UMH - MOLECULAR MODELING

MOLECULAR MODELING

Course

Code: 1404

Degree: Bachelor's in Biotechnology

Faculty of Experimental Sciences

Year: Year 3 of Bachelor's in Biotechnology

Semester: Spring

Type: Required

Language: Spanish

ECTS credits: 6

Lecture: 3

Laboratory: 3

Hours: 150

Directed: 60

Shared: 5

Autonomous: 85

Subject matter: Techniques in Biotechnology

Module: Bioengineering

Degree website

Department: Biochemistry and Molecular Biology

Area: BIOCHEMISTRY AND MOLECULAR BIOLOGY

Course instructors are responsible for the course content descriptions in English.

Description

In silico molecular construction. Computational design of ligands. molecular docking. Search for structure-function relationships. Theoretical evaluation of molecular energy. Biomimetic.

Faculty

Name	Coordinator	Lecture	Laboratory
FERNÁNDEZ BALLESTER, GREGORIO JOAQUIN	■	■	■
DEVESA GINER, ISABEL			■
FERNANDEZ ESCAMILLA, ANA MARIA			■

Professional interest

The contents addressed in the subject of Molecular Modeling are intended to instruct the student in the fundamentals of the construction and manipulation of biomolecules in silico, in order to get the skills needed to search, design and develop molecular models that describe living things at the molecular level. For this purpose, the theoretical foundations needed to understand the molecular modeling applied to Biotechnology are shown. Then, the methodology needed to create and modify molecules, including the most common modeling techniques as well as molecular docking is described. After the need to refine the models created with minimization techniques and molecular dynamics is addressed. Finally, the most important applications of molecular modeling are discussed: the protein engineering approach and methods necessary to modify or improve existing molecules; next, the interactions that occur between biomolecules are explained, highlighting the transitional type (ligand-receptor), mainly protein-protein, protein-DNA, protein-carbohydrate and protein-lipid, and the prediction of protein function. The following stage describes how to find and validate new therapeutic targets and their possible application as therapeutic methods and molecular diagnosis. The interest of systems biology, since biomolecules do not act alone, but in combination with other molecules in complex molecular assemblies is also studied. The interest of directed evolution methods of protein and experimental techniques and scanning selection targets, with reference to the virus replication tools and gene expression is outlined. Throughout the program, a comprehensive explanation of the necessary bioinformatics tools as well as the underlying theory are portrayed, in order to perform molecular modeling of bioactive substances and computer simulation of possible interactions that can be predicted, to put them later into practice.

Competencies and learning outcomes

General competencies

Acquisition of basic scientific knowledge.
Capacity to identify, formulate, and resolve basic problems.
Ability to use the tools and instruments necessary for designing experiments and understanding the limits of the experimental approach.
Capacity to apply analytical and numerical methods for the analysis of problems.
Ability to implement efficient tools for troubleshooting within the field of knowledge.
Capacity for continuous improvement, experimentation, and innovation.
Critical and analytical skills in the field of the sciences.
Creative capacity within the field of the branch of knowledge.
Capacity to evaluate, optimize, and compare criteria in decision making.
Capacity to draft, represent, analyze, and interpret scientific documentation and relevant data within the branch of science.
Ability to transmit knowledge acquired in expert and non-expert environments.
Ability to work with multidisciplinary and multicultural teams.
Ability to update knowledge within the branch of sciences.
Social, ethical, and environmental commitment for the development of scientific solutions that are compatible and sustainable with the realities of human and natural environments.
Ability to adapt to and update new knowledge and scientific advances, adopting an ethical, innovative, and creative attitude in the practice of the profession.

Specific competencies

Ability to recognize and understand the molecular bases of biotechnological processes.
Acquire skills in instrumental and computation techniques used in biotechnology and know how to choose those most suitable for a specific biotechnological process.
Obtain sufficient ability to search for, design, and develop bioactive molecules.
Learn to find and validate new therapeutic targets and acquire skills in methods of molecular diagnosis and therapy.
Ability to analyze the usefulness of enzymes and their use in bioindustrial processes.
Apply basic mathematic fundamentals for the study and modeling of biological processes.

