Biology subjects

Bhakat, S.

Publications and source records attributed to Bhakat, S..

At least 19 recordsLinked to original sources

bioRxiv2026

REVEAL: RNA Ensemble Validation and Exploration with AI-guided Landscapes

Capturing the sparsely populated but functionally important, excited states of RNA remains a central challenge for molecular simulation, because the underlying transitions are rare events that unbiased molecular dynamics cannot reach from a single starting structure. Here we introduce REVEAL (RNA Ensemble Validation and Exploration with AI-guided Landscapes), a workflow that couples generative secondary structure sampling, secondary structure conditioned tertiary structure prediction with trRosettaRNA2, unbiased molecular dynamics and Markov state modeling. Using only the sequence of the engineered HIV-1 TAR mutant, in which the excited state ES2 is the dominant conformation, we show that REVEAL captures the reversible ES2 to GS register shift from 6.8 s of aggregate unbiased sampling across 34 seeds, recovering both basins, the intermediate states, and correctly identifies ES2 as the dominant state, consistent with the design of the construct. In contrast, molecular dynamics seeded from the ES2-dominant HIV-1 TAR mutant NMR ensemble remains trapped in ES2 despite substantially longer aggregate simulation time, and sequence-only ensemble predictors (AlphaFold3, Boltz-2, ESMFold2, OpenFold3 and Protenix-v2) place every structure near the ground state and invert the experimentally observed population ordering. The information content of the seed ensemble, rather than the total simulation time, determines whether the transition is sampled. We further introduce ''population-weighted consensus score'' (PWCS) that ranks conformers by how representative they are of the equilibrium ensemble directly from the simulation data, without experimental restraints and independent of the choice of collective variables. PWCS identifies the dominant state even when low-dimensional representations fail to separate the states. Built entirely from open-source tools, REVEAL provides a transparent and extensible route to RNA conformational ensembles beyond the single-structure paradigm.

biophysics↗

bioRxiv2026

Benchmarking generative AI and physics based molecular simulation for sampling conformational heterogeneity in T4 Lysozyme

Wild-type T4 lysozyme (T4L) is used as a benchmark to evaluate conformational sampling across generative AI, AI-accelerated molecular simulation (AMS), and physics-based enhanced molecular dynamics (EMD). A four-state model: exposed/open, exposed/closed, buried/open, and buried/closed; is defined using physically meaningful collective variables. While generative AI methods (AF-cluster, MSA subsampling of AlphaFold2, ConforFold, AlphaFlow, ESMFlow, ConfRover, BioEmu) largely sample only the exposed/open state, AMS integrating generative ensembles with iterative molecular dynamics, recovering all states and reproducing equilibrium populations similar to EMD and experimental smFRET signatures.

biophysics↗

bioRxiv2026

Accelerated sampling of protein dynamics using BioEmu augmented molecular simulation

We introduce a workflow that integrates BioEmu-generated conformational ensemble with physics-based molecular simulations and Markov State Models to sample Boltzmann-weighted conformational populations across biomolecules. Molecular simulations initiated from BioEmu ensemble capture active-to-inactive transitions in CDK2 and BRAF, two members of the serine-threonine kinase family, and elucidate how the disease-causing V600E mutation in BRAF drives population shifts among distinct metastable states relative to the wild type. Furthermore, we combined BioEmu ensemble with experimental cryo-EM data to construct all-atom conformational ensembles of biomolecules. In comparison to the AlphaFold2 reduced multiple sequence alignment (rMSA-AF2) approach, BioEmu-generated ensembles sample a broader conformational space for serine-threonine kinases but fail to capture conformational heterogeneity in several cases, including Glycine transporter 1 (GlyT1), a membrane transporter, and plasmepsin-II (PlmII), an aspartic protease. Systems where side-chain conformational heterogeneity governs protein dynamics such as cryptic pocket opening in PlmII or transitions between multiple metastable states in GlyT1; molecular simulations initiated from BioEmu generated ensemble do not capture the full spectrum of conformational heterogeneity. Overall, this study presents a straightforward framework for integrating generative AI based protein emulators with statistical physics to recover Boltzmann-weighted conformational ensembles at scale, while also highlighting critical limitations that necessitate careful, system-specific analysis when interpreting protein conformational landscapes.

