Machine learning unravels inherent structural patterns in Escherichia coli Hi-C matrices and predicts chromosome dynamics.

High dimensional nature of the chromosomal conformation contact map ('Hi-C Map'), even for microscopically small bacterial cell, poses challenges for extracting meaningful information related to its complex organization. Here we first demonstrate that an artificial deep neural network-based machine-learnt (ML) low-dimensional representation of a recently reported Hi-C interaction map of archetypal bacteria Escherichia coli can decode crucial underlying structural pattern. The ML-derived representation of Hi-C map can automatically detect a set of spatially distinct domains across E. coli genome, sharing reminiscences of six putative macro-domains previously posited via recombination assay. Subsequently, a ML-generated model assimilates the intricate relationship between large array of Hi-C-derived chromosomal contact probabilities and respective diffusive dynamics of each individual chromosomal gene and identifies an optimal number of functionally important chromosomal contact-pairs that are majorly responsible for heterogenous, coordinate-dependent sub-diffusive motions of chromosomal loci. Finally, the ML models, trained on wild-type E. coli show-cased its predictive capabilities on mutant bacterial strains, shedding light on the structural and dynamic nuances of ΔMatP30MM and ΔMukBEF22MM chromosomes. Overall our results illuminate the power of ML techniques in unraveling the complex relationship between structure and dynamics of bacterial chromosomal loci, promising meaningful connections between ML-derived insights and biological phenomena.

Emergence of Catalytic Triad by Short Peptide Based Nanofibrillar Assemblies.

Through millions of years of the evolutionary journey, contemporary enzymes observed in extant metabolic pathways have evolved to become specialized, in contrast to their ancestors, which displayed promiscuous activities with wider substrate specificities. However, there remain critical gaps in our understanding of how these early enzymes could show such catalytic versatility despite lacking the complex three-dimensional folds of the existing modern-day enzymes. Herein, we report the emergence of a promiscuous catalytic triad by short amyloid peptide based nanofibers that access paracrystalline folds of ß-sheets to expose three residues (lysine, imidazole, and tyrosine) toward solvent. The ordered folded nanostructures could simultaneously catalyze two metabolically relevant chemical transformations via C-O and C-C bond manipulations, displaying both hydrolase and retro-aldolase-like activities. Further, the latent catalytic capabilities of the short peptide based promiscuous folds also helped in processing a cascade transformation, suggesting the important role they might have played in protometabolism and early evolutionary processes.

Self-Assembled Hydrazide-Based Nanochannels: Efficient Water Translocation and Salt Rejection.

Nature has ingeniously developed specialized water transporters that effectively reject ions, including protons, while transporting water across membranes. These natural water channels, known as aquaporins (AQPs), have inspired the creation of Artificial Water Channels (AWCs). However, replicating superfast water transport with synthetic molecular structures that exclude salts and protons is a challenging task. This endeavor demands the coexistence of a suitable water-binding site and a selective filter for precise water transportation. Here, we present small-molecule hydrazides 1b-1d that self-assemble into a rosette-type nanochannel assembly through intermolecular hydrogen bonding and π-π stacking interactions, and selectively transport water molecules across lipid bilayer membranes. The experimental analysis demonstrates notable permeability rates for the 1c derivative, enabling approximately 3.18 × 108 water molecules to traverse the channel per second. This permeability rate is about one order of magnitude lower than that of AQPs. Of particular significance, the 1c ensures exclusive passage of water molecules while effectively blocking salts and protons. MD simulation studies confirmed the stability and water transport properties of the water channel assembly inside the bilayer membranes at ambient conditions.

A Halogen-Bond-Driven Artificial Chloride-Selective Channel Constructed from 5-Iodoisophthalamide-based Molecules.

Despite considerable emphasis on advancing artificial ion channels, progress is constrained by the limited availability of small molecules with the necessary attributes of self-assembly and ion selectivity. In this study, a library of small molecules based on 5-haloisophthalamide and a non-halogenated isophthalamide were examined for their ion transport properties across the lipid bilayer membranes, and the finding demonstrates that the di-hexyl-substituted 5-iodoisophthalamide derivative exhibits the highest level of activity. Furthermore, it was established that the highest active compound facilitates the selective chloride transport that occurs via an antiport-mediated mechanism. The crystal structure of the compound unveils a distinctive self-assembly of molecules, forming a zig-zag channel pore that is well-suited for the permeation of anions. Planar bilayer conductance measurements proved the formation of chloride selective channels. A molecular dynamics simulation study, relying on the self-assembled component derived from the crystal structure, affirmed the paramount significance of intermolecular hydrogen bonding in the formation of supramolecular barrel-rosette structures that span the bilayer. Furthermore, it was demonstrated that the transport of chloride across the lipid bilayer membrane is facilitated by the synergistic effects of halogen bonding and hydrogen bonding within the channel.

