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The formation of the pyroglutamate variant of amyloid beta (pGlu-Aβ), which is extremely hydrophobic, rapidly aggregating, and highly neurotoxic, is mediated by the action of secretory glutaminyl cyclase (sQC). The pGlu-Aβ often acts as a seed for the aggregation of the full length Aβ and contributes to the overall load of Aβ plaques in Alzheimer's disease (AD). Therefore, inhibiting sQC is a potential approach to limit the formation of pGlu-Aβ and to modify the progression of AD. This study presents two novel molecules containing benzimidazole-6-carboxamide, namely LSB-09 and LSB-24, as promising sQC inhibitors. These inhibitors demonstrated moderate toxicity in human neuroblastoma cell lines and possessed IC50 values in the micromolar range (40 and 4 μM for LSB-09 and LSB-24, respectively). Additionally, the X-ray crystal structure of the sQC-LSB-09 complex revealed a unique binding mode, and a systematic computational investigation elucidated the binding mode for LSB-24. The binding mode of these two benzimidazole-6-carboxamide inhibitors offers a potential platform for designing attractive lead candidates against sQC., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Inositol-requiring enzyme 1α (IRE1α) is a sensor of endoplasmic reticulum (ER) stress and drives ER stress response pathways. Activated IRE1α exhibits RNase activity and cleaves mRNA encoding X-box binding protein 1, a transcription factor that induces the expression of genes that maintain ER proteostasis for cell survival. Previously, we showed that IRE1α undergoes S -nitrosylation, a post-translational modification induced by nitric oxide (NO), resulting in reduced RNase activity. Therefore, S -nitrosylation of IRE1α compromises the response to ER stress, making cells more vulnerable. We conducted virtual screening and cell-based validation experiments to identify compounds that inhibit the S -nitrosylation of IRE1α by targeting nitrosylated cysteine residues. We ultimately identified a compound (1ACTA) that selectively inhibits the S -nitrosylation of IRE1α and prevents the NO-induced reduction of RNase activity. Furthermore, 1ACTA reduces the rate of NO-induced cell death. Our research identified S -nitrosylation as a novel target for drug development for IRE1α and provides a suitable screening strategy.

The CACHE challenges are a series of prospective benchmarking exercises to evaluate progress in the field of computational hit-finding. Here we report the results of the inaugural CACHE challenge in which 23 computational teams each selected up to 100 commercially available compounds that they predicted would bind to the WDR domain of the Parkinson's disease target LRRK2, a domain with no known ligand and only an apo structure in the PDB. The lack of known binding data and presumably low druggability of the target is a challenge to computational hit finding methods. Of the 1955 molecules predicted by participants in Round 1 of the challenge, 73 were found to bind to LRRK2 in an SPR assay with a K D lower than 150 μM. These 73 molecules were advanced to the Round 2 hit expansion phase, where computational teams each selected up to 50 analogs. Binding was observed in two orthogonal assays for seven chemically diverse series, with affinities ranging from 18 to 140 μM. The seven successful computational workflows varied in their screening strategies and techniques. Three used molecular dynamics to produce a conformational ensemble of the targeted site, three included a fragment docking step, three implemented a generative design strategy and five used one or more deep learning steps. CACHE #1 reflects a highly exploratory phase in computational drug design where participants adopted strikingly diverging screening strategies. Machine learning-accelerated methods achieved similar results to brute force (e.g., exhaustive) docking. First-in-class, experimentally confirmed compounds were rare and weakly potent, indicating that recent advances are not sufficient to effectively address challenging targets.

The dedicator of cytokinesis (DOCK)/engulfment and cell motility (ELMO) complex serves as a guanine nucleotide exchange factor (GEF) for the GTPase Rac. RhoG, another GTPase, activates the ELMO-DOCK-Rac pathway during engulfment and migration. Recent cryo-EM structures of the DOCK2/ELMO1 and DOCK2/ELMO1/Rac1 complexes have identified closed and open conformations that are key to understanding the autoinhibition mechanism. Nevertheless, the structural details of RhoG-mediated activation of the DOCK/ELMO complex remain elusive. Herein, we present cryo-EM structures of DOCK5/ELMO1 alone and in complex with RhoG and Rac1. The DOCK5/ELMO1 structure exhibits a closed conformation similar to that of DOCK2/ELMO1, suggesting a shared regulatory mechanism of the autoinhibitory state across DOCK-A/B subfamilies (DOCK1-5). Conversely, the RhoG/DOCK5/ELMO1/Rac1 complex adopts an open conformation that differs from that of the DOCK2/ELMO1/Rac1 complex, with RhoG binding to both ELMO1 and DOCK5. The alignment of the DOCK5 phosphatidylinositol (3,4,5)-trisphosphate binding site with the RhoG C-terminal lipidation site suggests simultaneous binding of RhoG and DOCK5/ELMO1 to the plasma membrane. Structural comparison of the apo and RhoG-bound states revealed that RhoG facilitates a closed-to-open state conformational change of DOCK5/ELMO1. Biochemical and surface plasmon resonance (SPR) assays confirm that RhoG enhances the Rac GEF activity of DOCK5/ELMO1 and increases its binding affinity for Rac1. Further analysis of structural variability underscored the conformational flexibility of the DOCK5/ELMO1/Rac1 complex core, potentially facilitating the proximity of the DOCK5 GEF domain to the plasma membrane. These findings elucidate the structural mechanism underlying the RhoG-induced allosteric activation and membrane binding of the DOCK/ELMO complex., Competing Interests: Conflict of interest The authors declare that they have no conflicts of interest with the contents of this article., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

The COVID-19 pandemic continues to pose a substantial threat to human lives and is likely to do so for years to come. Despite the availability of vaccines, searching for efficient small-molecule drugs that are widely available, including in low- and middle-income countries, is an ongoing challenge. In this work, we report the results of an open science community effort, the "Billion molecules against COVID-19 challenge", to identify small-molecule inhibitors against SARS-CoV-2 or relevant human receptors. Participating teams used a wide variety of computational methods to screen a minimum of 1 billion virtual molecules against 6 protein targets. Overall, 31 teams participated, and they suggested a total of 639,024 molecules, which were subsequently ranked to find 'consensus compounds'. The organizing team coordinated with various contract research organizations (CROs) and collaborating institutions to synthesize and test 878 compounds for biological activity against proteases (Nsp5, Nsp3, TMPRSS2), nucleocapsid N, RdRP (only the Nsp12 domain), and (alpha) spike protein S. Overall, 27 compounds with weak inhibition/binding were experimentally identified by binding-, cleavage-, and/or viral suppression assays and are presented here. Open science approaches such as the one presented here contribute to the knowledge base of future drug discovery efforts in finding better SARS-CoV-2 treatments., (© 2023 The Authors. Molecular Informatics published by Wiley-VCH GmbH.)

