, T206I that causes mitochondrial hyperfusion. Cells expressing this MFN2 mutant have elongated and interconnected mitochondria. T206I-MFN2 mutation in the GTPase domain increases MFN2 stability and renders cells susceptible to stress. We show that cells expressing T206I-MFN2 have a higher predisposition towards mitophagy under conditions of serum starvation. We also detect increased DRP1 recruitment onto the outer mitochondrial membrane, though the total DRP1 protein level remains unchanged. Here we have characterized a lesser studied CMT2A-linked MFN2 mutant to show that its presence affects mitochondrial morphology and homeostasis.

Structural Perspective of NR4A Nuclear Receptor Family and Their Potential Endogenous Ligands

There are 48 nuclear receptors in the human genome, and many members of this superfamily have been implicated in human diseases. The NR4A nuclear receptor family consisting of three members, NR4A1, NR4A2, and NR4A3 (formerly annotated as Nur77, Nurr1, and NOR1, respectively), are still orphan receptors but exert pathological effects on immune-related and neurological diseases. We previously reported that prostaglandin A1 (PGA1) and prostaglandin A2 (PGA2) are potent activators of NR4A3, which bind directly to the ligand-binding domain (LBD) of the receptor. Recently, the co-crystallographic structures of NR4A2-LBD bound to PGA1 and PGA2 were reported, followed by reports of the neuroprotective effects of these possible endogenous ligands in mouse models of Parkinson's disease. Based on these structures, we modeled the binding structures of the other two members (NR4A1 and NR4A3) with these potential endogenous ligands using a template-based modeling method, and reviewed the similarity and diversity of ligand-binding mechanisms in the nuclear receptor family.

Machine Learning Methods in Protein-Protein Docking

An exponential increase in the number of publications that address artificial intelligence (AI) usage in life sciences has been noticed in recent years, while new modeling techniques are constantly being reported. The potential of these methods is vast-from understanding fundamental cellular processes to discovering new drugs and breakthrough therapies. Computational studies of protein-protein interactions, crucial for understanding the operation of biological systems, are no exception in this field. However, despite the rapid development of technology and the progress in developing new approaches, many aspects remain challenging to solve, such as predicting conformational changes in proteins, or more "trivial" issues as high-quality data in huge quantities.Therefore, this chapter focuses on a short introduction to various AI approaches to study protein-protein interactions, followed by a description of the most up-to-date algorithms and programs used for this purpose. Yet, given the considerable pace of development in this hot area of computational science, at the time you read this chapter, the development of the algorithms described, or the emergence of new (and better) ones should come as no surprise.

Assessment of the bound conformation of bombesin to the BB1 and BB2 receptors

Bombesin is an endogenous peptide involved in a wide spectrum of physiological activities ranging from satiety, control of circadian rhythm and thermoregulation in the central nervous system, to stimulation of gastrointestinal hormone release, activation of macrophages and effects on development in peripheral tissues. Actions of the peptide are mediated through the two high affinity G-protein coupled receptors BB1R and BB2R. Under pathophysiological conditions, these receptors are overexpressed in many different types of tumors, such as prostate cancer, breast cancer, small and non-small cell lung cancer and pancreatic cancer. This observation has been used for designing cell markers, but it has not been yet exploited for therapeutical purposes. Despite the enormous biological interest of the peptide, little is known about the stereochemical features that contribute to their activity. On the one hand, mutagenesis studies identified a few receptor residues important for high bombesin affinity and on the other, a few studies focused on the relevance of diverse residues of the peptide for receptor activation. Models of the peptide bound to BB1R and BB2R can be helpful to improve our understanding of the stereochemical features granting bombesin activity. Accordingly, the present study describes the computational process followed to construct such models by means of Steered Molecular Dynamics, using models of the peptide and its receptors. Present results provide new insights into the structure-activity relationships of bombesin and its receptors, as well as render an explanation for the differential binding affinity observed towards BB1R and BB2R. Finally, these models can be further exploited to help for designing novel small molecule peptidomimetics with improved pharmacokinetics profile.

