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Results for “molecular biology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2026

Identification and molecular characterization of a novel TYLCV isolate breaking bred-resistance to threaten tomato cultivar

Tomato yellow leaf curl virus (TYLCV) is a devastating viral pathogen threatening agricultural crops globally. In this study, we identified a novel TYLCV isolate (TYLCV-YN6244), which caused viral epidemic in resistant tomato cultivars at Yuanmo county, Yunnan Province of China. We determined the complete genome of TYLCV-YN6244 and found it encoded six viral proteins characteristic of Geminivirus. We identified its V2 protein as a potent viral suppressor of RNA silencing (VSR), and generated infectious clone of wildtype TYLCV-YN6244, or V2-defective TYLCV-YN6244 (TYLCV-YN6244-{Delta}V2) in which V2 was deleted. Both of infectious clones were capable of systemically infecting tobacco and tomato. However, TYLCV-YN6244 but not TYLCV-YN6244-{Delta}V2 could cause disease symptoms in wildtype tobacco or tomato plants, and viral accumulation was drastically reduced in plants infected with TYLCV-YN6244-{Delta}V2 compared to TYLCV-YN6244 while the efficiency of virus-derived small interfering RNAs (vsiRNAs) biogenesis was conversely increased in plants infected with TYLCV-YN6244-{Delta}V2. Surprisingly, small RNA profiling indicated that 21nt and 22nt rather than 24nt vsiRNAs were predominantly produced in tomato plants infected with either TYLCV-YN6244 or TYLCV-YN6244-{Delta}V2. Furthermore, transcriptome analyses revealed that TYLCV-YN6244 or TYLCV-YN6244-{Delta}V2 infection differentially modulated metabolism and defense-related pathways in tomato, probably underlying distinct viral pathogenicity and disease symptoms induced in plants. Overall, our research not only identified a novel pathogenic TYLCV isolate but also characterized molecular biology and host response in tomato with infectious clones firstly developed, with implications in untangling virus-host interaction for developing novel resistance in crop tomato.

Plant Biology↗

bioRxiv2026

Identifying Novel Estrogenic Mitochondrial Targets in Hypothalamic Proopiomelanocortin Neurons by Chemoproteomics

Loss of estrogens at menopause is linked to impaired brain metabolism and increased risk of Alzheimers disease (AD). However, estrogen replacement therapies are limited due to the deleterious effects of estrogen on peripheral organs and increased risk of vascular dementia. We have developed a non-steroidal estrogenic compound, STX, which does not bind to the classical estrogen receptors and {beta}, but mimics estrogenic signaling in the central nervous system (CNS) without the peripheral reproductive actions. STX is protective against neurodegeneration in stroke and AD models, but its molecular targets are unknown. Here, we identified and validated STX neural targets using chemoproteomic, molecular biological, electrophysiological and metabolic assays of hypothalamic proopiomelanocortin (POMC) neurons. Chemoproteomic profiling identified voltage dependent anion channels (VDAC1-3) as major intracellular binding partners in mHypo43 (POMC) cells. Based on quantitative single-cell PCR, Vdac2 was identified as the dominant isoform in female hypothalamic POMC neurons. Seahorse metabolic flux analyses showed that STX potently increased glycolysis, oxidative respiration and mitochondrial ATP production in mHypo43 cells. Nanomolar concentrations of STX enhanced VDAC2 voltage-dependent gating in reconstituted lipid membranes and shifted the low-conductance states toward anion selectivity, consistent with increased ATP flux. Together, these findings reveal a mechanism for the neuroprotective effects of STX through enhancing mitochondrial bioenergetics and modulating VDAC channel properties, potentially increasing cellular energy stores. Therefore, this work identifies previously unrecognized estrogenic mitochondrial targets and provides a mechanistic basis for the neuroprotective actions of STX relevant to menopause-associated brain vulnerability.

neuroscience↗

bioRxiv2026

Monitoring microscope performance in an imaging facility using OMERO-metrics.

