BITS Faculty Publications

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Subject: search.filters.subject.Molecular dynamics (MD)

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    Multiscale modelling of thermally stressed superelastic polyimide
    (2025-04) Islam, Md Rushdie Ibne
    Many thermo-mechanical processes, such as thermal expansion and stress relaxation, originate at the atomistic scale. We develop a sequential multiscale approach to study thermally stressed superelastic polyimide to explore these effects. The continuum-scale smoothed particle hydrodynamics (SPH) model is coupled with atomistic molecular dynamics (MD) through constitutive modelling, where thermo-mechanical properties and equations of state are derived from MD simulations. The results are verified through benchmark problems of heat transfer. Finally, we analyse the insulating capabilities of superelastic polyimide by simulating the thermal response of an aluminium plate. The result shows a considerable reduction in the thermal stress, strain and temperature field development in the aluminium plate when superelastic polyimide is used as an insulator. The present work demonstrates the effectiveness of the multi-scale method in capturing thermo-mechanical interactions in superelastic polyimide.
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    In silico evaluation of bisphosphonates identifies leading candidates for SARS-CoV-2 RdRp inhibition
    (Elsevier, 2025-05) Garg, Mohit; Murugesan, Sankaranarayanan
    The novel coronavirus disease (COVID-19) pandemic has resulted in 777 million confirmed cases and over 7 million deaths worldwide, with insufficient treatment options. Innumerable efforts are being made around the world for faster identification of therapeutic agents to treat the deadly disease. Post Acute Sequelae of SARS-CoV-2 infection or COVID-19 (PASC), also called Long COVID, is still being understood and lacks treatment options as well. A growing list of drugs are being suggested by various in silico, in vitro and ex vivo models, however currently only two treatment options are widely used: the RNA-dependent RNA polymerase (RdRp) inhibitor remdesivir, and the main protease inhibitor nirmatrelvir in combination with ritonavir. Computational drug development tools and in silico studies involving molecular docking, molecular dynamics, entropy calculations and pharmacokinetics can be useful to identify new targets to treat COVID-19 and PASC, as shown in this work and our recent paper that identified alendronate as a promising candidate. In this study, we have investigated all bisphosphonates (BPs) on the ChEMBL database which can bind competitively to nidovirus RdRp-associated nucleotidyl (NiRAN) transferase domain, and systematically down selected seven candidates (CHEMBL608526, CHEMBL196676, CHEMBL164344, CHEMBL4291724, CHEMBL4569308, CHEMBL387132, CHEMBL98211), two of which closely resemble the approved drugs minodronate and zoledronate. This work and our recent paper together provide an in silico mechanistic explanation for alendronate and zoledronate users having dramatically reduced odds of SARS-CoV-2 testing, COVID-19 diagnosis, and COVID-19-related hospitalizations, and indicate that similar observational studies in Japan with minodronate could be valuable.
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    Proteome analysis of soybean root apoplast combined with alphafold prediction reveal macrophomina phaseolina infection strategies and potential targets for engineering resistance
    (2024-12) Chandrasekar, Balakumaran
    Macrophomina phaseolina (Tassi) Goid. is a hemibiotrophic pathogen that causes charcoal rot (CR) disease in various legumes, including soybean. To date, no reliable resistance gene sources have been identified in soybean or other legumes to combat M. phaseolina. Therefore, the identification of mechanistic targets is crucial for improving resistance against the pathogen. The apoplast is a critical region where intense molecular cross-talk occurs between plants and pathogens, and the outcome of their interactions is determined in this compartment. Here, we employed label-free quantitative (LFQ) proteomics to investigate the dynamics of soybean root apoplast during M. phaseolina infection. We have detected several secreted proteins of M. phaseolina and differential regulation of soybean-secreted proteins in root apoplast during infections. Glycome analysis and callose deposition assays have revealed changes in soybean root cell wall compositions and potential polysaccharide targets of M. phaseolina. AlphaFold 2 (AF2) analysis was instrumental in revealing several interesting sequence-unrelated structurally similar (SUSS) effectors and effectors with novel structural folds secreted by M. phaseolina. Structured-guided engineering of protease-inhibitor complexes is emerging as an important strategy to engineer resistance in plants against pathogens. AlphaFold Multimer (AFM) analysis of candidate-secreted proteins from soybean and M. phaseolina has predicted cysteine and serine protease-inhibitor complexes with high confidence. We have validated these interactions using molecular dynamics (MD) and competitive activity-based protein profiling (ABPP) approaches. Therefore, our work provides insights into Soybean-M. phaseolina interactions in the root apoplast and unveil potential candidates for engineering resistance
