Biology subjects

Bahar, I.

Publications and source records attributed to Bahar, I..

33 records · Page 2Linked to original sources

bioRxiv2021

Llamanade: an open-source computational pipeline for robust nanobody humanization

Nanobodies (Nbs) have recently emerged as a promising class of antibody fragments for biomedical and therapeutic applications. Despite having marked physicochemical properties, Nbs are derived from camelids and may require "humanization" to improve translational potentials for clinical trials. Here we have systematically analyzed the sequence and structural properties of Nbs based on NGS (next-generation sequencing) databases and high-resolution structures. Our analysis reveals substantial framework diversities and underscores the key differences between Nbs and human Immunoglobulin G (IgG) antibodies. We identified conserved residues that may contribute to enhanced solubility, structural stability, and antigen-binding, providing insights into Nb humanization. Based on big data analysis, we developed "Llamanade, a user-friendly, open-source to facilitate rational humanization of Nbs. Using Nb sequence as input, Llamanade provides information on the sequence features, model structures, and optimizes solutions to humanize Nbs. The full analysis for a given Nb takes less than a minute on a local computer. To demonstrate the robustness of this tool, we applied it to successfully humanize a cohort of structurally diverse and highly potent SARS-CoV-2 neutralizing Nbs. Llamanade is freely available and will be easily accessible on a web server to support the development of a rapidly expanding repertoire of therapeutic Nbs into safe and effective trials. Author SummaryCamelid Nbs are characterized by small size, excellent pharmacological properties and high flexibility in bioengineering for therapeutic development. However, Nbs are "xeno" antibodies, which require "humanization" to improve their translational potential. Currently, there is a lack of systematic investigation of Nbs to rationally guide humanization. No dedicated software has been developed for this purpose. Here, we report the development of Llamanade, an open-source computational pipeline and the first dedicated software to facilitate rational humanization of Nbs. To subjectively evaluate Llamanade, we used it to humanize a cohort of structurally diverse and ultrapotent antiviral Nbs against SARS-CoV-2. Robust humanization by Llamanade significantly improved the humanness level of Nbs to closely resemble fully human IgGs. Importantly, these highly humanized antiviral Nbs remained excellent solubility and comparably high bioactivities to the non-humanized Nb precursors. We envision that Llamanade will help advance Nb research into therapeutic development.

bioinformatics↗

bioRxiv2021

Elastic Network Modeling of Cellular Networks Unveils Sensor and Effector Genes that Control Information Flow

The high-level organization of the cell is embedded in long-range interactions that connect distinct cellular processes. Existing approaches for detecting long-range interactions consist of propagating information from source nodes through cellular networks, but the selection of source nodes is inherently biased by prior knowledge. Here, we sought to derive an unbiased view of long-range interactions by adapting a perturbation-response scanning strategy initially developed for identifying allosteric interactions within proteins. We deployed this strategy onto an elastic network model of the yeast genetic network. The genetic network revealed a superior propensity for long-range interactions relative to simulated networks with similar topology. Long-range interactions were detected systematically throughout the network and found to be enriched in specific biological processes. Furthermore, perturbation-response scanning identified the major sources and receivers of information in the network, named effector and sensor genes, respectively. Effectors formed dense clusters centrally integrated into the network, whereas sensors formed loosely connected antenna-shaped clusters. Long-range interactions between effector and sensor clusters represent the major paths of information in the network. Our results demonstrate that elastic network modeling of cellular networks constitutes a promising strategy to probe the high-level organization of the cell.

systems biology↗

bioRxiv2021

ClustENMD: Efficient sampling of biomolecular conformational space at atomic resolution

SummaryEfficient sampling of conformational space is essential for elucidating functional/allosteric mechanisms of proteins and generating ensembles of conformers for docking applications. However, unbiased sampling is still a challenge especially for highly flexible and/or large systems. To address this challenge, we describe the new implementation of our computationally efficient algorithm ClustENMD that is integrated with ProDy and OpenMM softwares. This hybrid method performs iterative cycles of conformer generation using elastic network model (ENM) for deformations along global modes, followed by clustering and short molecular dynamics (MD) simulations. ProDy framework enables full automation and analysis of generated conformers and visualization of their distributions in the essential subspace. Availability and implementationClustENMD is open-source and freely available under MIT License from https://github.com/prody/ProDy. Contactburak.kaynak@pitt.edu or doruker@pitt.edu Supplementary informationSupplementary materials comprise method details, figures, table and tutorial.