Long-time-step molecular dynamics can retard simulation of protein-ligand recognition process.

Molecular dynamics (MD) simulation of biologically relevant processes at realistic time scale and atomistic precision is generally limited by prohibitively large computational cost, due to its restriction of using an ultrashort integration time step (1-2 fs). A popular numerical recipe to reduce the associated computational burden is adopting schemes that would allow relatively longer-time-step for MD propagation. Here, we explore the perceived potential of one of the most frequently used long-time-step protocols, namely the hydrogen mass repartitioning (HMR) approach, in alleviating the computational overhead associated with simulation of the kinetic process of protein-ligand recognition events. By repartitioning the mass of heavier atoms to their linked hydrogen atoms, HMR leverages around twofold longer time step than regular simulation, holding promise of significant performance boost. However, our probe into direct simulation of the protein-ligand recognition event, one of the computationally most challenging processes, shows that long-time-step HMR MD simulations do not necessarily translate to a computationally affordable solution. Our investigations spanning cumulative 176 µs in three independent proteins (T4 lysozyme, sensor domain of MopR, and galectin-3) show that long-time-step HMR-based MD simulations can catch the ligand in its act of recognizing the native cavity. But, as a major caveat, the ligand is found to require significantly longer time to identify buried native protein cavity in an HMR MD simulation than regular simulation, thereby defeating the purpose of its usage for performance upgrade. A molecular analysis shows that the longer time required by a ligand to recognize the protein in HMR is rooted in faster diffusion of the ligand, which reduces the survival probability of decisive on-pathway metastable intermediates, thereby slowing down the eventual recognition process at the native cavity. Together, the investigation stresses careful assessment of pitfalls of long-time-step algorithms before attempting to utilize them for higher performance for biomolecular recognition simulations.

Interpretation of organizational role of proteins on E. coli nucleoid via Hi-C integrated model.

Several proteins in Escherichia coli work together to maintain the complex organization of its chromosome. However, the individual roles of these so-called nucleoid-associated proteins (NAPs) in chromosome architectures are not well characterized. Here, we quantitatively dissect the organizational roles of Heat Unstable (HU), a ubiquitous protein in E. coli and MatP, an NAP specifically binding to the Ter macrodomain of the chromosome. Toward this end, we employ a polymer physics-based computer model of wild-type chromosome and their HU- and MatP-devoid counterparts by incorporating their respective experimentally derived Hi-C contact matrix, cell dimensions, and replication status of the chromosome commensurate with corresponding growth conditions. Specifically, our model for the HU-devoid chromosome corroborates well with the microscopy observation of compaction of chromosome at short genomic range but diminished long-range interactions, justifying precedent hypothesis of segregation defect upon HU removal. Control simulations point out that the change in cell dimension and chromosome content in the process of HU removal holds the key to the observed differences in chromosome architecture between wild-type and HU-devoid cells. On the other hand, simulation of MatP-devoid chromosome led to locally enhanced contacts between Ter and its flanking macrodomains, consistent with previous recombination assay experiments and MatP's role in insulation of the Ter macrodomain from the rest of the chromosome. However, the simulation indicated no change in matS sites' localization. Rather, a set of designed control simulations showed that insulation of Ter is not caused by bridging of distant matS sites, also lending credence to a recent mobility experiment on various loci of the E. coli chromosome. Together, the investigations highlight the ability of an integrative model of the bacterial genome in elucidating the role of NAPs and in reconciling multiple experimental observations.

Phenol sensing in nature is modulated via a conformational switch governed by dynamic allostery.