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    A structure-based pharmacophore modelling approach to identify and design new neprilysin (NEP) inhibitors: An in silico-based investigation
    (Elsevier, 2024-06) Gaikwad, Anil Bhanudas
    Neutral endopeptidase or neprilysin (NEP) cleaves the natriuretic peptides, bradykinin, endothelin, angiotensin II, amyloid β protein, substance P, etc., thus modulating their effects on heart, kidney, and other organs. NEP has a proven role in hypertension, heart disease, renal disease, Alzheimer's, diabetes, and some cancers. NEP inhibitor development has been in focus since the US FDA approved a combination therapy of angiotensin II type 1 receptor inhibitor (valsartan) and NEP inhibitor (sacubitril) for use in heart failure. Considering the importance of NEP inhibitors the present work focuses on the designing of a potential lead for NEP inhibition. A structure-based pharmacophore modelling approach was employed to identify NEP inhibitors from the pool of 1140 chemical entities obtained from the ZINC database. Based on the docking score and pivotal interactions, ten molecules were selected and subjected to binding free energy calculations and ADMET predictions. The top two compounds were studied further by molecular dynamics simulations to determine the stability of the ligand-receptor complex. ZINC0000004684268, a phenylalanine derivative, showed affinity and complex stability comparable to sacubitril. However, in silico studies indicated that it may have poor pharmacokinetic parameters. Therefore, the molecule was optimized using bioisosteric replacements, keeping the phenylalanine moiety intact, to obtain five potential lead molecules with an acceptable pharmacokinetic profile. The works thus open up the scope to further corroborate the present in silico findings with the biological analysis.
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    Novel hydrazine derivatives as selective DPP-IV inhibitors: findings from virtual screening and validation through molecular dynamics simulations
    (Springer, 2014-04) Kumar, Gautam
    The present study demonstrates and validates the discovery of two novel hydrazine derivatives as selective dipeptidyl peptidase-IV (DPP-IV) inhibitors. Virtual screening (VS) of publicly available databases was performed using virtual screening workflow (VSW) of Schrödinger software against DPP-IV and the most promising hits were selected. Selectivity was further assessed by docking the hits against homology modeled structures of DPP8 and DPP9. Two novel hydrazine derivatives were selected for further studies based on their selectivity threshold. To assess their correct binding modes and stability of their complexes with enzyme, molecular dynamic (MD) simulation studies were performed against the DPP-IV protein and the results revealed that they had a better binding affinity towards DPP-IV as compared to DPP 8 and DPP 9. The binding poses were further validated by docking these ligands with different softwares (Glide and Gold). The proposed binding modes of hydrazines were found to be similar to sitagliptine and alogliptine. Thus, the study reveals the potential of hydrazine derivatives as highly selective DPP-IV inhibitors.
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    Inspection of in-house designed novel thiochromone amino-acid conjugate derivatives as Lm-NMT inhibitor – An in-silico analysis
    (Elsevier, 2023-03) Murugesan, Sankaranarayanan
    Leishmaniasis is a complex neglected tropical disease caused by various leishmanial parasites that primarily affect the world's poorest people. A limited number of standard medications are available for this disease that has been used for several decades, which have drawbacks such as resistance, higher cost, and patient compliance, making it difficult to reach the poor. The search for novel chemical entities to treat leishmaniasis has led to target-based scaffold research. Thiochromone moieties in conjugation with aromatic amino acids have been considered for the study, along with possible substitutions of the electron-withdrawing and electron-donating groups. N-myristoyl transferase (NMT) has been selected as the molecular target for the study responsible for protein-protein interaction and ribosylation of proteins necessary for the growth inside the human body of the parasite. The designed novel thiochromone analogs were docked against the selected leishmanial NMT using the in-silico methods, physicochemical and toxicity properties were predicted, and Structure-Activity Relationship was also established in-silico. Finally, a molecular dynamics simulation study for 100 ns gave an idea about the stability of the protein-ligand complex. A time frame analysis of each 10 ns confirmation was also studied to understand better the putative binding pattern designed analogs.