biophysics↗

bioRxiv2021

Psychomotor impairments and therapeutic implications revealed by a mutation linked with Infantile Parkinsonism-Dystonia

Parkinson disease (PD) is a progressive, neurodegenerative disorder affecting over 6.1 million people worldwide. Although the cause of PD remains unclear, studies of highly-penetrant mutations identified in early-onset familial parkinsonism have contributed to our understanding of the molecular mechanisms underlying disease pathology. Dopamine (DA) transporter (DAT) deficiency syndrome (DTDS) is a distinct type of infantile parkinsonism-dystonia that shares key clinical features with PD, including motor deficits (progressive bradykinesia, tremor, hypomimia) and altered DA neurotransmission. Here, we define structural, functional, and behavioral consequences of a Cys substitution at R445 in human DAT (hDAT R445C), identified in a patient with DTDS. We found that this R445 substitution disrupts a phylogenetically conserved intracellular (IC) network of interactions that compromise the hDAT IC gate. This is demonstrated by both Rosetta molecular modeling and fine-grained simulations using hDAT R445C, as well as EPR analysis and X-ray crystallography of the bacterial homolog leucine transporter. Notably, the disruption of this IC network of interactions supported a channel-like intermediate of hDAT and compromised hDAT function. We demonstrate that Drosophila melanogaster expressing hDAT R445C show impaired hDAT activity, which is associated with DA dysfunction in isolated brains and with abnormal behaviors monitored at high-speed time resolution. We show that hDAT R445C Drosophila exhibit motor deficits, lack of motor coordination (i.e. flight coordination) and phenotypic heterogeneity in these behaviors that is typically associated with DTDS and PD. These behaviors are linked with altered dopaminergic signaling stemming from loss of DA neurons and decreased DA availability. We rescued flight coordination through enhanced DAT surface expression via the lysosomal inhibitor chloroquine. Together, these studies shed light on how a DTDS-linked DAT mutation underlies DA dysfunction and, more broadly, the clinical phenotypes shared by DTDS and PD.

neuroscience↗

bioRxiv2021

Impact of South African 501.V2 Variant on SARS-CoV-2 Spike Infectivity and Neutralization: A Structure-based Computational Assessment

MotivationThe SARS-CoV-2 variants emerging from South Africa (501.V2) and the UK (B.1.1.7) necessitate rapid assessment of the effects of the corresponding amino acid substitutions in the spike (S) receptor-binding domain (RBD) of the variants on the interactions with the human ACE2 receptor and monoclonal antibodies (mAbs) reported earlier to neutralize the spike. ResultsMolecular modeling and simulations reveal that N501Y, shared by both variants, increases ACE2 binding affinity, and may impact the collective dynamics of the ACE2-RBD complex, occupying a central hinge site that modulates the overall dynamics of the complex. In contrast, the substitutions K417N and E484K in the South African variant 501.V2 would reduce the ACE2-binding affinity by abolishing two interfacial salt bridges that facilitate RBD binding to ACE2, K417(S)-D30(ACE2) and E484 (S)-K31(ACE2). These two mutations may thus be more than compensating the attractive effect induced by N501Y, overall resulting in an ACE2-binding affinity comparable to that of the wildtype RBD. Further analysis of the impact of these mutations on the interactions with mAbs targeting the spike indicate that the substitutions K417N and E484K may also abolish the salt bridges between the spike and selected mAbs, such as REGN10933, BD23, H11_H4, and C105, thus reducing the binding affinity and effectiveness of these mAbs. Contactbahar@pitt.edu Supplementary informationSupplementary data are available at Bioinformatics online.

molecular biology↗

bioRxiv2020

A monoclonal antibody against staphylococcal enterotoxin B superantigen inhibits SARS-CoV-2 entry in vitro

We recently discovered a superantigen-like motif, similar to Staphylococcal enterotoxin B (SEB), near the S1/S2 cleavage site of SARS-CoV-2 Spike protein, which might explain the multisystem-inflammatory syndrome (MIS-C) observed in children and cytokine storm in severe COVID-19 patients. We show here that an anti-SEB monoclonal antibody (mAb), 6D3, can bind this viral motif, and in particular its PRRA insert, to inhibit infection by blocking the access of host cell proteases, TMPRSS2 or furin, to the cleavage site. The high affinity of 6D3 for the furin-cleavage site originates from a poly-acidic segment at its heavy chain CDR2, a feature shared with SARS-CoV-2-neutralizing mAb 4A8. The affinity of 6D3 and 4A8 for this site points to their potential utility as therapeutics for treating COVID-19, MIS-C, or common cold caused by human coronaviruses (HCoVs) that possess a furin-like cleavage site.