biophysics↗

bioRxiv2025

CryoPhold: CryoEM meets AlphaFold and molecular simulation to reveal protein dynamics

Here we are introducing CryoPhold, a modular workflow that unifies AlphaFold-based ensemble generation, Bayesian reweighting against experimental cryo-EM maps, molecular simulation, and machine learning to quantify conformational populations and identify structural fingerprints that govern protein functions. Proteins are inherently dynamic, interconverting among conformational states that govern their function. Perturbations such as mutations, ligand binding, and pH changes modulate these dynamics and are implicated in many diseases. While cryogenic electron microscopy (cryo-EM) has transformed structure determination, it typically yields an averaged density map representing a static snapshot. A central challenge remains capturing the thermodynamics underlying protein motions and corresponding structural fingerprints that modulate function. CryoPhold enables Bayesian reweighting of AlphaFold-generated structural ensembles against experimental cryo-EM maps, generating posterior structural ensembles that are consistent with experimental data while preserving conformational heterogeneity. Molecular simulations seeded from the posterior ensemble capture time-dependent dynamics, while machine learning models trained on featurized molecular simulation data identify structural fingerprints ("hotspots") that modulate protein dynamics. Finally, Markov state models trained on featurized molecular simulation data quantify metastable state populations and free-energy landscapes. By integrating a generative AI-based protein structure prediction model, experimental cryo-EM density, physics-based sampling, and machine learning, CryoPhold enables dynamics paradigm to capture biomolecular motion. The workflow enables prediction of equilibrium populations and structural fingerprints governing conformational dynamics in human transporter protein, GlyT1. It further captures structural changes and population shifts associated with oncogenic BRAF mutants, key driving factors behind melanoma progression.

biophysics↗

bioRxiv2025

Generalizable Protein Dynamics in Serine-Threonine Kinases: Physics is the key

Kinases play crucial roles in signaling pathways across oncology, inflammation, and neurodegenerative diseases. Historically, their conformational states have been defined by the DFG motif: DFGin and DFGout. However, this binary paradigm overlooks the broader conformational heterogeneity of apo kinases, which encompasses multiple metastable states within an expanded DFG-Phe ensemble. We introduced a novel nomenclature that integrates the dynamics of the DFG-Phe, activation loop, and C-helix, highlighting how these regions respond to various ensemble perturbations (e.g., mutations, ligand binding, and protein-protein interactions). A major bottleneck in studying kinases lies in sampling their wide-ranging conformations because static snapshots often remain trapped in specific free energy minima, limiting traditional molecular dynamics simulations from exploring multiple functionally relevant states starting from a single structure. To accelerate conformational sampling, we introduce a computational framework that integrates AlphaFold, machine learning, physics- based simulations, and Markov state modeling. Rather than focusing on single-structure snapshots or structural hypotheses generated by protein structure prediction models, our framework captures shifts in conformational populations under varying perturbations, shedding light on both the thermodynamics and kinetics of the transitions. We show generalizability of our ensemble definitions and protocol across members of serine-threonine kinases and tyrosine kinases. A key innovation lies in our machine learning algorithms, which capture slowly varying structural features to uncover hidden states and generate latent representations of conformational motions across different kinase domains. The physics-refined structural ensemble sampled from the latent layers is then used to launch new simulations that more comprehensively explore the full conformational landscape than traditional molecular simulation approaches. By capturing how these conformational shifts influence downstream protein-protein interactions, conformational allostery, and cryptic pocket formation, our accelerated simulation framework provides deeper insights into generalized molecular recognition mechanism in kinases and how conformational heterogeneity is influenced by ensemble perturbations. This framework can be extended to investigate broader protein families--such as G protein-coupled receptors (GPCRs) and tumor necrosis factors (TNFs)--where functional outcomes are dictated by conformational heterogeneity.

biophysics↗

bioRxiv2024

Revealing Mechanism of Allostery in RIPK2 kinase

Withdrawal StatementThe authors have withdrawn their manuscript owing to a conflict of interest. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author, Soumendranath Bhakat.

biophysics↗

bioRxiv2023

AlphaFold-SFA: accelerated sampling of cryptic pocket opening by fusing AlphaFold, slow feature analysis and metadynamics