Analysis of stabilization mechanisms in β-lactoglobulin-based amorphous solid dispersions by experimental and computational approaches

Our previous work shows that β-lactoglobulin-stabilized amorphous solid dispersion (ASD) loaded with 70 % indomethacin remains stable for more than 12 months. The stability is probably due to hydrogen bond networks spread throughout the ASD, facilitated by the indomethacin which has both hydrogen donors and acceptors. To investigate the stabilization mechanisms further, here we tested five other drug molecules, including two without any hydrogen bond donors. A combination of experimental techniques (differential scanning calorimetry, X-ray power diffraction) and molecular dynamics simulations was used to find the maximum drug loadings for ASDs with furosemide, griseofulvin, ibuprofen, ketoconazole and rifaximin. This approach revealed the underlying stabilization factors and the capacity of computer simulations to predict ASD stability. We searched the ASD models for crystalline patterns, and analyzed diffusivity of the drug molecules and hydrogen bond formation. ASDs loaded with rifaximin and ketoconazole remained stable for at least 12 months, even at 90 % drug loading, whereas stable drug loadings for furosemide, griseofulvin and ibuprofen were at a maximum of 70, 50 and 40 %, respectively. Steric confinement and hydrogen bonding to the proteins were the most important stabilization mechanisms at low drug loadings (≤ 40 %). Inter-drug hydrogen bond networks (including those with induced donors), ionic interactions, and a high Tg of the drug molecule were additional factors stabilizing the ASDs at drug loading greater than 40 %.

Transcription factor NAC1 activates expression of peptidase-encoding AtCEPs in roots to limit root hair growth

Plant genomes encode a unique group of papain-type Cysteine EndoPeptidases (CysEPs) containing a KDEL endoplasmic reticulum (ER) retention signal (KDEL-CysEPs or CEPs). CEPs process the cell-wall scaffolding EXTENSIN (EXT) proteins that regulate de novo cell-wall formation and cell expansion. Since CEPs cleave EXTs and EXT-related proteins, acting as cell-wall-weakening agents, they may play a role in cell elongation. The Arabidopsis (Arabidopsis thaliana) genome encodes 3 CEPs (AtCPE1-AtCEP3). Here, we report that the genes encoding these 3 Arabidopsis CEPs are highly expressed in root-hair (RH) cell files. Single mutants have no evident abnormal RH phenotype, but atcep1-3 atcep3-2 and atcep1-3 atcep2-2 double mutants have longer RHs than wild-type (Wt) plants, suggesting that expression of AtCEPs in root trichoblasts restrains polar elongation of the RH. We provide evidence that the transcription factor NAC1 (petunia NAM and Arabidopsis ATAF1, ATAF2, and CUC2) activates AtCEPs expression in roots to limit RH growth. Chromatin immunoprecipitation indicates that NAC1 binds to the promoter of AtCEP1, AtCEP2, and, to a lower extent, AtCEP3 and may directly regulate their expression. Inducible NAC1 overexpression increases AtCEP1 and AtCEP2 transcript levels in roots and leads to reduced RH growth while the loss of function nac1-2 mutation reduces AtCEP1-AtCEP3 gene expression and enhances RH growth. Likewise, expression of a dominant chimeric NAC1-SRDX repressor construct leads to increased RH length. Finally, we show that RH cell walls in the atcep1-3 atcep3-2 double mutant have reduced levels of EXT deposition, suggesting that the defects in RH elongation are linked to alterations in EXT processing and accumulation. Our results support the involvement of AtCEPs in controlling RH polar growth through EXT processing and insolubilization at the cell wall.