Microscopes are essential tools for discoveries on a scale invisible to the unaided human eye. The development of immuno-fluorescence followed by molecular biology techniques and fluorescent fusion proteins have revolutionised the use of optical microscopy in bioscience. The quality of the data produced is dependent upon the sample, its preparation and the instrument used. However, instruments can degrade over time without easily visible changes to the produced images and, in turn, negatively impacts results. By testing instruments and doing comparisons between results over time and between different instruments, problems can be highlighted and corrective action can be taken. Using small fluorescent beads the point spread function (PSF) of the microscope can be recorded and the image resolution measured. Beads were prepared in a concentration matched to the field of view size and dried onto coverslips and mounted on slides. The beads were then imaged as 3D Z-stacks of sufficient size to fully enclose the PSF of the system. This data was uploaded to OMERO and processed using OMERO-metrics, an OMERO plugin developed for this purpose. This paper summarizes the development of workflows and protocols to enable this process, presents the results obtained and demonstrates the detection of significant instrument issues.

biophysics↗

bioRxiv2026

Barcoded-Plasmid DNA library construction for recording cell lineage trees enabled by a Scalable and modular Biofoundry-based Automated Robotic Pipeline

High-quality plasmid DNA purification at high throughput remains a significant bottleneck in molecular biology and bioengineering. Current methods frequently fail to deliver sufficient yields of pure, transfection-grade DNA required for genetic engineering applications in mammalian cells. Here, we present a Biofoundry-based automated pipeline using the CyBio FeliX robotic liquid handling platform to rapidly purify plasmid DNA with minimal manual intervention. The protocol leverages Solid Phase Reversible Immobilisation (SPRI)-based magnetic bead technology to ensure consistency, scalability, and DNA purity suitable for downstream viral particle production and mammalian cell transfection. The pipeline supports flexible processing of between 8 and 96 samples per run, making it adaptable across a wide range of experimental scales. The protocol is openly available via Earlham Institute GitHub repository, enabling broad adoption across the bioscientific community and contributing to the growing toolkit of reproducible, scalable engineering biology workflows. In this work, we employed an integrated robotic pipeline to process 528 pooled DNA plasmids and built a Lentiviral DNA plasmid library for lineage tracing, validated the library by sequencing, and demonstrated efficacy in downstream mammalian cell transfection experiments.

synthetic biology↗

bioRxiv2026

Long-read sequencing reveals novel mitochondrial genome variants undetected by short-read sequencing in Korean population

While long-read sequencing technologies (e.g., PacBio Revio, ONT) have revolutionized high-quality genome assembly for the human pangenome, mitochondrial genome (mtDNA) analysis still largely relies on short-read and Sanger sequencing. However, short-read sequencing often lacks the resolution required to resolve complex variations due to the unique features of mtDNA, such as high mutation rates and repetitive homopolymeric regions, which frequently lead to alignment artifacts and mapping ambiguities. To address this, we evaluated whether applying long-read sequencing to mtDNA improves analytical quality in empirical data. Through comprehensive bioinformatics analyses, we compared the performance of long-read sequencing against short-read sequencing and microarrays. Our results revealed that long-read sequencing detected the highest number of variants (n = 533), significantly outperforming both short-read sequencing (n = 525) and microarrays (n = 49). Notably, both sequencing methods provided significantly higher resolution in haplogroup assignment compared to microarrays in terms of phylogenetic depth (p < 0.05). Long-read sequencing demonstrated superior detection power, particularly for InDels. We identified two novel non-synonymous variants, including a unique InDel detected exclusively by long-read sequencing. Protein modeling and stability analysis validated that this InDel causes structural instability (RMSD > 2.0 [A],{Delta}{Delta} G = -45.21 kcal/mol). Furthermore, we confirmed that this novel InDel is shared among haplogroup A samples in both the 1000 Genomes Project ONT dataset and the Korean population, highlighting the practical implications of long-read sequencing for molecular biology and population genetics.