The carboxyl terminal domain of the largest subunit of eukaryotic RNA polymerase II (RNAPII) consists of highly conserved tandem repeats of Tyr 1 Ser 2 Pro 3 Thr 4 Ser 5 Pro 6 Ser 7 , referred as CTD. The CTD undergoes posttranslational modifications where the interplay of kinases imparts specific CTD phosphorylations, recognized by regulatory proteins that help in the mRNA transcription. Here, the Ser5 phosphorylation (Ser5P) remains high during the transcription initiation, followed by the Ser2P which peaks towards the termination and the Ser7P remains high throughout the transcription process. The Paf1 elongation complex (Paf1C) through its Cdc73 subunit is recruited to the phosphorylated CTD and play active role during different stages of mRNA transcription. We show that the CTD binding domain of Cdc73 is an independent folding unit which interacts with the hyper phosphorylated CTD. The 500 ns MD simulation studies further identified the binding interface and the pattern of CTD phosphorylation involved in the interaction with Cdc73. The possible key residues were mutated and the subsequent pull down analysis suggests that the phosphorylated Ser2, Ser5 and Ser7 of the tandem CTD heptads interact respectively with Arg310, Arg268 and Arg300 of Cdc73. Our finding provides new insight for Cdc73 function during mRNA transcription., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

The catalytic subunit of RNA Polymerase II contains a highly conserved carboxy terminal domain (CTD) composed of multiple tandem heptad sequence Tyr 1 Ser 2 Pro 3 Thr 4 Ser 5 Pro 6 Ser 7 . The non-proline residues in CTD undergo posttranslational modifications, with Ser5 phosphorylation (Ser5P) predominating at the start of the transcription cycle and Ser2P at the end, while other phosphorylation levels are high all throughout. The differentially phosphorylated CTD is recognized by regulatory proteins, helpful during mRNA transcription and export. One such protein Npl3 is composed of two RNA binding domains and a C-terminus RGG/SR domain. The Ser411 of Npl3 is reported to make direct contact with Ser2P of CTD for its recruitment and function, while the Npl3 lacking of C-terminal 25 amino acids (Npl3Δ 389 - 414 ) showed no apparent defects in mRNA synthesis. Here, we report that the RNA binding domains of Npl3 are separate folding units and interact also with the CTD. The interaction between Npl3 and CTD appears to involve not just Ser2P, but also the Ser5P and Ser7P. The Arg126 of the first RNA binding domain interacts with Ser2P whereas the Arg235 of the second RNA binding domain interacts with either Ser7P or Ser5P of another heptad. The finding provides new insight of Npl3 function for mRNA transcription., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Atherosclerosis is a chronic inflammatory disease characterized by plaque build-up in the arteries, leading to the obstruction of blood flow. Macrophages are the primary immune cells found in the atherosclerotic lesions and are directly involved in atherosclerosis progression. Macrophages are derived from extravasating blood monocytes. The monocytic CD40 receptor is important for monocyte recruitment on the endothelium expressing the CD40 ligand (CD40L). Thus, targeting monocyte/macrophage interaction with the endothelium by inhibiting CD40-CD40L interaction may be a promising strategy for attenuating atherosclerosis. Monoclonal antibodies have been used against this target but shows various complications. We used an array of computer-aided drug discovery tools and molecular docking approaches to design a therapeutic inhibitory peptide that could efficiently bind to the critical residues (82Y, 84D, and 86N) on the CD40 receptor essential for the receptor's binding to CD40L. The initial screen identified a parent peptide with a high binding affinity to CD40, but the peptide exhibited a positive hepatotoxicity score. We then designed several novel peptidomimetic derivatives with higher binding affinities to CD40, good physicochemical properties, and negative hepatotoxicity as compared to the parent peptide. Furthermore, we conducted molecular dynamics simulations for both the apo and complexed forms of the receptor with ligand, and screened peptides to evaluate their stability. The designed peptidomimetic derivatives are promising therapeutics targeting the CD40-CD40L interaction and may potentially be used to attenuate atherosclerosis., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

AIOLOS, encoded by IKZF3 , is a member of the IKZF family of proteins that plays an important role in regulating late B-cell differentiation. Human individuals heterozygous for the AIOLOS p.N160S variant displayed impaired humoral immune responses as well as impaired B and T cell development. We have previously reported that a mouse strain harboring an Ikzf3 N159S allele that corresponds to human IKZF3 N160S recapitulated immune-deficient phenotypes, such as impaired B cell development and loss of CD23 expression. In this study, we investigated the effect of the Ikzf3 N159S variant and found that B1a cell development was impaired in Ikzf3 N159S/N159S mice. In addition, CD62L expression was severely decreased in both B and T lymphocytes by the Ikzf3 N159S mutation, in a dose-dependent manner. Mixed bone marrow chimera experiments have revealed that most immunodeficient phenotypes, including low CD62L expression, occur in intrinsic cells. Interestingly, while Ikzf3 N159S/N159S lymphocytes were still present in the spleen, they were completely outcompeted by control cells in the lymph nodes, suggesting that the capacity for homing or retention in the lymph nodes was lost due to the Ikzf3 N159S mutation. The homing assay confirmed severely decreased homing abilities to lymph nodes of Ikzf3 N159S/N159S B and T lymphocytes but selective enrichment of CD62L expressing Ikzf3 N159S/N159S lymphocytes in lymph nodes. This finding suggests that impaired CD62L expression is the major reason for the impaired homing capacity caused by the Ikzf3 N159S mutation. Interestingly, an excess amount of Ikaros, but not Aiolos, restored CD62L expression in Ikzf3 N159S/N159S B cells. Together with the loss of CD62L expression due to Ikaros deficiency, the Aiolos N159S mutant protein likely interferes with Ikaros function through heterodimerization, at least in activating the Sell gene encoding CD62L expression. Thus, our results revealed that Aiolos N159S causes some immunodeficient phenotypes via the pathogenesis referred to as the heterodimeric interference as observed for Aiolos G158R variant., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Chang, Yamashita, Padhi, Zhang and Taniuchi.)

Multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continue to evolve carrying flexible amino acid substitutions in the spike protein's receptor binding domain (RBD). These substitutions modify the binding of the SARS-CoV-2 to human angiotensin-converting enzyme 2 (hACE2) receptor and have been implicated in altered host fitness, transmissibility, and efficacy against antibody therapeutics and vaccines. Reliably predicting the binding strength of SARS-CoV-2 variants RBD to hACE2 receptor and neutralizing antibodies (NAbs) can help assessing their fitness, and rapid deployment of effective antibody therapeutics, respectively. Here, we introduced a two-step computational framework with 3-fold validation that first identified dissociation constant as a reliable predictor of binding affinity in hetero- dimeric and trimeric protein complexes. The second step implements dissociation constant as descriptor of the binding strengths of SARS-CoV-2 variants RBD to hACE2 and NAbs. Then, we examined several variants of concerns (VOCs) such as Alpha, Beta, Gamma, Delta, and Omicron and demonstrated that these VOCs RBD bind to the hACE2 with enhanced affinity. Furthermore, the binding affinity of Omicron variant's RBD was reduced with majority of the RBD-directed NAbs, which is highly consistent with the experimental neutralization data. By studying the atomic contacts between RBD and NAbs, we revealed the molecular footprints of four NAbs (GH-12, P2B-1A1, Asarnow_3D11, and C118)-that may likely neutralize the recently emerged Omicron variant-facilitating enhanced binding affinity. Finally, our findings suggest a computational pathway that could aid researchers identify a range of current NAbs that may be effective against emerging SARS-CoV-2 variants., (© 2023 Wiley Periodicals LLC.)

The usage of nitrification inhibitors is one of the strategies that reduce or slow down the denitrification process to prevent nitrogen loss to the atmosphere in the form of N 2 O. Directly targeting microbial denitrification could be one of the mitigation strategies; however, until now little efforts have been devoted toward the development of denitrification inhibitors. Here, we have identified small-molecule inhibitors of one of the proteins involved in the fungal denitrification pathway. Specifically, virtual screening was employed to identify the inhibitors of copper-containing nitrite reductase ( Fo NirK) of the filamentous fungus Fusarium oxysporum . Three series of chemical compounds were identified, out of which compounds belonging to two chemical scaffolds inhibited Fo NirK enzymatic activity in low micromolar ranges. Several compounds also displayed moderate inhibition of fungal denitrification activity in vivo. Evaluation of in vitro activity against NirK from denitrifying bacterium Achromobacter xylosoxidans ( Ax NirK) and in vivo bacterial denitrification revealed a similar inhibitory profile.

