Force fields are mathematical functions used to describe potential energy in molecular modeling simulations. Common classical force fields include AMBER, CHARMM, GROMACS, GROMOS, and MMFF. AMBER was developed at UCSF and has parameter sets for proteins, nucleic acids, small molecules. GROMACS is a molecular dynamics software that supports different force fields like AMBER and CHARMM. GROMOS is a united atom force field optimized for alkanes. MMFF is derived from quantum calculations and experimental data for drug-like molecules. CHARMM was developed at Harvard and has broad coverage of biomolecules and organic compounds.
Molecular Mechanics in Molecular ModelingAkshay Kank
In this slide you learn about the computational chemistry and its role in designing a drug molecule. Also learn concept about the molecular mechanics and its application to Computer Aided Drug Design. difference between the Quantum mechanics and Molecular Mechanics.
Homology modeling, also known as comparative modeling of protein, refers to constructing an atomic-resolution model of the "target" protein from its amino acid sequence and an experimental three-dimensional structure of a related homologous protein.
Molecular Mechanics in Molecular ModelingAkshay Kank
In this slide you learn about the computational chemistry and its role in designing a drug molecule. Also learn concept about the molecular mechanics and its application to Computer Aided Drug Design. difference between the Quantum mechanics and Molecular Mechanics.
Homology modeling, also known as comparative modeling of protein, refers to constructing an atomic-resolution model of the "target" protein from its amino acid sequence and an experimental three-dimensional structure of a related homologous protein.
HERE IN THIS PRESENTATION HY HOMOLOGY MODELING IS EXPLAIN , WITH EXAMPLES OF PROTEIN PRIMARY AND SECONDARY, SHOWING THE IMAGES FORM WHICH MAKES EASY TO UNDERSTAND
THE ENERGY MINIMIZATION, FOR THE STUDENTS OF M.PHARM, B.PHARM AND OTHERS USEFUL FOR ACADEMIC TOO. THE PRESENT DATA IS MOST USEFUL FOR PHARMACY PURPOSE.
Energy minimization methods - Molecular ModelingChandni Pathak
Methods to minimize the energy of molecules during drug designing - Computational chemistry. According to the PCI syllabus, B.Pharm 8th Sem - Computer-Aided Drug Design (CADD).
Prediction of the three dimensional structure of a given protein sequence i.e. target protein from the amino acid sequence of a homologous (template) protein for which an X-ray or NMR structure is available based on an alignment to one or more known protein structures
The screening of chemical libraries with traditional methods, such as high-throughput screening (HTS), is expensive and time consuming. Quantitative structure–activity relation (QSAR) modeling is an alternative method that can assist in the selection of lead molecules by using the information from
reference active and inactive compounds. This approach requires good molecular descriptors that are representative of the molecular features responsible for the relevant molecular activity.
Ab Initio Protein Structure Prediction is a method to determine the tertiary structure of protein in the absence of experimentally solved structure of a similar/homologous protein. This method builds protein structure guided by energy function.
I had prepared this presentation for an internal project during my masters degree course.
HERE IN THIS PRESENTATION HY HOMOLOGY MODELING IS EXPLAIN , WITH EXAMPLES OF PROTEIN PRIMARY AND SECONDARY, SHOWING THE IMAGES FORM WHICH MAKES EASY TO UNDERSTAND
THE ENERGY MINIMIZATION, FOR THE STUDENTS OF M.PHARM, B.PHARM AND OTHERS USEFUL FOR ACADEMIC TOO. THE PRESENT DATA IS MOST USEFUL FOR PHARMACY PURPOSE.
Energy minimization methods - Molecular ModelingChandni Pathak
Methods to minimize the energy of molecules during drug designing - Computational chemistry. According to the PCI syllabus, B.Pharm 8th Sem - Computer-Aided Drug Design (CADD).
Prediction of the three dimensional structure of a given protein sequence i.e. target protein from the amino acid sequence of a homologous (template) protein for which an X-ray or NMR structure is available based on an alignment to one or more known protein structures
The screening of chemical libraries with traditional methods, such as high-throughput screening (HTS), is expensive and time consuming. Quantitative structure–activity relation (QSAR) modeling is an alternative method that can assist in the selection of lead molecules by using the information from
reference active and inactive compounds. This approach requires good molecular descriptors that are representative of the molecular features responsible for the relevant molecular activity.
Ab Initio Protein Structure Prediction is a method to determine the tertiary structure of protein in the absence of experimentally solved structure of a similar/homologous protein. This method builds protein structure guided by energy function.
I had prepared this presentation for an internal project during my masters degree course.
Force field analysis - Organizational Change and Development - Manu Melwin Joymanumelwin
It provides a framework for looking at the factors (forces) that influence a situation, originally social situations.
It looks at forces that are either driving movement toward a goal (helping forces) or blocking movement toward a goal (hindering forces).
The principle, developed by Kurt Lewin.
Associate Professor Regine Wagner's workshop slides. Workshop to support the FLI, CSU (Aus) & Massey (NZ) research project “Fostering institutional change through distributive leadership approaches: Engaging academics and teaching support staff in blended and flexible learning”is being conducted as a partnership between CSU and Massey Universities.
