Biology subjects

Sanyal, D.

Publications and source records attributed to Sanyal, D..

7 recordsLinked to original sources

bioRxiv2026

Co-targeting Metabolic Neighbours Constraints Bacterial Adaptive Evolution

Antibiotic resistance often arises through genetic changes that reduce drug susceptibility, with mutation representing one of the primary mechanisms. Here, we report a dual targeting strategy that restricts these escape routes by simultaneously inhibiting two metabolic neighbours in folate biosynthesis pathway. To establish a general framework for limiting adaptive escape in bacteria, we screened the folate pathway to identify enzymes with shared conserved structural features. This analysis identified dihydroneopterin aldolase (folB) and dihydroneopterin triphosphate 2'-epimerase (folX) as optimal dual targets due to their shared pocket architecture and their roles early in the folate pathway. We then screened a large chemical space of FDA-approved small molecules to identify candidates predicted to bind both folB and folX, followed by experimental validation. We identified Arbutin showing the strongest growth inhibition in E. coli and emerging as the potent dual-target inhibitor, validated by metabolic rescue assays that confirmed direct inhibition of both folB and folX. Experimental evolution further revealed that populations exposed to Arbutin exhibit constrained adaptive trajectories and minimal increases in tolerated drug concentration, consistent with the evolutionary bottleneck imposed by dual-enzyme inhibition. Together, these results establish a framework for developing evolution-resistant antibacterials by targeting structurally convergent enzymes within metabolic pathways.

biophysics↗

bioRxiv2026

Computational predictions and evolutionary analysis of LrK10 kinase-related putative PSTOL1 gene homeologs in wheat and orthologs of its wild relatives.

Phosphorus Starvation Tolerance 1 in rice (OsPSTOL1, known as Phosphorus uptake 1, Pup1) is a receptor-like cytoplasmic protein kinase that confers tolerance to phosphorus deficiency. The OsPSTOL1 gene possesses a Ser/Thr kinase and shows high amino-acid sequence similarity with the leaf rust receptor-like kinase (OsLrK10). We hypothesize that the putative wheat TaPSTOL1 and TaLrK10 have a common ancestral origin and that putative TaPSTOL1 diverged recently acquiring new structural modifications and biological functions in the process. In this study, we identified all putative TaPSTOL1 homeologs and examine the evolutionary relationship between TaPSTOL1 and TaLrK10 in Triticum species. Our results indicate that the putative TaPSTOL1 diverged recently without possessing the amino-terminal domain, which is a typical characteristic of TaLrK10. We observed numerous conversions tracts between these two genes and the substitution pattern of randomly selected amino acids indicates that dynamic selection pressures acted on both genes. The putative TaPSTOL1 shows high nucleotide diversity compared to TaLrK10 within Triticum species. Further, a multiple-sequence analysis reveals that the third exon of TaLrK10 appears to have been duplicated and diverged as a putative single-exon based TaPSTOL1 in bread wheat. Overall, our comparative analysis indicates that both TaPSTOL1 and TaLrK10 appears to have diverged from a common ancestor, acquiring distinct structural organizations and biological functions.

genomics↗

bioRxiv2026

Adaptive Landscapes of Plasmodium Falciparum Dihydrofolate Reductase Reveal Pathways to Antifolate Resistance

Antifolate resistance in Plasmodium falciparum dihydrofolate reductase (pfDHFR) remains a major challenge for malaria control. To understand how this enzyme maintains function under antifolate selection, we developed PfPATH, a computational framework that integrates mutational fitness measurements, evolutionary interactions, and structural information to map adaptive trajectories. PfPATH adaptive walks reveal that evolution is constrained to a narrow ridge in sequence space defined by a small subset of residues. Most resistance mutations are individually deleterious and become viable only when supported by stabilizing changes, restricting adaptation to a few high-resistance pathways. Structure network analyses show that these mutations do not disrupt the global enzyme architecture but instead reorganize internal communication to preserve catalytic function. Consistent with this, molecular dynamics and free-energy analyses indicate that resistant variants remain stable while sampling a broader ensemble of low-energy conformational substates. Together, these results reveal a narrow and predictable route to antifolate escape.

biophysics↗

bioRxiv2024

Navigating the Fitness Landscapes of Plasmodium falciparum Dihydrofolate Reductase: Evolutionary Insights into Antifolate Resistance