genomics↗

bioRxiv2026

Advancing Plant Health in Sub-Saharan Africa: Understanding National Agricultural Research Institutions capacities for Strategic Investment Priorities to Boost Genetic Gains Against Crop Biotic Stress

Plant health research within National Agricultural Research and Extension Systems (NARES) represents a critical yet neglected pillar of agricultural resilience in sub-Saharan Africa (SSA), where crop productivity remains substantially below global averages due to persistent biotic and abiotic stresses. Although plant health units have a strategic mandate to support crop protection, disease surveillance, and varietal improvement, the institutional capacity of these units across NARES in SSA is not defined. Here, we assessed 36 plant health units across 26 SSA countries to determine research capacity, identify operational constraints, and examine their contributions to crop improvement and food security. Our findings reveal the existence of a strong human capital operating under structurally constrained systems. More than 65% of personnel possess postgraduate qualifications, indicating the presence of a highly trained scientific workforce with considerable potential to drive plant health innovation. However, this expertise is undermined by severe infrastructural and institutional limitations that restrict research delivery. Access to essential facilities remains low, whereby only 53% of respondents had access to plant pathology laboratories, 43% had molecular biology platforms, and 37% had glass/screenhouses, while only 30% of respondents maintained phenotyping infrastructure such as sick plots or endemic/hot spot disease sites. These deficiencies undermine plant health research in areas like biotic stress resistance screening, pathogen diagnostics, and diversity. It was noted that plant health units primarily target staple food crops central to regional food systems, including cereals (maize, rice, sorghum, and millets), legumes (groundnut and cowpea), and root and tuber crops (cassava and potato). All these crops are affected by diverse biotic stresses that include fungi, bacteria, viruses, insect pests, and parasitic weeds. Yet research effectiveness to address these challenges is further constrained by unclear or fragmented protocols, poorly equipped laboratories, weak data capture, and management systems. Critical gaps were consistently identified in pathogen isolation and characterization, disease phenotyping, surveillance and mapping, experimental design, and data management. Workforce composition raises additional concerns regarding long-term system sustainability. Women account for only 18% of plant health personnel, while researchers younger than 35 years represent just 10% of the workforce, reflecting weak generational succession and gender inequity. These demographic imbalances constitute an existential threat to institutional continuity and innovation capacity. In summary, closing these gaps will require coordinated investment in infrastructure, technical training, institutional strengthening, and digital modernization. Equally important is the development of inclusive workforce strategies that improve gender representation and strengthen succession pathways. Unlocking the potential of NARES plant health networks is essential for accelerating resilient crop development, strengthening agricultural productivity, and advancing food security across SSA.

pathology↗

bioRxiv2026

Enhancing Recombinant Vector Assembly Efficiency: A Novel Methodological Approach

With the rapid development of modern biotechnology, DNA vectors have become fundamental tools for inserting, transferring, and expressing specific gene sequences in various fields such as gene cloning, gene expression, gene editing, and gene therapy. However, when dealing with complex structured DNA sequences, traditional vector construction methods face challenges with low connection efficiency. This study proposes a new method for constructing recombinant vectors by employing a strategy of high-temperature treatment followed immediately by placement on ice, effectively reducing the complexity of DNA structures and enhancing the efficiency of PCR product-vector connection, thereby improving the construction efficiency of recombinant vectors. This paper describes the technical details of the method, experimental validation, and applications in gene cloning, gene recombination editing, and the preparation of gene therapy drugs, providing a new efficient tool for molecular biology experiments.

biochemistry↗

bioRxiv2026

RheoScale 2.0: Revealing the Hidden Roles of Protein Positions via Substitution Patterns