Sampling rare events in proteins is crucial for comprehending complex phenomena like cryptic pocket opening, where transient structural changes expose new binding sites. Understanding these rare events also sheds light on protein-ligand binding and allosteric communications, where distant site interactions influence protein function. Traditional unbiased molecular dynamics simulations often fail to sample such rare events, as the free energy barrier between metastable states is large relative to the thermal energy. This renders these events inaccessible on the timescales typically simulated by standard molecular dynamics, limiting our understanding of these critical processes. In this paper, we proposed a novel unsupervised learning approach termed as slow feature analysis (SFA) which aims to extract slowly varying features from high-dimensional temporal data. SFA trained on small unbiased molecular dynamics simulations launched from AlphaFold generated conformational ensembles manages to capture rare events governing cryptic pocket opening, protein-ligand binding, and allosteric communications in a kinase. Metadynamics simulations using SFA as collective variables manage to sample deep cryptic pocket opening within a few hundreds of nanoseconds which was beyond the reach of microsecond long unbiased molecular dynamics simulations. SFA augmented metadynamics also managed to capture accelerated ligand binding/unbinding and provided novel insights into allosteric communication in receptor-interacting protein kinase 2 (RIPK2) which dictates protein-protein interaction. Taken together, our results show how SFA acts as a dimensionality reduction tool which bridges the gap between AlphaFold, molecular dynamics simulation and metadynamics in context of capturing rare events in biomolecules, extending the scope of structure-based drug discovery in the era of AlphaFold.

biophysics↗

bioRxiv2023

A morphotype of Saccolaimus saccolaimus (Chiroptera: Emballonuridae) from West Bengal, India with a comparative note of the species.

An adult Saccolaimus saccolaimus Temminck, 1838 is described here with morphometric measurements in detail. The present species though showed morphological similarities with the species reported from India and abroad but it bears an exceptional character, a white oval pad at the base of the thumb. A comparative note of the species found in India and other countries are also presented here with a suggestion to rethink the IUCN status of the species "Least Concern" in India.

zoology↗

bioRxiv2023

Redescription of Dendrophthoe falcata (L. f.) Ettingsh (Loranthaceae) with notes on haustorium

Morphology of Dendrophthoe falcata (L. f.) Ettingsh var coccinea is described in detail from West Bengal with notes on the histology of haustorium. Structural peculiarity of the style is explained in the light of embryo sac development. Section of immature fruit shows different zones including embryo. Three types of haustoria namely woody gall, clasping union ad epicortical root is observed in different species of the host plant. Section of haustorium shows penetration peg which reach the host xylem to suck the sap. In guava plant, two types of haustoria develop - primary or true haustorium which penetrate the host stem and secondary haustorium which develop in between two roots of the parasite. Secondary haustorium is oval in shape with a few concentric rings like thickening and never develops penetration peg.

plant biology↗

bioRxiv2022

Accelerating cryptic pocket discovery using AlphaFold

Cryptic pockets, or pockets absent in ligand-free, experimentally determined structures, hold great potential as drug targets. However, cryptic pocket opening is often beyond the reach of conventional biomolecular simulations because certain cryptic pocket openings involve slow motions. Here, we investigate whether AlphaFold can be used to accelerate cryptic pocket discovery either by generating structures with open pockets directly or generating structures with partially open pockets that can be used as starting points for simulations. We use AlphaFold to generate ensembles for 10 known cryptic pocket examples, including 5 that were deposited after AlphaFolds training data was extracted from the PDB. We find that in 6 out of 10 cases AlphaFold samples the open state. For plasmepsin II, an aspartic protease from the causative agent of malaria, AlphaFold only captures partial pocket opening. As a result, we ran simulations from an ensemble of AlphaFold-generated structures and show that this strategy samples cryptic pocket opening, even though an equivalent amount of simulations launched from a ligand-free experimental structure fails to do so. Markov state models (MSMs) constructed from the AlphaFold-seeded simulations quickly yield a free energy landscape of cryptic pocket opening that is in good agreement with the same landscape generated with well-tempered metadynamics. Taken together, our results demonstrate that AlphaFold has a useful role to play in cryptic pocket discovery but that many cryptic pockets may remain difficult to sample using AlphaFold alone.

