Biology subjects

Sanyal, T.

Publications and source records attributed to Sanyal, T..

7 recordsLinked to original sources

bioRxiv2025

Mapping the evolution of computationally designed protein binders

Computational protein design enables the generation of binders that target specific epitopes on proteins. However, current approaches often require substantial screening from which hits require further affinity maturation. Methods for experimentally improving designed proteins and exploring their sequence-affinity landscapes could therefore streamline the development of high-affinity binders and inform future design strategies. Here, we use OrthoRep, a system for continuous hypermutation in vivo, to drive the evolution of computationally designed mini protein binders ("minibinders") that target a mammalian receptor. Despite their small sizes (59-72 amino acids), we successfully affinity matured multiple minibinders through strong selection for improved binding and also sampled new regions of minibinder fitness landscapes through extensive neutral drift. One evolved minibinder variant was used to construct a combinatorially complete sequence-affinity map for its six affinity increasing mutations, which revealed nearly full additivity in their contributions to binding. Another minibinder was subjected to both deep mutational scanning and extensive evolution under weak selection, resulting in an evolutionarily diverged collection of binder sequences that revealed non-additive relationships among mutations. Our results highlight that the affinity of computationally designed binders can be rapidly increased through evolution and provide a scalable approach for the evolutionary exploration and subsequent mapping of sequence-affinity landscapes. We suggest that this work will complement protein binder design both as a reliable experimental optimization process and as a vehicle for generating new training data.

synthetic biology↗

bioRxiv2023

Unique Binding and Stabilization Mechanisms Employed By and Engineered Into Nanobodies.

Nanobodies are single domain antibody variants that bind an antigen with the precision and affinity of a conventional antibody at only a fraction of their size. In solving the crystal structures of our nanobody-GFP complexes and compared with other available structures, we uncover mechanism that enable nanobodies to function so efficiently and effectively as single-domain antibodies. We show that unlike conventional antibodies, a nanobody repertoire maximizes sampling of their antigen surface by binding a single antigen in at least three different orientations which can be predicted by their paratope composition. We also structurally reengineering these nanobodies to improve their antigen affinity, their stability, or both - results which also revealed the strong connection between nanobody stability and affinity. We achieved this by either directly modifying the paratope, or by altering a particular region within their third framework, which is a highly conserved area that we determined plays a role in controlling nanobody stability. Our study suggests that these unique characteristics of nanobodies allow them to interact with antigens as effectively as conventional antibodies, despite their smaller size. This understanding provides methods to facilitate optimizing, humanizing and functionalizing nanobodies, thus paving the way for their utilization in diverse areas such as research, diagnostics, and therapeutic development. Significance StatementNanobodies are a unique type of antibody fragment found in select animals, containing all its antigen binding ability reduced to a single [~]15 kDa protein. There is increasing development of nanobodies for research, diagnostics, and therapeutics, yet how nanobodies function so effectively as single domain antigen binders with the precision and affinity of conventional antibodies is unclear. In this study, we present key observations to help answer this question, where one key finding is the strong relationship between nanobody stability and antigen affinity aided by the identification of a highly conserved region in nanobodies essential for maintaining nanobody stability. This region may have been retained in nanobodies in lieu of stabilizing mechanisms induced by dimerization as seen in conventional antibodies.

biochemistry↗

bioRxiv2023

Nanobody repertoire generated against the spike protein of ancestral SARS-CoV-2 remains efficacious against the rapidly evolving virus

To date, all major modes of monoclonal antibody therapy targeting SARS-CoV-2 have lost significant efficacy against the latest circulating variants. As SARS-CoV-2 omicron sublineages account for over 90% of COVID-19 infections, evasion of immune responses generated by vaccination or exposure to previous variants poses a significant challenge. A compelling new therapeutic strategy against SARS-CoV-2 is that of single domain antibodies, termed nanobodies, which address certain limitations of monoclonal antibodies. Here we demonstrate that our high-affinity nanobody repertoire, generated against wild-type SARS-CoV-2 spike protein (Mast, Fridy et al. 2021), remains effective against variants of concern, including omicron BA.4/BA.5; a subset is predicted to counter resistance in emerging XBB and BQ.1.1 sublineages. Furthermore, we reveal the synergistic potential of nanobody cocktails in neutralizing emerging variants. Our study highlights the power of nanobody technology as a versatile therapeutic and diagnostic tool to combat rapidly evolving infectious diseases such as SARS-CoV-2.