In silico and in vitro evaluation of newly synthesized pyrazolo-pyridine fused tetrazolo-pyrimidines derivatives as potential anticancer and antimicrobial agents

Diversely functionalized pyrazolo-pyridine fused tetrazolo-pyrimidines 10aa-am and 10ba-bn were successfully synthesized via a catalyst-free synthetic protocol with moderate to very good yields. The compounds were evaluated for cytotoxicity against MCF-7 and HEK-293 cells using MTT assay. Among the tested compounds, 10ab (IC50- 23.83 µM) and 10ah (IC50- 23.30 µM) demonstrated the highest potency against MCF-7 cells, while 10bc (IC50- 14.46 µM) and 10bh (IC50- 2.53 µM) exhibited excellent cytotoxicity against HEK-293 cells. Additionally, antibacterial screening was performed against three Gram-negative bacteria (E. coli, P. aeruginosa, and S. enterica) and three Gram-positive bacteria (S. aureus, B. megaterium, and B. subtilis) using broth dilution method, while antifungal activity was assessed against three fungal strains (A. niger, Penicillium, and S. cerevisiae) using agar well diffusion method. In antimicrobial screening, the majority of the compounds demonstrated significant antibacterial efficacy compared to antifungal activity. We also conducted comprehensive computational studies, including DFT calculations, molecular docking and dynamics, and drug-likeness assessments. In the DFT study, compounds 10ac and 10bc displayed stable conformations, indicating their potential for higher therapeutic activity. Molecular docking analyses revealed compelling interactions, with compound 10ah demonstrating docking score -7.42 kcal/mol against catalytical domain PARP1 (PDB ID: 7KK4) and 10bh exhibiting a best docking score -10.77 kcal/mol against human corticotropin-releasing factor receptor 1 (PDB ID: 4Z9G). A 100 ns molecular dynamics (MD) simulation study of compounds 10ah and 10bh revealed the stable conformation and binding energy in a stimulating environment. In drug-likeness assessments, both the compounds 10ah and 10bh adhere all the established guidelines.Communicated by Ramaswamy H. Sarma.

The Adsorption of P2X2 Receptors Interacting with IgG Antibodies Revealed by Combined AFM Imaging and Mechanical Simulation

The adsorption of proteins onto surfaces significantly impacts biomaterials, medical devices, and biological processes. This study aims to provide insights into the irreversible adsorption process of multiprotein complexes, particularly focusing on the interaction between anti-His6 IgG antibodies and the His6-tagged P2X2 receptor. Traditional approaches to understanding protein adsorption have centered around kinetic and thermodynamic models, often examining individual proteins and surface coverage, typically through Molecular Dynamics (MD) simulations. In this research, we introduce a computational approach employing Autodesk Maya 3D software for the investigation of multiprotein complexes' adsorption behavior. Utilizing Atomic Force Microscopy (AFM) imaging and Maya 3D-based mechanical simulations, our study yields real-time structural and kinetic observations. Our combined experimental and computational findings reveal that the P2X2 receptor-IgG antibody complex likely undergoes absorption in an 'extended' configuration. Whereas the P2X2 receptor is less adsorbed once is complexed to the IgG antibody compared to its individual state, the opposite is observed for the antibody. This insight enhances our understanding of the role of protein-protein interactions in the process of protein adsorption.

The cytokinin receptor OHK4/OsHK4 regulates inflorescence architecture in rice via an IDEAL PLANT ARCHITECTURE1/WEALTHY FARMER'S PANICLE-mediated positive feedback circuit

Inflorescence architecture is important for rice (Oryza sativa) grain yield. The phytohormone cytokinin (CK) has been shown to regulate rice inflorescence development; however, the underlying mechanism mediated by CK perception is still unclear. Employing a forward genetic approach, we isolated an inactive variant of the CK receptor OHK4/OsHK4 gene named panicle length1, which shows decreased panicle size due to reduced inflorescence meristem (IM) activity. A 2-amino acid deletion in the long α-helix stalk of the sensory module of OHK4 impairs the homodimerization and ligand-binding capacity of the receptor, even though the residues do not touch the ligand-binding domain or the dimerization interface. This deletion impairs CK signaling that occurs through the type-B response regulator OsRR21, which acts downstream of OHK4 in controlling inflorescence size. Meanwhile, we found that IDEAL PLANT ARCHITECTURE1(IPA1)/WEALTHY FARMER'S PANICLE (WFP), encoding a positive regulator of IM development, acts downstream of CK signaling and is directly activated by OsRR21. Additionally, we revealed that IPA1/WFP directly binds to the OHK4 promoter and upregulates its expression through interactions with 2 TCP transcription factors, forming a positive feedback circuit. Altogether, we identified the OHK4-OsRR21-IPA1 regulatory module, providing important insights into the role of CK signaling in regulating rice inflorescence architecture.