The control of cell movement through manipulation of cytoskeletal structure has therapeutic prospects notably in the development of novel anti-metastatic drugs. In this study, we determine the structure of Ras-binding domain (RBD) of ELMO1, a protein involved in cytoskeletal regulation, both alone and in complex with the activator RhoG and verify its targetability through computational nanobody design. Using our dock-and-design approach optimized with native-like initial pose selection, we obtain Nb01, a detectable binder from scratch in the first-round design. An affinity maturation step guided by structure-activity relationship at the interface generates 23 Nb01 sequence variants and 17 of them show enhanced binding to ELMO1-RBD and are modeled to form major spatial overlaps with RhoG. The best binder, Nb29, inhibited ELMO1-RBD/RhoG interaction. Molecular dynamics simulation of the flexibility of CDR2 and CDR3 of Nb29 reveal the design of stabilizing mutations at the CDR-framework junctions potentially confers the affinity enhancement., (© 2023. The Author(s).)

DNA methyltransferases (DNMTs) catalyze methylation at the C5 position of cytosine with S-adenosyl-L-methionine. Methylation regulates gene expression, serving a variety of physiological and pathophysiological roles. The chemical mechanisms regulating DNMT enzymatic activity, however, are not fully elucidated. Here, we show that protein S-nitrosylation of a cysteine residue in DNMT3B attenuates DNMT3B enzymatic activity and consequent aberrant upregulation of gene expression. These genes include Cyclin D2 (Ccnd2), which is required for neoplastic cell proliferation in some tumor types. In cell-based and in vivo cancer models, only DNMT3B enzymatic activity, and not DNMT1 or DNMT3A, affects Ccnd2 expression. Using structure-based virtual screening, we discovered chemical compounds that specifically inhibit S-nitrosylation without directly affecting DNMT3B enzymatic activity. The lead compound, designated DBIC, inhibits S-nitrosylation of DNMT3B at low concentrations (IC 50  ≤ 100 nM). Treatment with DBIC prevents nitric oxide (NO)-induced conversion of human colonic adenoma to adenocarcinoma in vitro. Additionally, in vivo treatment with DBIC strongly attenuates tumor development in a mouse model of carcinogenesis triggered by inflammation-induced generation of NO. Our results demonstrate that de novo DNA methylation mediated by DNMT3B is regulated by NO, and DBIC protects against tumor formation by preventing aberrant S-nitrosylation of DNMT3B., (© 2023. The Author(s).)

The ongoing evolution of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has resulted in the recent emergence of a highly divergent variant of concern (VOC) defined as Omicron or B.1.1.529. This VOC is of particular concern because it has the potential to evade most therapeutic antibodies and has undergone a sustained genetic evolution, resulting in the emergence of five distinct sub-lineages. However, the evolutionary dynamics of the initially identified Omicron BA.1 and BA.2 sub-lineages remain poorly understood. Herein, we combined Bayesian phylogenetic analysis, mutational profiling, and selection pressure analysis to track the virus's genetic changes that drive the early evolutionary dynamics of the Omicron. Based on the Omicron dataset chosen for the improved temporal signals and sampled globally between November 2021 and January 2022, the most recent common ancestor (tMRCA) and substitution rates for BA.1 were estimated to be that of 18 September 2021 (95% highest posterior density (HPD), 4 August-22 October 2021) and 1.435 × 10 -3 (95% HPD  =  1.021 × 10 -3 - 1.869 × 10 -3 ) substitution/site/year, respectively, whereas 3 November 2021 (95% highest posterior density (HPD) 26 September-28 November 2021) and 1.074 × 10 -3 (95% HPD  =  6.444 × 10 -4 - 1.586 × 10 -3 ) substitution/site/year were estimated for the BA.2 sub-lineage. The findings of this study suggest that the Omicron BA.1 and BA.2 sub-lineages originated independently and evolved over time. Furthermore, we identified multiple sites in the spike protein undergoing continued diversifying selection that may alter the neutralization profile of BA.1. This study sheds light on the ongoing global genomic surveillance and Bayesian molecular dating analyses to better understand the evolutionary dynamics of the virus and, as a result, mitigate the impact of emerging variants on public health.

The structural information of a protein is pivotal to comprehend its functions, protein-protein and protein-ligand interactions. There is a widening gap between the number of known protein sequences and that of experimentally determined structures. The protein structure prediction has emerged as an efficient alternative to deliver the reliable structural information of proteins. However, it remains a challenge to identify the best model among the many predicted by one or a few structure prediction methods. Here we report ProFitFun-Meta, a neural network based pure single model scoring method for assessing the quality of predicted model structures by an effective combination structural information of various backbone dihedral angle and residue surface accessibility preferences of amino acid residues with other spatial properties of protein structures. The performance of ProFitFun-Meta was validated and benchmarked against current state-of-the-art methods on the extensive datasets, comprising a Test Dataset (n = 26,604), an External Dataset (n = 40,000), and CASP14 Dataset (n = 1200). The comprehensive performance evaluation of ProFitFun-Meta demonstrated its reliability and efficiency in terms of Spearman's (ρ) and Pearson's (r) correlation coefficients, GDT-TS loss (g), and absolute loss (d). An improved performance over the current state-of-the-art methods and leading performers of CASP14 experiment in quality assessment category demonstrated its potential to become an integral component of computational pipelines for protein modeling and design. The minimal dependencies, high computational efficiency, and portability to various Linux and Windows OS provide an additional edge to ProFitFun-Meta for its easy implementation and applications in various regimes of computational protein folding., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Authors.)

Understanding the origin of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a highly debatable and unresolved issue for scientific communities all over the world. Understanding the mechanism of virus entry to the host cells is crucial to deciphering the susceptibility profiles of animal species to SARS-CoV-2. The interaction of SARS-CoV-2 ligands (receptor-binding domain on spike protein) with its host cell receptor, angiotensin-converting enzyme 2 (ACE2), is a critical determinant of host range and cross-species transmission. In this study, we developed and implemented a rigorous computational approach for predicting binding affinity between 299 ACE2 orthologs from diverse vertebrate species and the SARS-CoV-2 spike protein. The findings show that the SARS-CoV-2 spike protein can bind to a wide range of vertebrate species carrying evolutionary divergent ACE2, implying a broad host range at the virus entry level, which may contribute to cross-species transmission and further viral evolution. Furthermore, the current study facilitated the identification of genetic determinants that may differentiate susceptible from resistant host species based on the conservation of ACE2-spike protein interacting residues in vertebrate host species known to facilitate SARS-CoV-2 infection; however, these genetic determinants warrant in vivo experimental confirmation. The molecular interactions associated with varied binding affinity of distinct ACE2 isoforms in a specific bat species were identified using protein structure analysis, implying the existence of diversified bat species' susceptibility to SARS-CoV-2. The current study's findings highlight the importance of intensive surveillance programmes aimed at identifying susceptible hosts, especially those with the potential to transmit zoonotic pathogens, in order to prevent future outbreaks., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Biochemical and structural analyses of purified proteins are essential for the understanding of their properties. However, many proteins are unstable and difficult to purify, hindering their characterization. The B2 proteins of the lasso peptide biosynthetic pathways are cysteine proteases that cleave precursor peptides during the maturation process. The B2 proteins are poorly soluble, and no experimentally solved structures are available. Here, we performed a rapid semicomprehensive mutational analysis of the B2 protein from the thermophilic actinobacterium, Thermobifida fusca (FusB2), using a cell-free transcription/translation system, and compared the results with the structure prediction by AlphaFold2. Analysis of 34 FusB2 mutants with substitutions of hydrophobic residues confirmed the accuracy of the predicted structure, and revealed a hydrophobic patch on the protein surface, which likely serves as the binding site of the partner protein, FusB1. Our results suggest that the combination of rapid cell-free mutant analyses with precise structure predictions can greatly accelerate structure-function research of proteins for which no structures are available.