biochemistry↗

bioRxiv2021

Nanobody Repertoires for Exposing Vulnerabilities of SARS-CoV-2

Despite the great promise of vaccines, the COVID-19 pandemic is ongoing and future serious outbreaks are highly likely, so that multi-pronged containment strategies will be required for many years. Nanobodies are the smallest naturally occurring single domain antigen binding proteins identified to date, possessing numerous properties advantageous to their production and use. We present a large repertoire of high affinity nanobodies against SARS-CoV-2 Spike protein with excellent kinetic and viral neutralization properties, which can be strongly enhanced with oligomerization. This repertoire samples the epitope landscape of the Spike ectodomain inside and outside the receptor binding domain, recognizing a multitude of distinct epitopes and revealing multiple neutralization targets of pseudoviruses and authentic SARS-CoV-2, including in primary human airway epithelial cells. Combinatorial nanobody mixtures show highly synergistic activities, and are resistant to mutational escape and emerging viral variants of concern. These nanobodies establish an exceptional resource for superior COVID-19 prophylactics and therapeutics.

biochemistry↗

bioRxiv2021

Bayesian metamodeling of complex biological systems across varying representations

Comprehensive modeling of a whole cell requires an integration of vast amounts of information on various aspects of the cell and its parts. To divide-and-conquer this task, we introduce Bayesian metamodeling, a general approach to modeling complex systems by integrating a collection of heterogeneous input models. Each input model can in principle be based on any type of data and can describe a different aspect of the modeled system using any mathematical representation, scale, and level of granularity. These input models are (i) converted to a standardized statistical representation relying on Probabilistic Graphical Models, (ii) coupled by modeling their mutual relations with the physical world, and (iii) finally harmonized with respect to each other. To illustrate Bayesian metamodeling, we provide a proof-of-principle metamodel of glucose-stimulated insulin secretion by human pancreatic {beta}-cells. The input models include a coarse-grained spatiotemporal simulation of insulin vesicle trafficking, docking, and exocytosis; a molecular network model of glucose-stimulated insulin secretion signaling; a network model of insulin metabolism; a structural model of glucagon-like peptide-1 receptor activation; a linear model of a pancreatic cell population; and ordinary differential equations for systemic postprandial insulin response. Metamodeling benefits from decentralized computing, while often producing a more accurate, precise, and complete model that contextualizes input models as well as resolves conflicting information. We anticipate Bayesian metamodeling will facilitate collaborative science by providing a framework for sharing expertise, resources, data, and models, as exemplified by the Pancreatic {beta}-Cell Consortium. Significance StatementCells are the basic units of life, yet their architecture and function remain to be fully characterized. This work describes Bayesian metamodeling, a modeling approach that divides-and-conquers a large problem of modeling numerous aspects of the cell into computing a number of smaller models of different types, followed by assembling these models into a complete map of the cell. Metamodeling enables a facile collaboration of multiple research groups and communities, thus maximizing the sharing of expertise, resources, data, and models. A proof-of-principle is provided by a model of glucose-stimulated insulin secretion produced by the Pancreatic {beta}-Cell Consortium.