A central challenge in molecular biology is understanding how amino acid substitutions modulate various features of protein function and stability. To illuminate the complexities of this relationship, high-throughput (HTP) assays are increasingly used to assess site-saturating mutagenesis libraries. A common downstream analysis is to average the set of twenty outcomes at each amino acid position for comparison with structural and evolutionary features. Average values clearly identify positions that tolerate most substitutions (neutral positions) and positions where most substitutions abolish activity (toggle positions). However, average values conceal the existence of rheostat positions, where different amino acid substitutions sample a wide range of outcomes. To quantitatively identify rheostat positions, we previously developed a histogram-based analysis that we here expand by: (i) incorporating new position classes observed in experimental studies of rheostat positions; (ii) formalizing a hierarchy of class assignments; (iii) refining error-based identification of neutral positions; and (iv) statistically assessing the robustness of class assignments to changes in experimental and computational parameters. RheoScale 2.0 is implemented in Excel and newly implemented in Python for facile integration with existing HTP pipelines; all parameters are customizable. Example analyses are shown for three HTP datasets of the SARS-CoV-2 papain-like protease. Results illustrate two aspects that influence interpretation of HTP data: First, position assignments (and substitution outcomes) depend highly on the measured feature. Second, many protein positions play multiple roles in the sequence-structure-function relationship. The recognition of varied position roles will advance understanding of pathogen evolution, protein engineering, and variant interpretation for personalized medicine. SummaryRheoScale 2.0 improves how high-throughput mutational data are interpreted by identifying protein positions where amino acid substitutions act like biological dimmer switches. By enabling more nuanced assignment of position behavior, beyond neutral or deleterious outcomes, this analysis framework advances studies of sequence-structure-function relationships and has broad relevance for understanding protein evolution, engineering proteins with desired properties, and interpreting variants linked to human disease. SOFTWARE AVAILABILITYhttps://github.com/liskinsk/RheoScale-calculator

biochemistry↗

bioRxiv2026

A Sequential Assembly Mechanism for Stable Cdc13 Dimerization on Telomeric DNA

The telomere-binding protein Cdc13 specifically binds to single-stranded telomeric DNA, playing a critical role in telomere protection and length regulation. While extensive biochemical, molecular biological, and genetic studies have shown that Cdc13 can form dimers or oligomers in solution and bind telomeric DNA with high specificity, the dynamic mechanism of its loading onto telomeres is less well characterized. Using two single-molecule methods, single-molecule fluorescence resonance energy transfer (smFRET) and colocalization single-molecule spectroscopy (CoSMoS), we demonstrate that Cdc13 initially loads onto telomeres as a monomer. This is followed by the recruitment of a second monomer, forming a stable Cdc13 dimer on a 12-nucleotide telomeric DNA segment. Although genetic studies suggest that monomeric Cdc13 binding alone is insufficient to maintain telomere length, it underscores the Cdc13 monomers regulatory importance in coordinating telomere synthesis and protection. This monomer-to-dimer transition provides a mechanistic basis for understanding the multi-tasked roles of Cdc13 in telomere replication and protection.

biophysics↗

bioRxiv2026

Understanding malaria transmission in Angola: first detection of Plasmodium malariae in Anopheles spp. and the role of secondary vectors in the Balombo region, Benguela Province