Alzheimer's disease (AD) is one of the most common, progressive neurodegenerative disorders affecting the aged populations. Though various disease pathologies have been suggested for AD, the impairment of the cholinergic system is one of the critical factors for the disease progression. Restoration of the cholinergic transmission through acetylcholinesterase (AChE) inhibitors is a promising disease modifying therapy. Being the first marketed drug for AD, tacrine reversibly inhibits AChE and thereby slows the breakdown of the chemical messenger acetylcholine (ACh) in the brain. However, the atomic level of interactions of tacrine towards human AChE (hAChE) is unknown for years. Hence, in the current study, we report the X-ray structure of hAChE-tacrine complex at 2.85 Å resolution. The conformational heterogeneity of tacrine within the electron density was addressed with the help of molecular mechanics assisted methods and the low-energy ligand configuration is reported, which provides a mechanistic explanation for the high binding affinity of tacrine towards AChE. Additionally, structural comparison of reported hAChE structures sheds light on the conformational selection and induced fit effects of various active site residues upon binding to different ligands and provides insight for future drug design campaigns against AD where AChE is a drug target., (Copyright © 2022 Elsevier B.V. All rights reserved.)

SPHK1 (sphingosine kinase-1) catalyzes the phosphorylation of sphingosine to sphingosine-1-phosphate (S1P), is found to be highly expressed in solid tumors. Here, extracellular vesicles (EVs) are identified as the key transporters of SPHK1 to the tumor microenvironment. Consequently, SPHK1-packaged EVs elevate S1P levels in the tumor microenvironment, where S1P appears as an immunosuppressive agent. However, the exact mechanism of how S1P mediates its immunosuppressive effects in cancer is not understood. It is investigated that S1P can induce T cell exhaustion. S1P can also upregulate programmed death ligand-1 (PDL-1) expression through E2F1-mediated transcription. Notably, an SPHK1 inhibitor PF543 improves T cell-mediated cytotoxicity. Furthermore, combining PF543 with an anti-PD-1 antibody reduces tumor burden and metastasis more effectively than PF543 alone in vivo. These data demonstrate a previously unrecognized mechanism of how SPHK1-packaged EVs contribute to the progression of ovarian cancer and thus present the potential clinical application of inhibiting SPHK1/S1P signaling to improve immune checkpoint blockage (anti-PD-1 antibody) therapy in ovarian cancer., (© 2022 The Authors. Advanced Science published by Wiley-VCH GmbH.)

The role of TIRAP (toll/interleukin-1 receptor (TIR) domain-containing adapter protein) in macrophage inflammatory signalling has been significantly evolved since its discovery in 2001 due to its dynamic nature and subcellular localization to regulate multiple signaling through several protein-protein interactions (PPIs). Structural analysis of these interactions can reveal a better understanding of their conformational dynamics and the nature of their binding. Tyrosine phosphorylation in the TIR domain of TIRAP is very critical for its function. In toll-like receptor (TLR) 4/2 signalling, Bruton's tyrosine kinase (BTK) and Protein kinase C delta (PKCδ) are known to phosphorylate the Y86, Y106, Y159, and Y187 of TIRAP which is crucial for the downstream function of MAPKs (mitogen-activated protein kinases) activation. The objective of this study is to understand the interaction of TIRAP with p38 MAPK through molecular docking and identify the importance of TIRAP tyrosine phosphorylation in p38 MAPK interaction. In this structural study, we performed an in-silico molecular docking using HADDOCK 2.4, pyDockWEB, ClusPro 2.0, and ZDOCK 3.0.2 tools to unravel the interaction between TIRAP and p38 MAPK. Further, manual in-silico phosphorylations of TIRAP tyrosines; Y86, Y106, Y159, and Y187 was created in the Discovery Studio tool to study the conformational changes in protein docking and their binding affinities with p38 MAPK in comparison to non-phosphorylated state. Our molecular docking and 500 ns of molecular dynamic (MD) simulation study demonstrates that the Y86 phosphorylation (pY86) in TIRAP is crucial in promoting the higher binding affinity (∆G bind ) with p38 MAPK. The conformational changes due to the tyrosine phosphorylation mainly at the Y86 site pull the TIRAP closer to the active site in the kinase domain of p38 MAPK and plays a significant role at the interface site which is reversed in its dephosphorylated state. The heatmap of interactions between the TIRAP and p38 MAPK after the MD simulation shows that the TIRAP pY86 structure makes the highest number of stable hydrogen bonds with p38 MAPK residues. Our findings may further be validated in an in-vitro system and would be crucial for targeting the TIRAP and p38 MAPK interaction for therapeutic purposes against the chronic inflammatory response and associated diseases., (© 2022. The Author(s).)

Fluorescent protein (FP) design is among the challenging protein design problems due to the tradeoffs among multiple properties to be optimized. Despite the accumulated efforts in design and characterization, progress has been slow in gaining a full understanding of sequence-property relationships to tackle the multiobjective design problem in FPs. In this study, we approach this problem by developing FPredX, a collection of gradient-boosted decision tree models, which mapped FP sequences to four major design targets of FPs, including excitation maximum, emission maximum, brightness, and oligomeric state. By training using one-hot encoded multiple aligned sequences with hyperparameters optimization in each model, FPredX models showed excellent prediction performance for all target properties compared with existing methods. We further interpreted the FPredX models by comparing the importance of positions along the aligned FP sequence to the predictive performance and suggested positions, which showed differential importance deemed by FPredX models to the prediction of each target property., (© 2021 Wiley Periodicals LLC.)

Motivation: An accurate estimation of the quality of protein model structures typifies as a cornerstone in protein structure prediction regimes. Despite the recent groundbreaking success in the field of protein structure prediction, there are certain prospects for the improvement in model quality estimation at multiple stages of protein structure prediction and thus, to further push the prediction accuracy. Here, a novel approach, named ProFitFun, for assessing the quality of protein models is proposed by harnessing the sequence and structural features of experimental protein structures in terms of the preferences of backbone dihedral angles and relative surface accessibility of their amino acid residues at the tripeptide level. The proposed approach leverages upon the backbone dihedral angle and surface accessibility preferences of the residues by accounting for its N-terminal and C-terminal neighbors in the protein structure. These preferences are used to evaluate protein structures through a machine learning approach and tested on an extensive dataset of diverse proteins., Results: The approach was extensively validated on a large test dataset (n = 25 005) of protein structures, comprising 23 661 models of 82 non-homologous proteins and 1344 non-homologous experimental structures. In addition, an external dataset of 40 000 models of 200 non-homologous proteins was also used for the validation of the proposed method. Both datasets were further used for benchmarking the proposed method with four different state-of-the-art methods for protein structure quality assessment. In the benchmarking, the proposed method outperformed some state-of-the-art methods in terms of Spearman's and Pearson's correlation coefficients, average GDT-TS loss, sum of z-scores and average absolute difference of predictions over corresponding observed values. The high accuracy of the proposed approach promises a potential use of the sequence and structural features in computational protein design., Availability and Implementation: http://github.com/KYZ-LSB/ProTerS-FitFun., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Several mutations in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have increased the transmission and mortality rate of coronavirus disease-19 (COVID-19) across the globe. Although many vaccines have been developed, a large proportion of the global population remains at high risk of infection. The current study aims to develop an antiviral peptide capable of inhibiting the interaction of SARS-CoV-2 spike protein and its six major variants with the host cell angiotensin-converting enzyme 2 (ACE2) receptor. An in-silico approach was employed to design a therapeutic peptide inhibitor against the receptor-binding domain (RBD) of the spike (S) protein of SARS-CoV-2 and its variants (B.1.1.7, B.1.351, P.1, B.1.617.1, B.1.617.2 and B.1.617.3). The binding specificity and affinity of our designed peptide inhibitor Mod13AApi (YADKYQKQYKDAY) with wild-type S-RBD and its six variants was confirmed by molecular docking using the HPEPDOCK tool, whereas complex stability was determined by the MD simulation study. The physicochemical and ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of inhibitory peptides were determined using the ExPASy tool and pkCSM server. The docking results and its properties from our in-silico analysis present the Mod13AApi, a promising peptide for the rapid development of anti-coronavirus peptide-based antiviral therapy. Blockage of the binding of the spike protein of SARS-CoV-2 variants with ACE2 in the presence of the therapeutic peptide may prevent deadly SARS-CoV-2 variants entry into host cells. Therefore, the designed inhibitory peptide can be utilized as a promising therapeutic strategy to combat COVID-19, as evident from this in-silico study., Competing Interests: Conflict of interestAll the authors have declared that they have no competing interests., (© The Author(s), under exclusive licence to Springer Nature B.V. 2021.)