The NtrC family of proteins senses external stimuli and accordingly stimulates stress and virulence pathways via activation of associated σ54-dependent RNA polymerases. However, the structural determinants that mediate this activation are not well understood. Here, we establish using computational, structural, biochemical, and biophysical studies that MopR, an NtrC protein, harbors a dynamic bidirectional electrostatic network that connects the phenol pocket to two distal regions, namely the "G-hinge" and the "allosteric linker." While the G-hinge influences the entry of phenol into the pocket, the allosteric linker passes the signal to the downstream ATPase domain. We show that phenol binding induces a rewiring of the electrostatic connections by eliciting dynamic allostery and demonstrates that perturbation of the core relay residues results in a complete loss of ATPase stimulation. Furthermore, we found a mutation of the G-hinge, ∼20 Å from the phenol pocket, promotes altered flexibility by shifting the pattern of conformational states accessed, leading to a protein with 7-fold enhanced phenol binding ability and enhanced transcriptional activation. Finally, we conducted a global analysis that illustrates that dynamic allostery-driven conserved community networks are universal and evolutionarily conserved across species. Taken together, these results provide insights into the mechanisms of dynamic allostery-mediated conformational changes in NtrC sensor proteins.

3site Multisubstrate-Bound State of Cytochrome P450cam.

We identified a multisubstrate-bound state, hereby referred as a 3site state, in cytochrome P450cam via integrating molecular dynamics simulation with nuclear magnetic resonance (NMR) pseudocontact shift measurements. The 3site state is a result of simultaneous binding of three camphor molecules in three locations around P450cam: (a) in a well-established "catalytic" site near heme, (b) in a kink-separated "waiting" site along channel-1, and (c) in a previously reported "allosteric" site at E, F, G, and H helical junctions. These three spatially distinct binding modes in the 3site state mutually communicate with each other via homotropic allostery and act cooperatively to render P450cam functional. The 3site state shows a significantly superior fit with NMR pseudo contact shift (PCS) data with a Q-score of 0.045 than previously known bound states and consists of D251 free of salt-bridges with K178 and R186, rendering the enzyme functionally primed. To date, none of the reported cocomplex of P450cam with its redox partner putidaredoxin (pdx) has been able to match solution NMR data and controversial pdx-induced opening of P450cam's channel-1 remains a matter of recurrent discourse. In this regard, inclusion of pdx to the 3site state is able to perfectly fit the NMR PCS measurement with a Q-score of 0.08 and disfavors the pdx-induced opening of channel-1, reconciling previously unexplained remarkably fast hydroxylation kinetics with a koff of 10.2 s-1. Together, our findings hint that previous experimental observations may have inadvertently captured the 3site state as an in vitro solution state, instead of the catalytic state alone, and provided a distinct departure from the conventional understanding of cytochrome P450.

A Benzohydrazide-Based Artificial Ion Channel that Modulates Chloride Ion Concentration in Cancer Cells and Induces Apoptosis by Disruption of Autophagy.

Fluctuations in the intracellular chloride ion concentration, mediated by synthetic ion transporters, have been known to induce cytotoxicity in cells by disrupting ionic homeostasis. However, the activity of these transporters in modulating autophagy remains largely unexplored. Here, we report a benzoylbenzohydrazide (1c) that self-assembles to form a supramolecular nanochannel lumen that allows selective and efficient transport of chloride ions across the cell membranes, disrupts ion homeostasis, and thus leads to the induction of apoptosis in cancer cells. It is important to note that the transporter was relatively nontoxic to cells of noncancerous origin. 1c was also shown to induce the deacidification of lysosomes, thereby disrupting autophagy in cancer cells. Taken together, these findings provide a rare example of an artificial ion channel that specifically targets cancer cells by induction of apoptosis via disruption of autophagy.

Nontoxic Artificial Chloride Channel Formation in Epithelial Cells by Isophthalic Acid-Based Small Molecules.

Artificial channels capable of facilitating the transport of Cl- ions across cell membranes while being nontoxic to the cells are rare. Such synthetic ion channels can mimic the functions of membrane transport proteins and, therefore, have the potential to treat channelopathies by replacing defective ion channels. Here we report isophthalic acid-based structurally simple molecules 1 a and 2 a, which self-assemble to render supramolecular nanochannels that allow selective transport of Cl- ions. As evident from the single-crystal X-ray diffraction analysis, the self-assembly is governed by intermolecular hydrogen bonding and π-π stacking interactions. The MD simulation studies for both 1 a and 2 a confirmed the formation of stable Cl- channel assembly in the lipid membrane and Cl- transport through them. The MQAE assay showed the efficacy of the compounds in delivering Cl- ions into cells, and the MTT assays proved that the compounds are nontoxic to cells even at a concentration of 100 µM.

Carbodicarbenes and Striking Redox Transitions of their Conjugate Acids: Influence of NHC versus CAAC as Donor Substituents.