Objectives (Learning outcomes)

01Contextualize and define the discipline of Molecular Modeling.
02Describe in detail the structural characteristics of the biomolecules.
03Define the foundations and theoretical calculation in molecular mechanics.
04To know the primary and secondary sequence database, and structure databases, simple and composed.
05Build and modify proteins, lipids, carbohydrates and DNA and complex derivatives and understand the usefulness of libraries of molecular fragments.
06Learn the methodology needed to carry out the homology modeling of proteins, protein complexes, and molecular docking.
07Understand and apply the methods of optimization of molecular models: minimization and molecular dynamics.
08Modifying existing biomolecules to change its function or increase thermal stability.
09Predicting protein function from molecular models.
010Describe the experimental and computational methods of scanning and selection of target molecules.
011Describe the steps necessary to discover biologically active molecules.
012Managing technology applications for molecular modeling.
013Learn how to use reference sources, websites, databases and any other Internet resource, and make reports of work done in the computer lab.
014Acquire computer skills that enable the management and transfer of data (X Server, Terminal Server, SFTP, SSH) on Linux and Windows architectures.

Teaching units

Association between objectives and units

Objective/Unit	U1	U2	U3	U4	U5
01
02
03
04
05
06
07
08
09
010
011
012
013
014

Schedule

Week	Teaching units	Directed hours	Shared hours	Autonomous hours	Total hours
1	U1,U2	5	0	5	10
2	U2	5	0	5	10
3	U2,U3	5	0	5	10
4	U3	7	0	3	10
5	U3,U4	6.5	0	3.5	10
6	U4	3.5	0	6.5	10
7	U4	5.5	0	4.5	10
8	U4	4	1	5	10
9	U4,U5	5	0	5	10
10	U4,U5	2.5	1	6.5	10
11	U4,U5	5.5	0	4.5	10
12	U4,U5	4.5	0	5.5	10
13	U5	1	1	8	10
14	U5	0	1	9	10
15	U5	0	1	9	10

Basic bibliography

Software

APBS
FILEZILLA
MV Ubuntu 2016
Marvin 6
OPENOFFICE
PUTTY
PYMOL
PYTHON27
SSH Secure Shell
Spdbv
TREEVIEW
VMD
Vmware Player
YASARA - 13
foldit

Methodology and grading

Methodology

Lecture: Pass on knowledge and activate cognitive processes in students, encouraging their participation.
Solving exercises and problems: Exercise, test, and apply previous knowledge through routine repetition.

Grading

The main evaluative procedures are: (1) Multiple choice test: Final exam (multiple choice type) consisting of 50-80 theory questions with 5 possible answers, of which only 1 is true. An index correction will be used to avoid random answering. 1/4 questions well answered are substracted by each wrong answer. The duration of the exam will take up to 1 hour. (2) short questions exam: the student is proposed 5-15 short questions of theoretical development to be carried out within a maximum time of 1 hour. (3) Final practical exam: in the computer room, the student is proposed 1-4 practical problems. To solve them, the student has all necessary local programs, complete Web access, including databases and internet resources, featuring up to 2 hours to complete it. (4) practice reports: Practices reports are digitally deposited on the servers of the department and its correction will help the teacher to have a better assessment of the student. (5) Observation techniques: Class attendance and student participation in tutorials, and practical classes dealing with problems and exercises will be taken into consideration by the teacher to be assessed for the final mark. Attendance at practices and delivery of practical exercises will also be positively valued. All theory and practice examinations are scored 10 points and will have a minimum limit, below which the subject cannot be passed. The student's final mark will be composed by 80% for tests based on exams, and 20% for tests not based on exams.>> Tests based on written exams (80%) consist of:

* Multiple choice test (15% of the final mark), approximate duration: 1h. Limit least 4/10.

* Short questions tests (30% of the final mark), approximate duration: 1h. 4/10 threshold.

* Practical exercises tests (33% of the final mark), approximate duration: 2h. 4/10 threshold (will take place in a computer room)

>> Tests not based on exams (20%):

* Attendance to computing practices (AI= attendance index [0,1] multiplies the practice mark).

* Delivery and correction of computing practices (17% of the final mark). 5/10 threshold.

* Extra group activities throughout the course (3% of the final mark).

Assessment test characteristics

The Molecular Modeling test will consist of three parts:
(1) Exam with multiple-answer questions, in which there will be only one true answer.
(2) Short development questions, with space limitations.
(3) Practical exam, with limited space, with access to the webs of the subject and the main modeling pages on the internet.

Correction criteria

Correction criteria:
In the part of the exam (1) a correction factor will be applied for errors, so that each question wrongly answered supposes a penalty of one fourth of the value of a correct question. Types (2) and (3) will be corrected in the traditional way.

Additional requirements

The student must attend the exam provided with:

(1) An identification card (ID, driving, UMH)
(2) A #2 pencil, eraser and pencil sharpener.
(3) Standard calculator not programmable (smartphone or similar prohibited).

Faculty: MOLECULAR MODELING