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.

Exploring the conformational changes of the Munc18-1/syntaxin 1a complex

Neurotransmitters are released from synaptic vesicles, the membrane of which fuses with the plasma membrane upon calcium influx. This membrane fusion reaction is driven by the formation of a tight complex comprising the plasma membrane N-ethylmaleimide-sensitive factor attachment receptor (SNARE) proteins syntaxin-1a and SNAP-25 with the vesicle SNARE protein synaptobrevin. The neuronal protein Munc18-1 forms a stable complex with syntaxin-1a. Biochemically, syntaxin-1a cannot escape the tight grip of Munc18-1, so formation of the SNARE complex is inhibited. However, Munc18-1 is essential for the release of neurotransmitters in vivo. It has therefore been assumed that Munc18-1 makes the bound syntaxin-1a available for SNARE complex formation. Exactly how this occurs is still unclear, but it is assumed that structural rearrangements occur. Here, we used a series of mutations to specifically weaken the complex at different positions in order to induce these rearrangements biochemically. Our approach was guided through sequence and structural analysis and supported by molecular dynamics simulations. Subsequently, we created a homology model showing the complex in an altered conformation. This conformation presumably represents a more open arrangement of syntaxin-1a that permits the formation of a SNARE complex to be initiated while still bound to Munc18-1. In the future, research should investigate how this central reaction for neuronal communication is controlled by other proteins.

The bacterial replication origin BUS promotes nucleobase capture

Genome duplication is essential for the proliferation of cellular life and this process is generally initiated by dedicated replication proteins at chromosome origins. In bacteria, DNA replication is initiated by the ubiquitous DnaA protein, which assembles into an oligomeric complex at the chromosome origin (oriC) that engages both double-stranded DNA (dsDNA) and single-stranded DNA (ssDNA) to promote DNA duplex opening. However, the mechanism of DnaA specifically opening a replication origin was unknown. Here we show that Bacillus subtilis DnaAATP assembles into a continuous oligomer at the site of DNA melting, extending from a dsDNA anchor to engage a single DNA strand. Within this complex, two nucleobases of each ssDNA binding motif (DnaA-trio) are captured within a dinucleotide binding pocket created by adjacent DnaA proteins. These results provide a molecular basis for DnaA specifically engaging the conserved sequence elements within the bacterial chromosome origin basal unwinding system (BUS).

PACT - Prediction of amyloid cross-interaction by threading

Amyloid proteins are often associated with the onset of diseases, including Alzheimer's, Parkinson's and many others. However, there is a wide class of functional amyloids that are involved in physiological functions, e.g., formation of microbial biofilms or storage of hormones. Recent studies showed that an amyloid fibril could affect the aggregation of another protein, even from a different species. This may result in amplification or attenuation of the aggregation process. Insight into amyloid cross-interactions may be crucial for better understanding of amyloid diseases and the potential influence of microbial amyloids on human proteins. However, due to the demanding nature of the needed experiments, knowledge of such interactions is still limited. Here, we present PACT (Prediction of Amyloid Cross-interaction by Threading) - the computational method for the prediction of amyloid cross-interactions. The method is based on modeling of a heterogeneous fibril formed by two amyloidogenic peptides. The resulting structure is assessed by the structural statistical potential that approximates its plausibility and energetic stability. PACT was developed and first evaluated mostly on data collected in the AmyloGraph database of interacting amyloids and achieved high values of Area Under ROC (AUC=0.88) and F1 (0.82). Then, we applied our method to study the interactions of CsgA - a bacterial biofilm protein that was not used in our in-reference datasets, which is expressed in several bacterial species that inhabit the human intestines - with two human proteins. The study included alpha-synuclein, a human protein that is involved in Parkinson's disease, and human islet amyloid polypeptide (hIAPP), which is involved in type 2 diabetes. In both cases, PACT predicted the appearance of cross-interactions. Importantly, the method indicated specific regions of the proteins, which were shown to play a central role in both interactions. We experimentally confirmed the novel results of the indicated CsgA fragments interacting with hIAPP based on the kinetic characteristics obtained with the ThT assay. PACT opens the possibility of high-throughput studies of amyloid interactions. Importantly, it can work with fairly long protein fragments, and as a purely physicochemical approach, it relies very little on scarce training data. The tool is available as a web server at https://pact.e-science.pl/pact/ . The local version can be downloaded from https://github.com/KubaWojciechowski/PACT .