Herein, a new type of carbodicarbene (CDC) comprising two different classes of carbenes is reported; NHC and CAAC as donor substituents and compare the molecular structure and coordination to Au(I)Cl to those of NHC-only and CAAC-only analogues. The conjugate acids of these three CDCs exhibit notable redox properties. Their reactions with [NO][SbF6 ] were investigated. The reduction of the conjugate acid of CAAC-only based CDC with KC8 results in the formation of hydrogen abstracted/eliminated products, which proceed through a neutral radical intermediate, detected by EPR spectroscopy. In contrast, the reduction of conjugate acids of NHC-only and NHC/CAAC based CDCs led to intermolecular reductive (reversible) carbon-carbon sigma bond formation. The resulting relatively elongated carbon-carbon sigma bonds were found to be readily oxidized. They were, thus, demonstrated to be potent reducing agents, underlining their potential utility as organic electron donors and n-dopants in organic semiconductor molecules.

A Synergistic View on Osmolyte's Role against Salt and Cold Stress in Biointerfaces.

We present our perspective on the role of osmolytes in mitigating abiotic stresses such as hypersalinity and sudden temperature changes. While the stabilizing effect of osmolytes on protein tertiary structures has been extensively studied, their direct impact on abiotic stress factors has eluded mainstream attention. Via highlighting a set of recent success stories of a joint venture of computer simulations and experimental measurements, we summarize the mechanistic insights into osmolytic action, particularly in the context of salt stress and combined cold-salt stress at the interface of biomolecular surfaces and saline environments. We stress the importance of chemical specificity in osmolytic activity, the interplay of differential osmolytic behaviors against heterogeneous salt stress, and the capability of osmolytes to adopt combined actions. Additionally, we discuss the potential of incorporating nanomaterial-based systems to enrich our understanding of osmolyte bioactions and facilitate their practical applications. We anticipate that this discourse will inspire interdisciplinary collaborations and motivate further investigations on osmolytes, ultimately broadening their applications in the fields of health and disease.

A deep encoder-decoder framework for identifying distinct ligand binding pathways.

The pathway(s) that a ligand would adopt en route to its trajectory to the native pocket of the receptor protein act as a key determinant of its biological activity. While Molecular Dynamics (MD) simulations have emerged as the method of choice for modeling protein-ligand binding events, the high dimensional nature of the MD-derived trajectories often remains a barrier in the statistical elucidation of distinct ligand binding pathways due to the stochasticity inherent in the ligand's fluctuation in the solution and around the receptor. Here, we demonstrate that an autoencoder based deep neural network, trained using an objective input feature of a large matrix of residue-ligand distances, can efficiently produce an optimal low-dimensional latent space that stores necessary information on the ligand-binding event. In particular, for a system of L99A mutant of T4 lysozyme interacting with its native ligand, benzene, this deep encoder-decoder framework automatically identifies multiple distinct recognition pathways, without requiring user intervention. The intermediates involve the spatially discrete location of the ligand in different helices of the protein before its eventual recognition of native pose. The compressed subspace derived from the autoencoder provides a quantitatively accurate measure of the free energy and kinetics of ligand binding to the native pocket. The investigation also recommends that while a linear dimensional reduction technique, such as time-structured independent component analysis, can do a decent job of state-space decomposition in cases where the intermediates are long-lived, autoencoder is the method of choice in systems where transient, low-populated intermediates can lead to multiple ligand-binding pathways.

A Hi-C data-integrated model elucidates E. coli chromosome's multiscale organization at various replication stages.

The chromosome of Escherichia coli is riddled with multi-faceted complexity. The emergence of chromosome conformation capture techniques are providing newer ways to explore chromosome organization. Here we combine a beads-on-a-spring polymer-based framework with recently reported Hi-C data for E. coli chromosome, in rich growth condition, to develop a comprehensive model of its chromosome at 5 kb resolution. The investigation focuses on a range of diverse chromosome architectures of E. coli at various replication states corresponding to a collection of cells, individually present in different stages of cell cycle. The Hi-C data-integrated model captures the self-organization of E. coli chromosome into multiple macrodomains within a ring-like architecture. The model demonstrates that the position of oriC is dependent on architecture and replication state of chromosomes. The distance profiles extracted from the model reconcile fluorescence microscopy and DNA-recombination assay experiments. Investigations into writhe of the chromosome model reveal that it adopts helix-like conformation with no net chirality, earlier hypothesized in experiments. A genome-wide radius of gyration map captures multiple chromosomal interaction domains and identifies the precise locations of rrn operons in the chromosome. We show that a model devoid of Hi-C encoded information would fail to recapitulate most genomic features unique to E. coli.