Recent evidence has documented the potential roles of histone-modifying enzymes in autism-spectrum disorder (ASD). Aberrant histone H3 lysine 9 (H3K9) dimethylation resulting from genetic variants in histone methyltransferases is known for neurodevelopmental and behavioral anomalies. However, a systematic examination of H3K9 methylation dynamics in ASD is lacking. Here we resequenced nine genes for histone methyltransferases and demethylases involved in H3K9 methylation in individuals with ASD and healthy controls using targeted next-generation sequencing. We identified a novel rare variant (A211S) in the SUV39H2, which was predicted to be deleterious. The variant showed strongly reduced histone methyltransferase activity in vitro. In silico analysis showed that the variant destabilizes the hydrophobic core and allosterically affects the enzyme activity. The Suv39h2-KO mice displayed hyperactivity and reduced behavioral flexibility in learning the tasks that required complex behavioral adaptation, which is relevant for ASD. The Suv39h2 deficit evoked an elevated expression of a subset of protocadherin β (Pcdhb) cluster genes in the embryonic brain, which is attributable to the loss of H3K9 trimethylation (me3) at the gene promoters. Reduced H3K9me3 persisted in the cerebellum of Suv39h2-deficient mice to an adult stage. Congruently, reduced expression of SUV39H1 and SUV39H2 in the postmortem brain samples of ASD individuals was observed, underscoring the role of H3K9me3 deficiency in ASD etiology. The present study provides direct evidence for the role of SUV39H2 in ASD and suggests a molecular cascade of SUV39H2 dysfunction leading to H3K9me3 deficiency followed by an untimely, elevated expression of Pcdhb cluster genes during early neurodevelopment., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

Nematode chitinases play vital roles in various physiological processes, including egg hatching, larva moulting, and reproduction. Small-molecule inhibitors of nematode chitinases have potential applications for controlling nematode pests. On the basis of the crystal structure of Ce Cht1, a representative chitinase indispensable to the eggshell chitin degradation of the model nematode Caenorhabditis elegans , we have discovered a series of novel inhibitors bearing a ( R )-3,4-diphenyl-4,5-dihydropyrrolo[3,4- c ]pyrazol-6(2 H )-one scaffold by hierarchical virtual screening. The crystal structures of Ce Cht1 complexed with two of these inhibitors clearly elucidated their interactions with the enzyme active site. Based on the inhibitory mechanism, several analogues with improved inhibitory activities were identified, among which the compound PP28 exhibited the most potent activity with a K i value of 0.18 μM. This work provides the structural basis for the development of novel nematode chitinase inhibitors.

Protein engineering and design principles employing the 20 standard amino acids have been extensively used to achieve stable protein scaffolds and deliver their specific activities. Although this confers some advantages, it often restricts the sequence, chemical space, and ultimately the functional diversity of proteins. Moreover, although site-specific incorporation of non-natural amino acids (nnAAs) has been proven to be a valuable strategy in protein engineering and therapeutics development, its utility in the affinity-maturation of nanobodies is not fully explored. Besides, current experimental methods do not routinely employ nnAAs due to their enormous library size and infinite combinations. To address this, we have developed an integrated computational pipeline employing structure-based protein design methodologies, molecular dynamics simulations and free energy calculations, for the binding affinity prediction of an nnAA-incorporated nanobody toward its target and selection of potent binders. We show that by incorporating halogenated tyrosines, the affinity of 9G8 nanobody can be improved toward epidermal growth factor receptor (EGFR), a crucial cancer target. Surface plasmon resonance (SPR) assays showed that the binding of several 3-chloro-l-tyrosine (3MY)-incorporated nanobodies were improved up to 6-fold into a picomolar range, and the computationally estimated binding affinities shared a Pearson's r of 0.87 with SPR results. The improved affinity was found to be due to enhanced van der Waals interactions of key 3MY-proximate nanobody residues with EGFR, and an overall increase in the nanobody's structural stability. In conclusion, we show that our method can facilitate screening large libraries and predict potent site-specific nnAA-incorporated nanobody binders against crucial disease-targets., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

The extant complex proteins must have evolved from ancient short and simple ancestors. The double-ψ β-barrel (DPBB) is one of the oldest protein folds and conserved in various fundamental enzymes, such as the core domain of RNA polymerase. Here, by reverse engineering a modern DPBB domain, we reconstructed its plausible evolutionary pathway started by "interlacing homodimerization" of a half-size peptide, followed by gene duplication and fusion. Furthermore, by simplifying the amino acid repertoire of the peptide, we successfully created the DPBB fold with only seven amino acid types (Ala, Asp, Glu, Gly, Lys, Arg, and Val), which can be coded by only GNN and ARR (R = A or G) codons in the modern translation system. Thus, the DPBB fold could have been materialized by the early translation system and genetic code.

Modeling the binding pose of an antibody is a prerequisite to structure-based affinity maturation and design. Without knowing a reliable binding pose, the subsequent structural simulation is largely futile. In this study, we have developed a method of machine learning-guided re-ranking of antigen binding poses of nanobodies, the single-domain antibody which has drawn much interest recently in antibody drug development. We performed a large-scale self-docking experiment of nanobody-antigen complexes. By training a decision tree classifier through mapping a feature set consisting of energy, contact and interface property descriptors to a measure of their docking quality of the refined poses, significant improvement in the median ranking of native-like nanobody poses by was achieved eightfold compared with ClusPro and an established deep 3D CNN classifier of native protein-protein interaction. We further interpreted our model by identifying features that showed relatively important contributions to the prediction performance. This study demonstrated a useful method in improving our current ability in pose prediction of nanobodies.

Many viruses that cause serious diseases in humans and animals, including the betacoronaviruses (beta-CoVs), such as SARS-CoV, MERS-CoV, and the recently identified SARS-CoV-2, have natural reservoirs in bats. Because these viruses rely entirely on the host cellular machinery for survival, their evolution is likely to be guided by the link between the codon usage of the virus and that of its host. As a result, specific cellular microenvironments of the diverse hosts and/or host tissues imprint peculiar molecular signatures in virus genomes. Our study is aimed at deciphering some of these signatures. Using a variety of genetic methods we demonstrated that trends in codon usage across chiroptera-hosted CoVs are collaboratively driven by geographically different host-species and temporal-spatial distribution. We not only found that chiroptera-hosted CoVs are the ancestors of SARS-CoV-2, but we also revealed that SARS-CoV-2 has the codon usage characteristics similar to those seen in CoVs infecting the Rhinolophus sp. Surprisingly, the envelope gene of beta-CoVs infecting Rhinolophus sp., including SARS-CoV-2, had extremely high CpG levels, which appears to be an evolutionarily conserved trait. The dissection of the furin cleavage site of various CoVs infecting hosts revealed host-specific preferences for arginine codons; however, arginine is encoded by a wider variety of synonymous codons in the murine CoV (MHV-A59) furin cleavage site. Our findings also highlight the latent diversity of CoVs in mammals that has yet to be fully explored.