immunology↗

bioRxiv2020

Identification of a unique TCR repertoire, consistent with a superantigen selection process in Children with Multi-system Inflammatory Syndrome

Multisystem Inflammatory Syndrome in Children (MIS-C), a hyperinflammatory syndrome associated with SARS-CoV-2 infection, shares many clinical features with toxic shock syndrome, which is triggered by bacterial superantigens. The superantigen specificity for binding different V{beta}-chains results in V{beta}-skewing, whereby T cells with specific V{beta}-chains and diverse antigen specificity are overrepresented in the TCR repertoire. Here, we characterized the TCR repertoire of MIS-C patients and found a profound expansion of TCR Beta Variable gene (TRBV)11-2. Furthermore, TRBV11-2 skewing was remarkably correlated with MIS-C severity and serum cytokine levels. Further analysis of TRBJ gene usage and CDR3 length distribution of MIS-C expanding TRBV11-2 clones revealed extensive junctional diversity, indicating a superantigen-mediated selection process for TRBV expansion. In silico modelling indicates that polyacidic residues in TCR V{beta}11-2 engage in strong interactions with the superantigen-like motif of SARS-CoV-2 spike glycoprotein. Overall, our data indicate that the immune response in MIS-C is consistent with superantigenic activation. HighlightsO_LIMultisystem Inflammatory Disease in Children (MIS-C) patients exhibit T cell receptor (TCR) repertoire skewing, with expansion of T cell Receptor Beta Variable gene (TRBV)11-2 C_LIO_LITRBV11-2 skewing correlates with MIS-C severity and cytokine storm C_LIO_LIJ gene/CDR3 diversity in MIS-C patients is compatible with a superantigen selection process C_LIO_LIIn silico modelling indicates TCR V{beta}11-2 engages in CDR3-independent interactions with the polybasic insert P681RRAR in the SAg-like motif of SARS-CoV-2 spike C_LI

immunology↗

bioRxiv2020

Decoding of persistent multiscale structures in complex biological networks

In any omics study, the scale of analysis can dramatically affect the outcome. For instance, when clustering single-cell transcriptomes, is the analysis tuned to discover broad or specific cell types? Likewise, protein communities revealed from protein networks can vary widely in sizes depending on the method. Here we use the concept of "persistent homology", drawn from mathematical topology, to identify robust structures in data at all scales simultaneously. Application to mouse single-cell transcriptomes significantly expands the catalog of identified cell types, while analysis of SARS-COV-2 protein interactions suggests hijacking of WNT. The method, HiDeF, is available via Python and Cytoscape.

systems biology↗

bioRxiv2020

An insertion unique to SARS-CoV-2 exhibits superantigenic character strengthened by recent mutations

Multisystem Inflammatory Syndrome in Children (MIS-C) associated with Coronavirus Disease 2019 (COVID-19) is a newly recognized condition in which children with recent SARS-CoV-2 infection present with a constellation of symptoms including hypotension, multiorgan involvement, and elevated inflammatory markers. These symptoms and the associated laboratory values strongly resemble toxic shock syndrome, an escalation of the cytotoxic adaptive immune response triggered upon the binding of pathogenic superantigens to MHCII molecules and T cell receptors (TCRs). Here, we used structure-based computational models to demonstrate that the SARS-CoV-2 spike (S) exhibits a high-affinity motif for binding TCR, interacting closely with both the - and {beta}-chains variable domains complementarity-determining regions. The binding epitope on S harbors a sequence motif unique to SARS-CoV-2 (not present in any other SARS coronavirus), which is highly similar in both sequence and structure to bacterial superantigens. Further examination revealed that this interaction between the virus and human T cells is strengthened in the context of a recently reported rare mutation (D839Y/N/E) from a European strain of SARS-CoV-2. Furthermore, the interfacial region includes selected residues from a motif shared between the SARS viruses from the 2003 and 2019 pandemics, which has intracellular adhesion molecule (ICAM)-like character. These data suggest that the SARS-CoV-2 S may act as a superantigen to drive the development of MIS-C as well as cytokine storm in adult COVID-19 patients, with important implications for the development of therapeutic approaches. SignificanceAlthough children have been largely spared from severe COVID-19 disease, a rare hyperinflammatory syndrome has been described in Europe and the East Coast of the United States, termed Multisystem Inflammatory Syndrome in Children (MISC). The symptoms and diagnostic lab values of MIS-C resemble those of toxic shock, typically caused by pathogenic superantigens stimulating excessive activation of the adaptive immune system. We show that SARS-CoV-2 spike has a sequence and structure motif highly similar to those of bacterial superantigens, and may directly bind to the T cell receptors. This sequence motif, not present in other coronaviruses, may explain the unique potential for SARS-CoV-2 to cause both MIS-C and the cytokine storm observed in adult COVID-19 patients.