Molecular dynamics simulations elucidate oligosaccharide recognition pathways by galectin-3 at atomic resolution.

The recognition of carbohydrates by lectins plays key roles in diverse cellular processes such as cellular adhesion, proliferation, and apoptosis, which makes it a therapeutic target of significance against cancers. One of the most functionally active lectins, galectin-3 is distinctively known for its specific binding affinity toward ß-galactoside. However, despite the prevalence of high-resolution crystallographic structures, the mechanistic basis and more significantly, the dynamic process underlying carbohydrate recognition by galectin-3 are currently elusive. To this end, we employed extensive Molecular Dynamics simulations to unravel the complete binding event of human galectin-3 with its native natural ligand N-acetyllactosamine (LacNAc) at atomic precision. The simulation trajectory demonstrates that the oligosaccharide diffuses around the protein and eventually identifies and binds to the biologically designated binding site of galectin-3 in real time. The simulated bound pose correlates with the crystallographic pose with atomic-level accuracy and recapitulates the signature stabilizing galectin-3/oligosaccharide interactions. The recognition pathway also reveals a set of transient non-native ligand poses in its course to the receptor. Interestingly, kinetic analysis in combination with a residue-level picture revealed that the key to the efficacy of a more active structural variant of the LacNAc lay in the ligand's resilience against disassociation from galectin-3. By catching the ligand in the act of finding its target, our investigations elucidate the detailed recognition mechanism of the carbohydrate-binding domain of galectin-3 and underscore the importance of ligand-target binary complex residence time in understanding the structure-activity relationship of cognate ligands.

Graphene as Photothermal Therapeutic Agents.

Light-assisted hyperthermic therapy is a promising strategy to treat cancer. Graphene and their derivatives with unique physiochemical properties, intrinsic near infrared absorption, and ability to transduce the absorbed light energy into heat, have attracted researchers to use them for photothermal therapy (PTT). In addition, the presence of surface functional groups and large surface area that can facilitate interactions with hydrophobic molecules has favored the use of graphene allotropes for developing PTT-based combinatorial therapies. In this book chapter we have reviewed different graphene-based PTT-assisted photodynamic, gene, chemo, and immunotherapeutic strategies developed to improve the outcome of cancer treatment. We have also discussed how PTT from graphene derivatives can improve the therapeutic outcomes of gene, chemo, and immunotherapies. Finally, this book chapter provides promising insights to develop novel graphene-based multifunctional PTT-assisted combinatorial therapeutics with both imaging and therapeutic regimens to treat cancer.

Magnetofluoro-Immunosensing Platform Based on Binary Nanoparticle-Decorated Graphene for Detection of Cancer Cell-Derived Exosomes.

Multi-functionalized carbon nanomaterials have attracted interest owing to their excellent synergic properties, such as plasmon resonance energy transfer and surface-enhanced Raman scattering. Particularly, nanoparticle (NP)-decorated graphene (GRP) has been applied in various fields. In this study, silver NP (AgNP)- and magnetic iron oxide NP (IONP)-decorated GRP were prepared and utilized as biosensing platforms. In this case, AgNPs and GRP exhibit plasmonic properties, whereas IONPs exhibit magnetic properties; therefore, this hybrid nanomaterial could function as a magnetoplasmonic substrate for the magnetofluoro-immunosensing (MFI) system. Conversely, exosomes were recently considered high-potential biomarkers for the diagnosis of diseases. However, exosome diagnostic use requires complex isolation and purification methods. Nevertheless, we successfully detected a prostate-cancer-cell-derived exosome (PC-exosome) from non-purified exosomes in a culture media sample using Ag/IO-GRP and dye-tetraspanin antibodies (Ab). First, the anti-prostate-specific antigen was immobilized on the Ag/IO-GRP and it could isolate the PC-exosome from the sample via an external magnetic force. Dye-tetraspanin Ab was added to the sample to induce the sandwich structure. Based on the number of exosomes, the fluorescence intensity from the dye varied and the system exhibited highly sensitive and selective performance. Consequently, these hybrid materials exhibited excellent potential for biosensing platforms.

Reconciling conformational heterogeneity and substrate recognition in cytochrome P450.