Acceleration of Protein Degradation by 20S Proteasome-Binding Peptides Generated by In Vitro Artificial Evolution

Although the 20S core particle (CP) of the proteasome is an important component of the 26S holoenzyme, the stand-alone 20S CP acts directly on intrinsically disordered and oxidized/damaged proteins to degrade them in a ubiquitin-independent manner. It has been postulated that some structural features of substrate proteins are recognized by the 20S CP to promote substrate uptake, but the mechanism of substrate recognition has not been fully elucidated. In this study, we screened peptides that bind to the 20S CP from a random eight-residue pool of amino acid sequences using complementary DNA display an in vitro molecular evolution technique. The identified 20S CP-binding amino acid sequence was chemically synthesized and its effects on the 20S CP were investigated. The 20S CP-binding peptide stimulated the proteolytic activity of the inactive form of 20S CP. The peptide bound directly to one of the α-subunits, opening a gate for substrate entry on the α-ring. Furthermore, the attachment of this peptide sequence to α-synuclein enhanced its degradation by the 20S CP in vitro. In addition to these results, docking simulations indicated that this peptide binds to the top surface of the α-ring. These peptides could function as a key to control the opening of the α-ring gate.

The Legionella collagen-like protein employs a unique binding mechanism for the recognition of host glycosaminoglycans

Bacterial adhesion is a fundamental process which enables colonisation of niche environments and is key for infection. However, in Legionella pneumophila, the causative agent of Legionnaires' disease, these processes are not well understood. The Legionella collagen-like protein (Lcl) is an extracellular peripheral membrane protein that recognises sulphated glycosaminoglycans (GAGs) on the surface of eukaryotic cells, but also stimulates bacterial aggregation in response to divalent cations. Here we report the crystal structure of the Lcl C-terminal domain (Lcl-CTD) and present a model for intact Lcl. Our data reveal that Lcl-CTD forms an unusual dynamic trimer arrangement with a positively charged external surface and a negatively charged solvent exposed internal cavity. Through Molecular Dynamics (MD) simulations, we show how the GAG chondroitin-4-sulphate associates with the Lcl-CTD surface via unique binding modes. Our findings show that Lcl homologs are present across both the Pseudomonadota and Fibrobacterota-Chlorobiota-Bacteroidota phyla and suggest that Lcl may represent a versatile carbohydrate binding mechanism.

Phospholipids are imported into mitochondria by VDAC, a dimeric beta barrel scramblase

Mitochondria are double-membrane-bounded organelles that depend critically on phospholipids supplied by the endoplasmic reticulum. These lipids must cross the outer membrane to support mitochondrial function, but how they do this is unclear. We identify the Voltage Dependent Anion Channel (VDAC), an abundant outer membrane protein, as a scramblase-type lipid transporter that catalyzes lipid entry. On reconstitution into membrane vesicles, dimers of human VDAC1 and VDAC2 catalyze rapid transbilayer translocation of phospholipids by a mechanism that is unrelated to their channel activity. Coarse-grained molecular dynamics simulations of VDAC1 reveal that lipid scrambling occurs at a specific dimer interface where polar residues induce large water defects and bilayer thinning. The rate of phospholipid import into yeast mitochondria is an order of magnitude lower in the absence of VDAC homologs, indicating that VDACs provide the main pathway for lipid entry. Thus, VDAC isoforms, members of a superfamily of beta barrel proteins, moonlight as a class of phospholipid scramblases - distinct from alpha-helical scramblase proteins - that act to import lipids into mitochondria.

