Molsoft develops new technology and proprietary algorithms for molecular
modeling with applications to protein and small molecule structure prediction,
docking and structure based drug design; molecular visualization and animation,
bioinformatics, cheminformatics, and laboratory information management systems.
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Internal Coordinate Mechanics (ICM) MolSoft's ICM software package is based on the internal coordinates (IC) representation of molecular objects that naturally reflects the covalent bond geometry of molecules (Abagyan et al., 1994). Unlike simple Cartesian coordinates, IC variables consist of covalent bond lengths and angles, torsion angles and six positional coordinates of a molecular object. Because of chemical bond rigidity, most molecular objects can be accurately represented by free torsion variables while keeping covalent bond coordinates fixed. This dramatically reduces the number of free variables in the system without sacrificing accuracy, while improving convergence time for conformational optimizations at least 1000-fold. Moreover, further reduction of free variable space and system complexity in ICM can be achieved by effectively freezing IC variables in more rigid or less important parts of the model. When carefully applied and validated, such complexity reductions reduce unnecessary noise in the modeling system and enable faster and more reproducible energy optimizations.
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Biased Probability Monte Carlo The core technology used in most of our structure prediction algorithms is
global free energy optimization in a subset of internal coordinates that
describes inter or inter-molecular geometry. For structure prediction and large
scale conformational sampling ICM employs a family of new global optimization
techniques such as: Biased Probability Monte Carlo (Abagyan and Totrov, 1994), pseudo-Brownian docking algorithm (Abagyan et al., 1994) and local deformation loop movements (Abagyan and Mazur, 1989 ).
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3D Ligand Editor The ICM Ligand Editor is an intuitive graphical interface for ligand optimization and drug design. The editor was developed in close collaboration with Medicinal Chemists at Novartis and designed for ease of use and high accuracy ligand modeling. The ligand editor is available in ICM-Pro and ICM-Chemist-Pro.
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Novartis FOCUS MolSoft and Novartis have developed a new desktop modeling and communication environment for drug discovery called FOCUS based on MolSoft's Internal Coordinate Mechanics (ICM) software. The FOCUS platform is described in a publication in the ACS Journal of Chemical Information and Modeling (see Stiefl et al 2015). FOCUS is a platform that helps users communicate chemical and structural data, develop new ideas and support decision making during the drug design cycle. FOCUS can be integrated into an informatics and high performance computing environment giving the user a single interface to many capabilities.
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Induced Fit Docking ICM contains a selection of tools to account for pocket flexibility (induced fit) in docking and virtual screening. The importance of considering flexibility in proteins is well understood (1-3) and is an important consideration when undertaking structure-based drug design. There are three main approaches in ICM for incorporating induced fit:
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Atomic Property Fields The Atomic Property Field (APF) method developed by MolSoft ( Totrov 2008) is a 3D pharmacophoric potential implemented on a continuously distributed grid which can be used for ligand docking and scoring. APF can be generated from one or more high affinity scaffolds and seven properties are assigned from empiric physico-chemical components.
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Rapid Isostere Discovery Engine (RIDE) RIDE is a fast 3D molecular similarity search method based on Atomic Property Fields, developed at MolSoft. RIDE searches databases of compound conformers for molecules that are isosteric to the query, i.e. have similar 3D configurations and distributions of atomic properties.RIDE is available in the ICM-Pro + VLS package.
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PROTAC Modeling Targeted Protein Degradation (TPD) is an approach that is attracting substantial interest for modulating challenging drug
targets. A major class of TPDs are Proteolysis-Targeting Chimera protein degraders (PROTACs). PROTACs are heterobifunctional molecules where two ligands are joined by linker. One ligand recruits the target and the other recruits and binds an E3 ubiquitin ligase. This interaction induces ubiquitylation of the target and degradation by the ubiquitin-proteasome system, the PROTAC is then recycled.
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RNA Drug Discovery
MolSoft has a long history of developing methods for RNA drug discovery. The first ever successful virtual screen was against an RNA-protein interaction (tat-TAR). RNA drug discovery companies such as Arrakis Therapeutics, Novartis and Nymirum have published success stories using MolSoft ICM. More...
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ICM Cloud
All ICM products can be run on the cloud - AWS, Google Cloud or Azure. You can read about the World's Largest ever virtual screen resulting in 3 new lead compounds from Novartis and a 680 million structure-based screen performed in 24 hours by USC. More...
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ICM - Internal Coordinate Mechanics
MolSoft's ICM software package is based on the internal coordinates (IC) representation of molecular objects that naturally reflects the covalent bond geometry of molecules (Abagyan et al., 1994). Unlike simple Cartesian coordinates, IC variables consist of covalent bond lengths and angles, torsion angles and six positional coordinates of a molecular object. Because of chemical bond rigidity, most molecular objects can be accurately represented by free torsion variables while keeping covalent bond coordinates fixed. This dramatically reduces the number of free variables in the system without sacrificing accuracy, while improving convergence time for conformational optimizations at least 1000-fold. Moreover, further reduction of free variable space and system complexity in ICM can be achieved by effectively freezing IC variables in more rigid or less important parts of the model. When carefully applied and validated, such complexity reductions reduce unnecessary noise in the modeling system and enable faster and more reproducible energy optimizations.
