Biology subjects

Sahil, M.

Publications and source records attributed to Sahil, M..

7 recordsLinked to original sources

bioRxiv2025

I helix Mediates the Allosteric Regulation in Cytochrome P450cam

Cytochrome P450cam, a key monooxygenase in the P450 superfamily, is pivotal in metabolic and industrial processes. Despite extensive studies, a unified mechanism governing its conformational heterogeneity, substrate-dependent allostery, and multi-substrate binding remains elusive. Here, integrating molecular dynamics simulations, NMR pseudocontact shift (PCS) analysis, and crystallographic data, we identify the I-helix (I) as the central regulator of P450cams allostery. Its intrinsic flexibility, dictated by glycine residues (G248 and G249), orchestrates enzyme conformational dynamics. Specifically, I transitions between straight and kinked conformations, modulating the opening and closing of substrate access channels (channel-1 and channel-2) and mediating allosteric communication between active and allosteric sites. Substrate binding stabilizes the straight conformation, promoting channel closure and enhancing allosteric regulation. This I-helix-based mechanism reconciles 125 crystallographic poses, spanning straight-to-kinked I conformations. Notably, the kink-inducing glycine G249 is evolutionarily conserved across species, including humans, underscoring Is fundamental role in enzyme function and broader significance within the P450 superfamily. NMR PCS measurements align with the kinked and straight conformations in the substrate-free and substrate-bound states, with Q-scores of 0.108 and 0.061, respectively. Leveraging this mechanistic insight, we designed proof-of-concept P450cam mutants locked in either constitutively open or closed conformations for the first time. By shifting the focus from the traditional FG-helix-centric view to an I-helix-centric framework, this study provides a comprehensive blueprint for conformational and allosteric regulation, paving the way for engineering tailored P450 variants.

biochemistry↗

bioRxiv2024

Unbiased learning of protein conformational representation via unsupervised random forest

Accurate data representation is paramount in biophysics to capture the functionally relevant motions of biomolecules. Traditional feature selection methods, while effective, often rely on labeled data based on prior knowledge and user-supervision, limiting their applicability to novel systems. Here, we present unsupervised random forest (URF), a self-supervised adaptation of traditional random forests that identifies functionally critical features of biomolecules without requiring prior labels. By devising a memory-efficient implementation, we first demonstrate URFs capability to learn important sets of inter-residue features of a protein and subsequently to resolve its complex conformational landscape, performing at par or surpassing its traditional supervised counterpart and 15 other leading baseline methods. Crucially, URF is supplemented by an internal metric, the learning coefficient, which automates the process of hyper-parameter optimization, making the method robust and user-friendly. URFs remarkable ability to learn important protein features in an unbiased fashion was validated against 10 independent protein systems including both both folded and intrinsically disordered states. In particular, benchmarking investigations showed that the protein representations identified by URF are functionally meaningful in comparison to current state-of-the-art deep learning methods. As an application, we show that URF can be seamlessly integrated with downstream analyses pipeline such as Markov state models to attain better resolved outputs. The investigation presented here establishes URF as a leading tool for unsupervised representation learning in protein biophysics.

biophysics↗

bioRxiv2024

Dynamic Insights into Hsp90 Inhibitor Binding: Uncovering Intermediate States and Conformational Plasticity

Heat shock protein 90 (Hsp90) is a vital molecular chaperone involved in protein folding, stabilization, and activation, making it a key target in cancer therapy. Tar-geting the N-terminal domain of Hsp90 (N-Hsp90) has emerged as a potential strategy for developing anticancer therapies due to its involvement in the folding and function of oncoproteins. However, the precise molecular details of how inhibitors bind to N-Hsp90 remain elusive due to inherent conformational plasticity involving loop-in and loop-out states of loop-4 (L4). In this work, we utilized unbiased molecular dynamics (MD) simulations coupled with Markov state modeling (MSM) and machine learning techniques to investigate the binding dynamics of the inhibitor Geldanamycin (GDM). Our findings reveal a complex two-stage binding mechanism involving the formation of a non-native intermediate state prior to the final bound state. We demonstrate that GDM binding predominantly stabilizes the loop-out conformation of N-Hsp90, chal-lenging prior beliefs and suggesting that both conformational selection and induced fit mechanisms are involved. Through a detailed residue-level analysis using Random For-est based ML classifiers, we quantify the relative contributions of these mechanisms, highlighting the dynamic interplay between Hsp90s conformational states during in-hibitor binding. These findings enhance our understanding of Hsp90s conformational plasticity and could inform the design of more effective Hsp90 inhibitors.

biochemistry↗

bioRxiv2023

A host AAA-ATPase exhibits bacteriolytic activity for clearance of microbial infection