Small proteins modulate ion-channel-like ACD6 to regulate immunity in Arabidopsis thaliana

The multi-pass transmembrane protein ACCELERATED CELL DEATH 6 (ACD6) is an immune regulator in Arabidopsis thaliana with an unclear biochemical mode of action. We have identified two loci, MODULATOR OF HYPERACTIVE ACD6 1 (MHA1) and its paralog MHA1-LIKE (MHA1L), that code for ∼7 kDa proteins, which differentially interact with specific ACD6 variants. MHA1L enhances the accumulation of an ACD6 complex, thereby increasing the activity of the ACD6 standard allele for regulating plant growth and defenses. The intracellular ankyrin repeats of ACD6 are structurally similar to those found in mammalian ion channels. Several lines of evidence link increased ACD6 activity to enhanced calcium influx, with MHA1L as a direct regulator of ACD6, indicating that peptide-regulated ion channels are not restricted to animals.

Modelling and Molecular Dynamics Predict the Structure and Interactions of the Glycine Receptor Intracellular Domain

Glycine receptors (GlyRs) are glycine-gated inhibitory pentameric ligand-gated ion channels composed of α or α + β subunits. A number of structures of these proteins have been reported, but to date, these have only revealed details of the extracellular and transmembrane domains, with the intracellular domain (ICD) remaining uncharacterised due to its high flexibility. The ICD is a region that can modulate function in addition to being critical for receptor localisation and clustering via proteins such as gephyrin. Here, we use modelling and molecular dynamics (MD) to reveal details of the ICDs of both homomeric and heteromeric GlyR. At their N and C ends, both the α and β subunit ICDs have short helices, which are major sites of stabilising interactions; there is a large flexible loop between them capable of forming transient secondary structures. The α subunit can affect the β subunit ICD structure, which is more flexible in a 4α2:1β than in a 4α1:1β GlyR. We also explore the effects of gephyrin binding by creating GlyR models bound to the gephyrin E domain; MD simulations suggest these are more stable than the unbound forms, and again there are α subunit-dependent differences, despite the fact the gephyrin binds to the β subunit. The bound models also suggest that gephyrin causes compaction of the ICD. Overall, the data expand our knowledge of this important receptor protein and in particular clarify features of the underexplored ICD.

Misfolding of fukutin-related protein (FKRP) variants in congenital and limb girdle muscular dystrophies

Fukutin-related protein (FKRP, MIM ID 606596) variants cause a range of muscular dystrophies associated with hypo-glycosylation of the matrix receptor, α-dystroglycan. These disorders are almost exclusively caused by homozygous or compound heterozygous missense variants in the FKRP gene that encodes a ribitol phosphotransferase. To understand how seemingly diverse FKRP missense mutations may contribute to disease, we examined the synthesis, intracellular dynamics, and structural consequences of a panel of missense mutations that encompass the disease spectrum. Under non-reducing electrophoresis conditions, wild type FKRP appears to be monomeric whereas disease-causing FKRP mutants migrate as high molecular weight, disulfide-bonded aggregates. These results were recapitulated using cysteine-scanning mutagenesis suggesting that abnormal disulfide bonding may perturb FKRP folding. Using fluorescence recovery after photobleaching, we found that the intracellular mobility of most FKRP mutants in ATP-depleted cells is dramatically reduced but can, in most cases, be rescued with reducing agents. Mass spectrometry showed that wild type and mutant FKRP differentially associate with several endoplasmic reticulum (ER)-resident chaperones. Finally, structural modelling revealed that disease-associated FKRP missense variants affected the local environment of the protein in small but significant ways. These data demonstrate that protein misfolding contributes to the molecular pathophysiology of FKRP-deficient muscular dystrophies and suggest that molecules that rescue this folding defect could be used to treat these disorders.