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    Synthesis, anti-acetylcholinesterase evaluation, molecular docking and molecular dynamics simulation of novel psoralen derivatives
    (Bentham Science, 2024-02) Murugesan, Sankaranarayanan
    Seven new psoralen derivatives were synthesised by carbodiimide coupling to active carboxylic acid to amide formation in mild reaction conditions. Methods: The psoralen derivatives were produced through the condensation of seven different types of amine groups consisting of electron withdrawing groups and electron donating groups. Results: All the synthesised compounds were obtained with moderate to high yields. Structural characterization using ATR-FTIR, 1H NMR, 13C NMR, and HRMS has confirmed their structure. Moreover, in silico evaluation of the psoralen derivatives against the AChE enzyme was performed, and acetylcholinesterase inhibitory activity of psoralen derivatives was also conducted. Conclusion: Results from molecular docking show the potential of compound 12e as AChE inhibitors due to its highest binding energy value. It was further supported by the antiacetylcholinesterase activity of compound 12e, which has 91.69% inhibition, comparable to galantamine (94.12%). Furthermore, 100 ns run molecular dynamics (MD) simulation was used to refine docking results.
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    Molecular docking and dynamics identify potential drugs to be repurposed as sars-cov-2 inhibitors
    (World Scientific, 2024) Murugesan, Sankaranarayanan
    The novel coronavirus disease 19 (COVID-19) has resulted in an estimated 20 million excess deaths and the recent resurgence of COVID-19 in China is predicted to result in up to 1 million deaths over the next few months. With vaccines being ineffective in the case of immunocompromised patients, it is important to continue our quest for safe, effective and affordable drugs that will be available to all countries. Drug repurposing is one of the strategies being explored in this context. Recently, out of the 7817 drugs approved worldwide, 214 candidates were systematically down-selected using a combination of 11 filters including FDA/TGA approval status, assay data against SARS-CoV-2, pharmacokinetic, pharmacodynamic and toxicity profiles. These down-selected drugs were subjected in this study to virtual screening against various SARS-CoV-2 targets followed by molecular dynamics studies of the best scoring ligands against each target. The chosen molecular targets were spike receptor binding domain, nucleocapsid protein RNA binding domain and key nonstructural proteins 3, 5 and 12–14. Four drugs approved for other indications — alendronate, cromolyn, natamycin and treprostinil — look sufficiently promising from our in-silico studies to warrant further in-vitro and in-vivo investigations as appropriate to ascertain their extent of antiviral activities.
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    Molecular docking and in silico adme(t) evaluation of selective phytochemical inhibitors of vegf2 target for the treatment of diabetic retinopathy
    (Bentham Science, 2024-10) Murugesan, Sankaranarayanan
    Diabetic retinopathy (DR) is the leading cause of vision loss in diabetic patients. Currently, the treatment involves the use of glucocorticoids or a VEGF antagonist, which are “off-label” at present. However, the conventional method of drug discovery and development is a time-consuming process that requires more than a decade of meticulous research and huge financial support. While there are a few effective small organic molecules against DR that were identified many years ago, nutraceuticals - naturally available functional foods containing vitamins, antioxidants, minerals, fatty acids, and amino acids - can also help delay the progression of some diseases.
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    Atomic scale insights into material removal mechanisms in nanoscale machining of copper beryllium
    (Sage, 2023-12) Kumar, Amit; Sharma, Anuj
    The heterogeneous nature of the copper beryllium (CuBe) workpiece because of the presence of hard particles tends to affect material removal. When machining a CuBe material, it is anticipated that the mechanism of cutting and surface formation may differ from those seen when cutting a homogenous Cu material. Although these mechanisms are popular for the diamond turning of homogeneous materials, they have not been thoroughly studied in relation to CuBe alloys, which contain hard beryllium precipitates. Therefore, the effect of hard particles in the workpiece specimen on the nano-regime diamond turning of CuBe alloy needs to be understood. To explain the influence of Beryllium (Be) particles on the cutting tool and the workpiece surface, a molecular dynamics (MD) simulation was performed. It is revealed that the material removal mechanism in the case of CuBe is phase-dependent. Ductile machining is dominant in the Cu phase, and brittle fracture is dominant in the Be rich phase. It is also observed that the a/r ratio equal to 1 is suitable for cutting in the Cu phase and for ductile regime machining conditions in the Be phase. The a/r ratio higher than 1 causes higher cutting forces, and thus shear plane cutting takes place, which leads to a higher amount of material removal.