Background: Angola is one of the most affected countries in sub-Saharan Africa and was off-track to meet the WHO Global Technical Strategy targeting of a 75% reduction in malaria incidence and mortality by 2025. Recent studies highlighted major knowledge gaps regarding malaria vectors in Angola, particularly secondary vectors. A malaria control project initiated in 2007 in Balombo (Benguela Province, central Angola) has monitored malaria dynamics for 18 years, revealing increased Plasmodium prevalence and more frequent detection of non-falciparum species, mainly Plasmodium malariae (in co-infection with P. falciparum) in villagers of the Balombo region. This study aimed to characterize Anopheles populations in this region by assessing species composition, behavioural patterns, and infection rate. And to a less extent, to compare the performance of two indoor and outdoor mosquito trapping methods. Methods: Surveys were conducted during the rainy (December 2023 and 2024) and dry seasons (July 2024) in villages around the town of Balombo. Adult mosquitoes were collected indoors and outdoors using CDC Light Traps and BG-Pro traps in randomly selected houses. Female Anopheles were morphologically and molecularly identified. Primary and secondary vectors were screened for Plasmodium spp. using qPCR-high resolution melting, and positive samples were sequenced. Results: A strong seasonal effect was observed in Anopheles populations, with higher abundance, diversity, and Plasmodium- infection rates during the rainy season. An. funestus remained the main vector, but Plasmodium spp. was also detected in five other species: An. arabiensis, An. gambiae, An. marshallii, An. rufipes, and An. maculipalpis. This is the first report of P. malariae in Anopheles mosquitoes and the first mention of the role of secondary vectors in malaria transmission in Benguela Province. Conclusion: This study provides a thorough and updated inventory of Anopheles species in the Balombo region. Molecular biology confirmed the presence of P. falciparum and P. malariae in several species of Anopheles underscoring the existence of a complex transmission system in villages of Balombo. Infected exophagic and exophilic Anopheles species, exhibiting opportunistic behaviour, likely contribute, as secondary vectors, to the increase of Plasmodiumspp. transmission in the study sites. Therefore, confirming the need to implement complementary interventions targeting outdoor malaria transmission.

microbiology↗

bioRxiv2026

PyKappa: Rule-based modeling in Python

Rule-based languages have proven effective for modeling systems of interacting structured entities as typically encountered in chemistry and molecular biology. We present PyKappa, a rule-based modeling package written in Python whose interpreted nature enables interactive simulation and analysis, including by agentic AI. The package seeks to broaden the base of developers by utilizing a widely known programming language and serves as an easy-to-deploy teaching tool. Using PyKappa, we conduct a case study of phase separation.

systems biology↗

bioRxiv2026

Make it so: Rapid and affordable plasmid sequencing on ONT platforms with PICARD-seq

Plasmid construction underpins molecular biology and synthetic biology, yet validation is often limited to the inserted fragment rather than the whole plasmid, and around a third of laboratory-made plasmids carry sequence errors that can affect function. Sanger sequencing scales poorly across whole plasmids, while short-read approaches cannot resolve the repeated DNA parts, such as promoters, that are common in synthetic constructs. We present PICARD-seq, a rapid nanopore-based protocol that uses off-the-shelf Tn5 rapid barcoding reagents and a MinION to sequence pools of whole plasmids in under a day, and we systematically benchmark the computational pipelines available for analysing the resulting data. Using a curated set of 25 plasmids of known sequence spanning 3.0-20.6 kbp, including various dilution series and repetitive multi-part constructs, we ran five independent replicates of each pipeline. The ONT EPI2ME Clone Validation workflow was fast (13-18 min) but stochastic, varying between replicates for both plasmids assembled and what sequence was returned; Canu outperformed the default Flye assembler, and reducing the minimum coverage parameter from 60x to 20x substantially improved assembly of large, repetitive, and dilute samples. The ensemble assembler Autocycler was slower (81-111 min) but gave the highest and most consistent rate of recovering the expected sequence. Complementary read mapping with minimap2 distinguished genuine sequence differences from assembly artefacts. Applying PICARD-seq to problematic plasmids revealed backbone concatemers, a misincorporated promoter part, and a mixed population of rearranged molecules in a repetitive construct. PICARD-seq makes routine whole-plasmid validation practical and affordable for individual laboratories.

bioinformatics↗

bioRxiv2026

Downstream mRNA Secondary Structure, Not Codon Elongation Supply, Coordinates Co-Translational Protein Folding Across the Human Ribosomal Exit Tunnel