The research methodology includes a force field analysis as a mechanism for analysing and describing the driving and constraining forces that shape the project at international, national, and local institutional levels.
This event featured an update from the Presidential Commission for the Study of Bioethical Issues delivered by Michelle Groman (HLS '05), Associate Director at the Bioethics Commission. Since its inception in 2009, President Obama's Commission has issued reports on synthetic biology, human subjects research, whole genome sequencing, pediatric medical countermeasure research, and incidental findings. Currently, the Commission is examining the ethical implications of neuroscience research and the application of neuroscience research findings as part of the federal government’s BRAIN Initiative. The Commission also has developed educational materials to support teaching of bioethics ideas, principles, and theories in traditional and non-traditional settings.
The final half-hour of the event featured a discussion of career opportunities in law and bioethics, led by Ms. Groman and Holly Fernandez Lynch, Petrie-Flom Center Executive Director.
My introduction to electron correlation is based on multideterminant methods. I introduce the electron-electron cusp condition, configuration interaction, complete active space self consistent field (CASSCF), and just a little information about perturbation theories. These slides were part of a workshop I organized in 2014 at the University of Pittsburgh and for a guest lecture in a Chemical Engineering course at Pitt.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
2. What is a force field?
In the context of molecular
modelling, a force field refers to the
form and parameters of
mathematical functions used to
describe the potential energy of a
system of particles
3. Types of force fields
• All atom
• united atom
• coarse grained
Classical force fields:
AMBER GROMACS GROMOS
CHARMM MMFF MM2/MM3
4. •
• developed by : late Peter Kollman's group at the University of California,
San Francisco.
• AMBER is also the name for the molecular dynamics software package
http://ambermd.org/
family of AMBER force fields: (on basis of parameter sets)
1.ff09/ff03 etc. :Peptide, protein and nucleic acid
parameters
2. GAFF (Generalized AMBER force field): parameters
for small organic molecules
3. GLYCAM: for simulating carbohydrates
5. AmberFFC is designed to convert six
AMBER force fields (FF) (Amber 91, Amber
91X, Amber 94, Amber 96, Amber 98 and
Amber 99) freely available in the public
domain, for use with commercial molecular
modeling packages, using the Accelrys Inc.
6. In this different AMBER potentials models
are ported for use in the GROMACS MD
suite. AMBER ports for GROMACS versions
3.1.4, 3.2.1, and 3.3/3.3.1 have been tested
against AMBER 8.0
• AMBER-94
• AMBER-96
• AMBER-GS
• AMBER-99
• AMBER-99f
• AMBER-99SB
7. • GROMACS (GROningen MAchine for Chemical Simulations) is a molecular
dynamics simulation package.(it is not a force field)
• developed at the University of Groningen.
• simulates the Newtonian equations of motion for systems with hundreds
to millions of particles.
• http://www.gromacs.org
• rewritten in the C programming language from the Fortran77-based
program GROMOS, which had been developed in the same group.
8. • support for different force fields makes GROMA
For example, AMBER,CHARMM can be applied
9. Usage of Gromacs
• GROMACS is open source software released under the GPL.
The program is written for Unix-like operating systems; it can
run on Windows machines if the Cygwin Unix layer is used
• It is primarily designed for biochemical molecules like proteins,
lipids and nucleic acids that have a lot of complicated bonded
interactions.
• but since GROMACS is extremely fast at calculating the
Nonbonded interactions (that usually dominate simulations)
many groups are also using it for research on non-biological
systems, e.g. polymers.
10. • GROMOS(GROningen MOlecular Simulation com
is a force field for molecular dynamics simulati
University of Groningen.
• The united atom force field was optimized with
phase properties of alkanes.
• GROMOS is also the name for the molecular dyn
associated with this force field.
11. Versions of Gromos
• GROMOS87
• GROMOS96
• GROMOS05
• GROMOS11
There is also inclusion of the so-called "ffgmx“
force field, which is somewhat of a derivative of
the GROMOS87 force field.
13. MMFF
• MMFF is a class II force field derived from ab- initio calculations
and experimental data.
• It is designed to be a transferable force field for pharmaceutical
compounds that accurately treats conformational energetics
and nonbonded interactions .
Use of MMFF
MMFF has a wide coverage for all organic molecules for drug design.
Limitation
• less accurate for protein simulations in explicit solvent .
• MMFF currently cannot be run with simulations in parallel mode
14. CHARMM
• CHemistry at HARvard Macromolecular Mechanics.
• The commercial version of CHARMM, called CHARMm
(note the lowercase 'm'), is available from Accelrys.
• It is class I force field & has the broadest coverage for organic molecules
amongst all the force fields .
The CHARMm forcefield has optimized parameters for:
• proteins and nucleic acids
• organic molecules
non-standard amino acids
non-standard nucleic acid bases
co-factor
• metal ions
16. Types of CHARMM
• CHARMm Polar H
• charmm19
• charmm22
• charmm27
Use of CHARMM
The CHARMm force field can be used for simulations with different solvent
models, including explicit solvents and various types of generalized Born implicit
solvent models. With a broad coverage for organic molecules and an adequate
accuracy for proteins , the CHARMm force field is widely used for studying
protein-ligand, protein-protein interactions.