The Ser7 of RNA Pol II-CTD influences the recruitment of Cdc73 for mRNA transcription.

The carboxyl terminal domain of the largest subunit of eukaryotic RNA polymerase II (RNAPII) consists of highly conserved tandem repeats of Tyr1Ser2Pro3Thr4Ser5Pro6Ser7, 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.

Novel peptide inhibitors targeting CD40 and CD40L interaction: A potential for atherosclerosis therapy.

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.

The Saccharomyces cerevisiae SR protein Npl3 interacts with hyperphosphorylated CTD of RNA Polymerase II.

The catalytic subunit of RNA Polymerase II contains a highly conserved carboxy terminal domain (CTD) composed of multiple tandem heptad sequence Tyr1Ser2Pro3Thr4Ser5Pro6Ser7. 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 (Npl3Δ389-414) 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.

Impaired tissue homing by the Ikzf3N159S variant is mediated by interfering with Ikaros function.

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 Ikzf3N159S allele that corresponds to human IKZF3N160S recapitulated immune-deficient phenotypes, such as impaired B cell development and loss of CD23 expression. In this study, we investigated the effect of the Ikzf3N159S variant and found that B1a cell development was impaired in Ikzf3N159S/N159S mice. In addition, CD62L expression was severely decreased in both B and T lymphocytes by the Ikzf3N159S 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 Ikzf3N159S/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 Ikzf3N159S mutation. The homing assay confirmed severely decreased homing abilities to lymph nodes of Ikzf3N159S/N159S B and T lymphocytes but selective enrichment of CD62L expressing Ikzf3N159S/N159S lymphocytes in lymph nodes. This finding suggests that impaired CD62L expression is the major reason for the impaired homing capacity caused by the Ikzf3N159S mutation. Interestingly, an excess amount of Ikaros, but not Aiolos, restored CD62L expression in Ikzf3N159S/N159S B cells. Together with the loss of CD62L expression due to Ikaros deficiency, the AiolosN159S mutant protein likely interferes with Ikaros function through heterodimerization, at least in activating the Sell gene encoding CD62L expression. Thus, our results revealed that AiolosN159S causes some immunodeficient phenotypes via the pathogenesis referred to as the heterodimeric interference as observed for AiolosG158R variant.

Identification of Fungal and Bacterial Denitrification Inhibitors Targeting Copper Nitrite Reductase.

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 N2O. 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 (FoNirK) of the filamentous fungus Fusarium oxysporum. Three series of chemical compounds were identified, out of which compounds belonging to two chemical scaffolds inhibited FoNirK 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 (AxNirK) and in vivo bacterial denitrification revealed a similar inhibitory profile.

Targeting Ras-binding domain of ELMO1 by computational nanobody design.

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.

Pivotal role for S-nitrosylation of DNA methyltransferase 3B in epigenetic regulation of tumorigenesis.

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 (IC50 ≤ 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.

A novel consensus-based computational pipeline for screening of antibody therapeutics for efficacy against SARS-CoV-2 variants of concern including Omicron variant.

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.

Bayesian Molecular Dating Analyses Combined with Mutational Profiling Suggest an Independent Origin and Evolution of SARS-CoV-2 Omicron BA.1 and BA.2 Sub-Lineages.

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.

An integrated protein structure fitness scoring approach for identifying native-like model structures.

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.

Targeting LIF/LIFR signaling in cancer.

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.

Cell-Free Mutant Analysis Combined with Structure Prediction of a Lasso Peptide Biosynthetic Protease B2.

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.

Crystal structure of human acetylcholinesterase in complex with tacrine: Implications for drug discovery.

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.

A novel structure-based approach for identification of vertebrate susceptibility to SARS-CoV-2: Implications for future surveillance programmes.

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.

TIRAP-mediated activation of p38 MAPK in inflammatory signaling.

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 (∆Gbind) 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.

Tumor Derived Extracellular Vesicles Drive T Cell Exhaustion in Tumor Microenvironment through Sphingosine Mediated Signaling and Impacting Immunotherapy Outcomes in Ovarian Cancer.

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.

FPredX: Interpretable models for the prediction of spectral maxima, brightness, and oligomeric states of fluorescent proteins.

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.

ProFitFun: a protein tertiary structure fitness function for quantifying the accuracies of model structures.

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.

In-Silico Design of a Novel Tridecapeptide Targeting Spike Protein of SARS-CoV-2 Variants of Concern.

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.