Intrinsically disordered regions/proteins (IDRs) are abundant across all the domains of life, where they perform important regulatory roles and supplement the biological functions of structured proteins/regions (SRs). Despite the multifunctionality features of IDRs, several interrogations on the evolution of viral genomic regions encoding IDRs in diverse viral proteins remain unreciprocated. To fill this gap, we benchmarked the findings of two most widely used and reliable intrinsic disorder prediction algorithms (IUPred2A and ESpritz) to a dataset of 6108 reference viral proteomes to unravel the multifaceted evolutionary forces that shape the codon usage in the viral genomic regions encoding for IDRs and SRs. We found persuasive evidence that the natural selection predominantly governs the evolution of codon usage in regions encoding IDRs by most of the viruses. In addition, we confirm not only that codon usage in regions encoding IDRs is less optimized for the protein synthesis machinery (transfer RNAs pool) of their host than for those encoding SRs, but also that the selective constraints imposed by codon bias sustain this reduced optimization in IDRs. Our analysis also establishes that IDRs in viruses are likely to tolerate more translational errors than SRs. All these findings hold true, irrespective of the disorder prediction algorithms used to classify IDRs. In conclusion, our study offers a novel perspective on the evolution of viral IDRs and the evolutionary adaptability to multiple taxonomically divergent hosts., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Background and Objective: Coronavirus disease 2019 is a novel disease caused by the severe acute respiratory syndrome coronavirus (SARS-CoV)-2 virus. It was first detected in December 2019 and has since been declared a pandemic causing millions of deaths worldwide. Therefore, there is an urgent need to develop effective therapeutics against coronavirus disease 2019. A critical step in the crosstalk between the virus and the host cell is the binding of the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein to the peptidase domain of the angiotensin-converting enzyme 2 (ACE2) receptor present on the surface of host cells., Methods: An in silico approach was employed to design a 13-amino acid peptide inhibitor (13AApi) against the RBD of the SARS-CoV-2 spike protein. Its binding specificity for RBD was confirmed by molecular docking using pyDockWEB, ClusPro 2.0, and HDOCK web servers. The stability of 13AApi and the SARS-CoV-2 spike protein complex was determined by molecular dynamics simulation using the GROMACS program while the physicochemical and ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of 13AApi were determined using the ExPASy tool and pkCSM server. Finally, in vitro validation of the inhibitory activity of 13AApi against the spike protein was performed by an enzyme-linked immunosorbent assay., Results: In silico analyses indicated that the 13AApi could bind to the RBD of the SARS-CoV-2 spike protein at the ACE2 binding site with high affinity. In vitro experiments validated the in silico findings, showing that 13AApi could significantly block the RBD of the SARS-CoV-2 spike protein., Conclusions: Blockage of binding of the SARS-CoV-2 spike protein with ACE2 in the presence of the 13AApi may prevent virus entry into host cells. Therefore, the 13AApi can be utilized as a promising therapeutic agent to combat coronavirus disease 2019., (© 2021. The Author(s).)

The complex and multifactorial nature of neuropsychiatric diseases demands multi-target drugs that can intervene with various sub-pathologies underlying disease progression. Targeting the impairments in cholinergic and glutamatergic neurotransmissions with small molecules has been suggested as one of the potential disease-modifying approaches for Alzheimer's disease (AD). Tacrine, a potent inhibitor of acetylcholinesterase (AChE) is the first FDA approved drug for the treatment of AD. Tacrine is also a low affinity antagonist of N-methyl-D-aspartate receptor (NMDAR). However, tacrine was withdrawn from its clinical use later due to its hepatotoxicity. With an aim to develop novel high affinity multi-target directed ligands (MTDLs) against AChE and NMDAR, with reduced hepatotoxicity, we performed in silico structure-based modifications on tacrine, chemical synthesis of the derivatives and in vitro validation of their activities. Nineteen such derivatives showed inhibition with IC 50 values in the range of 18.53 ± 2.09 - 184.09 ± 19.23 nM against AChE and 0.27 ± 0.05 - 38.84 ± 9.64 μM against NMDAR. Some of the selected compounds also protected rat primary cortical neurons from glutamate induced excitotoxicity. Two of the tacrine derived MTDLs, 201 and 208 exhibited in vivo efficacy in rats by protecting against behavioral impairment induced by administration of the excitotoxic agent, monosodium glutamate. Additionally, several of these synthesized compounds also exhibited promising inhibitory activitiy against butyrylcholinesterase. MTDL-201 was also devoid of hepatotoxicity in vivo . Given the therapeutic potential of MTDLs in disease-modifying therapy, our studies revealed several promising MTDLs among which 201 appears to be a potential candidate for immediate preclinical evaluations., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. C.R., E.K.R., E.J.V., S.A., C.S. and R.V.O. are inventors of patent application containing data presented in this manuscript., (© 2021 The Authors.)

Acetylcholinesterase (AChE) inhibitors are the most effective drugs for Alzheimer's disease treatment. However, considering the potential and failure rates of AChE inhibitors, chemical scaffolds targeting cholinesterase specifically are still very limited. Herein, we report a new class of AChE inhibitors identified by employing a virtual screening approach that combines shape similarity with molecular docking calculations. Virtual screening followed by the evaluation of AChE inhibitory activity allowed us to identify 1,2,4-triazolylthioethanones as a novel class of AChE inhibitors. Thirteen compounds with 1,2,4-triazolylthiothanone core and IC 50 values in the range of 0.15±0.07 to 3.32±0.92 μM have been reported here. Our findings shed light into a class of AChE inhibitors that could be useful starting point for the development of novel therapeutics to tackle Alzheimer's disease., (© 2021 Wiley-VCH GmbH.)

Functionalizing C-H bond poses one of the most significant challenges for chemists providing them with very few substrate-specific synthetic routes. Despite being incredibly plastic in their enzymatic ability, they are confined with deficient enzymatic action and limited explicitness of the substrates. In this study, we have endeavored to characterize novel cytochrome P450 from Bacillus aryabhattai (CYP-BA), a homolog of CYP P450-BM3, by taking interdisciplinary approaches. We conducted structure and sequence comparison to understand the conservation pattern for active site residues, conserved fold, evolutionary relationships among others. Molecular dynamics simulations were performed to understand the dynamic nature and interaction with the substrates. CYP-BA was successfully cloned, purified, and characterized. The enzyme's stability toward various physicochemical parameters was evaluated by UV-vis spectroscopy and Circular Dichroism (CD) spectroscopy. Various saturated fatty acids being the natural cytochrome P450 substrates were evaluated as catalytic efficiency of substrate oxidation by CYP-BA. The binding affinity of these natural substrates was monitored against CYP-BA by isothermal titration calorimetry (ITC). The catalytic performance of CYP-BA was satisfactory enough to proceed to the next step, that is, engineering to expand the substrate range to include polycyclic aromatic hydrocarbons (PAH). This is the first evidence of cloning, purifying and characterizing a novel homolog of CYP-BM3 to enable a better understanding of this novel biocatalyst and to provide a platform toward expanding its catalytic process through enzyme engineering., (Copyright © 2021. Published by Elsevier Inc.)

Missense mutations of human choline acetyltransferase (CHAT) are mainly associated with congenital myasthenic syndrome (CMS). To date, several pathogenic mutations have been reported, but due to the rarity and genetic complexity of CMS and difficult genotype-phenotype correlations, the CHAT mutations, and their consequences are underexplored. In this study, we systematically sift through the available genetic data in search of previously unreported pathogenic mutations and use a dynamic in silico model to provide structural explanations for the pathogenicity of the reported deleterious and undetermined variants. Through rigorous multiparameter analyses, we conclude that mutations can affect CHAT through a variety of different mechanisms: by disrupting the secondary structure, by perturbing the P-loop through long-range allosteric interactions, by disrupting the domain connecting loop, and by affecting the phosphorylation process. This study provides the first dynamic look at how mutations affect the structure and catalytic activity in CHAT and highlights the need for further genomic research to better understand the pathology of CHAT., (© 2021 Wiley Periodicals LLC.)