The rapid emergence of drug resistance in malaria parasites poses a significant challenge to the efficacy of antifolate treatments. Traditional drug development approaches, which often rely on empirical screening with limited mechanistic insights, tend to overlook the complex evolutionary mechanisms that enable Plasmodium falciparum to evade drug inhibition while preserving enzyme functionality. In this study, we employed computational techniques to investigate the mutational landscape of dihydrofolate reductase (DHFR), focusing on regions essential for enzyme stability and resistance. Our analysis uncovered conserved residues essential for stability, mutation hotspots that enhance adaptability under drug pressure and co-evolving clusters revealing critical functional interdependencies. Through integrated approaches including mutational scanning, epistatic interaction modeling, and fitness trajectory mapping, we elucidated distinct evolutionary pathways that drive resistance. We were able to track the adaptive paths taken by wild-type residues upon mutation, revealing the steps required to reach high-fitness peaks within the rugged fitness landscape. These findings provide valuable insights into the molecular mechanisms of antifolate resistance. We suggest that future drug design should target co-evolving networks and conserved regions to support the development of next-generation therapies to overcome resistance.

biophysics↗

bioRxiv2024

Mapping DHPS Evolvability: Identification of Novel Evolutionarily Critical Sub-Structure through Evolutionary and Structural Analyses of DHPS

Protein evolution shapes pathogen adaptation-landscape, particularly in developing drug resistance. The rapid evolution of target proteins under antibiotic pressure leads to escape mutations leading to the problem of antibiotic resistance. A deep understanding of the evolutionary dynamics of antibiotic target proteins presents a plausible intervention strategy for disrupting the evolutionary trajectory of resistance. Mutations in Dihydropteroate synthase (DHPS), an essential folate pathway protein and a key target for sulfonamide antibiotics, result in reduced antibiotic binding, leading to resistance. Deploying an array of statistical analyses on the DHPS sequence-space and integrating those with deep mutational analysis and structure-based network-topology models we identified critical DHPS-subsequences. Our analysis of the frustration landscape of DHPS predicts how conformational and mutational changes shift the energy distributions within the DHPS substructures. Combining dimensionality reduction and optimality analysis we identified a substructure critical to DHPS evolvability, and computed its druggablity. Our integrated evolution and structure-informed framework identified a DHPS-substructure with significant evolutionary and structural impact. Targeting this region could constrain DHPS evolvability and disrupt the resistome, presenting a new avenue for antibiotic development and contributing to the broader effort to address the problem of antibiotic resistance.

biophysics↗

bioRxiv2021

IMMUND: an Early Stage Diagnostic and Therapeutic Frame for Neurodegenerative Diseases and Multiple Sclerosis based on Immunological Markers

For neurodegenerative diseases, the impact of immunological markers is one of the modern research areas. It has been observed that neuroinflammation increases the cellular precipitation of some of the key proteins associated with neurodegenerative diseases. Therefore, the possibility of functional loss can be enhanced due to neuroinflammation which leads to the initiation of any related diseases. In this regard, autoantibodies, which are known for their autophagy nature, can be considered as key elements for early diagnostic as well as early therapeutics. In this article, we have proposed a comprehensive framework to unveil the diagnostic as well as the therapeutic possibility of the autoantibodies which are largely associated with Mild-Moderate Alzheimers Disease, Early-Stage Parkinsons Disease, and Multiple Sclerosis. Here, we have introduced a new concept of average p-value where multiple p-values of an autoantibody in a singular disease have been considered as a multi-occurrence of that sample in cellular systems. Also, multiple proteins from a single protein family under a differentially expressed range have been prioritized. As a result, the top ten autoantibodies have been selected for further study and also considered as diagnostic markers. Interestingly, most of the selected autoantibodies are either cytokines or immunoglobulins. Subsequently, we have performed an evolutionary sequence-structure space study to identify the druggable structural facet for the selected autoantibodies. To make the therapeutic perspective more robust, we have introduced the concept of protein moonlighting. Hence, it provides more robustness in therapeutic identification. Finally, two autoantibodies i.e., Q9NYV4 and P01602 are identified as a novel marker.

neuroscience↗

bioRxiv2020

An exploration of the SARS-CoV-2 spike receptor binding domain (RBD), a complex palette of evolutionary and structural features

SARS-CoV-2 spike protein (S) is associated with the entry of virus inside the host cell by recruiting its loop dominant receptor binding domain (RBD) and interacting with the host ACE2 receptor. Our study deploying a two-tier approach encompassing evolutionary and structural analysis provides a comprehensive picture of the RBD, which could be of potential use for better understanding the RBD and address its druggability issues. Resorting to an ensemble of sequence space exploratory tools including co-evolutionary analysis and deep mutational scans we provide a quantitative insight into the evolutionarily constrained subspace of the RBD sequence space. Guided by structure network analysis and Monte Carlo simulation we highlight regions inside the RBD, which are critical for providing structural integrity and conformational flexibility of the binding cleft. We further deployed fuzzy C-means clustering by plugging the evolutionary and structural features of discrete structure blocks of RBD to understand which structure blocks share maximum overlap based on their evolutionary and structural features. Deploying this multi-tier interlinked approach, which essentially distilled the evolutionary and structural features of RBD, we highlight discrete region, which could be a potential druggable pocket thereby destabilizing the structure and addressing evolutionary routes.

biophysics↗