biochemistry↗

bioRxiv2022

Computational modelling of local fluctuations causing transient solvent exposure of protein amides

Hydrogen exchange (HX) between protein amides and solvent water molecules can function as a probe for protein dynamics and provide a bridge between the experimental and computational worlds. However, it is important that the underlying assumptions are tested on well-known systems. Here we perform an analysis of a long MD simulation of BPTI, which has previously been used by Persson and Halle to propose a functional definition of the exchange-competent configurations. We find support for the hypothesis that the exchange-competent configurations typically do not constitute a metastable state per se, but rather occur as the outermost tail of the water distribution around a metastable broken state directly identifiable as having a broken intermolecular hydrogen bond and increased solvent-exposure. Furthermore, we estimate the lifetime of these broken states and the probability that exchange-competent configurations occur in them. We have also tested various sampling protocols and their ability to enhance the exploration of the broken states. Computational protocol used in this study can be applied to a broad range of sys-tems to gain valuable insight into the nature of the broken state, although further development is needed to devise a generally applicable quantitative method.

biophysics↗

bioRxiv2022

A nepenthesin insert allosterically controls catalysis in the malaria parasite protease plasmepsin V

Plasmepsin V (PM V) is a pepsin-like aspartic protease essential for growth of the malaria parasite Plasmodium falciparum. Previous work has shown PM V to be an ER-resident protease that processes parasite proteins destined for export into the host cell. Depletion or inhibition of the enzyme is lethal during asexual replication within red blood cells, as well as during the formation of sexual stage gametocytes. The structure of the P. vivax PM V has been characterized by x-ray crystallography, revealing a canonical pepsin fold punctuated by structural features uncommon to secretory aspartic proteases. Here we use parasite genetics to probe these structural features by attempting to rescue lethal PM V depletion with various mutant enzymes. We find an unusual nepenthesin 1-type insert to be essential for parasite growth and PM V activity. Mutagenesis of the nepenthesin insert suggests that both its amino acid sequence and one of the two disulfide bonds that undergird its structure are required for the nepenthesin inserts role in PM V function. Molecular dynamics simulations paired with Markov state modelling suggest that the nepenthesin insert allosterically controls PM V catalysis through multiple mechanisms.

microbiology↗

bioRxiv2021

A new species of the genus Microhyla Tschudi, 1838 (Amphibia: Anura: Microhylidae) from eastern India with notes on Indian species

A new species of the genus Microhyla, Microhyla bengalensis sp. nov., described from West Bengal state, India. The new species is distinguished from its congeners by a combination of the following morphological characters: 1) Small in size (SVL= 16.2 mm. in male); 2) truncated snout in dorsal view; 3) head wider than long (HW: HL= 1.36); 4) canthus rostralis and tympanum are indistinct; 5) nostril placed on the dorsal side of the snout; 6) tibiotarsal articulation not reaching the eye; 7) fingers and toes without disc; 8) toe webbing basal; 9) thigh and foot length are equal and smaller than shank; 10) skin tuberculated on dorsum; 11) teddy bear dark brown mark on dorsum; 12) an inverted V-shaped dark brown mark above the vent. A comparative morphological data of all the 14 Indian species of Microhyla is also provided.

zoology↗

bioRxiv2021

A new paradoxosomatid millipede, Manikidesmus suriensis (Polydesmida: Paradoxosomatidae) from West Bengal, India.

A new genus and species of the family Paradoxosomatidae from southern part of West Bengal, India is described. The new genus Manikidesmus gen. n. is diagnosed by combination of following characters: reduced paranota, distinct pleural keel, unpaired sternal lamella on 5th sternite, prefemur with setal brush, setal brush on tibia and tarsus in male, lamina medialis long straight with a curved hook, expanded post femoral lamina with a spine and tibiotarsus with a spine on the distofemoral process. The genus is distinguished from its Indian congeners by one or more diagnosed characters. In Manikidesmus suriensis, sp. n. tibia and tarsus bear setal brush in male (vs. absent in Oxidus and Chondromorpha), gonopod femur short, flat and without post femoral demarcation (vs. long, thin cylindrical with post femoral demarcation in Polydrepanum and Orthomorpha), tibiotarsus of gonopod long and a spine on the distofemoral process (vs. short and without spine in Anoplodesmus). In Kronopolites, coxa of gonopod densely bristled, collum with two rows of long bristles, femur long, slender and with a spine. All these characters are absent in the present genus. In Streptogonopus, gonopod femorite is distinctly demarcated from post femorite region and solenomere is twisted with solenophore but in the present species, femorite is not be separated from post femorite region and solenomere is free from solenophore.

zoology↗

bioRxiv2021

A new species of the genus Carlogonus (Spirostreptida: Harpagophoridae) from West Bengal, India.