Amyloid precursor protein (APP), upon proteolytic degradation, forms aggregates of amyloid β (Aβ) and plaques in the brain, which are pathological hallmarks of Alzheimer's disease (AD). Cathepsin B is a cysteine protease enzyme that catalyzes the proteolytic degradation of APP in the brain. Thus, cathepsin B inhibition is a crucial therapeutic aspect for the discovery of new anti-Alzheimer's drugs. In this study, we have employed mixed-feature ligand-based virtual screening (LBVS) by integrating pharmacophore mapping, docking, and molecular dynamics to detect small, potent molecules that act as cathepsin B inhibitors. The LBVS model was generated by using hydrophobic (HY), hydrogen bond acceptor (HBA), and hydrogen bond donor (HBD) features, using a dataset of 24 known cathepsin B inhibitors of both natural and synthetic origins. A validated eight-feature pharmacophore hypothesis (Hypo III) was utilized to screen the Maybridge chemical database. The docking score, MM-PBSA, and MM-GBSA methodology was applied to prioritize the lead compounds as virtual screening hits. These compounds share a common amide scaffold, and showed important interactions with Gln23, Cys29, His110, His111, Glu122, His199, and Trp221. The identified inhibitors were further evaluated for cathepsin-B-inhibitory activity. Our study suggests that pyridine, acetamide, and benzohydrazide compounds could be used as a starting point for the development of novel therapeutics.

The dedicator of cytokinesis (DOCK) family of guanine nucleotide exchange factors (GEFs) promotes cell motility, phagocytosis, and cancer metastasis through activation of Rho guanosine triphosphatases. Engulfment and cell motility (ELMO) proteins are binding partners of DOCK and regulate Rac activation. Here, we report the cryo-electron microscopy structure of the active ELMO1-DOCK5 complex bound to Rac1 at 3.8-Å resolution. The C-terminal region of ELMO1, including the pleckstrin homology (PH) domain, aids in the binding of the catalytic DOCK homology region 2 (DHR-2) domain of DOCK5 to Rac1 in its nucleotide-free state. A complex α-helical scaffold between ELMO1 and DOCK5 stabilizes the binding of Rac1. Mutagenesis studies revealed that the PH domain of ELMO1 enhances the GEF activity of DOCK5 through specific interactions with Rac1. The structure provides insights into how ELMO modulates the biochemical activity of DOCK and how Rac selectivity is achieved by ELMO., (Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).)

In the present study, we report a human-inherited, impaired, adaptive immunity disorder, which predominantly manifested as a B cell differentiation defect, caused by a heterozygous IKZF3 missense variant, resulting in a glycine-to-arginine replacement within the DNA-binding domain of the encoded AIOLOS protein. Using mice that bear the corresponding variant and recapitulate the B and T cell phenotypes, we show that the mutant AIOLOS homodimers and AIOLOS-IKAROS heterodimers did not bind the canonical AIOLOS-IKAROS DNA sequence. In addition, homodimers and heterodimers containing one mutant AIOLOS bound to genomic regions lacking both canonical motifs. However, the removal of the dimerization capacity from mutant AIOLOS restored B cell development. Hence, the adaptive immunity defect is caused by the AIOLOS variant hijacking IKAROS function. Heterodimeric interference is a new mechanism of autosomal dominance that causes inborn errors of immunity by impairing protein function via the mutation of its heterodimeric partner.

In structure-based virtual screening (SBVS), a binding site on a protein structure is used to search for ligands with favorable nonbonded interactions. Because it is computationally difficult, docking is time-consuming and any docking user will eventually encounter a chemical library that is too big to dock. This problem might arise because there is not enough computing power or because preparing and storing so many three-dimensional (3D) ligands requires too much space. In this study, however, we show that quality regressors can be trained to predict docking scores from molecular fingerprints. Although typical docking has a screening rate of less than one ligand per second on one CPU core, our regressors can predict about 5800 docking scores per second. This approach allows us to focus docking on the portion of a database that is predicted to have docking scores below a user-chosen threshold. Herein, usage examples are shown, where only 25% of a ligand database is docked, without any significant virtual screening performance loss. We call this method "lean-docking". To validate lean-docking, a massive docking campaign using several state-of-the-art docking software packages was undertaken on an unbiased data set, with only wet-lab tested active and inactive molecules. Although regressors allow the screening of a larger chemical space, even at a constant docking power, it is also clear that significant progress in the virtual screening power of docking scores is desirable.

Much of our understanding of proteins and proteomes comes from the traditional protein structure-function paradigm. However, in the last 2 decades, both computational and experimental studies have provided evidence that a large fraction of functional proteomes across different domains of life consists of intrinsically disordered proteins, thus triggering a quest to unravel and decipher protein intrinsic disorder. Unlike structured/ordered proteins, intrinsically disordered proteins/regions (IDPs/IDRs) do not possess a well-defined structure under physiological conditions and exist as highly dynamic conformational ensembles. In spite of this peculiarity, these proteins have crucial roles in cell signaling and regulation. To date, studies on the abundance and function of IDPs/IDRs in viruses are rather limited. To fill this gap, we carried out an extensive and thorough bioinformatics analysis of 283 000 proteins from 6108 reference viral proteomes. We analyzed protein intrinsic disorder from multiple perspectives, such as abundance of IDPs/IDRs across diverse virus types, their functional annotations, and subcellular localization in taxonomically divergent hosts. We show that the content of IDPs/IDRs in viral proteomes varies broadly as a function of virus genome types and taxonomically divergent hosts. We have combined the two most commonly used and accurate IDP predictors' results with charge-hydropathy (CH) versus cumulative distribution function (CDF) plots to categorize the viral proteins according to their IDR content and physicochemical properties. Mapping of gene ontology on the disorder content of viral proteins reveals that IDPs are primarily involved in key virus-host interactions and host antiviral immune response downregulation, which are reinforced by the post-translational modifications tied to disorder-enriched viral proteins. The present study offers detailed insights into the prevalence of the intrinsic disorder in viral proteomes and provides appealing targets for the design of novel therapeutics.

This study evaluated the inhibitory potential of various beta-lactamase inhibitors such as mechanism-based inhibitors (MBIs), carbapenems, monobactam, and non-beta-lactam inhibitors against Bla1, a class-A beta-lactamase encoded by Bacillus anthracis. The binding potential of different inhibitors was estimated using competitive kinetic assay, isothermal titration calorimetry, and Biolayer interferometry. We observed that tazobactam has better inhibition among other MBIs with a characteristics inhibition dissociation constant of 0.51 ± 0.13 μM. Avibactam was also identified as good inhibitor with an inhibition efficiency of 0.6 ± 0.04 μM. All the MBIs (K D  = 1.90E-04 M, 2.05E-05 M, 3.55E-04 M for clavulanate, sulbactam and tazobactam) showed significantly better binding potential than carbapenems (K D  = 1.02E-03 M, 2.74E-03 M, 1.24E-03 M for ertapenem, imipenem and biapenem respectively). Molecular dynamics simulations were carried out using Bla1-inhibitor complexes to understand the dynamics and stability. The minimum inhibitory concentration (MIC) was carried out by taking various substrates and inhibitors, and later it was followed by cell viability assay. Together, our study helps develop a proper understanding of Bla1 beta-lactamase and its interaction with inhibitory molecules. This study would facilitate comprehending the catalytic divergence of beta-lactamases and the newly emergent resistant strains, focusing on the new generation of therapeutics being less prone to antimicrobial resistance., Competing Interests: Declaration of competing interest Authors agree to the terms andcondition provided., (Copyright © 2021. Published by Elsevier B.V.)

Leukemia inhibitory factor (LIF), and its receptor (LIFR), are commonly over-expressed in many solid cancers and recent studies have implicated LIF/LIFR axis as a promising clinical target for cancer therapy. LIF/LIFR activate oncogenic signaling pathways including JAK/STAT3 as immediate effectors and MAPK, AKT, mTOR further downstream. LIF/LIFR signaling plays a key role in tumor growth, progression, metastasis, stemness and therapy resistance. Many solid cancers show overexpression of LIF and autocrine stimulation of the LIF/LIFR axis; these are associated with a poorer relapse-free survival. LIF/LIFR signaling also plays a role in modulating multiple immune cell types present in tumor micro environment (TME). Recently, two targeted agents that target LIF (humanized anti-LIF antibody, MSC-1) and LIFR inhibitor (EC359) were under development. Both agents showed effectivity in preclinical models and clinical trials using MSC-1 antibody are in progress. This article reviews the significance of LIF/LIFR pathways and inhibitors that disrupt this process for the treatment of cancer., (© 2021 Chongqing Medical University. Production and hosting by Elsevier B.V.)