How ribosomes pace translation to assist nascent protein folding remains an open question in molecular biology. While synonymous codon selection is widely hypothesized to regulate elongation rates to facilitate domain organization, distinguishing genuine translational kinetics from baseline amino acid preferences has proven technically difficult. Here, we analyze a non-redundant cohort of 1,270 high-resolution human crystal structures (410,151 residues) mapped to their native mRNA transcripts. When we mathematically isolate synonymous codon choices from amino acid identity using orthogonal linear projection, standard codon-supply metrics i.e. the tRNA Adaptation Index (tAI) and the Codon Adaptation Index (CAI), show negligible independent spatial coupling with downstream protein structure. Their uncorrected correlations predominantly reflect local amino acid chemistry rather than physical translation pacing. In contrast, downstream mRNA secondary structure stability (minimum free energy, MFE) displays a subtle but consistent correlation that survives amino acid control. Across 100,000 whole-proteome permutations per pair, this MFE signal centers at an offset of +15 to +16 codons across multiple independent physical properties, including residue packing density (r = -0.0699, Z = -23.64, p < 10-5), crystallographic rigidity (B-factor, r = +0.0614, Z = +13.74, p < 10-5), and solvent burial (SASA, r = +0.0492, Z = +18.98, p < 10-5). This +15 codon offset corresponds directly to the physical dimensions of the eukaryotic 80S ribosome: the path from the peptidyl transferase center to the internal uL4/uL22 constriction neck (~10 amino acids) plus the downstream mRNA helicase entry channel (~5 codons). While the overall effect size is modest, accounting for approximately 0.49% of local packing variance, its spatial specificity and consistency across independent structural metrics suggest that downstream mRNA stability acts as a localized mechanical brake during early chain compaction.

bioinformatics↗

bioRxiv2026

PRIME: A modular plasmid-based platform for continuous in vivo evolution across bacteria

Directed evolution enables the engineering of proteins with novel or improved functions, yet existing approaches often require extensive manual intervention and are difficult to sustain over long evolutionary trajectories. Here we introduce PRIME (Protein-primed Replication for In vivo Mutagenesis and Evolution), a plasmid-based orthogonal DNA replication system for continuous directed evolution in Escherichia coli. PRIME harnesses protein-primed DNA replication to establish an autonomous replicon that operates independently of the host genome. Coupling this system to an error-prone DNA polymerase enables targeted diversification of constructs encoded on the orthogonal plasmid while preserving genomic integrity. Using only standard laboratory equipment, we demonstrate the evolution of a construct expressing msfGFP with an 11.8-fold increase in fluorescence. The platform is fully compatible with standard molecular biology workflows and requires no specialised instrumentation. We further demonstrate its portability across bacterial hosts by establishing PRIME in Pseudomonas putida. PRIME thus provides a broadly accessible framework for continuous in vivo evolution, with wide-ranging applications in protein engineering and synthetic biology.

synthetic biology↗

bioRxiv2026

Autofocusing molecular simulations for integrative structural biology of broad conformational ensembles

Integrative structural biology seeks molecular descriptions consistent with complementary experimental measurements. A particular challenge arises for molecules whose broad conformational ensembles resist description by a few representative structures, such as natively unfolded proteins and fluid-phase biomembrane lipids. Although molecular simulations can generate such ensembles, their simultaneous agreement with a large number of experimental constraints is commonly prevented by model inaccuracies. Here we introduce autofocusing as an approach that integrates experimental information by automated finetuning of the physical model generating the ensemble. We demonstrate it for a fluid bilayer of the phospholipid POPC, for which no existing force field has simultaneously reproduced the complete set of 82 NMR C-H bond order parameters. Autofocusing brings all the 82 within experimental uncertainty while preserving agreement with independent small-angle X-ray scattering measurements and retaining or improving agreement with untargeted NMR relaxation rates and effective correlation times, thus supporting its description of membrane structure and dynamics beyond the calibration targets. The resulting simulations challenge a long-standing two-state interpretation of phosphatidylcholine headgroup structure, instead supporting a broad conformational ensemble poorly represented by crystal-derived conformers. These results establish autofocusing as a practical approach to constructing experimentally grounded conformational ensembles while retaining the computational tractability of classical molecular dynamics.