immunology↗

bioRxiv2020

Mechanisms of Action of Autophagy Modulators Dissected by Quantitative Systems Pharmacology Analysis

Autophagy plays an essential role in cell survival/death and functioning. Modulation of autophagy has been recognized as a promising therapeutic strategy against diseases/disorders associated with uncontrolled growth or accumulation of biomolecular aggregates, organelles or cells including those caused by cancer, aging, neurodegeneration, and liver diseases such as 1-antitrypsin deficiency. Numerous pharmacological agents that enhance or suppress autophagy have been discovered. However, their molecular mechanisms of action are far from clear. Here we collected a set of 225 autophagy modulators and carried out a comprehensive quantitative systems pharmacology (QSP) analysis of their targets using both existing databases and predictions made by our machine learning algorithm. Autophagy modulators include several highly promiscuous drugs (e.g. artenimol and olanzapine acting as activator, fostamatinib as inhibitor, or melatonin as dual-modulator), as well as selected drugs uniquely targeting specific proteins ([~]30% of modulators). They are mediated by three layers of regulation: (i) pathways involving core autophagy-related (ATG) proteins such as mTOR, AKT, and AMPK; (ii) upstream signaling events that regulates the activity of ATG pathways such as calcium-, cAMP-, and MAPK-signaling pathways; and (iii) transcription factors regulating the expression ATG proteins such as TFEB, TFE3, HIF-1, FoxO, and NF-{kappa}B. Our results suggest that PKA serves as a linker bridging between various signal transduction events and autophagy. These new insights contribute to a better assessment of the mechanism of action of autophagy modulators as well as their side effects, development of novel polypharmacological strategies, and identification of drug repurposing opportunities.

systems biology↗

bioRxiv2020

Disulfide bridge formation prevents CaMKII/Calmodulin interaction in Parkinson's disease

There is increasing evidence for disordered Ca2+ signaling in dopamine neurons in Parkinsons disease (PD), and this likely involves altered Ca2+/calmodulin-dependent protein kinase II (CaMKII) function. Previous work suggests that oxidative stress - a major feature in PD pathogenesis - affects regulatory methionine residues that sustain CaMKII activity in a Ca2+/CaM-independent manner. Here, applying computational modeling, we predicted formation of a defined disulfide bridge close to the CaMKII docking site for Ca2+/CaM binding. In vitro and in vivo investigations using PD models revealed formation of a disulfide bridge and loss of the CaMKII-calmodulin interaction. Mutagenesis of the relevant cysteine residues abrogated disulfide bridge formation and recovered the CaMKII-calmodulin interaction. Importantly, dopamine neurons from post-mortem PD brain specimens also lost this regulatory protein-protein interaction, providing relevance in the human disease. This study provides novel insights into oxidative CaMKII-CaM dysfunction, which may contribute to the pathophysiology of PD.

neuroscience↗

bioRxiv2019

Rhapsody: Pathogenicity prediction of human missense variants based on protein sequence, structure and dynamics

The biological effects of human missense variants have been studied experimentally for decades but predicting their effects in clinical molecular diagnostics remains challenging. Available computational tools are usually based on the analysis of sequence conservation and structural properties of the mutant protein. We recently introduced a new machine learning method that demonstrated for the first time the significance of protein dynamics in determining the pathogenicity of missense variants. Here we present a significant extension that integrates coevolutionary data from Pfam database and we also introduce a new interface (Rhapsody) that enables fully automated assessment of pathogenicity. Benchmarked against a dataset of about 20,000 annotated variants, the methodology is shown to outperform well-established and/or advanced prediction tools. We illustrate the utility of our approach by in silico saturation mutagenesis study of human H-Ras. The tool is made available both as a webtool (rhapsody.csb.pitt.edu) and an open source Python package (pip install prody-rhapsody).