Alzheimer's disease (AD) is an obstinate and progressive neurodegenerative disorder, mainly characterized by cognitive decline. Increasing number of AD patients and the lack of promising treatment strategies demands novel therapeutic agents to combat various disease pathologies in AD. Recent progresses in understanding molecular mechanisms in AD helped researchers to streamline the various therapeutic approaches. Inhibiting acetylcholinesterase (AChE) activity has emerged as one of the potential treatment strategies. The present study discusses the identification of two potent AChE inhibitors (ZINC11709541 and ZINC11996936) from ZINC database through conventional in silico approaches and their in vitro validations. These inhibitors have strong preferences towards AChE than butyrylcholinesterase (BChE) and didn't evoke any significant reduction in the cell viability of HEK-293 cells and primary cortical neurons. Furthermore, promising neuroprotective properties has also been displayed against glutamate induced excitotoxicity in primary cortical neurons. The present study proposes two potential drug lead compounds for the treatment of AD, that can be used for further studies and preclinical evaluation., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Nematode chitinases play crucial roles in various processes of the nematode lifecycle, including hatching, molting, and reproduction. Small-molecule inhibitors of nematode chitinases have shown promise for controlling nematode pests. However, the lack of structural information makes it a challenge to develop nematicides targeting nematode chitinases. Here, we report the first crystal structure of a representative nematode chitinase, that of Ce Cht1 from the model nematode Caenorhabditis elegans , to a 1.7 Å resolution. Ce Cht1 is a highly conserved chitinase among nematodes, and structural comparison with other chitinases revealed that Ce Cht1 has a classical TIM-barrel fold with some subtle structural differences in the substrate-binding cleft. Benefiting from the obtained crystal structure, we identified a series of novel inhibitors by hierarchical virtual screening. Analysis of the structure-activity relationships of these compounds provided insight into their interactions with the enzyme active site, which may inform future work in improving the potencies of their inhibitory activities. This work gives an insight into the structural features of nematode chitinases and provides a solid basis for the development of inhibitors.

Interaction of SARS-CoV-2 spike glycoprotein with the ACE2 cell receptor is very crucial for virus attachment to human cells. Selected mutations in SARS-CoV-2 S-protein are reported to strengthen its binding affinity to mammalian ACE2. The N501T mutation in SARS-CoV-2-CTD furnishes better support to hotspot 353 in comparison with SARS-CoV and shows higher affinity for receptor binding. Recombination analysis exhibited higher recombination events in SARS-CoV-2 strains, irrespective of their geographical origin or hosts. Investigation further supports a common origin among SARS-CoV-2 and its predecessors, SARS-CoV and bat-SARS-like-CoV. The recombination events suggest a constant exchange of genetic material among the co-infecting viruses in possible reservoirs and human hosts before SARS-CoV-2 emerged. Furthermore, a comprehensive analysis of codon usage bias (CUB) in SARS-CoV-2 revealed significant CUB among the S-genes of different beta-coronaviruses governed majorly by natural selection and mutation pressure. Various indices of codon usage of S-genes helped in quantifying its adaptability in other animal hosts. These findings might help in identifying potential experimental animal models for investigating pathogenicity for drugs and vaccine development experiments., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Symmetric proteins are currently of interest as they allow creation of larger assemblies and facilitate the incorporation of metal ions in the larger complexes. Recently this was demonstrated by the biomineralization of the cadmium-chloride nanocrystal via the Pizza designer protein. However, the mechanism behind this formation remained unclear. Here, we set out to investigate the mechanism driving the formation of this nanocrystal via truncation, mutation, and circular permutations. In addition, the interaction of other biologically relevant metal ions with these symmetric proteins to form larger symmetric complexes was also studied. The formation of the initial nanocrystal is shown to originate from steric strain, where His 58 induces a different rotameric conformation on His 73, thereby distorting an otherwise perfect planar ring of alternating cadmium and chlorine ions, resulting in the smallest nanocrystal. Similar highly symmetric complexes were also observed for the other biological relevant metal ions. However, the flexibility of the coordinating histidine residues allows each metal ion to adopt its preferred geometry leading to either monomeric or dimeric β-propeller units, where the metal ions are located at the interface between both propeller units. These results demonstrate that symmetric proteins are not only interesting to generate larger assemblies, but are also the perfect scaffold to create more complex metal based assemblies. Such metal protein assemblies may then find applications in bionanotechnology or biocatalysis., (© 2021 Wiley Periodicals LLC.)

Alzheimer's disease (AD), a common chronic neurodegenerative disease, has become a major public health concern. Despite years of research, therapeutics for AD are limited. Overexpression of secretory glutaminyl cyclase (sQC) in AD brain leads to the formation of a highly neurotoxic pyroglutamate variant of amyloid beta, pGlu-Aβ, which acts as a potential seed for the aggregation of full length Aβ. Preventing the formation of pGlu-Aβ through inhibition of sQC has become an attractive disease-modifying therapy in AD. In this current study, through a pharmacophore assisted high throughput virtual screening, we report a novel sQC inhibitor (Cpd-41) with a piperidine-4-carboxamide moiety (IC 50  = 34 μM). Systematic molecular docking, MD simulations and X-ray crystallographic analysis provided atomistic details of the binding of Cpd-41 in the active site of sQC. The unique mode of binding and moderate toxicity of Cpd-41 make this molecule an attractive candidate for designing high affinity sQC inhibitors., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Nuclear factor-κB (NF-κB) is an important transcription factor involved in various biological functions, including tumorigenesis. Hence, NF-κB has attracted attention as a target factor for cancer treatment, leading to the development of several inhibitors. However, existing NF-κB inhibitors do not discriminate between its subunits, namely, RelA, RelB, cRel, p50, and p52. Conventional methods used to evaluate interactions between transcription factors and DNA, such as electrophoretic mobility shift assay and luciferase assays, are unsuitable for high-throughput screening (HTS) and cannot distinguish NF-κB subunits. We developed a HTS method named DNA strand exchange fluorescence resonance energy transfer (DSE-FRET). This assay is suitable for HTS and can discriminate a NF-κB subunit. Using DSE-FRET, we searched for RelA-specific inhibitors and verified RelA inhibition for 32,955 compounds. The compound A55 (2-(3-carbamoyl-6-hydroxy-4-methyl-2-oxopyridin-1(2H)-yl) acetic acid) selectively inhibited RelA-DNA binding. We propose that A55 is a seed compound for RelA-specific inhibition and could be used in clinical applications.

Impaired enzymatic activity in D-amino acid oxidase (DAAO) caused by missense mutations has been shown to trigger amyotrophic lateral sclerosis (ALS) through an abnormal accumulation of D-serine in the spinal cord. While loss of enzymatic functions of certain ALS-causing DAAO variants have been studied before, a detailed understanding of structure-dynamics-function relationship of the rare DAAO variants has not been investigated hitherto. To address this, we carried out a comprehensive study of all the reported rare DAAO variants. By employing a spectrum of bioinformatics analyses along with extensive structural dynamics simulations, we show that certain rare variants disrupted key interactions with the active site and decreased the conformational flexibility of active site loop comprising residues 216-228, which is essential for substrate binding and product release. Moreover, these variants lost crucial interactions with the cofactor flavin-adenine-dinucleotide, resulting in weaker binding affinity. A detailed inspection revealed that these variants exhibited such characteristics due to the abrogation of specific salt bridges. Taken together, our study provides a gateway into the structural-dynamic features of the rare DAAO variants and highlights the importance of informatics-based integrated analyses in the screening and prioritization of variants a priori to the clinical-functional characterization.