Global Energy Optimization
The core technology used in most of our structure prediction algorithms is
global free energy optimization in a subset of internal coordinates that
describes inter or inter-molecular geometry. For structure prediction and large
scale conformational sampling ICM employs a family of new global optimization
techniques such as: Biased Probability Monte Carlo (Abagyan and Totrov, 1994), pseudo-Brownian docking algorithm (Abagyan et al., 1994) and local deformation loop movements
(Abagyan and Mazur, 1989 ).
Structure-based Prioritization of Protein Targets
The icmPocketFinder procedure identifies the substrate binding pockets in 98%
of all the cases (tested on over 10,000 pockets) An et al 2004). This procedure is based on
calculating the drug-binding density field and contouring it at a certain
level. In 2001 we published a fast procedure for accurate electrostatic
calculation using the boundary element algorithm (Totrov and Abagyan 2001). A combination of
"pocket-density" with other physical properties such as electrostatic
potential, hydrophobicity, hydrogen bonds is used to evaluate if a particular
protein target or protein-protein interface is "drugable" and prioritize the
targets. We developed a special procedure to improve the pocket models by
co-optimization of flexible pockets with some of the know ligands.
Accurate Fully Flexible Ligand Docking
We developed a fast and accurate algorithm for docking a continuously flexible
ligand in represented to a receptor pocket. In a benchmark study on 11
different receptors, the ICM flexible docking algorithm correctly docked 93% of
all ligand receptor pairs!
Virtual Ligand Screening
A particularly fast implementation of the flexible docking algorithm is used to
screen millions of compounds from vendor databases or in-house libraries. Our
technology allows to index and convert to 3D any chemical database in .sdf,
.mol or mol2 formats, then dock all the molecules and score them by estimated
binding affinity. The main purpose of this procedure is to separate binders and
non-binders and eliminate at least 99% of compounds which do not fit the pocket
and do not need to be experimentally tested. We have several different scoring
functions including a score based on the potential of mean force. The consensus
scoring reduces the number of false positives. The Molsoft-ICM docking and
virtual ligand screening was tested in benchmarks, competitions and, most
importantly, in several experimental lead discovery projects, including
discovery of novel RAR agonists [
sch01 ], antagonists [
sch00 ], RNA binders
[ fil02 ], FGFR tyrosine kinase inhibitors, Thyroid hormone receptor antagonists,
and PTB1B inhibitors.
Homology Modeling and Structure Prediction
Models of protein structure can be used for decision support in drug discovery,
e.g. prioritizing targets by 'drugability', for docking and virtual ligand
screening, for directing chemistry in lead optimization, for directing protein
functional studies via mutagenesis, as search models for molecular replacement,
etc... Molsoft developed proprietory technologies for:
- template finding: sensitive sequence search (or threading) to
identify one or several structural templates for further homology modeling
using full alignments with zero-end-gaps (ZEGA) and empirical structural
statistical significance [Abagyan, Batalov J.Mol.Biol. 1997]
- accurate treading or sequence-structure alignment using the ICM alignSS
algorithm that optimizes the sequence-structure match using residue
accessibilities, secondary structures and functional sites of the template and
sequence plus predicted secondary structure of the query sequence.
- fast homology model building and database loop searches with the build model
function. This algorithm builds a full model with all the loops in seconds.
Each loop searched in a full PDB database and selected on the basis of its
interaction energy with the loop environment.
- loop prediction through local global optimization
- model refinement using ICM global optimization algorithm
- local reliability prediction To assign a reliability value to each residue in
the model we developed algorithms including statistical potential or full
residue energies after refinement, plus by the local properties of the
alignments.
The ICM homology modeling algorithms have been successfully used in modeling
competitions [e.g. car95, hom97 ], benchmarks [ ras97 ], and in many research
projects [ sch01, nor01, tom00, sch00, kel00, gan00, car98, pat98,
sri98, yud97, yui97, mat97, etc.]
Global Optimization of Compound Geometries
In addition to an internal coordinate force field, Molsoft-ICM platform allows
to perform global optimization and analysis of small molecule geometries by
performing free geometry optimization in Cartesian space using the MMFF94 force
field including fully automated atom type assignments. The conformational
generation procedure accumulates a non-redundant set of representative
molecular geometries.
Molsoft-ICM Scripting Language and Molecular Environment
Molsoft has developed more than several focused applications, we designed and
developed the whole computational environment for bioinformatics,
cheminformatics, protein modeling, protein design, docking and screening. The
environment is tied together by a common scripting language for molecules,
numbers, strings, vectors, matrices, tables, sequences, alignments, profiles
and maps This environment covers molecular graphics and production of molecular
animations.
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