biophysics↗

bioRxiv2026

Rapid, reversible RNA/DNA precipitation using rare earth ion coordination

Efficient recovery and removal of nucleic acids remain major challenges in molecular biology, diagnostics, and viral-vector manufacturing. Conventional precipitation methods often require organic solvents, low temperatures, and extended centrifugation, while nuclease-based contaminant removal can be incomplete and/or is incompatible with downstream workflows. Here, we evaluate NADA, a trivalent rare earth-based reagent, for rapid, solvent-free precipitation of RNA and DNA, and ALGO-mediated recovery of the full range of properties of unmodified RNA. Using hepatitis B virus pre-genomic RNA, lambda bacteriophage DNA, and the HBV nucleocapsid as model systems, we show that NADA rapidly sequesters both ssRNA and dsDNA from solution, reducing Midori Green nucleic acid fluorescence and UV absorption to baseline levels. The NADA complex prevents HBV core protein binding to the HBV pgRNA, and therefore triggering of nucleocapsid formation, even when added simultaneously with core protein, suggesting that lanthanide ion coordination, out-competes the cognate Cp for viral RNA-binding interactions. Recovery with ALGO restores pgRNA integrity and functionality, enabling subsequent assembly of the expected T=4/T=3 nucleocapsids. In contrast, pre-assembled nucleocapsids resist NADA-ALGO treatment, demonstrating coat protein capsid-mediated protection of encapsidated pgRNA. Similar outcomes for lambda dsDNA establish NADA/ALGO as a rapid, reversible, and selective alternative platform for nucleic acid precipitation, with potential applications in viral particle purification, contaminant removal, and RNA handling workflows.

biochemistry↗

bioRxiv2025

Scaling in Biological Systems: A Molecular-Ensemble Duality

We have observed in muscle the statistical mechanics of irreversible chemical thermodynamics, revealing the solution to multiple seemingly unrelated paradoxes in science. Analogous to Boltzmanns H theorem, we observe that chemical reaction energy landscapes (ensemble entropic wells) irreversibly evolve over time, pulling reversible chemical reactions forward in time. Loschmidts paradox assumes that reversible molecular reactions scale up to irreversible changes in an ensemble, and many mathematical constructs have been created to satisfy this assumption (Boltzmanns H-function, chemical activities, the kinetics theory of gases, molecular mechanisms of biological function, etc.). However, using a simple statistical argument, here we show that the irreversible time evolutions of molecular and ensemble states are described by two different non-scalable entropies, creating a molecular-ensemble duality in any system on any scale. This inverts common understandings of mechanistic agency and the arrow of time and disproves all molecular mechanisms of irreversible ensemble processes. Significance StatemenThis statistical analysis inverts common understandings of mechanistic agency, entropy, and the arrow of time; it solves several paradoxes in physics; and it disproves molecular mechanisms of irreversible processes.

biophysics↗

bioRxiv2019

Intrinsic Disorder and Degeneracy in Molecular Scale Organization of Biological Membrane

The scale-rich spatiotemporal organization in biological membrane dictates the \"molecular encounter\" and in turn the larger scale biological processes such as molecular transport, trafficking and cellular signalling. In this work, we explore the degeneracy in lateral organization in lipid bilayer systems from the perspective of energy landscape theory. Our analysis on molecular trajectories show that bilayers with lipids having in-vivo characteristics have a highly frustrated energy landscape as opposed to a funnel-like energy landscape in in-vitro systems. Lattice evolution simulations, with Hamiltonian trained from atomistic trajectories using lipids topology and non-affine displacement measures to characterize the extent of order-disorder in the bilayer, show that the inherent frustration in in-vivo like systems renders them with the ability to access a wide range of nanoscale patterns with equivalent energy penalty. We posit that this structural degeneracy could provide for a larger repository to functionally important molecular organization in in-vivo settings.

biophysics↗