cell biology↗

bioRxiv2021

Integrative analysis reveals unique features of the Smc5/6 complex

Structural maintenance of chromosomes (SMC) complexes are critical chromatin modulators. In eukaryotes, the cohesin and condensin SMC complexes organize chromatin, while the Smc5/6 complex directly regulates DNA replication and repair. The molecular basis for Smc5/6s distinct functions is currently poorly understood. Here, we report an integrative structural study of the budding yeast Smc5/6 complex using electron microscopy, cross-linking mass spectrometry, and computational modeling. We show that while the complex shares a similar overall organization with other SMC complexes, it possesses several unique features. In contrast to the reported folded-arm structures of cohesin and condensin, our data suggest that Smc5 and Smc6 arm regions do not fold back on themselves. Instead, these long filamentous regions interact with subunits uniquely acquired by the Smc5/6 complex, namely the Nse2 SUMO ligase and the Nse5-Nse6 subcomplex. Further, we show that Nse5-Nse6 subcomplex adopts a novel structure with an extensive dimerization interface and multiple domains contacting other subunits of the Smc5/6 complex. We also provide evidence that the Nse5-Nse6 module uses its SUMO-binding motifs to contribute to Nse2-mediated sumoylation. Collectively, our integrative multi-scale study identifies distinct structural features of the Smc5/6 complex and functional cooperation amongst its co-evolved unique subunits.

molecular biology↗

bioRxiv2019

Anti-cancer property of Lenzites betulina (L) Fr. on cervical cancer cell lines and its anti-tumor effect on HeLa-implanted mice

In global scenario cervical cancer is increasing. New drugs from natural compounds are in search. Mushrooms are now recognized as miniature pharmaceutical factories producing hundreds of novel constituents. We have taken ethanolic extract Lenzities betulina (LBE) wild mushroom for evaluation of its as anti-cancer property against cervical cancer cell lines e.g. HeLa, CaSki and SiHa and anti tumor activity against HeLa implanted tumor on mice. The extraction was done by dip and stirring method in 90% ethanol for 72 h. For evaluation of anti-cervical cancer, several assays were performed such as MTT assay, cell morphology by phase contrast microscope and F-action polymerization by Laser scanning confocal microscope and nuclear morphology DAPI staining under inverted fluorescence microscope, MMP, ROS, cell cycle, autophagy and stem cell population by flow cytometry and DNA laddering were done. Western blotting was done for protein expression. To evaluate anti-metastatic activity, anti-cologenic assay and wound healing assay were adopted. For chemo-analysis of the LBE, GC-MS was done. The results from Cytotoxicity assay showed that at highest dose of LBE (1000 {micro}g/ml) after 24 h, percentage of cell inhibitions were 85.13 %, 77.13 % and 47.70 % against HeLa, CaSki and SiHa respectively and the calculated IC50 values were 492.52 {+/-} 2.6 {micro}g/ml, 612.22 {+/-} 4.2 {micro}g/ml, and 1210.30 {+/-} 6.4 {micro}g/ml respectively. Depending upon the cytotoxicity screening, HeLa cell line was considered for the further studies. Cell morphology study exhibited that LBE treated HeLa cells became round from normal spindle shape. DAPI staining showed that LBE treated nucleus became condensed and fragmented. DNA fragmentation at 230 and 300 base pair zone from agarose gel assay was observed. LBE induced ROS generation and reduced MMP. It up regulated the expression of apoptotic genes and p53 while down regulated Bcl2, pro-caspase 3 and pro caspase-9 gene. Cell cycle was arrested at G2/M checkpoint. Autophagic induction was exhibited by vacuole formation in treated cells. CSC population of treated cells was reduced and F-actin polymerization was observed in treated cells. In addition, LBE suppressed metastatic nature by inhibition of cell migration and colonization. The inhibition of growth of the tumors in HeLa cell-implanted mice showed that treatment with 50 mg LBE/kg of body weight of mice led to a marked reduction in the volume (93.22 {+/-} 9.2 %) and weight (90.42 {+/-}9.55 %) of the tumors. The GC-MS profile of LBE shows that out of 69 compounds, 9, 12-Octadecadienoic acid (Z, Z) and Ergosta-5, 8, 22-trien-3-ol, (3.beta22E) are in a significantly higher proportion with the percentage peak area 22.13 and 19.72 respectively. Library search for bioactivity showed that these compounds are anti-cancerous and interestingly 4-Hydroxy-6-methoxyaurone binding with P-glycoprotein inhibits the cancer cells to become drug resistant. In conclusion, LBE is very prominent anti-cervical cancer having a lot of anti-cancerous compounds which are probably acting synergistically. This report of anti-cervical cancer property of L. betulina is probably first time in oncology. Its therapeutic use in human model is urgent for new drug development.

cancer biology↗