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Dive Into the Science Behind It All 

What We Offer

High performance computing codes for advanced calculations

Software for Multiscale Modeling Inc. is a comprehensive solution to address requirements for Pharmaceutical Industry, and Material Science Requirements. The software solution provided consists of a system of high performance computing codes for advanced calculations of chemical processes in solution, designed based on molecular theory of solvation stemming from the  first principle statistical mechanics. A core engine to achieve solvation thermodynamics is the Three-Dimensional Reference Interaction Site Model (3D-RISM). It consists of efficient and well parallelized programs for standard computational chemistry applications in solution, extending to drug development platforms, material applications, and electronic structure simulations.

RISM calculation

RISM is rooted in the integral equation theory of liquids, where in statistical modelling of distribution functions of solvent, a picture of the dynamics of the system, can be obtained. The radial distribution functions (RDFs) are probabilistic functions for locating solvent at a specific distance from any reference point, e.g. any arbitrary shaped solute molecules. This is in turn gives the solvation structure around a solute of interest. We have carefully validated solvent models for different solvents, which are supplied as a prebuilt module for further use in research projects.

Quasidynamics with 3D-RISM-KH

–   not available in other software packages, including  Schrödinger software, Software for Chemistry & Materials, Molecular Operating Environment

 

Our Advantage and Strength

 

(1) Solvent + Co-solvent + Ions + Additives in a simulation setup – easy to emulate a real-life like situation.                  Examples of complex environment:  Blood-Brain Barrier permeability, Inhibitor Binding, Protein-Ligand Binding …

(2) Easy benchmarking protocol available for a large number of solvents for both biochemical and industrial process applications.

(3) Solvation parameters can be exported to use as descriptors in AI/ML applications in permeator design.

(4) Handling of simulation with concentration gradient in multiple solvents (and solutes) mixtures  makes it ideal for biologics design.

(5) Easy porting of 3D-RISM-KH available with AmberTools (and our custom interfacing) to initiate simulation starting from a molecular structure string as input.

Versatility in Application

The starting point of a RISM calculation is the Molecular Ornstein-Zernike (MOZ) equation, where a solvated system can be defined in 3D space by three spatial coordinates (r) and three angles (Θ). The resulting 6-dimensional equation is solved assuming spherical symmetry to get direct correlation function (effect of the first particle on the second one), and indirect correlation function (interaction of the first particle with the third one). To solve the MOZ equation, another equation, or a closure relation, is needed. There are a handful set of such closure equations available; viz. the HyperNetted Chain (HNC), Mean Spherical Approximation (MSA), Kovalenko-Hirata (KH), Kobryn-Gusarov-Kovalenko (KGK), etc. A choice of a closure relation is case specific, although the KH closure is extensively used, as it offers better numerical stability and parallelization.

Full Customer Experience Service

Application of the 3D-RISM-KH has been extensively validated for a multitude of  systems ranging from van der Waals liquid simulations to bio-nanomaterials property simulation in solvents. A unique nature of the 3D-RISM-KH theory is that it can incorporate variable ionic strength of solvation using concentrations of ions as key parameter in an otherwise very dilute solution.


A list of applications of the 3D-RISM-KH can be found in the scientific literature articles, the links to which are provided below.

3D-RISM Theory

  1. Chandler, D.; McCoy, J. D.; Singer, S. J. J. Chem. Phys., 1986, 85, 5971–5976. DOI: 10.1063/1.451510

  2. Kovalenko, A.; Hirata, F. Chem. Phys. Lett., 1998, 290, 237–244. DOI: 10.1016/S0009-2614(98)00471-0

  3. Kovalenko, A.; Hirata, F. J. Chem. Phys., 1999, 110, 10095–10112. DOI: 10.1063/1.478883

  4. Kovalenko A., Hirata F. J. Chem. Phys., 2000, 112, 10391–10402;10403–10417. DOI: 10.1063/1.481676

  5. Kovalenko, A. Three-dimensional RISM theory for molecular liquids and solid-liquid interfaces. In: Molecular Theory of Solvation. Hirata F. (Ed.), Understanding Chemical Reactivity Series. Vol. 24, Kluwer Academic Publishers, Norwell, 2003, Chapter 4, pp. 169–275.

  6. Gusarov, S.; Ziegler, T.; Kovalenko, A. J. Phys. Chem. A, 2006, 110, 6083–6090. DOI: 10.1021/jp054344t

  7. Gusarov, S.; Pujari B. S.; Kovalenko, A. J. Comput. Chem., 2012, 33, 1478–1494. DOI: 10.1002/jcc.22974

  8. Kovalenko, A. Partial Molar Volumes of Proteins in Solution: Prediction by Statistical–Mechanical, 3D–RISM–KB Molecular Theory of Solvation. In: Volume Properties: Liquids, Solutions and Vapours. Wilhelm, E., Letcher T. (Eds.), Royal Society of Chemistry, Cambridge, 2015, Chapter 22, pp. 575–610. DOI: 10.1039/9781782627043-00575

  9. Roy, D.; Kovalenko, A. 3D-RISM-KH Molecular Solvation Theory. In: Multiscale Dynamics Simulations: Nano and Nano-bio Systems in Complex Environments. Salahub, D. R.; Wei, D. (Eds.), RSC Publishing, London, 2021, Chapter 9, pp. 254–286. ISBN: 978-1-83916-178-0

  10. Roy, D.; Kovalenko, A. Solvation Free Energy by 3D-RISM-KH Theory. In: Gibbs Energy and Helmholtz Energy: Liquids, Solutions and Vapours. Wilhelm, E.; Letcher, T. M. (Eds.) RSC Publishing, London, 2022, Chapter 6, pp. 227–237. ISBN: 978-1-83916-201-5.