Cytochrome P450, the ubiquitous metalloenzyme involved in detoxification of foreign components, has remained one of the most popular systems for substrate-recognition process. However, despite being known for its high substrate specificity, the mechanistic basis of substrate-binding by archetypal system cytochrome P450cam has remained at odds with the contrasting reports of multiple diverse crystallographic structures of its substrate-free form. Here, we address this issue by elucidating the probability of mutual dynamical transition to the other crystallographic pose of cytochrome P450cam and vice versa via unbiased all-atom computer simulation. A robust Markov state model, constructed using adaptively sampled 84-µs-long molecular dynamics simulation trajectories, maps the broad and heterogenous P450cam conformational landscape into five key substates. In particular, the Markov state model identifies an intermediate-assisted dynamic equilibrium between a pair of conformations of P450cam, in which the substrate-recognition sites remain "closed" and "open," respectively. However, the estimate of a significantly higher stationary population of closed conformation, coupled with faster rate of open → closed transition than its reverse process, dictates that the net conformational equilibrium would be swayed in favor of "closed" conformation. Together, the investigation quantitatively infers that although a potential substrate of cytochrome P450cam would, in principle, explore a diverse array of conformations of substrate-free protein, it would mostly encounter a "closed" or solvent-occluded conformation and hence would follow an induced-fit-based recognition process. Overall, the work reconciles multiple precedent crystallographic, spectroscopic investigations and establishes how a statistical elucidation of conformational heterogeneity in protein would provide crucial insights in the mechanism of potential substrate-recognition process.

Spontaneous transmembrane pore formation by short-chain synthetic peptide.

Amphiphilic ß-peptides, which are synthetically designed short-chain helical foldamers of ß-amino acids, are established potent biomimetic alternatives of natural antimicrobial peptides. An intriguing question is how the distinct molecular architecture of these short-chain and rigid synthetic peptides translates to its potent membrane-disruption ability. Here, we address this question via a combination of all-atom and coarse-grained molecular dynamics simulations of the interaction of mixed phospholipid bilayer with an antimicrobial 10-residue globally amphiphilic helical ß-peptide at a wide range of concentrations. The simulation demonstrates that multiple copies of this synthetic peptide, initially placed in aqueous solution, readily self-assemble and adsorb at membrane interface. Subsequently, beyond a threshold peptide/lipid ratio, the surface-adsorbed oligomeric aggregate moves inside the membrane and spontaneously forms stable water-filled transmembrane pores via a cooperative mechanism. The defects induced by these pores lead to the dislocation of interfacial lipid headgroups, membrane thinning, and substantial water leakage inside the hydrophobic core of the membrane. A molecular analysis reveals that despite having a short architecture, these synthetic peptides, once inside the membrane, would stretch themselves toward the distal leaflet in favor of potential contact with polar headgroups and interfacial water layer. The pore formed in coarse-grained simulation was found to be resilient upon structural refinement. Interestingly, the pore-inducing ability was found to be elusive in a non-globally amphiphilic sequence isomer of the same ß-peptide, indicating strong sequence dependence. Taken together, this work puts forward key perspectives of membrane activity of minimally designed synthetic biomimetic oligomers relative to the natural antimicrobial peptides.

Mechanistic underpinning of cell aspect ratio-dependent emergent collective motions in swarming bacteria.

Self-propelled bacteria can exhibit a large variety of non-equilibrium self-organized phenomena. Swarming is one such fascinating dynamical scenario where a number of motile individuals group into dynamical clusters and move in synchronized flows and vortices. While precedent investigations into rod-like particles confirm that an increased aspect-ratio promotes alignment and order, recent experimental studies in bacteria Bacillus subtilis show a non-monotonic dependence of the cell-aspect ratio on their swarming motion. Here, by computer simulations of an agent-based model of self-propelled, mechanically interacting, rod-shaped bacteria under overdamped conditions, we explore the collective dynamics of a bacterial swarm subjected to a variety of cell-aspect ratios. When modeled with an identical self-propulsion speed across a diverse range of cell aspect ratios, simulations demonstrate that both shorter and longer bacteria exhibit slow dynamics whereas the fastest speed is obtained at an intermediate aspect ratio. Our investigation highlights that the origin of this observed non-monotonic trend of bacterial speed and vorticity with the cell-aspect ratio is rooted in the cell-size dependence of motility force. The swarming features remain robust for a wide range of surface density of the cells, whereas asymmetry in friction attributes a distinct effect. Our analysis identifies that at an intermediate aspect ratio, an optimum cell size and motility force promote alignment, which reinforces the mechanical interactions among neighboring cells leading to the overall fastest motion. Mechanistic underpinning of the collective motions reveals that it is a joint venture of the short-range repulsive and the size-dependent motility forces, which determines the characteristics of swarming.