bioinformatics↗

bioRxiv2018

Quantitative systems pharmacological analysis of drugs of abuse reveals the pleiotropy of their targets and the effector role of mTORC1

Existing treatments against drug addiction are often ineffective due to the complexity of the networks of protein-drug and protein-protein interactions (PPIs) that mediate the development of drug addiction and related neurobiological disorders. There is an urgent need for understanding the molecular mechanisms that underlie drug addiction toward designing novel preventive or therapeutic strategies. The rapidly accumulating data on addictive drugs and their targets as well as advances in machine learning methods and computing technology now present an opportunity to systematically mine existing data and draw inferences on potential new strategies. To this aim, we carried out a comprehensive analysis of cellular pathways implicated in a diverse set of 50 drugs of abuse using quantitative systems pharmacology methods. The analysis of the drug/ligand-target interactions compiled in DrugBank and STITCH databases revealed 142 known and 48 newly predicted targets, which have been further analyzed to identify the KEGG pathways enriched at different stages of drug addiction cycle, as well as those implicated in cell signaling and regulation events associated with drug abuse. Apart from synaptic neurotransmission pathways detected as a common upstream signaling module that senses the early effects of drugs of abuse, pathways involved in neuroplasticity are distinguished as determinants of neuronal morphological changes. Notably, many signaling pathways converge on important targets such as mTORC1. The latter is proposed to act as a universal effector of the persistent restructuring of neurons in response to continued use of drugs of abuse.

systems biology↗

bioRxiv2017

Quantitative Assessment Of Cell Fate Decision Between Autophagy And Apoptosis

Autophagy and apoptosis regulate cell survival and death, and are implicated in the pathogenesis of many diseases. The same type of stress signals can induce either process, but it is unclear how cells assess cellular damage and make a life or death decision by activating autophagy or apoptosis. A computational model of coupled apoptosis and autophagy is built here to study the systems-level dynamics of the underlying signaling network. The model explains the differential dynamics of autophagy and apoptosis in response to various experimental stress signals. Autophagic response dominates at low-to-moderate stress; whereas the response shifts from autophagy (graded activation) to apoptosis (switch-like activation) with increasing intensity of stress. The model reveals that this dynamic cell fate decision is conferred by a core regulatory network involving cytoplasmic Ca2+ as a rheostat that fine-tunes autophagic and apoptotic responses. A G-protein signaling-mediated feedback loop maintains cytoplasmic Ca2+ level, which in turn governs autophagic response through an AMP-activated protein kinase (AMPK)-mediated feedforward loop. The model identified Ca2+/calmodulin-dependent kinase kinase {beta} (CaMKK{beta}) as a determinant of the opposite roles of cytoplasmic Ca2+ in autophagy regulation. The results also demonstrated that the model could contribute to the development of pharmacological strategies modulate cell fate decisions.

systems biology↗

bioRxiv2016

Chromosomal dynamics predicted by an elastic network model explains genome-wide accessibility and long-range couplings

Understanding the three-dimensional (3D) architecture of the chromatin and its relation to gene expression and regulation is fundamental to understanding how the genome functions. Advances in Hi-C technology now permit us to have a glimpse into the 3D genome organization and identify topologically associated domains (TADs), but we still lack an understanding of the structural dynamics of chromosomes. The dynamic couplings between regions separated by large genomic distances (> 50 megabases) have yet to be characterized. We adapted a well-established protein-modeling framework, the Gaussian Network Model (GNM), to the task of modeling chromatin dynamics using Hi-C contact data. We show that the GNM can identify structural dynamics at multiple scales: it can quantify the fluctuations in the positions of gene loci, find large genomic compartments and smaller TADs that undergo en-bloc movements, and identify dynamically coupled distal regions along the chromosomes. We show that the predictions of the GNM correlate well with DNase-seq and ATAC-seq measurements on accessibility, the previously identified A and B compartments of chromatin structure, and pairs of interacting loci identified by ChIA-PET. We describe a method to use the GNM to identify novel cross-correlated distal domains (CCDDs) representing regions of long-range dynamic coupling and show that CCDDs are often associated with increased gene coexpression using a large-scale analysis of 212 expression experiments. Together, these results show that GNM provides a mathematically well-founded unified framework for assessing chromatin dynamics and the structural basis of genome-wide observations.

genomics↗