An array of host cytosol guarding factors impede bacterial proliferation and preserve cellular sterility. Amongst them, proteasomal degradation of ubiquitinated pathogens has emerged as a critical mechanism for ensuring cytosolic sanctity. We wondered how proteasomes, with their small size and inability to extract membrane-bound proteins, can eradicate pathogens. Here, we unveil a unique strategy, wherein VCP/p97, a host AAA-ATPase, eliminates pathogens by exerting mechanical force that physically unfolds and pulls out ubiquitinated proteins from bacterial membrane. Combining a single-molecule approach along with molecular dynamic simulation and in-vitro reconstitution, we demonstrate that protein extraction by p97 causes extensive membrane lysis and release of cytosolic contents from phylogenetically diverse microbes. Additionally, in an in-vivo mouse sepsis model, this segregase-dependent bactericidal effect of p97 abrogated microbial proliferation in host tissues. Overall, we discovered a distinct innate antimicrobial function of p97, that protects the host against lethal bacterial infections. One Sentence SummaryA host AAA-ATPase exhibits bacteriolytic activity.

microbiology↗

bioRxiv2023

Identifying Selectivity Filters in Protein Biosensor for Ligand Screening

Specialized sensing mechanisms in bacteria enable the identification of cognate ligands with remarkable selectivity in highly xenobiotic-polluted environments, where these ligands are utilized as energy sources. Here, via an integrated all-atom computer simulation, biochemical assay and isothermal titration calorimetry approaches we determine the molecular basis of MopR, a phenol biosensors complex selection process of ligand entry. Our results reveal a set of strategically placed selectivity filters along the ligand entry pathway of MopR. These filters act as checkpoints, screening diverse aromatic ligands at the protein surface based on their chemical features and sizes. Ligands meeting specific criteria are allowed to enter the sensing site in an orientation-dependent manner. Sequence and structural analyses demonstrate the conservation of this ligand entry mechanism across the sensor class, with individual amino acids along the selectivity filter path playing a critical role in ligand selection. Together, this investigation highlights the importance of interactions with the ligand entry pathway, in addition to interactions within the binding pocket, for achieving ligand selectivity in biological sensing. The findings enhance our understanding of ligand selectivity in bacterial phenol biosensors and provide insights for the rational expansion of the biosensor repertoire, particularly for the biotechnologically relevant class of aromatic pollutants.

biochemistry↗

bioRxiv2023

Discovery of a Novel 3site State as the Multi-Substrate Bound State of P450cam

Archetypal metalloenzyme Cytochrome P450cam (CYP101A1) catalyzes regioselective hydroxylation of its native substrate camphor in heme active site. However, the proposal of potential existence of additional substrate binding modes distal from the active site in P450cam and their concomitant roles in regulating recognition at active site have remained a matter of recurring discourse. Herein we report the discovery of a novel 3site state in P450cam, where three substrate molecules were observed to simultaneously bind to P450cam at three distinct sites including the heme active site. These three binding modes, hereby referred as catalytic, waiting and allosteric binding modes in 3site state, are allosterically inter-linked and function in mutually synergistic fashion. The 3site state possesses regio-selective conformations of substrate essential for catalysis and establishes substrate-ingress and product exit process to and from the active site via two distinct channels. The ensemble of three-state binding modes are found to be self-consistent with NMR pseudo-contact shift data obtained from TROSY-HSQC measurements and DEER based predictions. Binding of redox partner Putidaredoxin with 3site model retains closed conformation of 3site state, siding with NMR based hypothesis that the catalysis would take place in closed insulation of P450cam even in presence of its redox partner. Statement of SignificanceUbiquitous superfamily of mono-oxygenases cytochrome P450s are involved in broad range of metabolic process in all domains of life and are also important drug targets. Apart from the well known and established binding mode in heme active site, the substrate bindings at additional distal sites have been postulated in multitude of P450s. Using the archetypal bacterial cytochrome P450 i.e., P450cam, a novel 3site state of cytochrome P450 is elucidated in this work. The novel 3site state has two additional binding modes namely waiting and allosteric (also postulated previously), apart from known binding mode catalytic in the active site. The known functions of P450cam are found to be most optimally explained by this 3site state, instead of single substrate bound catalytic state. This state can be of critical importance for CYP superfamily at large and potentially be useful in understanding the non-Michaelis behaviour, observed in many P450s.

biochemistry↗

bioRxiv2022

Phenol Sensing in Nature Modulated via a Conformational Switch Governed by Dynamic Allostery

NtrC family of proteins sense external stimuli and accordingly stimulate stress and virulence pathways via activation of associated {sigma}54-dependent RNA polymerases. Here, we establish that MopR, an NtrC protein, harbors a dynamic bi-directional electrostatic network that connects the phenol pocket to two distal regions, namely the "G-hinge" and the "allo-steric-linker". While G-hinge influences the entry of phenol, the allosteric-linker passes the signal to the downstream ATPase domain. Phenol binding induces a rewiring of the electrostatic connections by eliciting dynamic allostery, and it was demonstrated that perturbation of the core relay residues results in a complete loss of ATPase stimulation. A mutation of the G-hinge,[~]20[A] from the phenol pocket, demonstrated 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. A global analysis illustrates that dynamic allostery-driven conserved community networks are universal and evolutionarily conserved across species.

biochemistry↗