  11. Roy, D.; Kovalenko, A. Biomolecular Simulations with the Three-Dimensional Reference Interaction Site Model with the Kovalenko-Hirata Closure Molecular Solvation Theory.                Int. J. Molec. Sci., 2021, 22, 5061–14. DOI: 10.3390/ijms22105061

Solvation Free Energy and Solvent Maps with the 3D-RISM-KH Theory (including Ligand Mapping, Molecular Docking, and Molecular Partitioning)

  1. Stumpe, M. C.; Blinov, N.; Wishart, D.; Kovalenko, A.; Pande, V. S. Calculation of Local Water Densities in Biological Systems – A Comparison of Molecular Dynamics Simulations and the 3D-RISM-KH Molecular Theory of Solvation. J. Phys. Chem. B, 2011, 115, 319–328 (Journal Cover).

  2. Imai, T.; Miyashita, N.; Sugita, Y.; Kovalenko, A.; Hirata, F.; Kidera, A. Functionality Mapping on Internal Surfaces of Multidrug Transporter AcrB Based on Molecular Theory of Solvation: Implications for Drug Efflux Pathway. J. Phys. Chem. B, 2011, 115, 8288–8295 (Journal Cover).

  3. Nikolic, D.; Blinov, N.; Wishart, D.; Kovalenko, A. 3D-RISM-Dock: A New Fragment-Based Drug Design Protocol. J. Chem. Theory Comput., 2012, 8, 3356–3372.

  4. Nikolić, D.; Moffat, K. A.; Farrugia, V. M.; Kobryn, A. E.; Gusarov, S.; Wosnick, J. H.; Kovalenko, A. Multi-Scale Modeling and Synthesis of Polyester Ionomers. Phys. Chem. Chem. Phys., 2013, 15, 6128–6138.

  5. Kovalenko, A. Multiscale modeling of solvation in chemical and biological nanosystems and in nanoporous materials. Pure Applied Chem., 2013, 85, 159–199 (Invited Paper).

  6. Huang, W.-J.; Blinov, N.; Wishart, D. S.; Kovalenko, A. Role of Water in Ligand Binding to Maltose-Binding Protein: Insight from a New Docking Protocol Based on the 3D-RISM-KH Molecular Theory of Solvation. J. Chem. Inf. Model., 2015, 55, 317–328.

  7. Omelyan, I.; Kovalenko, A. MTS-MD of biomolecules steered with 3D-RISM-KH mean solvation forces accelerated with generalized solvation force extrapolation. J. Chem. Theory Comput., 2015, 11, 1875–1895.

  8. Kovalenko, A.; Gusarov, S. Multiscale methods framework: self-consistent coupling of molecular theory of solvation with quantum chemistry, molecular simulations, and dissipative particle dynamics. Phys. Chem. Chem. Phys., 2018, 20, 2947–2969 (Invited).

  9. Roy, D.; Kovalenko, A. Performance of 3D-RISM-KH in Predicting Hydration Free Energy: Effect of Solute Parameters. J. Phys. Chem. A, 2019, 123, 4087–4093.

  10. Hinge, V. K.; Roy, D.; Kovalenko, A. Predicting skin permeability using the 3D-RISM-KH theory based solvation energy descriptors for a diverse class of compounds. J. Computer-Aided Mol. Des., 2019, 33, 605–611.

  11. Hinge, V. K.; Roy, D.; Kovalenko, A. Prediction of P-glycoprotein inhibitors with machine learning classification models and 3D-RISM-KH theory based solvation energy descriptors. J. Computer-Aided Molec. Des., 2019, 33, 965–971.

  12. Hinge, V. K.; Blinov, N.; Roy, D.; Wishart, D. S.; Kovalenko, A. The role of hydration effects in 5-fluorouridine binding to SOD1: insight from a new 3D-RISM-KH based protocol for including structural water in docking simulations. J. Computer-Aided Mol. Des., 2019, 33, 913–926.

  13. Roy, D.; Hinge, V. K.; Kovalenko, A. To Pass or Not To Pass: Predicting the Blood−Brain Barrier Permeability with the 3D-RISM-KH Molecular Solvation Theory. ACS Omega, 2019, 4, 16774–16780.

  14. Roy, D.; Hinge, V. K.; Kovalenko, A. Predicting Blood-Brain Partitioning of Small Molecules Using a Novel Minimalistic Descriptor-Based Approach via the 3D-RISM-KH Molecular Solvation Theory. ACS Omega, 2019, 4, 3055–3060.

  15. Roy, D.; Dutta, D.; Wishart, D. S.; Kovalenko, A. Predicting PAMPA permeability using the 3DRISM-KH theory: Are we there yet? J. Computer-Aided Mol. Des., 2021, 35, 261–269.

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