A new species of Carlogonus, Carlogonus bengalensis is described from West Bengal, India. The adult is blackish brown in colour with a yellowish curved tail, round body with 60 segments, 55 mm in length, 5th segment of male bears a hump, telopodite of the gonopod long, flat and band like with a single curved antetorsal process, mesal process with a red spine, proplical lobe with a curved orange spine, inner surface of metaplical fold with sigilla, palette spatula like and a few blepharochatae at the apical margin. Male bears white pad on femur and tibia. Comparison was made with the "exaratus group" of the genus Carlogonus.

zoology↗

bioRxiv2021

A new species of the genus Euphlyctis (Anura: Dicroglossidae) from West Bengal, India

A new species of green frog of the genus Euphlyctis Fitzinger, 1843 is described from West Bengal, a state of eastern India. A robust frog, SVL of male 86mm and that of female 132mm. The species is diagnosed by the presence of following characters: green dorsum and female with a greenish white mid-dorsal line, tibiotarsal articulation reaches eye, male with two vocal sac openings at the junction of jaw, female is larger than male though body parameters is proportionately longer in male, nostril snout length 3.45% of SVL, nostril much closer to snout tip than eye, units of hind limb i. e. thigh, shank and foot are almost equal in length, relative length of finger: II < IV < I < III. The new species is compared with existing eight species of the genus Euphlyctis.

zoology↗

bioRxiv2020

Revision of Indian Bipaliid species with description of a new species, Bipalium bengalensis from West Bengal, India (Platyhelminthes: Tricladida: Terricola)

A new species of Bipaliid land planarian, Bipalium bengalensis is described from Suri, West Bengal, India. The species is jet black in colour without any band or line but with a thin indistinct mid-dorsal groove. Semilunar head margin is pinkish in live condition with numerous eyes on its margin. Body length (BL) ranged from 19.00 to 45.00mm and width varied from 9.59 to 13.16% BL. Position of mouth and gonopore from anterior end ranged from 51.47 to 60.00% BL and 67.40 to 75.00 % BL respectively. Comparisons were made with its Indian as well as Bengal congeners. Salient features, distribution and biometric data of all the 29 species of Indian Bipaliid land planarians are revised thoroughly. Genus controversy in Bipaliid taxonomy is critically discussed and a proposal of only two genera Bipalium and Humbertium is suggested.

zoology↗

bioRxiv2020

Deviation of Dyar's rule in the post-embryonic development in millipedes - a comprehensive analysis.

Dyars value on the basis of length and width of nine polydesmid and 15 non-polydesmid millipede species were calculated. The value of polydesmid millipede ranged from 1.50 to 1.78 and that of non-polydesmid millipede ranged from 1.08 to 1.45. Weight progression factor was determined for nine species of millipede (two polydesmid and seven non-polydesmids). The result showed that the mean weight progression factor in polydesmid is 2.54 while that of non-polydesmid is 1.95. Both the results showed that Dyars value in polydesmida is significantly higher compared to that of non-polydesmida. In polydesmida, the number of stadium is only eight with higher Dyars value (mean 1.61) while in non-polydesmida, where number of stadium is more than eight have lower Dyars value (mean 1.23). As in other arthropods, Dyars value is inversely proportional to the number of stadium in millipede. The present study also affirmed Enders hypothesis in favour of adaptive importance of Dyars rule. Deviations from Dyars constant in these two group also support Crossbys growth rule. The variation of Dyars value in these two groups of millipede is related to the development time and habitat utilization. The variation of weight progression factor in these two groups is also linked to the development time as observed in other arthropods.

zoology↗